Forthcoming articles

International Journal of Computer Aided Engineering and Technology

International Journal of Computer Aided Engineering and Technology (IJCAET)

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International Journal of Computer Aided Engineering and Technology (164 papers in press)

Regular Issues

  • Model-Driven Development of Self-Adaptive Multi-Agent Systems with Context-Awareness   Order a copy of this article
    by Farid Feyzi 
    Abstract: In recent years, there has been an increasing interest in distributed and complex software systems which are capable of operating in open, dynamic and heterogeneous environments, and are required to adapt themselves to cope with environmental or contextual changes. In order to achieve or preserve the specific design objectives, such systems need to operate in an adaptive manner. Self-adaptive systems have the capability to dynamically modify their behavior at run-time in response to different kinds of changes. This paper presents a methodology to develop context-aware self-adaptive software systems by attempting to employ the model driven architecture (MDA) and agent-oriented technology advantages. The approach aims to combine these two promising research areas in order to overcome the complexity associated with the development of these systems and improve the quality and efficiency of the development process. The methodology focuses on the key issues in the analysis and design of self-adaptive multi-agent systems. Different abstraction levels based on MDA has been proposed and mappings between models in these levels provided. These mappings bridge the gap between the high-level models produced in computation independent (CIM) and platform independent models (PIM) as well as the low-level models based on specific implementation platform called SADE (Self-adaptation Development Environment). The proposed approach has been evaluated through a case study described in the paper.
    Keywords: Self-Adaptive System; Multi-Agent Systems; Self-* properties; Model-Driven Development.

  • Execution of UML based oil palm fruit harvester algorithm: novel approach   Order a copy of this article
    by Gaurang Patkar 
    Abstract: Farmers in rustic India have negligible access to rural specialists, who can investigate edit pictures and render counsel. Deferred master reactions to inquiries regularly achieve farmers past the point of no return. This review addresses the above issue with the target of building up another calculation to review Elaeis Guineensis types of palm natural product to help agriculturists and analysts. The structure outlined can unravel issues of human reviewing evaluating in light of two qualities and anticipate the rate of free unsaturated fat and oil content. Guidance can be rendered from best practices in light of this. After gathering agreement with agriculturists and starting examination it is discovered that alongside shading, the quantity of separated fruitlets additionally assumes significant part in reviewing. In the recently planned calculation both elements are mulled over for basic leadership. Since manual evaluating is inclined to blunder, the nature of oil expelled from substance is low. Hence, there is a need to outline calculation which is a structure for agriculturists and analysts. This structure can be utilized with any shading model in any ecological conditions. The computerization of the manual evaluating procedure is finished with the proposed Palm natural product Harvester calculation utilizing Unified Modeling Language chart (UML).
    Keywords: fruitlets; elaeis guineensis; modeling; elaeis guineensis; oil palm fruit; unified modeling langauage; free fatty acid.

  • A BIM-based framework for construction project scheduling risk management   Order a copy of this article
    by F.H. Abanda 
    Abstract: The management of risks has been at the heart of most construction projects. Building Information Modelling (BIM) provides opportunities to manage risks in construction projects. However, studies about the use of BIM in risk management are sketchy with a lack of a systematic approach in using BIM for managing risk in construction projects. Based on existing risk models, this study investigated and developed a BIM-based framework for the management of construction project scheduling risk. Although, the frameworks were developed by mining risk management processes from Synchro and Vico, both being amongst leading 4D/5D BIM software systems, they can inform risk management in BIM projects that are supported by 4D/5D BIM software systems that contain risk management modules. The frameworks were validated for their syntactic and semantic correctness.
    Keywords: BIM; construction projects; risk; Synchro; Vico; 4D/5D BIM.

  • On The Order Reduction of MIMO Large Scale Systems Using Block-Roots of Matrix Polynomials   Order a copy of this article
    by Belkacem Bekhiti, Abdelhakim Dahimene, Bachir Nail, Kamel Hariche 
    Abstract: The present paper deals with the problem of approximating linear timerninvariant MIMO large scale systems with reduced order system via the help of thernso called Block-moment matching method based on the dominance exist betweenrnsolvents of the system characteristic matrix polynomial, where the Block-rootsrnare reconstructed using a new proposed procedure. The validation and study ofrnaccurate approximation is done by a specified performance index called pulsernenergy criterion. The necessary condition for correctness and applicability of the proposed method is the Block-controllablity or Block-observability. Finally, for the demonstration of the proposed method efficiency a numerical example is illustrated.
    Keywords: Solvents; Block-roots; Matrix polynomial; Moment matching; MIMO systems.

  • A combining technique based on channel shortening equalization for ultra wideband cooperative Systems   Order a copy of this article
    by Asma Ouardas, Sidahmed Elahmar 
    Abstract: This paper presents a novel combining technique based on the channel shortening approach for cooperative diversity in the context of time hopping ultra wideband (TH-UWB) systems. Since UWB channel has very long impulse response as compared to the very narrow pulse used system, TH-UWB performances are affected by inter-symbol interference (ISI). Therefore, the use of the Rake diversity combining is very effective, but it increases the receiver complexity due to its large number of correlations. The idea is to introduce a channel shortening equalizer (CSE) [named also Time domain equalizer (TEQ)] before the Rake reception in first and second time slots at the relay and destination, respectively. This proposed combination structure shows that there are great results in both decreasing the complexity of the receiver architecture by significantly reducing the number of effective channel taps and mitigating ISI. The Decode and Forward (DF) is used as a relay protocol to retransmit signals from the source to the destination and the relay is supposed equipped with multiple antennas and antenna selection criterion is used to exploit the diversity with reduced complexity. In the considered relay network, UWB links between the nodes are modeled according to IEEE 802.15.4a standards. The performance of the proposed structure is compared to cases where the relay is equipped with a single antenna and multiple antennas (full diversity). Numerical results show that significant improvement in the BER of UWB system is obtained by combining cooperative diversity technique and Channel shortening technique (lower than 〖10〗^(-5)) with respect to both improving the system performance and reducing the system complexity by using the antenna selection strategy which achieved the full diversity gain.
    Keywords: Time Hopping Ultra Wideband; TH-UWB; Channel Shortening Equalizer; RAKE receiver; Cooperative diversity; Antenna selection; Decode and Forward.

  • A Rewriting Logic Based Semantics and Analysis of UML Activity Diagrams: A Graph Transformation Approach   Order a copy of this article
    by Elhillali Kerkouche, Khaled Khalfaoui, Allaoua Chaoui 
    Abstract: Activity diagrams are UML behaviour diagrams which describe global dynamic behaviours of systems in a user-friendly manner. Nevertheless, UML notations lack firm semantics which make them unsuitable for formal analysis. Formal methods are suitable techniques for systems analysis. Rewriting Logic and its language Maude provides a powerful formal method with flexible and expressive semantics for the specification and the analysis of systems behaviour. However, the learning cost of these methods is very high. The aim of this paper is to integrate UML with formal notation in order to make the UML semantics more precise which allow rigorous analysis of its models. In this paper, we propose a graph transformation based approach to generate automatically Maude specifications from UML Activity diagrams. The proposed approach is automated using the AToM3 tool, and it is illustrated through an example.
    Keywords: UML Activity Diagrams; Rewriting Logic; Maude language; Meta-Modelling; Graph Grammars; Graph Transformation; AToM3.

  • MEASUREMENT OF BLEB HEIGHT AREA AND EXTENT USING ANTERIOR SEGMENT OPTICAL COHERENCE TOMOGRAPHY   Order a copy of this article
    by T.R. Ganesh Babu, S. Nirmala, K. Vidhya 
    Abstract: To image trabecolectomy blebs using anterior segment optical coherence tomography AS-OCT and to measure the blebs morphological features such as bleb height area and extend.In this paper fuzzy local informationC-means clustering is used to segment the bleb boundary. A batch of 25 AS-OCT images are used to assess the performance of the determined parameters to the clinical parameters, and 91.43% accuracy is obtained in the determined parameters result.The mean value of bleb height, area and extend are 0.2 mm, 1.618 mm2, 0.343 mm respectively. The result showsthe potential applicability of the method for automated and objective mass screening for detection of bleb boundary.
    Keywords: Blebs; Fuzzy local information-c means clustering Trabeculectomy; Anterior chamber optical coherence tomography; median filter.

  • A Probabilistic Analysis of Transactions Success Ratio in Real-Time Databases   Order a copy of this article
    by Mourad Kaddes, Majed Abdouli, Laurent Amanton, Alexandre Berred, Bruno Sadeg, Rafik Bouaziz 
    Abstract: Nowadays, due to rapidly changing technologies, applications handling more data and providing real-time services are becoming more frequent. Realtime database systems are the most appropriate systems to manage these applications. In this paper, we study statistically the behavior of real-time transactions under the Generalized Earliest Deadline First scheduling policy (GEDF ). GEDF is a new scheduling policy in which a priority is assigned to a transaction according to both its deadline and a parameter which expresses the importance of the transaction in the system. In this paper, we focus our study on the influence of transactions composition. Precisely, we study the influence of transaction distribution on the system performances and on approximation of transactions success ratio behavior by a probability distribution. To this end, we have developed our RTDBS simulator and we have conducted intensive MonteCarlo simulations
    Keywords: Real-time databases system; Transactions; schedule; GEDF; Stochastics; Monte-carlo Simulation.

  • GENERALIZED ULAM-HYERS STABILITY OF A n-DIMENSIONAL ADDITIVE FUNCTIONAL EQUATION IN TWO DIFFERENT METHODS   Order a copy of this article
    by Arun Kumar M, Agilan P, Ramamoorthy S, MaheshKumar N 
    Abstract: In this paper, the authors investigate the general solution and generalized Ulam-Hyers stability of a n-dimensional additive functional equation with n > 2 in Banach spaces by applying direct and fixed point methods.
    Keywords: additive functional equation; fixed point Generalized Ulam-Hyers stability.

  • Optimistic and Pessimistic Solutions of the Fuzzy Shortest Path Problem by Physarium Polycephalum approach   Order a copy of this article
    by Renu Tuli, Vini Dadiala 
    Abstract: The remarkable behavior of Physarium polycephalum has been used to solve the fuzzy shortest path problem. A novel algorithm has been developed for varying degrees of optimism ranging from purely pessimistic to purely optimistic. Providing the decision maker (DM) a range of solutions gives him/her more flexibility in choosing the solution according to his/her degree of optimism. The triangular and trapezoidal fuzzy numbers representing cost or duration of travel are converted to crisp numbers by finding their total integral values and thereafter optimal solutions for varying degrees of optimism are obtained. The process is explained by four numerical examples including a tourist network problem and results obtained are compared with existing work. It has been observed that in comparison to the existing work, this method is not only easier to understand and implement but also gives better non-dominated optimal solutions.
    Keywords: Physarium polycephalum; triangular fuzzy numbers; trapezoidal fuzzy numbers; optimistic and pessimistic approachesrnrn.
    DOI: 10.1504/IJCAET.2020.10023992
     
  • Cryptographic Key Management Scheme for Supporting Multi-User SQL Queries over Encrypted Databases   Order a copy of this article
    by K. SRINIVASA REDDY, RAMACHANDRAM S 
    Abstract: Database outsourcing is getting more popular bringing in a new standard, called database-as-a-service, where an organizations database is stored in cloud. In such a setting, both access control and data confidentiality plays an important role, particularly when a data owner likes to publish his data for external use. Any cloud provider promises the security of its platform, while the execution of solutions to ensure confidentiality of the data stored in cloud databases is left to the data owner. The state-of-the-art solutions deal few preliminary issues with aid of SQL queries on encrypted data. In this paper, we propose a novel cryptographic key management scheme that combines data encryption and key management and supports multi-user SQL queries over encrypted databases. Our approach shows the proposed solutions for enforcing access control and for ensuring confidentiality of data. The experimental results obtained in this paper show the performance of proposed scheme.
    Keywords: data confidentiality; access control; key derivation; encryption; metadata.

  • Employment Effects and Efficiency of Ports   Order a copy of this article
    by Torsten Marner, Matthias Klumpp 
    Abstract: Expected increasing transport volumes in Germany and Europe, combined with increasing sustainability requirements, lead to a prospective major role of sea and inland ports in future transport systems. But especially for inland ports this increased expectations more and more lead to conflicts regarding port property denomination as city development heavily pursues non-transport and non-industry dedications e.g. with high-scale living quarters, recreation and office space concepts like e.g. in D
    Keywords: Employment effects; inland ports; cost-benefit analysis; bottlenecks; freight transport performance; data envelopment analysis.

  • Evolutionary Neural Network Classifiers for Software Effort Estimation   Order a copy of this article
    by Noor Alhamad, Fawaz Alzaghoul, Esra Alzaghoul, Mohammed Akour 
    Abstract: The estimation of software development efforts has become a crucial activity in software project management. Due to this importance, many researchers focused their efforts on proposing models for relationship construction between efforts and software size and requirements. However, there are still gaps and problems in software effort's estimation process; due to the lack of enough data available in the initial stage of project life cycle. The need for an enhanced and an accurate method for software effort estimation is an urgent issue that challenged software project-management researchers around the world. This work proposes a model based on Artificial Neural Network (ANN) and Dragonfly Algorithm (DA), in order to provide more accurate model for software effort estimation. The applicability of the model was evaluated using several experiments and the results were in favour of the enhancement with more accurate effort estimation.
    Keywords: COCOMO 81; Artificial Neural Network; Dragonfly Algorithm; Effort estimation.

  • Fuzzy multi-objective approach based small signal stability analysis and optimal control of a PMSG based wind turbine   Order a copy of this article
    by Shubhranshu Mohan Parida, Pravat Kumar Rout, Sanjeeb Kumar Kar 
    Abstract: The objective of this manuscript is to design a controller to enhance the degree of stability through small signal analysis in case of a grid connected permanent magnet synchronous generator (PMSG) based wind turbine and to ensure an optimal set of control parameters to achieve an enhanced performance. The optimal control parameters are computed by optimizing the placement of system eigenvalues and net errors by formulating a fuzzy based multi-objective approach. The idea behind the formulation of the objective function through a multi-objective approach involves the association of error with relative stability of the system through computation of the real parts of eigenvalues. To find the optimal control gains, a two-fold mutation based differential evolution optimization is used. Results from a Matlab based model are presented for validation of the proposed technique to demonstrate the system stability when subjected to wind speed variation.
    Keywords: permanent magnet synchronous generator; PMSG; Small signal stability; SSS; wind energy conversion system; WECS; differential evolution; DE; wind turbine ;WT.

  • ON ODD HARMONIOUS LABELING OF EVEN CYCLES WITH PARALLEL CHORDS AND DRAGONS WITH PARALLEL CHORDS   Order a copy of this article
    by Srividya Venkataramani, Govindarajan  
    Abstract: Labeling in graph theory is an active area of research due to its wide range of applications . A graph labelling is an assignment of integers to the vertices or edges or both subject to certain conditions. This paper deals with one such labelling called odd harmonious labelling. A graph G = (V,E) with 'V(G)' = p and 'E(G)' = q is said to be odd harmonious if there exist an injection f: V(G)  {0,1,2,.2q-1} such that the induced function f* : E(G) {1,3,5..2q-1}defined by f*(uv) = f(u) +f(v) is bijective. In this paper we prove that every even cycle Cn (n≥6) with parallel P3 chords is odd harmonious. We also prove that the disjoint union of two copies of even cycle Cn(n≥6) with parallel P3 chords and the joint sum of two copies of even cycle Cn with parallel P3chords is odd harmonious. Moreover we show that the Chain of even cycles Cn(n≥6) with parallel P3 chords , joining 2 copies of even cycle Cn with parallel P3 chords by a path Ht of order t and also Dragons with parallel chords obtained from every odd cycle Cn (n≥7) after removing two edges from the cycle Cn , Dragons with parallel P4 chords obtained from every odd cycle Cn (n≥ 9) after removing two edges from the cycle Cn are odd harmonious
    Keywords: Harmonious labelling; Odd harmonious labelling; Cycles with Parallel P3 chords; Joint Sum and Chain of cycles with parallel P3 chords.

  • Fixed point theorems by altering distance technique in complete fuzzy metric spaces   Order a copy of this article
    by Vishal Gupta, Rajesh Kumar Saini, Manu Verma 
    Abstract: The aim of this paper is to define the generalized altering distance function and to extend the Banach contraction principal in complete fuzzy metric spaces using altering distance. The f-mapping also plays an important role to find fixed point. Our result extends the result of Harandi et al. (2013) in fuzzy metric space.
    Keywords: Fuzzy Metric Space; Control Function; Altering Distance.

  • Design alternatives of Euclidian greatest common divisor with enhanced architecture   Order a copy of this article
    by Qasem Abu Al-Haija, Mohammad M. Asad, Ibrahim Marouf, Mahmoud A. Smadi 
    Abstract: In this paper, we proposed different comparable reconfigurable hardware implementations for greatest common divisor (GCD) and least common multiple (LCM) coprocessors using Euclids method and Plus-Minus method with variable datapath sizes. The proposed designs utilized ALTERA Cyclone IV FPGA family with target chip device EP4CGX-22CF19C7 along with Quartus II simulation package. Also, the proposed designs were synthesized and benchmarked in terms of the maximum operational frequency, the total path delay, the total design area and the total thermal power dissipation. Thus, Plus-Minus method proved its enhanced performance by speeding up the operational frequency recoding around 142 MHz of data processing frequency with is as twice as its counterpart for Euclids method while reducing the total path delay by almost 50% compared to Euclids method. However, Euclids method listed less hardware utilization and power dissipation with almost 36% and 10% less than the values for Plus-Minus method respectively. Consequently, Plus-Minus method can be efficiently employed to enhance the speed of computation for many GCD based applications such embedded system designs for public key cryptography.
    Keywords: Number theory; Greatest Common Divisor (GCD); Euclidian GCD; Least Common Multiple (LCM); Plus-Minus GCD; Field programmable gate arrays (FPGA); Integrated circuit synthesis.

  • A cloud broker architecture for cloud service selection based on Multi-criteria Decision Making and Rough Set Theory   Order a copy of this article
    by JAMAL TALBI 
    Abstract: Cloud computing is a rising field providing computation resources. It represents a new paradigm of utility computing and enormously growing phenomenon in the present IT industry and economy hype. The companies which provide services to customers are called as cloud service providers. The cloud users (CUs) increase and require secure, reliable and trustworthy cloud service providers (CSPs) from the market. So, its a challenge for a new user to choose the best provider. In this paper, we propose cloud broker architecture to help a new customer to find out the best CP. This architecture is based on a combination of Rough Set Theory and Multi-Criteria Analysis of some parameters related to the quality of service of the available providers. A mathematical model is used to do this analysis; it integrates Multi-Agent Systems to present an intelligent, distributed and collaborative method in order to add assistance to each actor in cloud computing environment.
    Keywords: cloud Computing; Cloud Broker Architecture; Rough Set Theory; Multi-Criteria Decision Analysis.

  • Two Generalized Fixed Point Theorems in $G$-metric Space Without Iterations   Order a copy of this article
    by Saravanan S, Phaneendra T 
    Abstract: Two generalized fixed point theorems are proved using the well-known infimum property of real numbers without an appeal to the iterative procedure.
    Keywords: The Infimum Property; $G$-Metric Space; $G$-Cauchy Sequence; Fixed Point; $G$-contractive Fixed Point.

  • Inverse kinematic Analysis of 5-Axis Hybrid Parallel Kinematic Machine using CAD and Regression analysis approach   Order a copy of this article
    by SURYAM LV, Balakrishna B 
    Abstract: Since three decades for their potentially desirable fast dynamic performance, rigidity, and acceptable accuracy parallel kinematic machines (PKM) attracted interest from industry and academia in the machine tool/robot sectors. PKMs are highly used for their higher accuracy as it relies on system stiffness and rigidity. In PKM, the Inverse kinematic analysis for finding the velocity and acceleration of a limb having more than Two Degree of freedom (DOF) manually is tedious. Also generation of transformation matrix is too complex. In present work, six degrees of freedom 5-axis Hybrid parallel kinematic machine (HPKM) with hemisphere workspace has been modeled and assembled in CATIA. Secondly, inverse kinematic analysis of PKM was carried out in digital mockup unit (DMU), CATIA. The velocities and accelerations of all the three limbs at three different feed rates and variations in joint angles were found. On the other hand, the regression equations were generated for velocity and acceleration of three limbs, joint angles with respect to position and time, while the tool travels along the semi circular contour trajectory
    Keywords: 5-Axis HPKM; Inverse Kinematics; DMU; contour trajectory; Regression analysis.

  • Multi-Response Optimization in CNC turning of Al-6082 T6 using Grey Taguchi Method coupled with Principal Component Analysis   Order a copy of this article
    by Suresh Kumar Gudimetta, P. Venkateshwar Reddy, Mohana Krishnudu Doni 
    Abstract: The present work focuses to analyze the importance of turning parameters on the responses: Machining Time, Surface Roughness and Material Removal Rate in CNC turning while machining of aluminum alloy Al-6082 T6 using tungsten carbide tool. Cutting Speed, feed rate and depth of cut with three levels each have been considered in the current work as the machining parameters. The present study uses the Taguchi's DOE methodology, Grey Relational approach and Principal Component Analysis (PCA) to optimize the response parameters simultaneously. Experiments have been conducted as per Taguchis L9 orthogonal array. The experimental results were then analyzed using the Grey Relational Analysis (GRA) along with the Principal Component Analysis (PCA). The Speed and Feed are observed to be statistically significant on the responses whereas the depth of cut is insignificant. Optimal levels for the parameters are determined using the Grey Taguchi Method and PCA. The confirmation test is carried out and the results are validated.
    Keywords: Multi-response optimization; Turning; Machining Time; Surface Roughness; Material Removal Rate; Grey Taguchi.

  • A New Bio-inspired Algorithm: Lizard Optimization   Order a copy of this article
    by Dharmpal Singh 
    Abstract: A new bio-inspired, Lizard algorithm (LA) is proposed for optimization of soft computing used in data mining. Here, an effort has been made to mimic the anole lizard behaviour to optimize problems of the data set. Furthermore, the experiments have been carried out on five benchmark problems with ten benchmark algorithms like Statistical, Fuzzy, Neural Network, Tabu Search, Simulated Annealing, HS, DEA, PCO, ABC and ACO on data set. The concept of average error and residual error were conducted to compare the performance of LA with that of other used algorithms. The concepts of residual analysis and Chi test (χ2) have also been performed on the proposed algorithm to check the righteous among the algorithms. And the result has shown that LA has achieved good optimization results in terms of both optimization accuracy and robustness.
    Keywords: Data mining; association rule; fuzzy logic; neural network; particle swarm optimization; artificial bee colony algorithm; ACO; TS; SA; DEA and harmony search algorithm Lizard algorithm.

  • The Rapid Development of Knowledge Bases Using UML Class Diagrams   Order a copy of this article
    by Aleksandr Yurin, Nikita Dorodnykh, Olga Nikolaychuk 
    Abstract: The knowledge bases design that employs conceptual models and their transformations is one of the most interesting areas of knowledge engineering and it remains critical. This paper presents an approach to the rapid development of knowledge bases for rule-based expert systems on the basis of the model-based generation of program codes. The approach proposed uses conceptual models in the form of UML class diagrams as a source of knowledge. However, the main principles of our approach can be used to analyze others models, for instance, OWL or block definition diagrams of SysML. In accordance with the technique that we propose, diagram concepts and relationships are extracted, mapped to the ontology of a subject domain and represented in the form of fact templates and logical rules. The original notation, namely the Rule Visual Modelling Language (RVML), is used to visualize and modify mapped elements. The C Language Integrated Production System (CLIPS) is used as the targeted knowledge base programming language. The new approach does not eliminate errors due to inaccurate or incompletely analyzed conceptual models; but provides minimization of programming errors resulting from hand coding. The algorithms describing model transformations are implemented as a software prototype. The case study that demonstrates the principal applicability of the approach and software was conducted. Moreover, the approach is used to design the knowledge base of a decision-support system for the industrial safety expertise of petrochemical facilities.
    Keywords: knowledge base; knowledge acquisition; code generation; UML class diagram; CLIPS.

  • Quantifying wind-driven rain on a heritage facade through computational fluid dynamics.   Order a copy of this article
    by Sat Ghosh, Yash Dugar, Namrata Kakoti, Chirag Shah 
    Abstract: The Chennai Central Station is a heritage structure and a stellar landmark its Neo-Gothic Visage is an iconic structure in the heart of this thriving metropolis. It has withstood the ravages of nature battering of gale force winds during tropical storms, unacceptable levels of particulate pollution, and the onslaught of driving rain. This 142 year old building can survive much longer combating further natural and man-made impacts if the existing fa
    Keywords: Lagrangian Integral Time Scales; Computational Fluid Dynamics; Turbulent Trajectories; Heritage Facades.

  • A hybrid approach of firefly and genetic algorithm for solving optimization problems   Order a copy of this article
    by Fazli Wahid, Rozaida Ghazali 
    Abstract: Firefly algorithm (FA) is a newly developed nature-inspired, meta-heuristic, stochastic algorithm that has seen many applications in solving problems of optimization nature since its introduction just a couple of years ago. FA is a simple, flexible, easily implementable and robust approach inspired from natural phenomenon of light emission by fireflies but a major drawback associated with FA is the random initial solution set generation. This random initial solution set leads to imbalanced relation between exploration and exploitation property that results in slow local and global convergence rates that ultimately degrade the solution quality. This issue can be resolved by providing some organized initial solution set instead of randomly generated solution search space which will balance the exploration and exploitation capability of FA during initial solution set generation stage. In this work, the targeted issue has been resolved by introducing genetic algorithm (GA) operators namely selection, mutation and cross over operators during initial solution set generation for standard FA. The proposed technique has been applied to few standard benchmark minimization and maximization functions and the results have been compared with standard FA and GA. A significant amount of improvement in the convergence rate can be observed that results in high quality solution for solving optimization problems.
    Keywords: Standard Firefly Algorithm; Genetic algorithm; Random solution generation; Hybrid GA-FA; Faster Convergence.

  • Multi Objective Optimization of Tube Hydroforming Process on IF Steel using Taguchi based Principal Component Analysis   Order a copy of this article
    by P. Venkateshwar Reddy, B. Veerabhadra Reddy, P. Janaki Ramulu 
    Abstract: Tube Hydroforming is one of the eccentric metal shaping procedures, especially utilized as a part of the automotive industry. This Process has accentuated much consideration inferable from its diversified applications. To emphasize, aerospace and automotive industries depend much upon this procedure. Earlier most of the researchers worked on the material characterization and the process parametric impacts of Tube Hydroforming process. However, very few have attempted on the multi-objective optimization of the critical process parameters. In this work, commercial Finite Element code Pam-Stamp 2G is utilized to do the simulations in view of the L27 orthogonal array. Hence a multi-objective optimization was studied that simultaneously maximizes the bulge ratio and minimizes the thinning ratio by Taguchi based Principal Component Analysis (PCA), which is the novelty of this work. The present work aims at exploring the impact of geometrical, process and material parameters on aforementioned responses using analysis of variance (ANOVA).
    Keywords: Multi-response optimization; Tube Hydroforming; FEM; IF-Steel; Taguchi Method; PCA.

  • The graph SSG(2) is odd graceful and odd harmonious   Order a copy of this article
    by J. Jeba Jesintha , K. Ezhilarasi Hilda Stanley 
    Abstract: A subdivided shell graph is obtained by subdividing the edges in the path of the shell graph . Let G1, G2 , G3,. . ., Gn be 'n' subdivided shell graphs of any order. The graph SSG(n) is obtained by adding an edge to apexes of Gi and Gi+1, i = 1, 2, . . . ,(n-1). The graph SSG(n) is called a path union of 'n' subdivided shell graphs of any order. In this paper we prove that the subdivided shell graph is odd harmonious. We also prove that SSG(n) is odd graceful and odd harmonious when n = 2.rn
    Keywords: Odd graceful labeling; odd harmonious labeling; shell graph; subdivided shell graph; the graph SSG(2).

  • Analysis, Identification and Design of Robust Control Techniques for Ultra-Lift Luo DC-DC Converter Powered by Fuel Cell   Order a copy of this article
    by Rajanand Patnaik Narasipuram 
    Abstract: In recent years the development of alternative energy source is getting more importance because of high quality characteristics in power generation system with low cost. The proliferation of DC-DC converter is widely used for high power and low voltage applications. In such cases, the Ultra-Lift Luo converter is the suitable one compared to Voltage Lift (VL) Luo-Converter and Super-Lift (SL) Luo-Converters because of their limitations in voltage transfer gain and more voltage ripples. This paper proposes the Proportional Integral (PI) and Fuzzy Logic (FL) controllers for the fast and efficient operation of Ultra-Lift (UL) Luo-converter. An Air Breathing Fuel Cell (ABFC) stack is developed and which is taken as an input power source to the Ultra-Lift Luo-converter. This paper will give focus on design, mathematical analysis and operation of fuel cell powered DC-DC converter is incorporated with PI and FL controllers which are simulated using MATLAB/Simulink software. Furthermore, simulation results of ABFC are also presented to review the effects of temperature from 30oC-70oC in fuel cell voltage. The dynamic response of PI and FL controllers are sifted for line as well as load voltage regulations and the simulation results are presented using MATLAB/Simulink.
    Keywords: Air Breathe Fuel Cell; ABFC; Fuel Cell; Stack; DC-DC converter; Proportional Integral controller; PI; Fuzzy Logic Controller; FL; Voltage Lift; VL; Super-Lift; SL; Ultra-Lift Luo-converter; UL;.

  • Simple and Effective Control and Optimization of a Wind Turbine Based on a DFIG   Order a copy of this article
    by Anis Tarfaya, Djalel Dib, Mehdi Ouada, Sihem Ghoudelbourk 
    Abstract: The objective of main contribution of this paper a satisfactory result control, optimization of a wind turbine based on a Doubly Fed Induction Generator (DFIG) , this system contain 1.5 MW wind turbine, gearbox , DC /AC inverter numerical simulation implementation of this model under Matlab /Simulink are reached using different toolbox, a direct vector control with direct field oriented control (FOC) applied and two maximum power point tracking control (MPPT) ,with and without speed control , for improving system performance under fast changing of wind speed conditions , the simulation results quickly and correctly track change in power set point, the disadvantage of classical FOC based on PI controller is eliminated by using Sliding mode controller, the result of simulation shows good performance of used method .
    Keywords: WIND ENERGY; DFIG; FOC; MPPT; SMC.
    DOI: 10.1504/IJCAET.2021.10020021
     
  • Spur Gear Safety Prediction through Analysis of Stress Intensity Factor   Order a copy of this article
    by Fung Z. Hiung, Haidar AL-Qrimli, Mustafa J. Al-Dulaimi, Kenobi I. Morris 
    Abstract: Application of gear in heavy industry is extremely challenging with the exposure to high load and high speed during transmission. These exposures produce an unfavorable condition in the gear operation as they induce crack. Induced crack might not only causes machine failures but catastrophic incidents that cost lives. Provided that the crack does not grow towards the shaft, the gear might still functioning but at a lower efficiency. Vice versa, the gear will tear into parts and causes catastrophic damages. Therefore, the study of crack propagation pathway was conducted by analyzing the crack tip behavior. The crack tip behavior was indicated using the stress intensity factor (SIF) by identifying the potential fracture mode of the crack gear model. The analysis had implemented the application of extended finite element method (XFEM) in ABAQUS to avoid the need of re-meshing as in finite element method (FEM). The simulation outcomes show that the cracked gear model is experiencing a significant compressive in-plane shear than tensile stress. It also allows the witnesses of crack propagation along the tooth.
    Keywords: Gear; Crack; Safety; Contact Stress; XFEM.
    DOI: 10.1504/IJCAET.2021.10017169
     
  • Development of smoke prediction model using numerical simulation   Order a copy of this article
    by Nurud Suhaimi, Abdullah Ibrahim, Saari Mustapha, Nor Mariah Adam, Rafee Baharuddin 
    Abstract: Conducting a full-scale fire test is the best way to acquire information regarding to smoke and fire condition for the purpose of fire safety protection and prevention installation. However, full scale fire experiment was expensive, time consuming and unrepeatable due to unstable nature of fire. The main goal of this study was to develop a quantitative tool to analyze the smoke temperature in a stairway by utilizing Fire Dynamic Simulator software. A result of this study provides mathematical correlation that could predict temperatures in adjacent vertical shaft used as stairway which is useful in performance based design. The smoke temperature predicted using developed model compared with numerical data showed error less than 30% were considered satisfactory and the equation considered acceptable for this study. rnrn
    Keywords: quantitative tool; smoke temperature; vertical shaft; FDS; mathematical correlationrnrnrn.

  • Optimization of Nozzle Diameter of Nebulizer for Salbutamol   Order a copy of this article
    by Vinoth N, Lokavarapu Bhaskara Rao 
    Abstract: In medicine, a nebulizer is equipment used to achieve medication in the form of spray breathe into lungs. The general methodological principle of nebulizers is to use oxygen or compressed air or ultrasonic powder, as means to breakup medicinal solutions into smaller mister dews, for direct breath from the mouthpiece of the equipment. The utmost normally used nebulizers are Jet nebulizer, which is also known as "atomizer". Jet nebulizers are associated with compressor that supports compressed air to flow at maximum velocity over a liquefied medication to turn into a mister, which is then breathed in by the patient. The objective of this study is to optimize the jet nebulizer in order to deliver medicine in minor sufficient dews to attain a satisfactory effectiveness of medicated aerosol to reach lungs. This study concentrates on design optimization of the nozzle by analysis of flow parameters, evaluation of the path of the fluid flow and determination of nozzle diameter and flow pressure.
    Keywords: Drug delivery; Nebulizer; Atomizer.
    DOI: 10.1504/IJCAET.2021.10018387
     
  • Two Way Distributed Sequential Pattern Mining using Fruitfly Algorithm along with Hadoop and Map Reduce Frame Work   Order a copy of this article
    by Vankudothu Malsoru, Naseer A. R., Narsimha G 
    Abstract: Data Mining is an effectual tool used to take out information from a big data as it provides several benefits to conquer the restrictions in it. In this paper, we present an innovative procedure developed using Updown Directed Acyclic Graph (UDDAG) with Fruit Fly Optimization algorithm, which is based on Sequential Pattern mining algorithm. In this work, the distributed sequential model mining algorithm is used to diminish the scanning time and scalability and the transferred database is employed to optimize the memory storage. The proposed method is used to expand the sequences in both the ends (prefixes and suffixes) of identified model thereby supplying the consequences in quicker model expansion resulting in fewer database projections when compared to conventional methods. Our proposed method is implemented in Hadoop distributed surroundings to resolve the scalability issues and executed on JAVA platform using big datasets with Hadoop and Map-reduce frame work.
    Keywords: Data Mining; Updown Directed Acyclic Graph; Fruit-fly algorithm; Distributed Sequential model mining; Hadoop with Map-Reduce framework.
    DOI: 10.1504/IJCAET.2021.10018474
     
  • Minimum layout of hypercubes and folded hypercubes into the prism over caterpillars   Order a copy of this article
    by Jessie Abraham, Micheal Arockiaraj 
    Abstract: The problem of embedding an n-node graph G into an n-node graph H is an important aspect in parallel and distributed processing. Graph embedding results have been successfully used to establish equivalence of interconnections in parallel and distributed machines. The binary hypercube is one of the most widely used multiprocessor systems due to its simple, deadlock-free routing and broadcasting properties. The folded hypercube is an important variant of hypercube with the same number of nodes. Trees are the fundamental graph theoretical models in many fields including artificial intelligence and various network designs. In this paper we consider the problem of embedding the hypercube and folded hypercube into the prism over a caterpillar in such a way as to minimize its layout.
    Keywords: embedding; folded hypercube; prism over a graph; layout.

  • Decidability of Compatibility for Data-Centric Web Services   Order a copy of this article
    by Mohamed Said Mehdi Mendjel, Hassina Seridi-Bouchelaghem 
    Abstract: The problem of checking compatibility of data-centric services is discussed herein. It focuses, more specifically, on compatibility of data-centric services' protocols such that a service protocol is the description of the service's external behaviour. Our study comprises two parts: The first part consists of checking the services' protocols compatibility, which is represented by the same database instance with different queries. Here, we prove that the verification problem is decidable; the second part consists of studying the same problem but including a database. Hence, the problem of data infinity, which remains undecidable although the use of classic verification algorithms. This study is concluded by the implementation of a verification tool based specifically on guarded services with a finite database.
    Keywords: Artifacts; Business Protocols; Data-Centric Services; Infinity of Data; Compatibility of Web Services.

  • Latency- Optimized 3D Multi-FPGA System with Serial Optical Interface   Order a copy of this article
    by Asmeen Kashif, Mohammad Khalid 
    Abstract: Multi-FPGA Systems (MFSs) are capable of prototyping large SoCs. However, planar 2D MFSs with electrical interconnections have broader spatial distribution and large off-chip delays. One good solution for this problem is to use a three-dimensional (3D) architecture, where multiple FPGAs are stacked on top of each other rather than being spread across a 2D plane.This provides lower off-chip latency with smaller footprint. 3D MFS performance can be further improved through reduction in the number of interconnects by employing serial communication. Nevertheless, electrical interconnects are limited in their performance due to latency. Replacing electrical interconnections by optical interface further reduces off-chip delays. Additionally, the selection of MFS routing architecture also has substantial effect on system performance. In this paper, we propose novel 3D MFSs with different routing architectures that employ serialized optical interface improving system frequency significantly. An experimental architecture evaluation framework and associated CAD tools were developed. The proposed architectures were experimentally evaluated and provided average system frequency gain of 37% across six benchmark circuits.
    Keywords: 3D Multi-FPGA; optical interface; multiplexing; routing architectures.

  • LESH - FEATURE EXTRACTION AND COGNITIVE MACHINE LEARNING TECHNIQUES FOR RECOGNITION OF LUNG CANCER CELLS   Order a copy of this article
    by Ummadi Janardhan 
    Abstract: The Novel Local Energy-based Shape Histogram (LESH) feature mining strategy was proposed for different cancer predictions. This paper stretches out unique work to apply the LESH system to distinguish lung cancer using machine learning approaches. As the traditional neural network systems are complex and time consuming, machine learning approaches are considered in this work, which atomizes the process of tumor identification. Before LESH feature extraction, we upgraded the radiograph pictures utilizing a complexity constrained versatile histogram adjustment approach. Subjective machine learning classifiers are chosen specifically extraordinary learning machine approach, Support vector machine (SVM) connected utilizing the LESH impassive features for effective analysis of right therapeutic state in the x-ray and MRI pictures. The framework comprises of feature extraction stage, including choice stage and order stage. For including extraction/choice distinctive wavelets capacities have been connected to locate the noteworthy exactness. Grouping K-nearest neighbor calculation has been created/used for arrangement. The informational collection used in the proposed work has 114 knob regions and 73 non-knob districts. Precision levels of more than 96% for characterization that have been accomplished which exhibit the benefits of the proposed approach.
    Keywords: LESH; Feature Extraction; Cancer Cell; K-Nearest Neighbor; Classification;.

  • Fuzzy predictor for parallel dynamic task allocation in multi-robot systems   Order a copy of this article
    by Teggar Hamza, Senouci Mohamed, Fatima Debbat 
    Abstract: This paper presents a model to decompose complex tasks in the form of elemental tasks executed in parallel by multi robots. In this model, a criterion of accuracy in the parallel dynamic tasks allocation process (APDTA) is defined. Through this APDTA, a predictor based on fuzzy logic called FP-TE is developed to evaluate the importance of elemental tasks in the system. The inputs of this predictor are described as observations acquired from sensor data. The FP-TE output will be used to allow each robot to individually decide what task should be executed. Simulation results on goods transportation by mobile robots are presented to demonstrate the effectiveness of this fuzzy predictor.
    Keywords: dynamic tasks allocation; multi-robot systems; fuzzy predictor; accuracy in tasks allocation; distributed MRS.

  • Prediction of Wine Quality and Protein Synthesis Using ARSkNN   Order a copy of this article
    by Ashish Kumar, Roheet Bhatnagar, Sumit Srivastava 
    Abstract: The amount of data available and information flow over the past few decades has grown manifold and will only increase exponentially. The ability to harvest and manipulate information from this data has become a crucial activity for effective and faster development. Multiple algorithms and approaches have been developed in order to harvest information from this data. These algorithms have different approaches and therefore result in varied outputs in terms of performance and interpretation. Due to their functionality, different algorithms perform differently on different datasets. In order to compare the effectiveness of these algorithms, they are run on different datasets under a given set of fixed restrictions e.g. hardware platform etc. This paper is an in depth analysis of different algorithms based on trivial classifier algorithm, kNN and the newly developed ARSkNN. The algorithms were executed on three different datasets and analysis was done by evaluating their performance taking into consideration the Accuracy percentage and Execution Time as performance measures.
    Keywords: Classification; Nearest Neighbors; ARSkNN; Similarity Measure;.

  • PARAMETER OPTIMIZATION OF FIBER REINFORCED POLYMER COMPOSITE BY RSM DESIGN MATRIX   Order a copy of this article
    by Sonia S Raj, Pradeep P, Edwin Raja Dhas John 
    Abstract: Polymer composite fabricated based on natural fibers gains popularity since they poses numerous advantages in auto-motives. But natural fibers suffer from lower strength which can be over come through hybridization with stronger synthetic fibers like carbon or glass. This work explodes the potential reinforcement of fibers from palm leaf stalks for fabricating polymer composites. The fibers were pre-treated with glass fibers to form as fiber mats and hybridized with glass fibers prior to reinforcement. These mats were reinforced in the polyester resin matrix as different layers to form a hybrid composite. Experiments were done by varying the length of fiber, fiber volume and with different treatments using response surface methodology. Tensile strength was measured as response. The tensile strength was spotted maximum in 8% potassium permanganate (KMnO4) treated palm fibers with optimum fiber length 40 mm and volume fraction of 20%. The surface study on these composites through SEM (Scanning Electron Microscope) examination was satisfactory. Hence this specimen combination was best suited and recommended to manufacture components like car bonnet, bumper etc
    Keywords: Parameters; Composite; response surface methodology.

  • ADAPTIVE FRAME ASSESSMENT TACTICS FOR HIGH QUALITY THERAPEUTIC VIDEO COMPRESSION   Order a copy of this article
    by D. Raveena Judie Dolly, D.J. Jagannath 
    Abstract: Video compression came into existence three decades ago. It became a challenging and demanding task due to massive information content, as in the case of medical procedures and other essential footage. Digital storage of medical information has become a staggering task, since the requirements for information storage have become limited and expensive in the fast growing engineering technology. This daunting situation is a result of the unavailability of above par methodologies to store mega sized videos. Hence, video compression makes itself vital for the modern age. An exhaustive investigation using Adaptive frame determination (AFD) is proposed in this research work for obtaining high quality compressed video. The perception of choosing the frames varies from the traditional method of video compression. Adaptive frame determination ascertains frames based on correlation for obtaining enhanced visual quality. Appropriate choice of the frames (Intra Frame, Predictive frame, Bi-directional frame) based on the motion type leads to better reconstruction quality which is validated by the two most reliable performance metrics, PSNR(Peak signal to noise ratio) and SSIM (Structural similarity Index).
    Keywords: Adaptive frame determination (AFD); medical video compression; Intra Frame; Predictive frame; Bi-directional frame; Group of Pictures (GoP).

  • Design of RF Planar Slow Wave Interaction Structure for THz Devices   Order a copy of this article
    by KISHORE KUMAR KAMARAJUGADDA, Movva Pavani 
    Abstract: Microfabricated planar slow wave structure (SWS) in a traveling wave tube (TWT) has shown a superior performance when compared with the circular helix structure for RF Power Amplification. The circular helix structure applications are limited to the maximum operating frequency of 70GHz.In the proposed paper, a rectangular planar slow wave structure operating at Terahertz (THz) is designed. Fabrication of the beam interaction system is complex especially operating at higher frequencies as the device dimensions decrease. Use of planar interaction system simplifies the miniaturized fabrication process. The present paper focused on the design of Staggered Double Vane Slow Wave Structure (SWS) and simulated the corresponding Dispersion Diagram and S-Parameters of the model by using CST Studio Suite software. The results for designed RF planar Slow Wave Structure are then analyzed.
    Keywords: Slow Wave Structure; Travelling Wave Tube; Waveguide; Eigen mode Analysis; Transient Analysis; Rectangular Waveguide Cutoff Frequency.
    DOI: 10.1504/IJCAET.2021.10020698
     
  • VLSI Based Self-Healing Solution for Delay Faults in Synchronous Sequential Circuits   Order a copy of this article
    by Nithya Ganesan, Muthiah Ramaswamy 
    Abstract: The paper evolves a methodology in an effort to heal the occurrence of delay faults in synchronous sequential circuits.The delay fault appears to critical in the operation of digital circuits owing to the largenumber of gates integrated on a chip and manifests themselves in the incorrect timing behavior of some logic elements within the network. The scheme allows detection of a wider range of delay faults with improved resolution and envisages measures to restore the true values at the primary output through appropriate changes in the structure. It uses saboteurs for fault injection and handles delay faults both in combinational and memory blocks of synchronous sequential circuit. The approach turns out to be comparatively simple and helps to improve the long-term reliability of high-performance digital circuits besides enabling to decrease the cost and area overhead over the existing triple modular redundancy (TMR) and Distributed Minority and Majority voting based redundancy (DMMR) fault healing schemes. The fact that the Spartan architecture synthesizes the VLSI codes foster to validate the Modelsim based simulated results and perpetuates a claim for its use in real world digital utilities.
    Keywords: Area overhead; delay faults; fault coverage; self-healing; synchronous sequential circuits; TMR; DMMR.

  • A Novel Multi-Purpose Watermarking Scheme using Multiple Watermarks   Order a copy of this article
    by Ayesha Shaik, Masilamani V. 
    Abstract: Most of the existing digital watermarking schemes mainly target a single or a few required objectives. The novelty of the proposed technique is to meet the four main objectives of the digital watermarking namely copyright protection, data authentication, usage monitoring, and user authentication. This scheme uses multiple watermarks for meeting these goals using discrete wavelet transform (DWT) and singular value decomposition (SVD) transforms. This technique achieves high peak signal-to-noise ratio (PSNR) and high robustness against average filtering, median filtering, salt and pepper noise, gamma correction, and contrast enhancement attacks. The experimental results show that the proposed method is effective in achieving four primary goals of watermarking. The validation of the proposed technique is tested using the images from BOWS and SIPI datasets.
    Keywords: Copyright Protection; Data Authentication; User Authentication; Usage Monitoring; DWT; SVD; Watermarking.

  • Optimization of optical burst switched networks using multi-objective bat algorithm   Order a copy of this article
    by Harpreet Kaur, Munish Rattan 
    Abstract: There is a growing demand for OBS (optical burst switching) networks, which is based on the concept of providing switching of data bursts without any intermediate switching and O/E/O conversions. The OBS technology is very economical and flexible to create new definitions for networking processes. OBS networks can also help in creating several types of new services which involve more bandwidth usage. The present research paper focuses on the OBS network and its benefits. The major problems of burst contention and congestion control using OBS networks are addressed in this research. In this paper, a possible solution to burst contention and congestion control is presented by the use of an algorithm, called BAT algorithm. The multiobjective optimization problem is solved using a MOBA (Multiobjective BAT) algorithm. The results of the MOBA algorithm are demonstrated in optimizing the performance metrics of the Optical Burst Switched Networks. Static traffic was considered for three different types of networks which were modeled using MATLAB. The proposed algorithm presented effective results to maximize the traffic demand, burst loss ratio minimization, and reduction in overall burst block probability. The final results of the simulation showed that the network is able to handle the huge amount of traffic while communication with the help of Multi-Objective BAT algorithm.
    Keywords: Optical Burst Switching (OBS) networks; BAT Algorithm; burst contention; burst loss ratio; Congestion Control; Burst blocking probability.

  • A STUDY ON MACHINABILITY BEHAVIOR OF Al6061-ZnO(P) METAL MATRIX COMPOSITE THROUGH WIRE CUT ELECTRO DISCHARGE MACHINING USING MULTI OBJECTIVE OPTIMIZATION ON THE BASIS OF RATIO ANALYSIS (MOORA)   Order a copy of this article
    by SAKTHI SADHASIVAM RM, RAMANATHAN K 
    Abstract: Aluminium matrix composites (AMC) are effective and qualified material in the industrial domain. They are broadly used in automobile, aerospace, marine and structural applications due to their awesome mechanical properties. Due to the presence of abrasive reinforcing particles, conventional or formal machining of these materials induces severe tool wear, poor surface finish and thus reduces tool life. Hence by un-conventional machining methods these materials are machined and in manufacturing, these methods are continue to raise at an accelerated rate. Wire-cut electro discharge machining (WEDM) is one of the best un-conventional machining process for AMCs. In this work, an attempt has been made to fabricate aluminium (A6061) metal reinforced zinc oxide (ZnO) particles by the stir casting technique and determine the machinability behavior of the sample. The process parameters regarded are pulse on (μs) time, voltage (v) and wire feed rate (f) and the measurable output parameters are metal removal rate (MRR) and surface roughness (Ra). The number of experiments are carried through taguchis L9(33) orthogonal array as per design of experiment procedure. Among the various optimization processes, MOORA is one of the effective multi-objective optimization method to determine the best condition for machining on the basis of ratio analysis. The results determined are used for the manufacturers to choose the best condition for machining the AMCs using WEDM.
    Keywords: AMC; WEDM; L9 orthogonal array; MOORA; ANOVA.

  • Parameters Optimization of Support Vector Machine Using Modified Grasshopper Optimization Algorithm Based L   Order a copy of this article
    by Gehad Sayed, Ghada Khoriba, Mohamed Haggag 
    Abstract: Grasshopper optimization algorithm (GOA) is one of the most recently meta-heuristic optimization algorithms. It was first developed by S. Saremi et al. in 2017. Although, GOA has shown good performance, it still has demerits respect to low precision, slow convergence and easily stuck at local minima. This paper presents a modified version of GOA based on L
    Keywords: Lévy-Flight; Global Optimization; Parameters Optimization; Support Vector Machine.

  • Aggregated Symmetric Key Based Hierarchical Group Data Sharing in Cloud   Order a copy of this article
    by Sijo Panicker, Mohamed Shameem P, Mruthula NR 
    Abstract: Cloud computing can be defined as a type of computing that relies on sharing computing resources rather than having local servers or personal devices to handle applications. Cloud storage is a model of data storage where digital data is stored in logical pools and the physical storage spans multiple servers and multiple users. Data sharing is the major advantage in cloud computing hence cloud computing security is a major concern. Cloud computing security refers to the set of procedures, processes and standards designed to provide information security assurance in a cloud computing environment. The capabilities of selectively sharing encrypted data with different users via public cloud storage may greatly ease security concern over inadvertent data leaks in the cloud. A key challenge to designing such encryption scheme lies in the efficient management of encryption keys to be used for the documents .In order to examine the flexibility, scalability and fine grained access scheme of outsourced data in cloud computing, this paper introduces a new scheme called Aggregated Symmetric Key Based Hierarchical Data Sharing scheme by extending the file sharing capabilities of Key Aggregate Searchable Encryption (KASE) with a hierarchical taxonomy. In HASK we propose an algorithm called Hierarchical Asymmetric Searchable encryption HASK as the enhanced scheme for KASE.
    Keywords: Identity based encryption; HASK; access control; KASE.

  • Optical fiber long period grating based chemical sensor for the analysis of silica in boiler water   Order a copy of this article
    by A.J.I. BALAN PILLAI, Benjamin Varghese Pandikudy, Kottarathil Naduvil Madhusoodanan 
    Abstract: Silica deposits in turbine blades, boiler tubes and cooling water circuits lead to serious loss in efficiency of power plants. Hence silica deposition is one parameter that is seriously monitored in power stations. Fiber optic sensors, especially long period grating sensors have been found to offer a convenient method for the accurate determination of silica in boiler water. We are hereby reporting the design, development and characterization of a novel long period grating based fiber optic sensor for the accurate analysis of silica. A highly sensitive LPG is fabricated. A suitable set up consisting of a Teflon cell, a broad band source and an optical spectrum analyzer is developed. The reactive silica measurement is carried out using the heteropoly blue colorimetric method. Detailed analysis of silica is done using the developed sensor, a spectrophotometer and an evanescent wave fiber optic sensor and the results are provided.
    Keywords: Long period grating; silica analysis; heteropoly blue method.

  • Triple Notch Slotted Monopole Antenna with Complementary Split Ring Resonators   Order a copy of this article
    by Madhav BTP, Ramya U, Lakshman P, Prabhakar VSV, Venkateswara Rao M 
    Abstract: This paper solemnly aims on demonstrating the triple band notched design of ultra-wideband with complementary split ring resonator (CSRR) along with inverted T-shaped stub in the patch. The designed antenna occupying the compact size is of 24.8mmX30.3mm. Proposed antenna was fabricated on RT/duroid material with Ɛr of 2.2 and height 0.8 mm. It is emitting an unvarying dipole like pattern in E-plane and omni directional pattern in H-plane in the UWB band. Amalgamation of defected ground structure (DGS), CSRR and inverted T-shaped stub results in characteristics frequencies of triple notch bands at 4.4 GHz (aeronautical radio navigation), 6.8 GHz (RFID) and 9.2 GHz (Radar applications) respectively. Simulation was performed by HFSS to analyse antenna parameters at desired frequency bands. A stable gain of 4 dB over the operating band is obtained except at notch bands. The prototyped antenna is providing excellent matching results with simulation results.
    Keywords: Complementary Split Ring Resonator (CSRR); Defected Ground Structure (DGS); Slotted Monopole; Triple Notch.

  • Factors influencing entrepreneurial intention among college students: a survey of research models 20062015   Order a copy of this article
    by P. Sumathi, V. Kumaravel 
    Abstract: In todays world, entrepreneurship is seen as a major economic wealth in many places and it is also a best medicine for unemployment problem in developing countries. The objective of this study is to study the inter relationship between demographic factors and entrepreneurial intention and to examine the role of curriculum in entrepreneurial intention of students. The data, we used for analysing entrepreneurial intention were collected from various journals by different authors reviews from the period of 20062015. The most of the models mainly are analysed with the base of theory of planned behaviour (TPB) model that includes, subjective norms, attitude towards this behaviour and perceived behavioural control. Results of this study show that many authors states the demographic factors will have less influence on entrepreneurial intention. Apart from that attitude and their personality traits will influence highly on entrepreneurial intention to become an entrepreneur.
    Keywords: entrepreneurial intention; entrepreneurship; unemployment; attitude.

  • A multi-objective optimization of TIG welding parameters using Response Surface Methodology   Order a copy of this article
    by Shekhar Srivastava, Sandeep Kumar, Rajiv Kumar Garg 
    Abstract: This study is aimed to examine the effect of different variables such as gas flow rate, travel speed and current for the welding of mild steel (IS:2062) with TIG welding. In this study, an effect of the identified variables has been studied on bead width, bead height and penetration. Pilot experiments were performed to find the most effective levels of factors to be used for experimentation. Experimental runs have been designed using Central Composite Design (CCD) technique and analysis had been done to inquest the action of different input parameters on output parameters quality characteristics. The selection of the range of input parameter was done on the basis of the size of the specimen. On the basis of experimental observation, the mathematical model has been formed using regression analysis through statistical software. An attempt has been made to minimize the bead width and height and maximize the depth of penetration using response surface methodology.
    Keywords: Bead Geometry; CCD; Gas Flow Rate; Penetration; RSM; TIG.
    DOI: 10.1504/IJCAET.2021.10021175
     
  • Aeroengine State Prediction Based on Generative Adversarial Networks and Deep Learning   Order a copy of this article
    by Qiang Fu, Huawei Wang 
    Abstract: The artificial intelligence technology represented by deep learning provides the possibility to make a comprehensive characterization of the aeroengine state from state monitoring information. The premise of these algorithms is based on big data. Thus, how to obtain a sufficient sample size of monitoring data has become a bottleneck restricting its application. First, this paper applies the generative adversarial networks to generate aeroengine condition monitoring data to expand data volume. Experimental results confirm that the generated data can reflect the regularity of the original monitoring data after a large number of network training iterations. Second, the deep learning algorithm is employed to predict the aeroengine status of the monitoring data and its generated data. Prediction accuracy is compared with the traditional neural network prediction method, which demonstrates the effectiveness of the deep learning prediction and the combination of the generative adversarial networks and deep learning. This aspect can solve the problem of limited data volume. By contrast, this feature can realize the deep excavation of condition monitoring feature information, which provides the possibility of comprehensively and accurately characterizing the aeroengine state. The GAN method simultaneously provides data support for the inaccurate deep learning prediction of the performance state of the aeroengine condition monitoring data.
    Keywords: aeroengine; deep learning; generative adversarial networks; state prediction.

  • Adaptive neuro-fuzzy approach for prediction of global solar radiation for twenty five cities falling under seven K   Order a copy of this article
    by VINAY ANAND TIKKIWAL, Sajai Vir Singh, Dinesh Bisht, Hari Om Gupta 
    Abstract: Estimation of solar energy is essential for the identification of suitable locations for solar based energy systems and their optimal sizing. In this work, capability of adaptive neuro-fuzzy inference system (ANFIS) for the estimation of global solar radiation has been investigated for 25 different locations in India. Using geographical parameters like latitude, longitude, and, altitude, along with meteorological parameters such as sunshine duration, temperature as inputs, five ANFIS models have been developed. The relevant significance of input parameters with respect to global solar radiation has been evaluated using the regression method. The accuracy of prediction for the models has been evaluated using standard statistical indicators including mean absolute percentage error (MAPE), mean bias error (MBE), root mean square error (RMSE) and, t-statistic. The models have been ranked using the rank score method. For the best ANFIS model, MAPE= 9.7%, RMSE= 0.80 and, MBE= 6.6E-06 were obtained. The results indicate that the developed models have good prediction accuracy for cities having starkly different climates.
    Keywords: Global Solar radiation; Neuro-fuzzy computing; ANFIS; Prediction; Solar Energy; Renewable Energy; Artificial Intelligence; Soft Computing.

  • Investigating the Teaching of " Advanced Quality Methods" Through Lean Manufacturing Techniques in Industrial Engineering   Order a copy of this article
    by Isam Badawi 
    Abstract: Advanced Quality Methods (ISE420) is one of the elective courses of the industrial engineering curriculum at The University of Hail (UoH). The purpose of this research is to determine whether the 5S hands-on exercise resulted in improving students understanding of lean manufacturing techniques. The theoretical part was covered through lecturing, case studies, and speakers from Hail Industrial City (HIC). The experimental part was covered through hands-on exercises and field visits to selected industrial companies at HIC. The 5S hands-on exercise provided students with a great learning opportunity as it helped them to better appreciate the efficiency of lean manufacturing in reducing the process assembly time in laboratory experiments from 3315.6 seconds to 849.6 seconds. The exercise procedures enhanced the students ability of recognizing the lean manufacturing waste identification. Students were more motivated to explore team-based projects, evolved a better level of interdependence, and increased their innovation abilities through lean manufacturing methodology.
    Keywords: Lean Manufacturing; Quality Methods; 5S; Manufacturing Waste.

  • Finite element analysis of the side bolster beam of the wagon tippler   Order a copy of this article
    by Om Prakash, ANIL C. MAHATO 
    Abstract: Wagon tippler unloads the raw materials from an open type railway wagon by tilting it upto 160 deg. from its pivot point. The main components of the tippler are side bolster beam, cradle platform, a pair of end rings with gear, hydraulic clamping assembly, two pinions and a long line shaft (LLS). The output power of the drive unit is transmitted to two different pinions which are mounted at both ends of the LLS. The failure of LLS assembly stops the tippler operation completely. To avoid the situation, an alternative approach i.e. the output power of the drive unit is transmitted to the drive side end ring, only, and further the power is transmitted to the non-drive side end ring through side bolster beam. That approach leads to eliminate the need of LLS. A side bolster beam, which supports the loaded wagon during tippling operation, is also utilized as a power transmission unit. The side bolster beam is subjected to combined stresses, i.e. bending and torsional, due to loading and power transmission, respectively. A failure analysis is performed on the existing design of the side bolster beam using the Finite Element Analysis (FEA) technique to examine its strength.
    Keywords: Wagon tippler; side bolster beam; modelling and simulation; finite element analysis.

  • Surrogate Based Model for Metamaterial Synthesis   Order a copy of this article
    by Sambhudutta Nanda, Prasanna Kumar Sahu, Rabindra Kishore Mishra 
    Abstract: In this work, we propose a novel CAD (Computer-aided design) model design for metamaterial analysis, based on Neuro-Space Mapping. Neuro-Space Mapping is a combination of two Robust optimization techniques, Artificial Neural Network and Space Mapping (Surrogate-based modeling). The developed model calculates the permeability of a metamaterial unit cell, for which closed-form formula is not available. The model takes the dimensions of the metamaterial unit cell as the input, and the gives the output as the SRR (Split Ring Resonator) dimension. From the SRR dimension, the material parameters are calculated using available closed-form formula. The model is first developed with a Ω-atom unit cell, and then verified applying the model to a Deformed- Ω atom unit cell.
    Keywords: Metamaterial; ANN; Space Mapping; FLANN.

  • UML/Event-B based modeling and verification of the car cruise control system   Order a copy of this article
    by Boutekkouk Fateh, Merouani Hemza, Merouani Imad 
    Abstract: Method B, as well as its Event-B extension are formal methods used for therndevelopment of computer systems whose accuracy must be formally established.rnEvent B development is an incremental specification of multiple machines/contexts. Itrnstarts with an abstract mathematical specification of the system and ends with therncorresponding computer code. A great asset of Event-B is the Rodin platform, whichrnis based on Eclipse and can be extended with plug-ins.rnThe iUML-B plug-in is the combination of the UML notation and the Event-Brnmethod. It allows generating an Event-B code automatically from two views: staticrn(class diagrams) and dynamic (state/transition diagram). The functional view is notrntaken into account by Rodin. To remedy to this problem, we propose a flow ofrnspecification and formal verification based on the UML notation and the Event B.rnThis flow is carried out by successive refinement starting from a very abstractrnspecification purely functional based on the UML case diagram. To validate ourrnapproach, we applied our flow to the car cruise controller system.
    Keywords: Intelligent cars; Cruise Control system; Formal verification; Event-B; Rodin platform.

  • Physico-tribo-mechanical performance and multi-criteria ranking optimization of novel Eriphorium-comosum/polyester composites   Order a copy of this article
    by Shivani Chauhan, Jitendra Katiyar, Vinay Patel 
    Abstract: Natural fiber composites are of extensive in demand owing to ecofriendly attributes of natural fibers such as high specific strength and stiffness, renewability, biodegradability, less energy consumption and low CO2 emission. In the current research, a novel Himalayan natural fibers i.e. Eriphorium-comosum (Hairy Cottongrass) is introduced as a reinforcing fiber to polyester resin. The physico-tribo-mechanical properties of the hand-layup fabricated polyester composites were evaluated for different sizes (15, 30, 45, 60 mm) and weight percent (3, 6, 9%) loading of Eriphorium-comosum fibers. The properties are optimized by applying multi-criteria TOPSIS technique which demonstrates that the polyester composite reinforced at 3 wt.% loading of Eriphorium-comosum of size 45 mm exhibits the best overall physico-tribo-mechanical performance.
    Keywords: Polyester composite; natural fiber; polymer composite; mechanical properties; tribology,.

  • An Approach For Optimization of Flexible Flow Shop Group Scheduling With Sequence Dependent Setup Time And Preventive Maintenance   Order a copy of this article
    by Ajai Jain, AVICHAL JAIN 
    Abstract: In the present work, a scheduling approach based on Genetic Algorithm is developed for flexible flowshop group scheduling with sequence dependent setup time (SDST) and preventive maintenance for minimization of makespan performance measure. The present work considers sequence dependent set up time among groups and among part types within a group. The performance of approach is evaluated in two manufacturing environments. Four case studies in each manufacturing environment are taken into consideration. Results indicate that the proposed methodology is able to address the various complexities of group scheduling problem with SDST and preventive maintenance.
    Keywords: flexible flow shop scheduling; sequence dependent setup time; Genetic Algorithm; preventive maintenance.

  • Lossless Compression of Biomedical Images using Block-Based Arithmetic Encoding Employing Resolution Independent Gradient Edge Detector   Order a copy of this article
    by Urvashi Sharma, Meenakshi Sood, Emjee Puthooran 
    Abstract: Medical imaging technology and its application for examining human body has grown very fast. Medical images generally require high spatial and temporal resolution images. However higher resolution image requires a large amount of data for its representation. Therefore, radiological modalities such as CT scanners, MRI, X-Ray etc. produce a tremendous amount of data which needs to be stored for many years in hospitals due to legal reasons. Compressing medical images will result in efficient storage and transmission of the data over a communication channel. Lossy compression techniques have high coding efficiency but they are not suitable for quality critical biomedical image compression. Near-lossless or lossless coding is essential in such case. Among various approaches of lossless compression of medical images, predictive coding techniques have high coding efficiency and low complexity. In this paper, a new technique is presented for lossless predictive coding using Resolution Independent Gradient Edge Detection (RIGED) and Block Adaptive Arithmetic Coding for different modalities of volumetric medical images. RIGED is used for pixel value prediction and coding redundancy is removed using Block based Arithmetic encoding. Block-based arithmetic encoding is applied to the residual image obtained using RIGED algorithm. An empirical analysis was performed on different block sizes to find optimum block size for higher compression. The proposed approach performs better as compared to the state of the art lossless compression algorithms CALIC and JPEG-LS in terms of compression ratio. Experimentation results on a set of volumetric medical images showed that the proposed technique provides an improvement over the CALIC and the JPEG-LS by 0.18 % and 6.65 % Bits Per Pixel (BPP).
    Keywords: Predictive Coding; Compressed Image; Bits Per Pixel; Block Adaptive Arithmetic Encoding; Compression Ratio.

  • Finite element analysis of long bolted extended end plate moment connections in cold formed steel tubular sections   Order a copy of this article
    by M.Senthil Pandian, M.Helen Santhi 
    Abstract: Recent advancements in computer and software technology have enhanced the use of finite element (FE) methods for the simulation of complex systems almost in all engineering domains. In this paper, 3D non- linear FE simulation of a long bolted extended end plate beam-column moment connection in a steel framed structure is investigated using ANSYS software. The simulation parameters such as the end plate thickness, number of bolts and column with and without concrete infill are considered to evaluate the performance of the connections. The simulation results are validated with the experimental test results and found that the FE models are capable of representing the actual behaviour of structures with less cost and time.
    Keywords: finite element analysis; simulation; end plate; long bolt; concrete infill; moment connection.

  • Effect of titanium oxide, alumina oxide and silicon carbide on mechanical properties and thermal properties of reinforced nylon composites for industrial applications   Order a copy of this article
    by S. Sathees Kumar, V. Vignesh 
    Abstract: This study deals with the determination of mechanical and thermal performances of Titanium Oxide (TiO2), Alumina Oxide (AO) and Silicon Carbide (SC) reinforced Nylon 6 (N6) composites. The composites are prepared by injection moulding method by varying the weight percentages. The effects of adding TiO2, AO and SC particles reinforced with N6 composites has investigated and result observed by tensile strength, impact and hardness test. The fracture surface morphologies have observed through Scanning Electron Microscope (SEM) method. Thermal performances of N6 composites are reviewed by the Thermogravimetric (TG) analysis. The exploratory comes about show that upon expanding the addition of TiO2 (5 wt.%), AO (10 wt.%) and SC (5 wt.%) particles improved the tensile properties and thermal stability of the N6 polymer matrix composites. In addition, the impact strength and hardness properties are escalate the expansion of SC (10 wt.%), TiO2 (5 wt.%), AO (5 wt.%) content with N6. For substantiate the work, the composite gear has fabricated for industrial and vehicle applications.
    Keywords: Alumina; Titanium oxide; Thermal stability; Silicon carbide;.

  • A revisited representation of the Red-black tree   Order a copy of this article
    by Lynda Bounif, Djamel Eddine Zegour 
    Abstract: Nowadays, the Red-black tree is probably the most used balanced data structure. It searches, inserts and deletes keys in O log (n) time and it is highly recommended for applications with frequent updates. However this balanced binary tree is complicated in the implementation because of the different cases in both the insertion and deletion and the use of the red and black colors. Thats why we propose in this paper a simpler representation of this structure. The new representation uses one extra bit in order to gain simplicity and efficiency. The Red-black tree is seen as a partitioned binary tree and uses instead of colors three kinds of subtrees: 01, 10 and 11 subtrees. We show on one hand that we can simply express the insert algorithm, and on the other hand that the performance of the algorithm is slightly better. Efficiency is due to the fact that the search branch used in the new representation is reduced by half. Therefore this representation can replace easily the standard algorithms of Red-black tree in practice.
    Keywords: Binary search trees; balanced trees; Red-black tree; data structure.

  • Fatigue and dynamic analysis on a disc brake with different slots in the friction material under finite life condition   Order a copy of this article
    by Naresh Kumar Konada, Suman Koka Naga Sai 
    Abstract: In the present research work, an attempt is made to study and analyze the behaviour of a disc brake assembly for fatigue and dynamic loads under finite life condition. Friction material cross section is varied in this work (No slot, single slot, double slot, three slot and multi slot) sliding against a gray cast iron disc. The pressure acting on the friction material is varied from 1MPa to 4MPa with sinusoidal loading for fatigue analysis. Dynamic analysis is performed by applying angular velocity to the disc and impact velocity to the friction material. Dynamic analysis is performed starting from 1000 cycles to 100000 cycles on the disc brake assembly. Both fatigue and dynamic analysis are performed based on few assumptions. The values of vonmises stress and deformation for different configurations of disc brake pad systems are evaluated using ANSYS software, finite element methods and the best configurations of materials are selected for the design.
    Keywords: Carbon fiber; Grey cast iron; Solid works; FEM; Fatigue and dynamic loading; Finite life.

  • ERSA: Enhanced RSA Cryptography Algorithm to Guarantee High Security Level for Data in Cloud Environment   Order a copy of this article
    by Sivakami Kathiresan, Umadevi V 
    Abstract: Cloud computing includes ubiquitous advantages and applications that probe many enterprises towards it. However, data security and user security are still major trepidation in cloud environment where an efficient cryptography scheme is required. To tackle this security problem, this paper presents a novel enhanced Rivest Shamir Adleman (ERSA) algorithm to ensure high security level in cloud environment. Here three major phases that are utilized ERSA algorithm are involved to resolve security threats in cloud. Security enhancement is realized by following phases: (i) authentication phase in which ERSA based digital signature is utilized for user authentication, (ii) evaluation phase exploits fuzzy inference system (FIS) for ensuring required security level, and (iii) encryption phase involves with ERSA algorithm for encrypting data to be stored in cloud. ERSA algorithm improves security in two ways. One is by generating prime numbers accordance to required security level using Sieve of Atkins (SoA) algorithm. Another one is by enhancing security of RSA key with the help of non-prime factor. Involvement of non-prime factor improves security level while involvement of SoA minimizes time consumed for key generation. Thus RSA algorithm is improved in terms of security level and time consumption through simple computations in ERSA algorithm. Extensive simulation results ensure better performance in encryption time, decryption time, key generation time, and security level.
    Keywords: Enhanced-RSA; Sieve of atkins; Fuzzy inference system; Non-prime factor; Authentication; Cloud.

  • Effect of tension-stiffening on finite element analysis of glass fiber reinforced polymer (GFRP) reinforced concrete members   Order a copy of this article
    by Md Shah Alam, Amgad Hussein 
    Abstract: Glass Fiber Reinforced Polymer (GFRP) bars have different mechanical properties than conventional steel reinforcing bars. Concrete members reinforced with these bars behave differently than steel reinforced members. Tension stiffening is the properties of carrying tension in between cracks of reinforced concrete members. This paper presents the results of an investigation into the effect of tension stiffening in nonlinear finite element analysis of concrete beam reinforced with glass fiber reinforced polymer (GFRP) bars. The beam that was investigated was identical of a test beam. The test beam was reinforced in longitudinal direction and there was no shear reinforcement, i.e. shear critical beam. The influence of tension stiffening on different behavioral aspects including load deflection behavior, ultimate load, and deflection are discussed along with a comparison with the test results of the beam. The analysis was carried out using commercial finite element analysis (FEA) software, ABAQUS. The concrete model was calibrated before using in the analysis. The results revealed that the tension stiffening model has great influence on FEA of GFRP reinforced beam and some of the models are not suitable for FEA of shear critical GFRP reinforced concrete beam.
    Keywords: Reinforced Concrete; Material models; Shear Behavior; Finite Element Analysis; GFRP Reinforcement; Tension-Stiffening.

  • An Improved Fuzzy Adaptive Teaching Learning-based Optimization Algorithm for Generating Pairwise Test Suites   Order a copy of this article
    by Fakhrud Din, Kamal Z. Zamli 
    Abstract: Pairwise testing has proved its applicability to adequately test software with huge number of inputs. It can avoid the otherwise impractical exhaustive testing by employing an efficient sampling strategy. Strategies based on meta-heuristic algorithms offer optimal pairwise test suite sizes for software applications. Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm has shown competitiveness against other meta-heuristic-based strategies in terms of pairwise test suite generation. Although useful, the present design of ATLBO is lacking in dealing with stagnation or abnormal convergence after some iterations. A remedial operator is introduced in ATLBO in order to address this issue and hence further enhance its convergence speed. With this modification, ATLBO is used for the pairwise test suite generation problem. From the conducted experiments, it can be concluded that the performance of ATLBO with remedial operator is comparable with other pairwise strategies based on hyper-heuristic, meta-heuristic and greedy algorithms.
    Keywords: Pairwise Testing; Adaptive Teaching Learning-based Optimization; Mamdani Fuzzy Inference System.

  • Dynamical Model for Dispersion of Toxicity due to Vehicles   Order a copy of this article
    by Nita Shah, Moksha Satia, Foram Thakkar 
    Abstract: Vehicle is the major source used for transporting an instrument from one place to another place, especially on land. The use of vehicle is not limited to the transportation for an individual but it can also be used to transport cargo materials. Life-span of the vehicle is the estimation key for knowing how much the vehicle is polluted. Management of vehicles can save the toxicity spread. Therefore, a model is proposed to analyse the impact of the dispersion of toxicity due to vehicles. The model consists of three types of vehicles private, public and cargo vehicles which are divided into polluted and non-polluted vehicles and lastly its contribution to create toxicity. The model deals with the system of non-linear differential equations. Stability and backward bifurcation of model are worked out. Trajectories analysis is performed to support the derived results.
    Keywords: Keywords: Mathematical model; Polluted and non-polluted vehicles; Toxicity; Stability; Backward bifurcation.

  • Mitosis Detection from Histological Images using Handcrafted features and Artificial Neural Network   Order a copy of this article
    by Hanan Hussain, Omar Hujran, Nitha KP 
    Abstract: Breast cancer is one of fatal cancer that affects women across the globe. It occurs due to the abnormal changes in DNA and results in the rapid division of cells called mitosis. Mitosis count in histopathological images is relevant since it is one of the factors required to predict the Grading of cancer. Due to a huge number of mitosis count present in the examining slide, a huge amount of time is wasted for manual detection done by a pathologist, Further, it is subject to human prone errors. In order to provide accurate and fast detection, a new approach for mitosis detection using handcrafted features along with Artificial Neural Network (ANN) for histopathological images is proposed. This approach includes three steps: Image Preprocessing, Segmentation, Feature, and Classification. Preprocessing involves conversion on RGB image to Red channel since they provide the best distinction of nuclei from the cytoplasm, it is then converted it into a smooth image with intact cell boundaries in which data in boundary cells are preserved for further processing. Segmentation includes the selection of candidate cells, which is done using Fuzzy C means clustering, where a joined component with the biggest area is considered as background and other joined components as cells. For Hand Crafted (HC) feature extraction, Intensity feature and textural features are selected from segmented cells of Red channel and Green channel image. Finally, during Classification, Random Forest (RF) classifier is trained using selected HC features and ANN is trained using a bag of features. Both ANN and RF are ensemble to predict the outcome. Cells are detected as mitotic and non-mitotic after classification, If not classified by any of the above classifiers, then their weighted average is taken and the final outcome is predicted. The system was tested with inputs from public dataset Mitos-Atypia14 and an accuracy of 91.6% is obtained.
    Keywords: Breast Cancer Detection; Mitosis Detection; Artificial Neural Network; Random Forest Classifier.

  • DEVELOPING AN OPTIMAL MAPREDUCE FUNCTION FOR WIRELESS SENSOR NETWORKS IN A SECURE WAY   Order a copy of this article
    by Priya Vedhanayagam 
    Abstract: In this research work, security risk in Wireless Sensor Network is addressed and an efficient approach to overcome security issue and to reduce the energy depletion in WSN was proposed. Here, sensors are grouped into three different clusters and cluster head is elected for each on the basis of sensing ability, battery power and memory. The nodes find the shortest path, forms the network to send the sensed data to CH in an encrypted form in a peer to peer manner. The CH will decrypt, aggregate the data received from the cluster before sending it to the BS to reduce the energy consumption and CH generate a signature by using three types of keys to ensure the authenticity. The communication from CH to BS is broadcast. Now the BS verifies the sign and the large dataset (observed, historical) are processed parallel in map reduce paradigm for query processing.
    Keywords: Wireless sensor network; data aggregation; nodes; cluster head; MapReduce; security.

  • Interactive administration service based on HMM speech recognition system   Order a copy of this article
    by Mohamed Hamidi, Hassan Satori, Ouissam Zealouk, Khalid Satori, Naouar Laaidi 
    Abstract: The objective of this study is designing a secure interactive Amazigh speech system over the VoIP network. Our work explores the use of Interactive Voice Response (IVR) system to manage the firewall and backup tasks where a voice platform was created based on HMM automatic speech recognition. To increase the security level the biological voiceprint is adopted for identification and management tasks. The speech system is trained to recognize the five words, thirty-three alphabets and ten first digits of Amazigh language. We performed experiences by varying IVR and ASR system parameters to manage a distant voice control administration system of the network. The designed system was implemented on the open source solution. Our finding shows that the best performance for admin test is above 80 % when the system was trained by using 3 HMMs and 8 GMMs whereas the non-admin recognition rate is less than 5 % which demonstrates the security aspect of our system.
    Keywords: Automatic speech recognition; IVR; Asterisk server; Amazigh language.

  • An intelligent Decision support system based on collaboration and case-based reasoning   Order a copy of this article
    by Latifa Boudjellali, Noria Taghezout, Fatima Zohra Benkaddour 
    Abstract: This paper presents an intelligent decision support system as a real contribution to solving key disaster management problems. The objective is to reach the stage of collaboration and identification of the availability of human and material resources for the various modules of the emergency organization plan. The collaborative environment supports the various actors in a process of planning and implementing disaster emergency preparation by using videoconferencing for real-time analysis and decision-making. We propose the system architecture, including several modules such as case reasoning, ontology and similarity measurement. In order to be able to trigger the action plan within a given time frame, we integrate videoconferencing to facilitate exchange on disaster information such as text, image, or video between experts. After collecting this information (the damage as well as the impact of the disaster that exceeds the capacities of local stakeholders and resources that are not available locally ...). The experts will do an effective analysis to identify the best way to collaborate. The interest is to provide an essential environment to define a structure plan, actions including an updated inventory of available resources for disaster management. Some experiments have been carried out in a province in western Algeria to evaluate the effectiveness of the proposed platform.
    Keywords: Intelligent Decision Support System (IDSS); Disasters management; Case-Based Reasoning(CBR); disasters ontology; Videoconferencing; ORSEC plan.
    DOI: 10.1504/IJCAET.2022.10024685
     
  • A Novel Value-based Multiplier Architecture to Multiply BCD Numbers by Powers of 10   Order a copy of this article
    by Mohammad Samadi Gharajeh 
    Abstract: Multiplying the BCD numbers by powers of 10 is one of the main elements in electronic circuits. The existing general multipliers perform this operation with high complexity and staggering financial costs. This paper proposes a novel multiplier to multiply BCD numbers by powers of 10. It uses a value-based architecture instead of the static architecture which is used in general multipliers. The proposed multiplier is composed of multiple embedded sub-multipliers so that each one multiplies one of the BCD numbers by the powers of 10. The multiplication results of each sub-multiplier are calculated by some mathematical equations based on input binary bits. Furthermore, the final output of the proposed multiplier are produced based the multiplication results of the sub-multipliers with the aid of a proposed selection unit. Whereas multiplying the BCD numbers by powers of 10 is one of the essential operations in complex circuits, the proposed multiplier can be used to improve the performance of existing electronic circuits. Comparison results demonstrate that the proposed multiplier surpasses some of the existing general multipliers in term of the number of logic gates. The proposed architecture is programmed by the VHDL codes and is simulated using the Active-HDL simulation environment.
    Keywords: Electronic Circuit; Multiplier; BCD Number; Power of 10; Value-based Architecture.

  • Audio Event Detection using Deep learning model   Order a copy of this article
    by Sophiya E, Jothilakshmi S 
    Abstract: Humans are surrounded by a complex audio stream that carries meaningful information about our everyday environment. Hearing is one of the most important capabilities to identify and detect audio events which require immediate action such as ambulance siren, gunshot, baby cry, etc. Thus, an automatic audio analysis is getting popular in recent years which have wide range of applications such as continuous monitoring for public safety, abnormal events, wildlife monitoring, health care, audio indexing and retrieval. The objective of the proposed system is to provide the event class and the event time boundaries between multiple events present in an audio. The proposed audio event detection is implemented with a deep learning model. The real time data are collected from major locations of urban city. Audio events were recognized using signal processing techniques. The model is learned from Log Mel spectrogram features.
    Keywords: Audio processing; Audio scene analysis; Audio event Detection; Deep learning; Deep Convolutional Neural Network.

  • Towards Reliable Electronic Exam Networks   Order a copy of this article
    by Gautam Srivastava, Jabbar El-Gburi, Senthilkumar Mohan 
    Abstract: In today's world, stable systems are what everyone is seeking. Furthermore, traits people desire in any system are trust, guarantees of security and fairness. Electronic exams should be considered as the hardest to defy to maintain trust in their relevance. Examination procedures concern any educational organization which leads to various security techniques being utilized in order to maintain a minimum required level of security. In this paper, we present a secure e-exam network system that performs several processes such as evaluation, and management where all components are in a digital layout. We present a cryptographic platform that should be considered to obtain the required security standards of any educational institution for exam administering networks.
    Keywords: cryptography; fairness; secrecy; security; e-learning; electronic exams security; networks.

  • Automated Question and Test-paper Generation System   Order a copy of this article
    by Abhijit Joshi, Neeti Vyas, Harsh Kothari, Akshay Jain 
    Abstract: This paper focuses on a very simple yet an issue of utmost importance in todays fast-paced life. Today everyone desires to get their work done on a click, so why not automate the time-consuming process of question generation. Automating the process of getting answers from a text, given a set of questions is simple to achieve and there are many websites and apps which can help us do the same. But reversing the process that is getting the questions from a given text is not as simple as it seems to appear. This paper focuses on the issue of generating questions from a given input text. A text document is given as input and our system will generate possible set of questions on it. The categories of questions range from MCQ questions, objective questions, factual and inference-based questions. NLP based tools are used for automating the process of question generation. Here focus is on three key areas, first being POS tagging followed by pronoun resolution and summarization. Once the text is resolved and summarized, then questions are generated based on it. In this system, one just needs to give the text document as input and gets the questions on the go. This system will be very beneficial for school teachers and students. It would assist teachers in generating questions, which would further lessen their burden and help them plan for better course works. It would help the students in tackling a wide range of questions, which would prove to be very beneficial for their exam preparation.
    Keywords: Question generation; NLP; discourse connective; distractor; pronoun resolution.

  • Automatic Scenario-Oriented Test Case Generation from UML Activity Diagrams: A Graph Transformation and Simulation Approach   Order a copy of this article
    by Abdelkamel Hettab, Allaoua Chaoui, Mohammed Boubakir, Elhillali Kerkouche 
    Abstract: Model-based testing (MBT) is an activity that allows designing and generating test cases from the initial specification of the system under test (SUT).rnUML (Unified Modeling Language) is a standard for model-based specifications, while UML-ADs (UML Activity Diagrams) are usually used for modeling the overall behavior of systems. This paper presents a Graph transformation based approach to generate automatically scenario-oriented test cases from UMLADs.rnTo facilitate the test scenario generation process, an intermediate model called EADG (Extended Activity Dependency Graph) is proposed. The approach consists of generating EADG models from UML-ADs. Then, test scenarios are generated from the obtained EADG models. This approach also allows testers to validate their proposed test scenarios by applying them on UML-ADs using a graphical simulation. All ideas presented above are implemented using the graph transformation tool AToM3. To this end, two meta-models and three graph grammars are proposed for presenting and generating EADG and test scenarios models, and for performing the graphical simulation. The approach is applied on a case study and experimental results show that our approach has a high rate of fault-detection capability. This approach can detect more defects in complex structures of concurrency and nested loops.rn
    Keywords: Automatic Test Case Generation; Graph Transformation; UML Activity Diagram; Model-Based Testing; Test coverage criteria; AToM3.

  • DEVELOPMENT OF A PRIORITY DISPATCHING RULE AND NOVEL PRODUCTION SCHEDULING ALGORITHM FOR JOB SHOP   Order a copy of this article
    by Narassima M S, Shriram K V, Anbuudayasankar S P 
    Abstract: Manufacturing industry plays a significant role in economic development of a country. There is always a need to improve the functioning of these industries. Efforts are being made to address the complex issues that arise every day in manufacturing sector. Job shop relates some such intricate problems as it handles a variety of jobs with varying demand. Current study involves improving the overall production process in a job shop handling several components. Any job shop problem involves sequencing and scheduling of incoming jobs. An initial observation was made to study the overall operational flow of the job shop. The study was organized into three phases, first phase relating to sequencing of jobs in a job shop for which a Priority Dispatching Rule (PDR) was developed using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Second phase involves the development of a Discrete Event Simulation (DES) model of the press shop in order to compare the performance measures of various PDRs. The final phase deals with the development of an active production scheduling algorithm that can generate an active schedule for a job shop. All these three phases need to be integrated for better, optimized solutions as they are all interdependent.
    Keywords: Production Scheduling; Job shop; Priority Dispatching Rules (PDRs); Technique for Order Preference by Similarity to Ideal Solution (TOPSIS); Discrete Event Simulation (DES); Active Scheduling; Production Scheduling algorithm.

Special Issue on: Computer-Aided Intelligent Systems

  • DOUBLE-PULSE STAND-OFF EXPLOSIVE VAPOUR DETECTION SYSTEM FOR FLEXIBLE PERILOUS MATERIALS   Order a copy of this article
    by Muthukumaresan Mb, Sakthivel S 
    Abstract: Most of the military organization now takes the help of robots to carry out many risky jobs that cannot be done by the soldier. These robots used in military are usually employed with the integrated system, Including video screens, sensors, gripper and cameras. The military robots also have different shapes according to the purposes of each Robot. Here the new system is proposed with the help of low power Zigbee wireless sensor network to trace out the intruders (unknown persons) an d the robot will take the necessary action automatically. Thus the proposed system, an Intelligent Unmanned Robot (IUR) Using Zigbee saves human live and reduces manual error in defense side. This is specially designed robotic system to save human life and protect the country from enemies.
    Keywords: Microcontroller; ZIGBEE module; IUR robot.
    DOI: 10.1504/IJCAET.2020.10022740
     
  • Optimized RBIDS: Detection and Avoidance of Black Hole Attack through NTN Communication in Mobile Ad-hoc Networks   Order a copy of this article
    by Gayathri VM, Supraja Reddy 
    Abstract: A Mobile Ad-hoc Networks which is an emerging technology in various fields of computer science along with Sensor Applications providing a big credential to the people via smart innovation. In this network, each node connected on requirement basis. Since it is infrastructure-less any node can come into the network topology and participate in the packet transmission. Each and every node in the network topology join based on their sequence number, distance, RF based calculation. Any node satisfies these requirements can involve in transferring packets as a router or intermediate nodes. It becomes an open door for the attackers to enter into the network which results more vulnerable state. In this paper, we are concern about the black hole attack in the network which results in dropping of packets where originally it has to send to the destination. It happens because of false identity of the node. Implementation using NS2 simulator on demand protocol namely AODV. An algorithm is proposed to improvise the network performance by detecting the malicious node called RBIDS. This algorithm applies on every individual node over a period of time to calculate their performance based on regression values.
    Keywords: NTN;RBIDS;AODV;Regression.

  • A new parallel DSP hardware compatible algorithm for noise reduction and contrast enhancement in video sequence using Zynq-7020   Order a copy of this article
    by MADHURA S, Suresha K 
    Abstract: Various video processing applications such as liquid crystal display processing, high quality video photography, terrestrial video recording and medical imaging systems requires robust noise reduction and contrast enhancement technique which provides visually pleasing For real time implementation novel hardware architecture has been designed using Look-Up-Table (LUT) acceleration approach which helps achieve high speed processing. Until now a lot of researchers have worked on noise removal and contrast enhancement of digital videos, but the developed algorithms works with only some verity of noises and failed to produce desirable results for various types of distortions and real-time implementation is still remaining a challenge. Hence appropriate filter needs to be designed which address both kinds of errors. In this paper adaptive trilateral filter has been designed for noise reduction, the results are measured using qualitative and quantitative analysis which has aided in better utilization of hardware for real-time implementation. The experimental results show that the proposed algorithm provides a frame rate of 40 fps on an average and has a resolution of 720x576. The proposed algorithm was implemented on ZedBoard Znyq-7020 development kit by Xilinx.
    Keywords: video enhancement; segmentation; trilateral filtering; real-time implementation; Znyq-7020.

  • HDFS Based Parallel and Scalable Pattern Mining Using Clouds for Incremental Data   Order a copy of this article
    by Sountharrajan S., Suganya E, Aravindhraj N, Rajan C 
    Abstract: Increased usage of Internet led to the migration of large amount of data to the cloud environment which uses Hadoop and Map Reduce framework for managing various mining applications in distributed environment. Earlier research activity in distributed mining comprises of solving complex problems using distributed computational techniques and new algorithmic designs. But as the nature of the data and user requirement becomes more complex and demanding, the existing distributed algorithms fails in multiple aspects. In our work, a new distributed frequent pattern algorithm, named Hadoop based Parallel Frequent Pattern mining (HPFP) has been proposed to optimally utilize the clusters efficiently and mine repeated patterns from large databases very effectively. The empirical evaluation shows that HPFP algorithm improves the performance of mining operation by increasing the level of parallelism and execution efficacy. HPFP achieves complete parallelism and delivers superior performance to become an efficient algorithm in HDFS, than existing distributed pattern mining algorithms.
    Keywords: Cloud Computing; Hadoop Distributed File System; Map Reduce; Association Rules; Frequent Pattern Growth Algorithm; Distributed Mining; Parallel Pattern Mining.

  • An Efficient Packet Image Transmission based on Texture Content for Border side Security Using Sensor Networks   Order a copy of this article
    by Pitchai Ramu, Reshma Gulsar, Raja Jayamani 
    Abstract: In the field of surveillance, several algorithms are developed to extract meaningful information from an image captured via a camera. In the presence of intrusion event, these cameras will transmit those captured images to the sink node via other intermediate nodes. Since, WSNs operate with limited resources, efficient utilization of resource is needed while processing and transporting images. Since the node does not need whole image data are mandatory. Prioritization is one of the methods to utilize the available resource. It will prioritize images from its macro-blocks dynamically. Here the camera is attached in a sensor node which forms Wireless Multimedia Sensor Networks (WMSN). Its employs an encoding scheme at the source node by naming the blocks as important or not-important based on the information they contain. Here image texture feature and spectral information is used as priority measures to weight importance of macro-blocks using their textural GLCM properties. Experimental results disclose that the priority encoding scheme adapts itself to the applications quality requirements while reducing the required bandwidth comparatively.
    Keywords: Wireless Sensor Network; Prioritization; Wireless Multimedia Sensor Networks; Texture; GLCM; Macro Block.

  • Hidden Object Detection for Classification of Threat   Order a copy of this article
    by Gautam KS, Senthil Kumar Thangavel 
    Abstract: The automated video surveillance has become important due to the focus from government and users for improving the smart nature of the buildings. A system developed for handling this can be used for prison, airport, banks etc. Though there are solutions for this they fail in situations of mishaps and objects that are hidden that could become a threat to the environment. In this paper a framework has been built using Modified K Means Segmentation Algorithm to detect hidden objects. The framework operates in two phases. Phase 1-Modified K Means Segmentation Algorithm for segmenting the hidden objects. Phase 2- Deep Convolutional Neural Network for classifying the hidden object The algorithm selects searched for the approximately optimal value of K and segments the object. The result of the algorithm is given to Deep Convolutional Neural Network for classifying the type of object. The algorithm is tested with manually built dataset using Fluke Tis40 Thermal Imager. The experiments were carried out in batches of 50*50 images and the performance of the approach is presented using Top-1 Accuracy and Mean Average Precision and they are 0.94 and 0.64 respectively. From the experimental analysis, we infer that the proposed algorithm works with precision 0.88 false discovery rate 0.12.
    Keywords: Video Analytics; Deep Learning; Deep Convolutional Neural Network; Thermal image; K-Means Segmentation.

  • Deep Learning based Techniques to Enhance the Precision of Phrase-Based Statistical Machine Translation System for Indian Languages   Order a copy of this article
    by Sanjanasri JP, Anand Kumar M, Soman KP 
    Abstract: The paper focuses on improving the existing Phrase-Based Statistical Machine Translation (PB-SMT) system by integrating deep learning knowledge to it. In this paper, a deep learning based PB-SMT system for Indian languages is developed, so as to improve the conditional probability of the phrase-table and replaced the neural probabilistic language model with the existing back off algorithm of n-gram language model to improve the performance of language model. It is shown that the deep feature based PB-SMT is better than the standard PB-SMT system. It is shown the significance of integrating manually created dictionaries that has been trained as separate translational model can enhance the result of statistical machine translation system when decoding. For automatic evaluation, it is shown that RIBES being a better evaluation metric for Indian languages compared to BLEU, a standard one.
    Keywords: Indian Languages; Phrase-based Statistical Machine Translation (PB-SMT); Neural Probabilistic Language Model (NPLM); Deep Belief Network (DBN); Pruning; Minimum Error Rate Training (MERT); Bilingual Evaluation Understudy (BLEU); Rank-based Intuitive Bilingual Evaluation Score (RIBES).

  • Enhancing Performance Of WSN By Utilizing Secure Qos Based Explicit Routing   Order a copy of this article
    by Kantharaju HC 
    Abstract: Wireless Sensor Networks (WSN) are infrastructure less and self-configured wireless networks that allows monitoring the physical conditions of an environment. Many researchers focus on enhancing the performance of WSN in order to provide effective delivery of data on the network, but still results in lower quality of services like data transmission time, energy consumption, delay and routing. We tackle this problem by introducing a new routing algorithm, QoS based Explicit Routing Algorithm which helps in transmitting the data from source node to destination node on WSN. We also involve clustering process in WSN based on GA and PSO algorithm (Genetic Algorithm and Particle Swarm Optimization) and followed by cluster head selection process which is more important on the routing process. Secure communication is the most important need for WSN, for that we propose IBDS (Identity based Digital Signature) and EIBDS (Enhanced Identity based Digital Signature) that involves reduction of computation overhead and also increasing resilience on the WSN. We also use AES (Advanced Encryption Standard), for ensuring the security between nodes and avoid hacking of data by other intruders. This process is done on base station, sensor nodes and cell coordinator nodes. Thus our proposed framework is effective by increasing the lifetime of nodes, improving secure communication between nodes.
    Keywords: Wireless Sensor Network; Cryptography; Digital Signature; Quality of Service.
    DOI: 10.1504/IJCAET.2020.10019757
     
  • Hybrid Data Model Of PACE and Quadruple: An Efficient Data Model for Cloud Computing   Order a copy of this article
    by CLARA KANMANI, Dr Suma V. , Guruprasad N 
    Abstract: Cloud computing is a promising computing paradigm that involves outsourcing of computing resources with the capabilities of expendable resource scalability, on-demand provisioning with little or no up-front IT infrastructure investment costs. The semantic web is an extension of the web through standards by the World Wide Web consortium (W3C). Resource Description Framework (RDF) is the semantic data model for cloud computing which provides interoperability but is not effective in terms of scalability, formal semantics and query optimization and reification. One of the challenges in cloud computing therefore is to enhance RDF data model which is achievable by addressing the current weakness of RDF reification mechanism.This paper hence put forth a comprehensive overview of challenges in RDF Reification. Further, the paper introduces a data model which uses hybrid approach of Provenance aware context entity(PACE) and quadruples method of reification. This hybrid RDF data model is deployed and tested for its performance on the AWS public cloud. Experimental results indicate that the proposed hybrid data model enhances accessibility, maintainability, and also accelerates query execution time.
    Keywords: Cloud computing; Semantic web; Resource description framework; Data model; PACE; Quadruple.

  • A Semi-Automated System for Smart Harvesting Of Tea Leaves   Order a copy of this article
    by Manesh Murthi, Senthil Kumar Thangavel 
    Abstract: Tea leaf cultivation is a major part of livelihood in hill station like Nilgiris. The conventional method of tea leaf plucking is done manually with a knife. Harvesting machines have also been designed that could quickly This gives better result in manpower who has better experience and knowledge about terrains. The paper has proposed a semi-automatic working model that has an arm that can move around and pluck the leaves. A complete preprocessing phase has been done using key frame extraction, rice counting, optical flow with noise model by the author in an earlier paper. This process is improved by using Active contour with optical flow algorithm that minimizes the region on which the tea leaf detection algorithm is applied. The second phase of the paper also suggests how deep learning approach can also be used for improving the performance of the proposed work. The proposed work is novel because it has capabilities of considering motion with keyframe capabilities and the noise model using deep learning. The proposed work has experimented with parameters like precision, recall, FAR, FRR to evaluate the nature of misclassifications.
    Keywords: Video analytics; Noise model Keyframe; Raspberry Pi; Arduino due; optical flow; rice counting; segmentation.

  • HYBRID WIND-SOLAR SYSTEM AN OPTIMIZED APPROACH FOR EFFICIENT POWER GENERATION   Order a copy of this article
    by RAVIKUMAR SUKUMARAN 
    Abstract: The most popular renewable energy technology is Hybrid Power System consisting of wind and solar energy sources because the system is reliable and complimentary in nature. Wind / PV Hybrid system is commonly used in Distributed Generation (DG). This paper proposes a new solution for improved voltage stability with quality power output. In this system voltage out from wind energy conversion system(WECS) and Photo voltaic panel are given to separate DC - DC converters, independently controlled and connected to a common D C bus and from there it is inverted. In the proposed controller the voltage stability is obtained by applying Honey Bee (HB) optimization algorithm along with a PI controller. The implementation of the proposed method is done by using Simulink platform. The performance of the suggested co ordinated control system is analyzed by comparing the computer simulation results with and with out using controllers and it shows that the proposed system is more efficient.
    Keywords: Hybrid Power System ; Distributed Generation(DG); Honey Bee algorithm; PI; Wind and solar energy.

  • PV CONTROL SYSTEMS USING ITERATED LOCAL SEARCH MPPT WITH AN IMPROVED SWITCHED CAPACITOR DC-DC CONVERTER   Order a copy of this article
    by Mohan Kumar JK, Abdul Rauf H, Umamaheswari R 
    Abstract: An optimization to the steady state performance of wide range of SC Converters made use in control of Photo Voltaic (PV) systems that aims to enhance its efficiency and Output Regulation performed by a Switched Capacitor Direct Current (SCDC) converter is proposed here. This uses many Power Converters to effectively transmit power via a large cable with greater Electro Magnetic Interference (EMI).Under no-load conditions this explained model shows that an Ideal DC voltage transformation is achieved by the converter and the loss during the conversion are altered because the drop in voltage due to the non-zero load current measured at the impedance at load side has lesser Electro-Magnetic Interference (EMI). The charging of capacitor and loss during discharging and the conduction loss at resistance is mainly due to the impedance of output resistance. Followed by this, our DC to DC converter is extended to a smart control technique to track Maximum Power Point (MPPT) of a PV system with constraints of varying temperature and irradiance along with ILS (Iterated Local Search).
    Keywords: Direct Current (DC) Converter; Photo-Voltaic (PV) System; Iterated Local Search (ILS) and Maximum Power Point Tracking (MPPT.

  • Artificial Intelligent Technology for safe driver assistance system   Order a copy of this article
    by Takialddin Al Smadi, Mohammed Al-Maitah 
    Abstract: This paper mainly studies Artificial Intelligent Technology for safe driver assistance. Intelligent vehicle, (IV) the system the capacity of AI to control the cars is difficult to overestimate. For example, unmanned machines require onboard systems that can handle a huge amount of data from the surveillance cameras, sensors, navigators, sensors measure the distance, etc. Of course, to recognize and analyze thousands of requests, Speed limit transmitted from placed transmitters in the road, to a receiver mounted inside the car somewhere on the dashboard of the vehicle and is a digital display indicating the current speed limit and the current car speed. This gave the driver a time to worry about other driving limitations, which carry out a safety driving in roads and not exceed a speed limit in them. As a result of using this device, we avoid the car accidents caused by exceeding the speed limit, traffic fouls by radars, and traffic fines. The work in this paper which Could be developed by adding another transmitter at the car side, to send each fine with its time, date, and the car ID , to another receiver fixed on the road side, this step could make the documenting process of the car violations easier for the traffic department. We didnt do this step because the time period for achieving the project was not enough to do it.
    Keywords: Safe Driving; assistance system; intelligent vehicle; road conditions; Traffic.
    DOI: 10.1504/IJCAET.2020.10014759
     
  • Proposed Variants of Charged System Search Algorithm for Location Area Optimization in Mobile Wireless Communication Networks   Order a copy of this article
    by Palaniappan Senthilnathan, Ameer John Sirajudeen, Venkatachalam Ilayaraja, Meenakshisundaram Iyapparaja 
    Abstract: Location area optimisation is used to diminish the location update cost and paging cost in mobile wireless communication networks. Retaining heuristic optimisation technique, helps to diminish the location and paging cost, the problem occurs in this technique is combinational optimisation in nature. Handiness of mobile users growing day by day and many users will be allocated to various mobile subscribers and thus forecasting the ideal area is always a big job. Charged system search algorithm (CSSA) is employed to overwhelm the local and global minima that happened often during the peers of the run process. The variants introduced into the CSSA include the wavelet models and the gravitational search algorithm (GSA) models. The prominent features of both wavelet model and GSA model are obtained and are shared with the charged system search algorithm to minimise the total cost experienced for location area optimisation in mobile wireless communication networks (MWCN).
    Keywords: heuristic optimisation technique; wavelet models; charged system search algorithm; CSSA; gravitational search algorithm; GSA; mobile wireless communication networks; MWCN.

  • PID Controller tuning using hybrid optimization technique based on Boxs evolutionary optimization and teacher-learner-based-optimization   Order a copy of this article
    by Vinay Pratap Singh, Naresh Patnana, Sugandh Pratap Singh 
    Abstract: In this paper, a hybrid optimization technique based on Boxs evolutionary optimization and teacher-learner-based-optimization (BEO-TLBO) is proposed for proportional-integral-derivative (PID) controller tuning of level control of three-tank system. The integral-square-error (ISE) of unit step response is minimized for obtaining optimal controller parameters. The ISE is designed in terms of alpha and beta parameters. In BEO-TLBO, a global search is first carried out over the entire search space to determine the set of desired controller parameters using teacher-learner-based-optimization (TLBO). The search is then refined in the second stage using Boxs evolutionary optimization (BEO). The results obtained using BEO-TLBO are compared with other existing techniques. Computer simulations reveal that the hybrid optimization based approach meets the desired specifications with greater accuracy as compared to the other existing methods.
    Keywords: Box’s evolutionary optimization (BEO); ISE; Optimization; PID controller; Teacher-learner-based-optimization (TLBO).

Special Issue on: Image Processing in Computer Vision - Techniques and Advancements

  • Markov random field classification technique for plant leaf disease detection   Order a copy of this article
    by Anusha Rao, Shrinivas B. Kukarni 
    Abstract: In recent era of technology, computer vision technique has grown attraction of the researchers. This technique helps to identify and classify the objects according to the application requirement. These techniques are widely used for plant leaf detection and helping to develop an automated process for plant leaf disease detection. A new approach is developed in this work for plant leaf disease detection using Markov Random Classification technique. MRF based problem is formulated for disease detection. In the next stage, the general stages of computer vision classification model i.e., pre-processing and feature extraction is applied. For pre-processing, noise removal and image enhancement models are applied and feature extraction is combination of statistical features. Neighborhood pixel modeling and MRF classification models are applied to obtain the classification of input data. Performance of three classification models is compared. Study shows that proposed approach gives robust performance for plant leaf disease detection and classification
    Keywords: plant leaf; plant disease; computer vision; Markov random field; MRF.
    DOI: 10.1504/IJCAET.2020.10022049
     
  • Automated extraction of dominant endmembers from hyperspectral image using SUnSAL and HySime   Order a copy of this article
    by Nareshkumar Patel, Himanshukumar Soni 
    Abstract: Linear Spectral Unmixing (LSU) is widely used technique, in the fieldrnof remote sensing (RS), for the accurate estimation of number of endmembers,rntheir spectral signatures and fractional abundances. Large data size, poor spatial resolution, not availability of pure endmember signatures in data set, rnmixing of materials at various scales and variability in spectral signature makes linear spectral unmixing as a challenging and inverse-ill posed task. Mainly there are three basic approaches to manage the linear spectral unmixing problem: Geometrical, Statistical and Sparse regression. First two approaches are kind of blind source separation (BSS). Third approach assumes the availability of some standard publically available spectral libraries, which contains spectral signatures of many materials measured on the earth surface using advance spectro radiometer. The problem of linear spectral unmixing, in semi supervised manner, is simplified to finding the optimal subset of spectral signatures from the spectral library known in advance. In this paper, the concept of soft thresholding is incorporated along with the sparse regression for automatic extraction of endmember signatures and their fractional abundances. Our simulation results, conducted for both standard publically available synthetic fractal data set and real hyperspectral data set, like cuprite image, shows procedural improvement in spectral unmixing.
    Keywords: Spectral Unmixing; Sparse Unmixing; Hyperspectral Unmixing;Alternating directional Method of Multiplier; ADMM; Hysime;.
    DOI: 10.1504/IJCAET.2020.10010900
     
  • Feature Extraction and Classification of COPD Chest X-ray Images   Order a copy of this article
    by P. Bhuvaneswari Samuel, A. Brintha Therese 
    Abstract: COPD (Chronic Obstructive Pulmonary Disease) is a group of lung disease like Emphysema, Chronic bronchitis, Asthma and some kinds of bronchiectasis .This group of diseases are expected to be one of the major cause of morbidility and the third case of mortality by 2020. Many people with COPD also develop lung cancer likely due to a history of smoking cigarettes. India contributes highest COPD mortality in the world. If the disease is identified in the early stage itself the survival rate will be increased. In this paper a novel method is proposed to classify the disease COPD in chest x-ray images. Prior to classification essential features to be extracted. In this regards some structural features include no of ribs in the chest x-ray , heart shape, diaphragm shape, distance between ribs of the given x-ray image are extracted by means of various image processing techniques. Based on the above said features the input image is classified as normal or COPD with various classifiers include MLC, LDA, Neural Network, Genetic Algorithm.600 x-ray images (PA view) are tested with the proposed method and classified based on the above features. The maximum classification accuracy achieved is 97.9% .Based on the comparison results of different classifiers, Genetic Algorithm based classification method proved to have more accuracy. This work not only ends up with the classification of COPD images, it also enables the medicos to identify the heart disease cardiomegaly.
    Keywords: COPD; Adaptive histogram equalization; Hough transform; Zernike moments; classification; MLC; LDA; Neural Network; Genetic Algorithm.
    DOI: 10.1504/IJCAET.2020.10010445
     
  • OBJECT-SPECIFIC FACE AUTHENTICATION SYSTEM FOR LIVENESS DETECTION USING COMBINED FEATURE DESCRIPTORS WITH FUZZY BASED SVM CLASSIFIER   Order a copy of this article
    by Koppola Mohan 
    Abstract: The Object Face Liveness Detection for Genuine face recognition and user authentication is a difficult task and day to day it becoming an interesting tricky in real time vision and security applications. Since many decades, various authors have proposed new technique and methods and developed but still the system has to improve to recognise the genuine object faces from spoofing objects with increasing in accuracy. However, by considering the various existing methods and techniques, were fails in finding of genuine objects from various shapes of object and individual differences between the objects. The ordinary classifier cannot simplifies well to various kind of objects in different directions especially in case of blur images. In order to overcome this problem, we proposed an Object-Specific Face Authentication System for Liveness Detection using Combined Feature Descriptors with Fuzzy based SVM Classifier, allows to select specific area from whole object, extract features from specific area of object leads reduction in processing time and complexity in feature extraction. Later the system recognises respective faces, finally it checks for live objects with the help of Fuzzy logic based SVM classifier. With these proposed Object-Specific Face Authentication System for Liveness Detection using Combined Feature Descriptors with Fuzzy based SVM Classifier makes it practical to train well performed individual Object to its certain face with liveness detection and got improvement in performance and accuracy.
    Keywords: Object-Specific Face; Genuine Object; Spoofing objects; Liveness Detection; Authentication; Anti-Spoofing; Feature Extractors; Region of Interest; HOG-LPQ Descriptors and Fuz-SVM Classifier.

  • Event Recognition and Classification in Sports Video Using HMM   Order a copy of this article
    by VIJAYAN ELLAPPAN, Rajkumar Rajasekaran 
    Abstract: Sports event recognition and classification is a challenging task due to the number of possible categories. On one hand, how to characterize legitimate occasion classification names and how to acquire preparing tests for these classes should be investigated; then again, it is non-inconsequential to accomplish acceptable order execution. To address these issues, we propose the use of the spatio-temporal behaviour of an object in the footage as an embodiment of a semantic event. This is accomplished by modelling the evaluation of the position of the object with a Hidden Markov Model(HMM). Snooker is used as an example for this purpose of research. The system firstly parses the video sequence based on the geometry of the content in the camera view and classifies the footage as a particular view type. Secondly, we consider the relative position of the white ball on the snooker table over the duration of a clip to embody semantic events. The temporal behaviour of the white ball is modelled using a HMM where each model is representative of a particular semantic event.
    Keywords: HMM; Event Recognition.

  • Cursive Script Identification using Gabor features and SVM classifier   Order a copy of this article
    by Mohammed Aarif K.O, SIVAKUMAR PORURAN 
    Abstract: Script identification is one of a challenging segment of optical character recognition system for bilingual or multilingual document image. Significant research work have been noted on script identification in the last two decades which highly concentrated on natural languages like Latin, Chinese, Hindi, French and so forth. A very little efforts are made on script identification of cursive languages like Arabic, Urdu, Pashto, etc. Most of the Urdu ancient literatures which are yet to be digitized includes both Urdu and Arabic text. In this paper we present a script identification of Urdu and Arabic text at word level using Gabor features with suitable orientation and frequencies. The proposed model is trained using SVM classifier and the results achieved are very promising
    Keywords: Script identification;cursive language; character recognition; Gabor filter; SVM.

  • Improving Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images using Feature Optimization   Order a copy of this article
    by Akara Thammastitkul, Bunyarit Uyyanonvara, Sarah Barman 
    Abstract: Diabetic retinopathy usually not presents symptoms in an early stage until it goes in a severe stage. An early stage of diabetic retinopathy is associated with the presence of microaneurysms (MAs). The occurrence of blindness can be reduced significantly if MAs are detected. This paper presented an approach to improve automatic MAs detection using feature optimization. Candidate MAs are detected using mathematic morphological. Original 20 features are present. To verify the relevance of all original features, feature optimization process is performed. The optimal feature set is searched by machine learning approach, like na
    Keywords: Diabetic retinopathy; Microaneurysms; Machine learning approach; Feature optimization.
    DOI: 10.1504/IJCAET.2020.10020251
     
  • A new and efficient approach for the removal of high density impulse noise in mammogram   Order a copy of this article
    by Sreedevi Saraswathy Amma, Elizabeth Sherly 
    Abstract: This paper proposes a combined approach for removing impulse noise from digital mammograms which implement a detection followed by filtering mechanism, in which, detection is done using a robust local image statistical measure called Modified Robust Outlyingness Ratio (MROR) followed by a filtering framework based on Extended Nonlocal Means (ENLM). All the pixels in the image are grouped into four different clusters based on the value of MROR. The detection system consists of two stages, coarse stage and fine stage. In each stage, different decision rules are adopted to detect the impulse noise in each cluster and to restore the image, the value of the noisy pixels is replaced with the modified median based value of the corresponding window based on the cluster position. For filtering, the NL-means filter is extended by introducing a reference image. Simulations are carried out on the MIAS database and the performance of the proposed filter has been evaluated quantitatively and qualitatively through experimental analysis and the results are compared with several existing filters such as Standard Median Filter (SMF), Adaptive Median Filter (AMF), Robust Outlyingness Ratio Non Local Means (ROR-NLM) and Modified Robust Outlyingness Ratio Non Local Means (MROR-NLM)
    Keywords: Impulse noise; image denoising; Non-Local means filter; noise detector; ROR; adaptive median filter; coarse stage; fine stage; MROR-ENLM.
    DOI: 10.1504/IJCAET.2020.10018160
     
  • Improved Motion Estimation Algorithm Based on Integrity Index and Its Implementation in x265   Order a copy of this article
    by Vidya More, Mukul Sutaone 
    Abstract: With the development of fast motion estimation (ME) algorithms to-rnwards video compression standard H.264, burden on integer-pel ME is slightly re-rnduced. However the integer-pel ME is becoming computationally complex due torndemand of higher and higher resolution videos. On the other hand, there is alwaysrntradeo between the speed and performance of these search algorithms. This workrnimprovises the performance of content awareness enabled integer-pel ME algorithmrnfor encoding the fast and slow motion video sequences of High De nition (HD)rnresolution category viz. 1280720 and 19201080. The algorithm proposes a novel notion of `Integrity Index 'with focus on increasing the PSNR and reducing the Bit-Rate. It is implemented in the frame work of x265 version 1.7 video encoder.rnMotion independent ME algorithm is analyzed quantitatively in terms of pa-rnrameters based on rate distortion and ME time. The proposed algorithm is foundrnto be performing better on BD-Rate and BD-PSNR parameters for the videos ofrnboth resolutions under consideration. Observed increase in motion estimation time is less than four seconds compared to hexagonal search algorithm of ME which is the benchmark in fast ME algorithm.
    Keywords: Integer-pel; Motion Estimation; x265; HEVC; Content Awareness.

Special Issue on: ICCMIA18 Computer-assisted Intervention and Analysis in Clinical and Medical Imaging

  • Tensor Flow Based Recurrent Neural Network Algorithm to Diagnose Diabetic Retinopathy   Order a copy of this article
    by T.Jemima Jebaseeli, C. Anand Deva Durai 
    Abstract: Type II diabetic patients have the chance of a sight-threatening Diabetic Retinopathy disease. It affects the retina of the eye and causes damages to the human vision. The pathological fundus images of the patients have lesions present in the retina in the form of Exudate, Microaneurysm, Cotton wool spots, and Hemorrhages. At the later stage, it leads to retinal detachment from the eye. Segmentation technique is used to identify the lesions present in the retina for diagnosis. It makes the job of an ophthalmologist easy and to predict the disease accurately. The early detection of disease can be treated and the patients can be saved from the vision loss. The fundus images contain illumination; hence Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for image enhancement. Recurrent Neural Network (RNN) is applied to segment the lesions from the pathological fundus images. The performance of the proposed approach achieved an average value of 98.91% sensitivity, 99.93% specificity, and 99.89% accuracy. The proposed technique is implemented using Tensor Flow framework for lesions segmentation and to diagnose Diabetic Retinopathy and validated over 109 pathological fundus images.
    Keywords: Lesion; Exudate; Microaneurysm; Hemorrhage; Cotton wool spots; Feature detection; Segmentation.
    DOI: 10.1504/IJCAET.2021.10023130
     

Special Issue on: ICICT-2018 Ubiquitous Sustainable Systems

  • A Novel Automatic System for Logo Based Document Image Retrieval Using Hybrid SVDM-DLNN   Order a copy of this article
    by Raveendra Kudamala, Vinothkanna Rajendran 
    Abstract: Many government and private organizations represent themselves to the public using their own symbols or logo which is unique from others so that anyone can easily identify their products or belongings. This gives an ownership and source documentation to the owner by simply providing such logos. Using these logos for document retrieval in World Wide Web is a booming research in present era. Since usage of virtual documentation is increased day by day and handling this large data becomes a problem while searching for single data. In present research arena various document image retrieval models are available based on classification and clustering techniques. In this graphical techniques are used to identify the issues in the automatic logo detection model using back propagation neural network along with the single value decomposition model (SVDM). This proposed research model concerned about the document retrieval system based on the logo matching process to attain better efficiency and accuracy than the earlier detection models.
    Keywords: Logo recognition; detection; segmentation; Document retrieval; Feature extraction; Logo extraction,Feature matching.
    DOI: 10.1504/IJCAET.2021.10024321
     
  • Design of Twin inverted L Microstrip Antenna using HFSS Software for sustainable systems   Order a copy of this article
    by Praveen Chenna, Trinatha Rao 
    Abstract: A novel design of twin inverted L compact and small size micro strip antenna is designed in the proposed work. The radiating structure consists of two inverted L shaped structures in coalesced form on FR-4 material. It is being used as substrate with dielectric constant of 4.4 and by properly arranging the lengths of two inverted L arms, size of the proposed structure is minimized is to be about 50mm in length,10mm in height and 1 mm width. In addition, the feeding configuration is simplified by using a short probe. The proposed twin inverted L shaped structure is compared with T shaped antenna and single inverted L shaped antenna and the measured results shows that the proposed structure is resonates at 12.5 GHz and has a wide impedance bandwidth of 15.2% .The gain and bandwidth are above -44 dB and 1.82 GHz respectively, the Radiation efficiency of 97.5%, S11 with -14.24 dB and VSWR<2 across the entire operating band.
    Keywords: inverted L antenna; FR-4; Radiation pattern; Gain.
    DOI: 10.1504/IJCAET.2021.10023552
     
  • A close scrutiny of dApps and developing an E-voting dApp using Ethereum Blockchain   Order a copy of this article
    by Banupriya N, Pooja Guru, Nevetha S, Roopini J, Nivedhitha M 
    Abstract: In the expeditiously advancing technological world, with the advent of Internet Of Things and Big Data everyday new people are getting connected and new devices are connected that store highly sensitive personal data. For example your Google Home is listening to you and collecting data, your Facebook knows a lot much about you; Amazons Alexa gets to know our everyday wants. This implies that our data is used to spy on us, advertise us and hence these Siren Servers [1] make the overall profit off of us. In the initial juncture the ideology behind the Web 1.0 which was called the read only web was just to allow us to read content and search for information. It just had a jot of interaction. Web 2.0 emanated as a read write web. It grants users the ability to contribute content; in fact applications such as YouTube and MySpace run on the users contribution. But progressively some of the technology giants such as Google, Amazon, Facebook, Microsoft, Yahoo, Pandora, Spotify, Walmart, and Baiduu have taken over the internet. These companies are called as the Siren Servers. Thus there is no room for competition in the web 2.0. This induced the emergence of Web 3.0 which is also called the read write execute web. While Blockchain is customarily associated with Bitcoins and transactions, they could also be used to provide various other services. dApps[2] are one of the incredible solutions for all the problems with web 2.0. dApps crucially use Blockchain as their root. When the Blocks store code instead of transactions dApp becomes alive. This could be exploited in many sectors for innumerable reasons such as data permanence, ownership, and accountability. Since Blockchain [3] is the foundation for dApps, dApps also possesses properties like security, privacy, immutability, verifiability, auditability making it highly trustworthy. The forthright key to bring individuality out, to terminate the need of middleman in all the services that we obtain, to own your data, to have transparency; to resist censorship and yet to be profitable; is to make any system decentralized. This paper throws light on developing a dApp (decentralized application) that could be used in a voting system. Everything around us is digitizing; which doesnt mean we are moving towards a safe and secured scheme, thus the revolutionary Blockchain technology is used to deploy an E-voting system [4] and this is done using the Ethereum[5] Blockchain which uses Solidity[6] as its programming language.
    Keywords: Blockchain; Decentralized Application; Web 3.0; Ethereum; Smart Contracts; Solidity.

  • Performance Analysis for user Identification in CR Networks by various Modulation Transmission Techniques   Order a copy of this article
    by Anil Kumar Budati, MOHAMMED Saleem Pasha 
    Abstract: The rapid development of newly invented wireless devices and its applications tends to spectrum scarcity. Cognitive Radio (CR) is a technology, which gives solution for the spectrum scarcity problem with dynamic spectrum access. The user presence or absence is identified by a spectrum sensing technique in CR Networks. There are various methods like Energy Detection (ED), Matched Filter Detector (MFD) and etc., are used for identification of user presence or absence in the spectrum. The performance of the user identification is estimated by the parameters of Probability of Detection (PD) and the Probability of false alarm (Pfa). The performance of the spectrum sensing method with Basiean Detection (BD) criteria by using static threshold is estimated by existing author for the above said parameters. In this paper, the authors estimated the performance of the above parameters with Neyman Pearson (NP) detection criteria is applying to MFD sensing method by using dynamic threshold. The performance is analyzed by comparing the existing BD with the proposed NP by using the modulation transmission techniques 8-PSK, 8-QAM and identified the better detection criteria.
    Keywords: Cognitive Radio; Spectrum Sensing; Neyman Pearson Approach; Probability of false Alarm; Probability of Detection,PSK; QAM.

  • Visible Light Communication for Position control of Robotic Vehicle   Order a copy of this article
    by V. Partha Saradi, P. Kailasapathi 
    Abstract: With increasing demand in the need for fast and secured transmission of data from one place to another in a wireless medium, many innovations open up with respect to the use of communication protocols. Off late, spectrum availability appears to be a very scarce resource and invites alternate methods of transmission to fortify the emerging challenges. The paper investigates the properties of a visible light communication (VLC) medium and develops a scheme for controlling the position of a Li-Fi based robotic vehicle. The fast transmission properties of light signal along with its edge over radio frequency and or Wi-Fi communication augur to exploit the potentials of the Li-Fi environment. The methodology involves the use of an Arduino microcontroller for the generation and reception of control signal at both the transmitter and receiver ends respectively The response to varying widths of pulse position modulation (PPM) signals bring out the ability of the scheme to respond to changes in position at varying speeds. The results envisage a new dimension to the scope of robotic vehicles for a space in automated domains in terms of faster and precise operational ambits.
    Keywords: Visible Light communication; Li-Fi; Arduino controller; Radio Frequency; Speed control of motor.
    DOI: 10.1504/IJCAET.2021.10024126
     
  • The Impact of Work Integrated Learning Towards Students Learning: Case of ICT Students in South African Universities of Technology   Order a copy of this article
    by Bethel Mutanga Murimo 
    Abstract: The change in global structure regarding labour demand has, in recent years, led to a strong shift towards high-skilled workers. This trend has become a contributing factor towards increasing unemployment rates in South Africa. Consequently, Work Integrated Learning (WIL) has been introduced in the curriculum of South African universities of technology (UoTs) to bridge the gap between theoretical knowledge and real-life industry experience. To learn the contribution of WIL in improving the quality of graduates, it becomes highly imperative to investigate the impact of WIL with focus on specific discipline. Therefore, based on the Kolbs learning model, this paper investigated the impact of WIL on undergraduate ICT students learning. A quantitative survey instrument was adapted from existing scales and used on a sample of 76 ICT undergraduate students who had recently completed WIL. The results showed that over 90% of the students indicated that WIL significantly enhanced their learning.
    Keywords: WIL; experiential learning; workplace; innovative learning; skilled labour.
    DOI: 10.1504/IJCAET.2022.10020164
     
  • An Evolutionary Frame Work on ADHD Diagnosis Based on Graph Theory and Ant Colony Optimization   Order a copy of this article
    by Catherine Joy R., Thomas George S., Albert Rajan A. 
    Abstract: Developing countries facing unavoidable issues for the parents lived with children due to Attention Deficit Hyperactivity Disorder (ADHD). This neuropsychiatric disorder has effects on the children in terms of inattentive, impulsive, and hyperactive. Graph theory provides useful description measures as predicted vectors for the classification process and this research work provides an automated diagnosis model for predicting the ADHD features based on the neural network classifier to differentiate ADHD patients and their healthy controls from a combined environment includes normal persons and affected patients. Ant colony optimization model is used to get converged results for the classifier results in terms of both phenotypic data and imaging data. ADHD-200 dataset is used for analysis in the proposed model. The experimental result yields an accuracy of 86% on two class diagnosis better than phenotypic approaches.
    Keywords: attention deficit hyperactivity disorder (ADHD); artificial neural network; ant colony optimization.

  • A Novel study and research on Multilayer AlAs/GaAs Quantum dot inner layer for solar cell applications   Order a copy of this article
    by VICTOR DU JOHN H 
    Abstract: Quantum dot solar cell is effectively used in many solar applications to obtain the maximum conversion efficiency. Using materials such as InAs and GaAs or the combination of strained InGaAs/AlGaAs on GaAs substrate provides an improved efficiency. Multi-layer quantum cells provides better energy coupling than other existing models defining the rate equations in terms of their applications is the current research in solar cell applications. The proposed research work addresses the issues present in the earlier solar cell applications by a deep literature survey and then the proposed model is designed using multilayer materials such as AlAs and GaAs quantum dot solar cells. The proposed model provides an improved conversion efficiency of 26.79% and the results are compared for all the available layers.
    Keywords: Photovoltaic cells; quantum dot; multi junction; solar lattice.

  • Improving Power Losses and Thermal Management in Switch Mode Power Converters Using Multiple Transformers   Order a copy of this article
    by Nagesh Vangala, Srinivasa Rao Gorantla, Rayudu Mannam 
    Abstract: Presently, DC power supply requirements in electronic applications are met by Switch mode power converters. With the advent of high capacity semiconductor devices such as SIC MOSFETs and diodes, the power delivered by converters can be very comfortably enhanced. Nevertheless, the magnetic components such as the power transformers may limit the power delivery because of their thermal resistances and temperature management. Also the geometry and the size of one single transformer may be a limiting factor for power delivery, though the other devices are rated high. In this paper a simple technique to parallel multiple small transformers to enhance the power rating of the converter while guaranteeing the power sharing among the transformers is proposed. Two DC-DC forward converters are designed and fabricated, one with single larger transformer and another with two smaller transformers with identical specifications. The test results are presented validating the proposed technique.
    Keywords: Forward Power converters; thermal management; power sharing; Efficiency; Transformer losses; thermal resistance; ferrite cores; SMPS; Multiple Transformers; Power Loss.

  • Experimental Evaluation of Image Segmentation for Heart Images   Order a copy of this article
    by Merjulah Roby, Chandra J 
    Abstract: The cardiac death is the principal reason of the death in the world. The research work focusses on finding an efficient image segmentation technique for the computer aided detection and also to decrease the noise in the image. The segmentation is implemented with the help of Fuzzy C-means clustering along with dual inverse thresholding function and Otsu thresholding. Experimental proof is evaluated with the help of Morphological functions and with Gaussian function. The result of the work provides an accurate segmentation for myocardial ischemia in the human heart photo image as well as magnetic resonance imaging.
    Keywords: Fuzzy C-Means (FCM); Segmentation; Dual Inverse thresholding; Otsu thresholding; Cardiac MR Images (MRI); Cardiac Photo; Morphological Functions; Gaussian Function.

  • LOW POWER SECTOR BASED TRANSITION REDUCTION BUS ENCODING TECHNIQUE IN SOC INTERCONNECTS   Order a copy of this article
    by Chintaiah Nannepaga, G. Umamaheswara Reddy 
    Abstract: The data word transmission process on an on-chip bus results in the switching of data bits on bus wires, which charges and discharges the capacitance associated with the wires. Consequently, dynamic power dissipation and increase in delay occurs. Data word transmission is required to change data values that are transmitted over these buses for reducing the transition activity, thereby decreasing the power consumption and delay of the bus. Bus encoding is the commonly used techniques to reduce the transition activity of the bus. In this study about the memory bus encoding i.e. a dynamic sector encoding technique, that is, a sector-based encoding technique is proposed. In this technique, the source word space is divided into a number of sectors with a unique identifier. A dynamic sector (DS) encoder reduces the number of transitions 19.23% more than that reduced by a binary encoder. DS encoding technique is a novel method that reduces the number of transition then reduce the power dissipation and delay when compared to previous encoding techniques which are used in the memory operations.
    Keywords: Deep submicron; Sector based; transitions; crosstalk; encoder.

  • Large Scale Air Pollution Monitoring Using Static Multihop Wireless Sensor Networks   Order a copy of this article
    by Movva Pavani, KISHORE KUMAR KAMARAJUGADDA 
    Abstract: In the proposed paper, an effective system for a large-scale air pollution monitoring using wireless sensor networks (WSN) on a real-time basis was developed. It is an Audrino based core with off the shelf pre-calibrated sensors to detect gases like Sulphur Dioxide (SO2), Carbon Monoxide (CO), Ammonia (NH3), and Particulate matter (PM10) in the air. Audrino board with the gas sensors, Global System for Mobile Communications (GSM) wireless link and also a low-cost ZigBee module forms the wireless sensor motes used for the field deployment. Wireless sensor network formed with ZigBee links can be scaled up using the GSM connectivity to interface with the external world. Air Pollution monitoring is performed using a system of sensor nodes with the help of wireless communication via ZigBee protocol. We proposed a static Wireless Sensor Network to monitor air pollution through the use of WSN. A Multihop Algorithm is implemented over this ZigBee WSN. A prototype version of the platform is realized and tested. Experimentation carried out using the developed wireless air pollution monitoring system under different physical conditions show that the system collects reliable source of real-time fine-grain pollution data.
    Keywords: Air Pollution Monitoring; Global System for Mobile Communications (GSM); WSN Mote; Multihop Algorithm; Pre-calibrated Sensors; Static Wireless Sensor Network.
    DOI: 10.1504/IJCAET.2022.10020581
     
  • Privacy Preservation of Clinical Dataset using SHA and key base Hashing   Order a copy of this article
    by Balaji Bodkhe, SANJAY SOOD 
    Abstract: Privacy preserving publishing of micro data is one of the most essential concerns in collective data publishing. In this work, we design a problem for data publishing using new technique called SKHF. There are too many techniques has described by existing authors but still an issue with real time data classification with sensitive information. Numerous researches have done in health care domain with privacy preserving, but still nobody had eliminate the data leakage and data loss issues. In this paper we describe the new approach for privacy base data broadcasting in distributed environment. In the proposed system, a hospital collects various patients data and publishes the records to an external entity. The privacy of data is preserved while sharing of information among hospitals and other providers. The proposed system is designed to preserving or maintains the privacy of an individual data in distributed database system by using the slicing algorithm. Basically it is used for publishing information of specific organizations like health care patient information as well as disease information etc. In this paper we studied anonymization. L-diversity, randomization and k-anonymity based techniques for privacy preservation; it also carried out the new technique for data privacy called Secure Key base Hash Function (SKHF) which provides the both kind of security in horizontals well as vertically manner.
    Keywords: SHA – 256; L-diversity; randomization; k-anonymity.

  • e- NL BEENISH: Extended- Network Lifetime Balanced Energy Efficient Network Integrated Super Heterogeneous Protocol for Wireless Sensor Network   Order a copy of this article
    by Baby Shalini, Vasudevan  
    Abstract: Wireless Sensor Networks (WSNs) have enormous number of compact and minute sensor nodes which are spreaded over a monitoring field for observing the event, transfer the report to the end user. Thus, saving the energy for passing the information and extending the networks lifetime is a big challenge. Clustering is an efficient method to enlarge the energy efficiency. In this paper, e-NL BEENISH is proposed with six energy levels of nodes. Experimental results give an idea about that our proposed method performs well again than existing protocols like TDEEC (Threshold Distributed Energy Efficient Clustering), BEENISH, IBEENISH(Improved BEENISH) in terms of data transmission and network lifetime
    Keywords: clustering; energy efficiency; end user; monitoring field.

  • Design and Implementation Of Control Unit Of Micro Grid in Multi Micro Grid Using Verilog Systems   Order a copy of this article
    by Bala Nagu Puppala, Uma Vani Marreddy 
    Abstract: This paper discussed about control logic of Multi Micro Grid in different conditions and optimization set point algorithm. In todays world a stable power supply is considered as a basic necessity, almost a fundamental right to serve critical facilities. Need huge capital to install traditional power plants, so Micro Grids and Multi Micro Grids are better choice. There is a lot of scope for power generation by using small power generating units like Micro Grids and combination of Multi Micro Grids. So need a control unit for maintaining constant frequency and voltage and provide a good service for consumer and it is free of pollution. This project proposes a new control unit for Islanding mode Micro grid of Multi Micro Grid system which consists of Distributed Energy Resources (DERs) such as solar PV, Diesel Generator, Micro Hydro model, Battery Bank with a bi-directional inverter and critical and non-critical loads. It can be operate in Multi Micro Grid with Main Grid mode, Multi Micro Grid mode as well as Island mode.
    Keywords: Micro Grid; Control Unit of Micro Grid; Control Unit of Multi Micro Grid.

  • Reputation Based Business Policy Violation Detection of Long Term Composed Services with Efficient Alleviation of Malicious Rating of Violated Service   Order a copy of this article
    by Tiroumal Mouroughane S, Thambi Durai. P 
    Abstract: The web services are the emergent technology in the field of business processes where the services offered by the organization are managed through the framework called Change management framework (CMF). By this framework any changes for the service offered by the organization can be added, modified or replaced in the form of the service request offered by either the customer or other business parties thus it is helpful for the organization to develop itself by satisfying the customer requirements in an autonomous manner. In this paper, we have presented a methodology for detecting the business policy violation with Alternating Turing Machine (ATM) and Reputation Measurement (RM). When a change request is encountered the detection of policy points is performed by ATM and if the policy violation occurs, it means reputation of the service is measured through RM by considering malicious intentions. In the case of non-policy violation or if the service has high reputation means that become integrated to the CMF otherwise it will sent to the exception handler. The framework is implemented in the visual studio with DOTNET language and the performance is analyzed with different number of change requests.
    Keywords: Change management framework (CMF); Long term Composed Service (LCS); Business Policy violation; Alternating Turing Machine (ATM);Reputation; Web service integration; Ballot Stuff Attack; Fake Identity.

Special Issue on: Advanced and Sustainable Solutions in Communications, Networking, Computing and Engineering Systems

  • An efficient Automatic Generation Control for Multiple Power Systems based PI-SA Algorithm   Order a copy of this article
    by Mohammed Shahooth 
    Abstract: In this research, an efficient automatic generation control (AGC) for two-parallel power system is proposed using simulated annealing (SA) optimization algorithm based proportional-integral (PI) controller. The aim of using the SA algorithm to automatically tune the parameters (k_p and k_i) of PI controller. The proposed controller (PI-SA) with AGC loop is highly important in order to minimize the frequency deviation and control the real power exchange in each power system under sudden load changes. Integral square error (ISE) is used as an objective function to evaluate the system performance in terms of maximum deviation, settling time, and peak time. Overall power system and proposed controller (PI-SA) are modeled using MATLAB environment. Simulation results showed that the proposed system is robust and has better dynamic response as compared to the results obtained by PI-GA control algorithm under same operation conditions.
    Keywords: Simulated annealing algorithm;PI controller;Two-parallel power system;rnintegral square error (ISE)rn.

  • Delta Robot Joints Control Based Linear MPC Controller   Order a copy of this article
    by Wesam Jasim 
    Abstract: Controlling the joints' angles of a robot is an important step lead to control the robot end effector position and/or speed. Thus, it has been a vast area of interest in research which has good investigating potentials using several control types such as classical, modern and optimal control methods. In this work, a linear Model Predictive Control MPC technique was proposed to control the joints' angle of a three degree of freedom delta robot. The inverse kinematics, direct kinematics, and dynamic model of the robot were analyzed. Then, the dynamic model represented in a linearized around an operating point state space model. In order to investigate the performance of the proposed MPC controller a simulator based MATLAB program was implemented. The simulation results have showed the efficiency of the proposed controller in joints' angles control problem. This illustrate that the MPC controller can derive the joints' angles to track the desired angles with invisible steady state error.
    Keywords: MPC technique; Delta robot; Simulation;rn Parallel Manipulatorrn.

  • Design Intelligent Solar Cell Tester System based on Microcontroller with Handling Robot   Order a copy of this article
    by Yosif Almashhadany 
    Abstract: Abstract: The electrical performance of photovoltaic cells is the best parameter for sorting the cells, the testing achieved with sunlight model. All testers have common problem about handling the small thin pieces and change its position from convey tester to storage box and via process. This paper presents an intelligent solar cell tester system with handling robot, controlled by intelligent controller based on microcontroller technique to execute all the required movement for cells through the testing process. The design built for real solar cell tester with four main types: Cadmium Telluride (CdTe), copper indium diselenide (CIS), monocrystalline, and polycrystalline. Each type of cells after testing will be distributed according to efficiency to four categories (A-D). Modeling Virtual reality (VR) was built for all system and execute the simulation according to real requirements. Two electric photo sensors are used to implement the sensing of action with microcontroller the first for controlled the process of testing and the other for controlled robot process. Robot path is controlled by microcontroller according to results of tester. Manual controllers for speed of conveying information exchange used between the results of tester and microcontroller.
    Keywords: Intelligent Solar cell tester; Modelling Virtual reality; microcontroller; photoelectric sensor; sunlight model.

  • Analytical and theoretical study of vibration-based damage detection technique in a composite structure   Order a copy of this article
    by Ahmed Uwayed 
    Abstract: Abstract: In this paper, free vibration-base damage detection technique has been used to identify fibre breakage within composite beam. In general, most of this type of techniques used the reduction in stiffness of any structure that affects the dynamic response of the structure to detect damage. To simulate fibre breakage, analytical method is used to calculate the stiffness of damaged area. This technique used a certain way to localize fibre breakage and identify the size of the damage area. Furthermore, this way shows that the difference of dynamic responses between the damaged part and the intact part within the composite beam increase with increasing the distance of the damage part to the fixed end. Also, an improvement of irregularity index has been conducted to enhance the damage detection of composite structures. This technique will be applied to a simulated data to evaluate the efficiency of this technique.
    Keywords: dynamic response; mode shape; irregularity; damage detection.rnrn.

  • Numerical Analysis of Lubricant Viscosity Variations on Operating Condition of Helical Gear System   Order a copy of this article
    by Khaldoon Brethee 
    Abstract: Abstract: This study presents dynamic model to investigate the effects of lubricant viscosity variations due to oil degradations or oxidations on both power supply parameters and vibration signals of helical gear system. The modelling has been extended to consider the effect of elastohydrodynamic lubrication (EHL) conditions to include the frictional effects between the meshed helical gear. A ten degree-of-freedom (10-DOF) model has developed to combine lateral, torsional and axial vibrations induced in helical gear transmissions with supporting bearings, powerful motor and applied load system. Additionally, it takes into accounts the effect of viscosity variations on both power supply parameters and vibration characteristics through the time-varying of EHL friction coefficient. The results conclude that an increase in the lubricant viscosity will increase internal fluid friction, which results in additional excitation of vibration, especially in the off-line-of-action (OLOA) direction. Also, the required input power of the motor is increased to overcome the higher friction power that occurred with using thicker lubricant. However, the vibration responses from both rotational and translational movements can be good indicators for lubrication conditions, where the translational one is more sensitive even though the rotational responses are generally more nonlinear. These changes mean that it is possible to use vibration signature to monitor the lubrication conditions and obtain an accurate diagnostic result for tooth surface defects.
    Keywords: dynamic model; vibration response; elastohydrodynamic friction; oil viscosity.

  • Load Deflection Behaviour and Properties of Sustainable Lightweight Aggregate Concrete Slabs   Order a copy of this article
    by Mahmoud Sheelan 
    Abstract: In this research natural aggregate was replaced once by waste walnut shell and other by lightweight porcelinate aggregate. This gives two benefits: reduce the weight of the structure and the consumption of waste by incorporating it in the concrete Percentages of replacement by volumetric rates ranging between (25%) to (100%) were adopted. Besides cement was replacement by 10% waste glass powder. Mechanical properties were invesitegated. Besides one-way slab was casted for 50% replacement and tested under four point flexural test. Results showed that that replacement of natural aggregate by lightweight aggregate regardless of it source decrease density, compressive strength, splitting strength. While an increasing in the deflection at failure was notice for slabs incorporating lightweight aggregate compared to reference one. Concrete containing 50% porcelinate demonstrated a slightly increased in strength compared with reference slab by 8.91% Concrete containing 50% WA demonstrated a clear reduction in strength compared with reference slab by 62.57% . The width of crack at failure for concrete incorporating walnut coarse aggregate was wider the for reference one. While concrete incorporating porcelinate failed with finer cracks than reference one.
    Keywords: Lightweight aggregatel; Porcelinate; rnWalnut shell rn.

  • Cost-Benefit Analysis of suggested Ramadi Barrage Hydroelectric Plant on the Euphrates River   Order a copy of this article
    by Sadeq Oleiwi 
    Abstract: In recent times, the demand for electricity have been increased in the world, and for many reasons, including the increase in the population, which in turn led to the urgent need to set up many factories to meet the basic needs. Power can be obtained from many sources. Clean energy is the focus of research in the world now. One reason is the increase in greenhouse gas emissions. Therefore, ways must be found to generate clean, environmentally friendly energy. In addition, countries with few sources such as oil are seeking a cheaper alternative. In this research we study electricity generation from low-altitude systems or barrage considering the potential profits and costs of the project, as well as support for research theories that support the idea of project success as well as the accuracy of finding costs and potential profits for the project. Ramadi barrage at Anbar province of Iraq was taken as a target in the study. A number of hypotheses were imposed, such as the number of turbines to be developed in a study area of 6 Kaplan turban. The amount of energy to be produced from Ramadi barrage would be between 12-24 megawatts at a total cost of 4,309,427$ with total benefits 7,999,018.86$/year.
    Keywords: Cost-Benefit Analysis; Euphrates River;rnRamadi Barrage; Hydroelectric Plantrn.

  • Numerical Analysis of Reinforced Concrete Columns Strengthened By Steel Tubes Under Sustained And Short Term Loadings   Order a copy of this article
    by Zahraa Salih 
    Abstract: This paper used finite element method to predict models of strengthening R.C. columns under short term loading and long term loading. The present study is an attempt to predict time-dependent behavior of reinforced concrete columns confined by steel square tube using model proposed by ACI 209R. Comparison of calculating results using this model shows a good agreement with the test results. Based on the results of an available experimental study of concrete filled steel tube, this paper presents a parametric study using finite element models carried out with the aim of analysis the long term behavior of plain concrete columns strengthened by steel plate. The results of the study are used to analyze the effect of different factors on strengthened column (the magnitude of sustained load, the concrete compressive strength, and length/thickness ratio).
    Keywords: Concrete columns; Steel tube; Short termrnLong termrn.

  • Effect of High TemperatureOn Bond strength of concrete reinforced with 180   Order a copy of this article
    by Mohammed Qasim 
    Abstract: High temperature has a great effect on the reinforced concrete properties including the bond strength between the steel bars and concrete. There is many studies on the residual bond strength of concrete reinforced with straight bars, but according to the knowledge of authors, there is no study upon the bond strength of concrete reinforced with hooked bars after exposing to high temperature, thus make this study which investigate this property a novel one. Pull-out prism specimens used to test the residual bond strength and all specimens have the same compressive strength (30MPa). The variables are the diameter of hooked bar (10 mm and 12 mm), and the temperature levels (200
    Keywords: Bond strength; hooked bars; high temperature; Pull-out; Slip.

  • Novel Method for Strengthening Insufficient Steel Reinforcement Splice Using CFRP Sheets   Order a copy of this article
    by Ziadoon Ali 
    Abstract: A steel lap of reinforcing steel in reinforced concrete sections affects on structural performance in two different schemes: by stress concentration in section, and through the configuration of the steel-concrete bond. In this paper, a new method for increased the capacity of insufficient laps products by using carbon fiber reinforced polymer CFRP sheets on bond strength is investigated experimentally. To test the strength of new laps reinforcing bar anchorages and to quantify the effect of the bond of the bar surface on development length, reinforced concrete beams were cast having laps in reinforcing bars in the concrete for a known bending span length. Specimens were tested in four-point flexure test to assess strength and mode of failure. Results were summarized and compared within a standard lap according to ACI specifications. The new method for splicing has more efficient of insufficient splice laps when it was compared with a standard lap.
    Keywords: Insufficient laps; rnCFRP sheets;rn Reinforced concrete beamsrn.

  • Finite Element Modelling of High-Strength Fibre Reinforced Concrete Columns Under Eccentric Loading   Order a copy of this article
    by Zaid Alazzawi 
    Abstract: This paper presents a numerical finite element model simulating the behaviour of high-strength fibre reinforced concrete columns under monotonic eccentric loading. The results of the numerical model in this study show very good agreement with the experimental part of the investigation which was presented previously in a separate paper. In addition to the ultimate capacity, lateral deflection and axial shortening are taken into considerations in the finite element model.
    Keywords: Columns; Eccentric loading; High-strength concrete; Fibre reinforced concrete; Finite element analysis.

  • Effect of Vehicles Acceleration and Heading on Reliability of VANET Routing Protocol   Order a copy of this article
    by Omar Alokashi 
    Abstract: Abstract. Intelligent transportation system is rapidly spreading in all vehicles which manufactured recently. Vehicular ad hoc networks (VANETs) are consid-ered as a promising technology to enable communication among member vehicles (V2V) in one side and vehicles with Road side unit in other side. Most applica-tions that supported by VANETs require a reliable connection, especially safety-based application. The major challenge in VANETs environment is the high mo-bility patterns which are caused by the quick and frequent topology changes. Consequently, the disconnection of the communication links is highly occurrence in VANETs, hence, a particular research attention has been focused to achieve the reliability of routing. Getting a continuous connection through a specified time between two vehicles is defined as the route reliability. This paper suggested a new vehicle acceleration and heading based reactive routing protocol (AH-AODV) which, enhanced by the original AODV (On-demand Distance Vector) routing protocol. In addition, the stability of the route is superior computed ac-cording to vehicle acceleration and heading in urban intersection. Based on the simulation results, our proposed protocol (AH-AODV) outperforms the AODV protocol significantly in Packet Delivery Ratio and the link failure percentage metrics.
    Keywords: : route weight; next-hop; like failure; reliable route; AODV; AH-AODV.

Special Issue on: ICIMIA 2017 Innovative Computer-Aided Techniques for Future Wireless Applications

  • PPHE- AUTOMATIC DETECTION OF SENSITIVE ATTRIBUTE IN PRIVACY PRESERVED HADOOP ENVIRONMENT USING DATA MINING TECHNIQUES   Order a copy of this article
    by Kumaran U, Neelu Khare 
    Abstract: Online Social Networks (OSN) has become highly popular, where users are more and more lured to reveal their private information. To balance privacy and utility, many privacy preserving approaches have been proposed which does not well meet users personalized requirements. Most social networks based data sources such as Twitter, Facebook etc., have unstructured data and no analytics or processing tools can work directly on this unstructured data. Commonly, users lack in data privacy and the access control mechanisms available to remove the risk of disclosure. Thus, the privacy preserving paradigm is required that automatically preserves the user privacy to find the sensitive attribute and reduce the risk of sensitive information leakage. In this paper, we present a Privacy Preserved Hadoop Environment (PPHE) which automatically detects sensitive attribute using data mining techniques. This work considers Twitter which enable users to post messages. The content of the posted tweets are wide ranging and contains private information such as email addresses, mobile numbers, physical addresses, and date of births. In this context, the purpose of our work is fourfold. First, we authenticate each twitter users using the integrated algorithm RSA and Elgamal Algorithm. Second, we categorize the tweets into private and non-private attributes based on Type-2 Fuzzy Logic System. Third, we apply data suppression technique for private tweets and finally sharing users content based on their similarity information. Content similarity has evaluated using Cosine Similarity. Finally we evaluate the system performance in terms of accuracy, precision, recall, and F-measure.
    Keywords: Privacy preserving Data Mining; Online Social Networks; Twitter; Data Mining Techniques.
    DOI: 10.1504/IJCAET.2021.10018182
     
  • SIBLAR: Secured Identity-Based Location Aware Routing Protocol for MANETs   Order a copy of this article
    by Suma R, Premasudha B G, Ravi Ram V 
    Abstract: A Mobile Ad-hoc Network (MANET) is a self-organizing distributed wireless network without any central infrastructure support wherein every participating node independently acts as a router. Several routing protocols are available for information dissemination in MANETs but their efficiency is limited due to security breaches. Providing security schemes for robust information dissemination is of high prominence for the real time deployment of MANET applications. From the existing literature it is understood that very few research efforts were made to ensure security for routing protocols and there is a huge scope for the design and development of secured routing protocols for MANETs. In this paper, we have considered the security issues with respect to Location Aided Routing (LAR) and proposed a Secured Identity Based Location Aware Routing (SIBLAR) protocol to achieve system security with improved key refreshment mechanism. MANET scenarios were created in ns2 and the efficiency of the proposed SIBLAR protocol was evaluated based on certain performance metrics. In the presence of security attacks, the proposed SIBLAR scheme is found efficient when compared to basic LAR.
    Keywords: MANET; Security Attacks; Identity-Based Security; Routing; LAR; Performance analysis.

  • Divide-by-16/17 dual modulus prescaler design with enhanced speed in 180nm CMOS technology   Order a copy of this article
    by Uma Nirmal, V.K. Jain 
    Abstract: In this work, we propose a high-speed dual modulus divide by 16/17 prescaler Design IV with 8.9 GHz operating rate. It uses RE-3 type DFF in synchronous divide by 2/3 prescaler design and asynchronous divide by 8 counter design. It reduces: design complexity, capacitive loading and delay. The proposed Design IV shows better results in terms of both speed and power performance than other ratioed and ratioless divide by 16/17 prescalers.It is implemented in 180nm CMOS technology and consumes only 0.38 mW power from a 1V supply voltage. The speed of the new Design IV is improved by ∼53% compared with conventional circuit with operating frequency 5.8GHz.
    Keywords: divide by 16/17 dual modulus prescaler (DMP); TSPC; D Flip Flop (DFF); RE-0; RE-1; RE-2; RE-3; RE-4.
    DOI: 10.1504/IJCAET.2021.10018090
     
  • IOT enabled traffic sign recognition for safe driving   Order a copy of this article
    by Iwin Thanakumar Joseph 
    Abstract: In this paper we have designed and constructed an IOT based platform which can automatically send information about the road signs. Here, we will demonstrate the basic idea of how to set up a communication between the upcoming vehicle and the sign boards. This system will play an important role for the recognition and detection of specific locations like markets, schools, speed breakers, universities, hospitals, offices.., etc. Detecting and recognizing traffic signs is a challenging problem. Traffic sign recognition (TSR) is an issue of concern for the driver may be because of the speed in which they tend to travel at, especially on highways . We present a device that will detect the road sign with the help of IOT using a very simple logic. This paper provides an overview of the traffic sign detection with the help of the output generated by the IOT devices like NodeMCU. This addresses the problem of fast traffic sign recognition and detection to enhance safe driving. The proposed method includes the following stages. First, the connection between the server and the client is achieved when the client comes into the Wi-Fi zone created by the server. Second, the client and server enters into state of communication and in this stage the client receives the input provided by the server and provides the corresponding output. The third and final stage is when the audio alert is obtained based on the output of the client. The proposed approach can be very helpful for the development of a safe a driving environment.
    Keywords: Traffic Sign Recognition(TSR); NodeMCU; Wi-Fi zone - ESP8266; Audio alert -APR33A3.
    DOI: 10.1504/IJCAET.2021.10016782
     
  • A Hybrid SATS Algorithm Based Optimal Power Flow for Security Enhancement Using SSSC   Order a copy of this article
    by Kumar Cherukupalli, Padmanabha Raju Chinda, Sujatha Peddakotla 
    Abstract: Security and performance of the power system is the prime concern in its planning and operation. It is essential to devise proper measures for maintenance and improvement of security in the power system. Static Synchronous Series Compensator (SSSC) is a type of series flexible AC transmission system device. The present research proposes a hybrid simulated annealing and tabu search (Hybrid SATS) algorithm with SSSC to solve security constrained optimal power flow problem. The primary objective of the research work is to enhance the security of power system and minimize the generator fuel cost. Contingency ranking is used to select line outages. The line flow limit violations in various single line outages are relieved effectively by Hybrid SATS with SSSC method, which keeps power flows within their security limits. Simulation studies are carried out on standard IEEE 30 bus to identify effectiveness of proposed hybrid method and the obtained outcomes are put in comparison to SA with SSSC and TS with SSSC methods.
    Keywords: Security Constrained Optimal Power Flow; Simulated Annealing; Tabu Search; Static Synchronous Series Compensator.

  • HUPM-MUO: High Utility Pattern Mining under Multiple Utility Objectives   Order a copy of this article
    by Muralidhar A, PATTABIRAMAN V 
    Abstract: Mining the pattern of interesting items play a significant role in data analysis and decision-making strategies of real-time applications. Often the term "interest" in pattern discovery denotes the frequency of the pattern. In recent research domain of data mining is considering the utility of the item instead frequency, which indicates often profit. This manuscript argues that neither utility nor frequency of the itemset alone influence the target objective. Moreover, the profit is not only the utility factor of the itemset, apart from profit, the objectives like storage, saleability and other domain specific requirements can also be the utility factors. In regard to this argument, the manuscript endeavored to define a novel model that discovers the top-K high utility patterns under multiple utility objectives (HUPM-MUO). The experimental study was carried on various datasets, which portraying the performance advantage of the proposed model over the other contemporary models.
    Keywords: High Utility Itemset; Utility Mining; Rank Distribution Distance; Multi-Utility Objectives.

  • A Hybrid Approach to Diagnosis Mammogram Breast Cancer Using Optimally Pruned Hybrid Wavelet Kernel Based Extreme Learning Machine with Dragonfly Optimization   Order a copy of this article
    by Diderot. P. Kumara Guru, N. Vasudevan 
    Abstract: Breast cancer is one of the leading dangerous cancer types that may result in death. So, it is necessary to detect the cancer spot and provide early diagnosis which is termed as early detection. The detection of this type of cancer is difficult at initial stage because the cancerous tumors are rooted in the common breast tissue structures. The main objective of this research is to model a breast cancer prediction system with a novel machine learning approach based on wavelets is proposed. The prediction of breast cancer for diagnosis process is made by the proposed algorithm named as Hybrid Optimally Pruned Wavelet Kernel-based Extreme Learning Machine (HOP-WKELM). Initially, the input is pre-processed for noise reduction using kuan filter. After that, Quantum Evolutionary Algorithm (QEA) is applied to segment the cancer part in mammogram image and feature extraction using Grey-level co-occurrence matrix (GLCM), Gabor filter and Local Binary Pattern (LBP) features. The extracted features are classified using HWKELM classifier. In this HWKELM, WKELM learning algorithm utilized the Dragonfly Swarm Behavior-based Optimization (DSBO) approach to optimize the parameters of kernel functions. The proposed strategies achieved a maximum accuracy of 98.8% and a maximum precision of 98.1% when compared with existing Adaboost systems.
    Keywords: Breast cancer; Hybrid Wavelet Kernel-based Extreme Learning Machine; GLCM; Gabor; LBP and DSBO.

  • Hardware Implementation of modified SSD LDPC decoder   Order a copy of this article
    by Rajagopal Anantharaman, Karibasappa K, Vasundara Patel K.S 
    Abstract: In this work, a modification approach to the Simplified Soft Distance algorithm is discussed by considering soft Euclidean squared distance as a performance metric. The SSD algorithm is theoretically independent of the signal to noise ratio of the received signal. Multiplication and addition terms are the only constituents of this algorithm which reduces the complexity.In this paper, an attempt has been done to compare and analyse the performance of modified SSD with other popular algorithms such as SPA, SSPA, and LogSPA. The algorithm is implemented on Virtex-5 xc5vlx110t FPGA kit to observe the real time implications and draw apt conclusions. From the FPGA results, this paper aims to conclude the performance of modified SSD is similar to that of Log SPA with changes observed as improved throughput speed and improved bit error rate (BER).
    Keywords: Simplified Soft Distance (SSD); Field Programmable Gate Array(FPGA); Bit Error Rate(BER); Sum Product Algorithm(SPA); Simplified Sum product Algorithm(SSPA); Logarithmic Sum Product Algorithm (LogSPA); Low Density Parity Check Codes (LDPC).

Special Issue on: Applications of Computer and Engineering Technology in Enabling Technologies and Industrial Case Studies

  • Dye sensitized solar power generating window: towards environmentally sustainable energy efficiency in ICT   Order a copy of this article
    by Zulfiqar Ali Umrani, Mehboob Khatani, Mohammad Aslam Uqaili, Norani Muti Mohamed, Nor Hisham Hamid, Bhawani Shankar Chowdhary 
    Abstract: Information Communication Technology (ICT) equipment generates significant amount of Green House Gas (GHG) which can be reduced via utilization of solar energy. Presently, the ICT produces more than 830 million tons of carbon dioxide (CO2). That is about 2 percent of global CO2 emissions, and it is expected to double by 2020 [1][2][3]. There is a need for ICT to first standardize, energy consumption and emissions and then investigate means to reduce the energy consumption via efficiency and innovation. The electricity consumption which dominates the direct carbon footprint of the ICT sector can be reduced by using renewable energy sources. Solar cells that operate efficiently under diffuse lighting are of great practical interest as they can serve as electric power sources for portable electronics and devices for wireless sensor networks and Internet of Things. This property allows them to operate and generate power inside the built environment. The dye sensitized solar cell (DSC) is a green and renewable energy device that works well in low light conditions. The transparent characteristic of DSCs makes it suitable for building integrated photovoltaic (BIPV) applications such as window systems. In this study, we fabricated and assembled a transparent power generating window of active area 0.228 m2 based on dye sensitized nanocrystalline TiO2 solar module that generates ~1.4A current and 5.8V open circuit voltage at 60 mW/cm2 and ~0.5 A short circuit current and 5.3 V at 33 mW/cm2 that was installed in a building environment to power up the ICT products. The device was connected with an ICT equipment and tested. The DSC successfully powered the ICT system. Such building integrated DSC systems can potentially power ICT devices in homes and offices.
    Keywords: ICT; dye sensitized solar cells; sustainability; Building integrated photovoltaics.

  • Impact of the Lossy Image Compression on the Biometric System Accuracy: A Case Study of Hand Biometrics   Order a copy of this article
    by Djamel Samai, Abdallah Meraoumia, Mouldi Bedda, Abdelmalik Taleb-Ahmed 
    Abstract: Biometric recognition systems use in several cases, images to authenticate or identify persons. Storing of large images require large storage space. To reduce the storage space, compression methods are employed. In this paper, we analyse the effect of lossy image compression on the performance of biometric identification systems. We propose a scheme to evaluate the Multi-Spectral Palmprint (MSP) and Finger-Knuckle Print (FKP) recognition performance at low bitrates. The images are compressed using Set Partitioning In Hierarchical Trees (SPIHT) encoding. A powerful texture descriptor is used to represent the extracted features of different images. It is based on quantising the phase information of the local Fourier transform, which leads to computationally efficient and compact feature representation. We have employed the Nearest Neighbour (NN) classifier, or the nonlinear multiclass Support Vector Machine (SVM) model to classify the feature extraction. The obtained results show that the compression does not significantly affect the performance of recognition systems at low bitrate. Thus, the low bitrate MSP or FKP images perform equivalent to the higher bit rate images in recognition system. In order to improve the proposed recognition systems and confirm the results found in the unimodal recognition systems, we made efficient multimodal recognition systems by fusion modalities at matching-score level. Experiments of identification proved the superiority of fusion modalities to every single modality.
    Keywords: Biometrics; MSP; FKP; SPIHT; ML-LPQ; Matching-score level.

  • An Extended Infrastructure Security Scheme for Multi-Cloud Systems with Verifiable Inter-Server Communication Protocol   Order a copy of this article
    by Vijay Gr, A. Rama Mohan Reddy 
    Abstract: Cloud service providers need to have elevated level of security than local system users as users outsource their data to a remote system relying on its genuineness and also data has to be protected from intruders that exist globally. Multi-cloud systems are more prone to various kinds of attacks due to numerous internal communication of sensitive data. Multi-cloud infrastructure security can be enhanced by using stringent encryption algorithms or protocols with several integrity checks on each transaction, but that may drastically reduce the efficiency of the system. This research is one of a kind where we propose a multi-cloud framework comprising different techniques for data security as well as internal server communication security that can efficiently secure the privacy of data from eavesdroppers. Use of efficient cryptographic algorithms, modified Diffie-Hellman key exchange scheme and fragmentation technique assure overall efficiency of system along with high security. The newest variant of SHA i.e. SHA-3 outperformed other variants in terms of time efficiency and security. Results on multi-cloud setup demonstrates efficiency of proposed framework in terms of time taken for data storage, computations and retrieval while eliminating risks of attacks.
    Keywords: Cloud Computing; Multi-Cloud; Data Security; Cryptography; Key Exchange Protocol.

  • PERFORMANCE ANALYSIS OF BIORTHOGONAL FILTER DESIGN USING THE LIFTING BASED SCHEME FOR MEDICAL IMAGE TRANSMISSION   Order a copy of this article
    by Chetan Huchegowda, Indumathi G, Naveen Huchegowda 
    Abstract: To minimize the storage space and for the fast transfer of the digital images, it is necessary for the medical images to undergo image compression. There are various techniques in which the images are being diagnosed, based on that the image compression is to being performed. The choice of the filters in the image compression is an issue, which affects the quality of the image. Hence, a novel biorthogonal filter using the lifting scheme has been developed. The proposed architecture gives the same characteristics of second generation wavelets. The proposed architecture is designed using MATLAB for different medical images and the PSNR, SNR, MSE, BPP and the Compression Ratios values are calculated. Finally the proposed lifting scheme architecture is designed using Verilog to obtain the details of area, delay and power.
    Keywords: DWT; DTDWT; medical Image Transmission ,Biorthogonal Filter.

  • MOEMS Based Accelerometer Sensor Using Photonic Crystal for Vibration Monitoring in Automotive Systems   Order a copy of this article
    by SUNDAR SUBRAMANIAN, Gopalakrishna K, Thangadurai N 
    Abstract: Diagnosing the vibration in automobiles has got great priority since it provides comfort to the passenger inside vehicle. This paper presents MOEMS accelerometer sensor by using photonic crystal. Spring mass system with photonic crystal technology is visualized and scrutinized. Optical sensing system with photonic crystal technology studied and simulated with rods in air and holes in slab configuration. Due to applied force deflection of rectangular defect slab for vertical and horizontal movement is verified. Gaussian pulse propagated through the defect region in photonic crystal slab was resulting wavelength shift for each defection of slab. Transmission spectrum obtained for each deflection direction of slab and configurations. Q factor analyzed for each displacement of slab found to be 3210 for HIS vertical movement. It is found that distinct change in wavelength has obtained for Holes in slab configuration during vertical and horizontal movement of slab compared to the results of Rods in air configuration. Obtained results showed feasibility of future fabrication for HIS configuration
    Keywords: Photonic crystal; Accelerometer; Rods in Air (RIA); Holes in slab (HIS); Vibration; Micro displacement; Light Propagation; Q-factor; Monitoring,MOEMS.

  • HETEROGENEOUS WIRELESS NETWORK SELECTION BY COMBINING GRA AND VIKOR UNDER FUZZY ENVIRONMENT   Order a copy of this article
    by SASIREKHA VENKATACHALAM, Ilangkumaran Mani, Arulmurugan Loganathan 
    Abstract: In Heterogeneous wireless environment, network selection is a strategic issue and has a significant impact on providing the best Quality of Service (QoS) to the users. The selection of an apt network among various alternatives is a kind of Multi Criteria Decision Making (MCDM) problem. This paper proposes a model based on VlseKriterijumskaOptimizacija I KompromisnoResenje (VIKOR) under fuzzy environment and Grey Relational Analysis (GRA) for the selection of suitable network in heterogeneous wireless environment. Here, Triangular fuzzy linguistic variables are used to handle the vagueness and subjectivity of the decision making process. This study focuses on four alternatives such as Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE), Worldwide Interoperability for Microwave Access (WiMAX), wireless local area network (WLAN) and six evaluation criteria such as throughput, delay, jitter, packet loss, cost, security are considered for choosing the suitable network in heterogeneous wireless environment. An efficient pair-wise comparison process and ranking of alternatives can be achieved for optimum network selection through the integration of Fuzzy with GRA and VIKOR. The obtained preference order of the network for Fuzzy-GRA-VIKOR and Fuzzy VIKOR are LTE>WiMAX> WLAN> UMTS and LTE>WiMAX> UMTS > WLAN respectively. Hence by comparing both these methods LTE is selected as the best network among the various alternatives. The combination of Fuzzy-GRA-VIKOR techniques will be assessed and suggested for each type of network traffic classes. This paper highlights the significance of MCDM techniques for network selection problem in heterogeneous wireless environment.
    Keywords: Multi Criteria Decision Making; MCDM; VlseKriterijumskaOptimizacija I KompromisnoResenje; VIKOR; Grey Relational Analysis; GRA; Fuzzy sets; Network selection.

  • An empirical analysis of the statistical learning models for different categories of Cross Project Defect Prediction.   Order a copy of this article
    by Lipika Goel, Mayank Sharma, Sunil Kr Khatri, D. Damodaran 
    Abstract: Currently, research community is addressing the problem of defect prediction with the availability of project defect data. The availability of different projects data lead to extend the research on Cross projects. Cross project defect prediction has now become an accepted area of software project management. Various defect prediction models have been applied on cross project data, focusing on the analysis and applications to evolve software reliability. In this paper, empirical study is carried out to investigate the predictive performance of available within project and cross project defect prediction models. Furthermore, different categories of cross project data are taken for training and testing to analyze various statistical models. Further in this study, k-fold cross validation is done on the training datasets to evaluate the training accuracy of the models. In this paper data models are analyzed and compared using various statistical performance measures. The findings during the empirical analysis of the data models state that Gradient Boosting predictor outperforms in the cross project defect prediction scenario. Results also infer that cross project defect prediction is comparable to within project defect prediction with statistical significance. Thereby we can say that even if little or no data exists for within project data then data from cross project can be considered for defect prediction.
    Keywords: defect prediction; cross projects; within-project,machine learning.

  • Parameter extraction of PSP MOSFET model using Particle Swarm Optimization   Order a copy of this article
    by Amit Rathod, Rajesh Thakker 
    Abstract: System on Chip (SoC) architecture offers performance acceleration by offloading compute-intensive functions in FPGA logic, together with application specific instruction set processor (ASIP). In this paper, we report a novel approach of SoC implementation for MOSFET parameter extraction at hardware level using Xilinxs Zynq 7000 SoC AVNET ZedboardTM platform. Parameter extraction of PSP MOS model of 65 nm technology devices has been carried out using Particle Swarm Optimization (PSO) algorithm. It is demonstrated that the SoC implementation of PSO algorithm is able to accurately minimize the rms error between model generated data and experimental data below 9.5%. ARM Cortex A9 processor inside the Zynq 7000 SoC, found capable to execute the MOSFET Model library. It has been observed that proposed SoC implementation of PSO algorithm runs 3.68 times faster compared to software based approach.
    Keywords: Evolutionary algorithm; MOSFET parameter extraction; Particle Swarm Optimization; PSP MOSFET model; System on Chip; Zynq 7000 SoC.

Special Issue on: Future Directions in Computer-Aided Engineering and Technology

  • Improved Indoor Location Tracking System for Mobile Nodes   Order a copy of this article
    by SUNDAR S, KUMAR R, Harish M.Kittur 
    Abstract: The solutions to the problem of the tracking a wireless node is approached conventionally by (i) Proximity Detection, (ii) Triangulation and (iii) Scene Analysis methods. In these, scene analysis method is simple, accurate and less expensive. Indoor localization technologies need to address the existing inaccuracy and inadequacy of Global Positioning based Systems (GPS) in indoor environments (such as urban canyons, inside large buildings, etc.).This paper presents a novel indoor Wi-Fi tracking system with minimal error in the presence of barrier using Bayesian inference method. The System integrates an Android App and python scripts (that run on server) to identify the position of the Mobile node within an indoor environment. The received signal strength indicator (RSSI) method is used for tracking. Experimental results presented to illustrate the performance of the system comparing with other methods. From the tracked nodes, a theoretical solution is proposed for finding shortest path using Steiner nodes.
    Keywords: Location Tracking; GPS; MANETs; Mobile nodes; Wi-Fi Access points; WLAN; Bayesian Inference; RSSI; Shortest paths; Steiner nodes.
    DOI: 10.1504/IJCAET.2020.10011974
     
  • Bi-level User Authentication for Enriching Legitimates and Eradicating Duplicates (EnEra) in Cloud Infrastructure   Order a copy of this article
    by Thandeeswaran R, Saleem Durai M A 
    Abstract: Ease of usage of Cloud computing leads to an exponential growth in all sectors. Exponential growth always attracts duplicates to consume and deplete resources. Cloud is not exempted from invaders and overwhelming the resource utilization thereby availability become a threat. Availability issue arises due to multiple requests towards the same victim, a DDoS attack. Hence, the major concern in the cloud is to rightly identify legitimates, and providing the required services all time go by avoiding DDoS attacks. Multiple techniques are available to identify and authenticate the users. This paper not only just try to authenticate the users but also works on eliminating the invaders in two fold. In the first phase, the user ID is scrambled in four different steps. In the second phase, the users are authenticated depending on the credits. Based on the traffic flow (in the case of network level attack) and on the interval between consequent service requests (in the case of service level attack), users are authenticated upon which services are provisioned accordingly. The simulation results presented here exhibits the strength of the proposed method in detection and prevention of DDoS attack in cloud computing environment.
    Keywords: DDoS attack; SSID; Authentication; credits; cloud environment; legitimate; attackers.

  • Improved automatic age estimation algorithm using a hybrid feature selection   Order a copy of this article
    by Santhosh Kumar G, Suresh H. N 
    Abstract: Age estimation (AE) is one of the significant biometric behaviors for emphasizing the identity authentication. In facial image, Automatic-AE is an actively researched topic, which is also an important but challenging study in the field of face recognition. This paper explores several algorithms utilized to improve AE and the combination of features and classifiers are associated. Initially, the facial image databases are trained and then the features are extracted by employing several algorithms like Histogram of Oriented Gradients (HOG), Binary Robust Invariant Scalable Keypoints (BRISK), and Local Binary Pattern (LBP). Here, the AE is done in three various age groups from 20 to 30, 31 to 50 and above 50. The age groups are classified by utilizing Na
    Keywords: Age estimation; BRISK; HOG; LBP; NBC.

  • Hybrid Algorithm for Twin Image Removal in Optical Scanning Holography   Order a copy of this article
    by P. Bhuvaneswari Samuel, A. Brintha Therese 
    Abstract: Optical Scanning Holography is an incoherent optical image processing system. It is a technique, where the complete information of an object or image will be recorded as a hologram and later reconstructed to get back the original image. In the hologram reconstruction process, a virtual image is formed along with the real image, which appears as a twin image noise. To eliminate such noises, a technique of Hybrid Algorithm is used while recording the hologram itself. Hybrid algorithm is derived from the combination of conventional Optical Transfer Function (OTF) used in existing method and the proposed OTF obtained by varying the spatial frequency and arrived to an optimal spatial frequency which imparts good quality of image. Various images are tested with the Hybrid Algorithm. The Matlab R2012b image processing tool is used for simulation and the simulated values are tabulated and compared with the existing method in terms of Peak Signal to Noise Ratio, Mean Square Error. In the reconstruction, the proposed method results are having 26% increment in the MSE and PSNR values. To further improve the MSE and PSNR values a case study using different denoising techniques combined with the proposed hybrid algorithm is used and found considerable improvement of 32%. Hence the image quality is increased.
    Keywords: Optical Scanning Holography; Fresnel Zone plate; OTF ; spatial frequency; twin image noise; denoising.
    DOI: 10.1504/IJCAET.2020.10010579
     
  • Evaluation of Video Watermarking Algorithms on Mobile Device   Order a copy of this article
    by Venugopala P S 
    Abstract: Advancement of Internet services and design of image and video capturing devices along with various storage technologies has made video piracy an issue. Asserting the originality of digital data and having a copyright on the file is always a challenging task. Digital watermarking is a technique of embedding secret information known as watermarks within image or video file. This can be used for authentication and ownership verification purposes. This paper presents an analysis of mobile deployment of various video watermarking algorithms. The analysis is carrie dout using the quality parameters like PSNR, time of execution and power consumption. The goal of video watermarking method, implemented on a mobile phone, is to enhance security and to achieve copyright protection for the video files that are captured using a mobile phone. The video file is applied with three different watermarking methods, DCT, LSB and Bit stream. These methods are compared for their performance using the parameters PSNR, power consumed and time of execution. It is observed that, the proposed Bitstream method gives better performance compared to other methods for these parameters.
    Keywords: DCT; LSB; Bit stream; Watermarking; Copyright protection.

  • Automatic Identification of Acute Arthritis from Ayurvedic Wrist Pulses   Order a copy of this article
    by Arunkumar N, Mohamed Shakeel P, Venkatraman V 
    Abstract: Traditional ayurvedic doctors examine the state of the body by analyzing the wrist pulse from the patient. Mysteriously the characteristics of the pulses vary corresponding to the various changes in the body. The three pulses acquired from the wrist are named as Vata, Pitta and Kapha. Ayurveda says that when there is imbalance in these three doshas, one will have disease. Two different diseases will have different patterns in their pulse characteristics. Thus the wrist pulse signal serves as a tool to analyze the health status of a patient. In the earlier work, we have standardized the signals for normal persons and then classified the diabetic cases using approximate entropy (ApEn) [10] and later enhanced the results using sample entropy. In the present work, sample entropy (SampEn) is being used to classify for the acute arthritis cases.
    Keywords: Vata; Pitta; Kapha; Approximate Entropy(ApEn); Sample Entropy (SamPEn).

  • A Real-Time Auto Calibration Technique for Stereo Camera   Order a copy of this article
    by Hamdi Boukamcha, Fethi Smach, Mohamed Atri 
    Abstract: Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision. Usually, to get accurate 3D results the camera should be manually calibrated accurately as well. This paper proposes a robust approach to Auto Calibration stereo camera Without intervention of the user. There are several methods and techniques of calibration that have been proven, in this work we exploiting the geometric constraint, namely, the epipolar geometry. We specifically focus to use 7 techniques for Features Extraction (SURF, BRISK, FAST, FREAK, MinEigen, MSERF, SIFT), however tries to establish the correspondences between points extracted in stereo images with Various Matching Techniques (SSD, SAD, Hamming).Then we exploit the Fundamental Matrix to estimate the epipolar Line by choosing the perfect Eight-point algorithms (Norm8Point, LMedS, RANSAC, MSAC, LTS). rnA large number of experiments have been carried out, and very good results have been obtained by Comparison &choice the perfect technique in every stage.rn
    Keywords: Auto calibration; Robust matching; Epipolar geometry; Fundamental matrix; Matching Technique.
    DOI: 10.1504/IJCAET.2020.10016061
     

Special Issue on: Recent Trends and Developments of Computer Vision and Image Processing

  • Effective user preference mining based personalized movie recommendation system   Order a copy of this article
    by Subramaniyaswamy V, Logesh R, Vijayakumar V, Hamid Reza Karimi, Marimuthu Karuppiah 
    Abstract: One of the primary issues of many websites is the suggestion of multiple choices to the users at the same time, which makes the task more complex and time consuming to find the right product. Web mining and recommendation system based on user behavior helps users by providing essential information without asking explicitly. Several movie recommendation systems are available to suggest movies, but often they dont do that effectively. To achieve enhanced effectiveness and efficiency, users movie ratings were retrieved, cleaned, formatted and grouped into proper, meaningful session and data profile was developed. In this paper, we have developed a new ontology for clear and better understanding of the movie domain. The user data consisting of movie ratings is used to recommend movies for the users. For the classification of users, we use Adaptive K-Nearest Neighbor (AKNN) approach and post classification process, movies are recommended to the active target user. The obtained results of the proposed recommendation approach are compared with existing baseline methods, and the results prove that the presented approach to be proficient.
    Keywords: Recommender Systems; Personalization; Adaptive kNN; Ontology; Web Mining; Classification.

  • An Approach for Infrared Image Pedestrian Classification based on Local Directional Pixel Structure Elements' Descriptor   Order a copy of this article
    by S. Rajkumar 
    Abstract: Pedestrian classification is a major problem in infrared (IR) images due to lack of shape, low signal-to-noise ratio and complex background. And it find applications in agriculture, forestry, night vision monitoring system, intelligence system and defense system. In this paper, local directional pixel structure elements' descriptor (LDPSED) based pedestrian classification approach is proposed to overcome these problems. In addition, for segment the objects (pedestrian and non-pedestrian) from an IR image interest point detection approach is proposed. The proposed method consists of three steps segmentation, feature extraction and classification. Firstly, objects are segmented from the input image. Secondly, the feature extraction is carried out on the segmented objects. Finally, support vector machine (SVM) is implemented for classification of objects in IR image into pedestrian and non-pedestrian. To prove the effectiveness of the proposed approach, we have conducted experimental test on the standard OTCBVS-BENCH-thermal collection over the OSU thermal pedestrian database. In addition, the classification results of the proposed approach is comparedrnwith the existing approaches. The efficiency of the proposed approach proved by high classification accuracy.
    Keywords: Infrared image; Local directional pattern; Structure element descriptor; Support Vector Machine; Pedestrian classification.

  • An Efficient Image System based Grey Wolf Optimizer Method for Multi Media Image Security using Reduced Entropy Based 3D Chaotic Map   Order a copy of this article
    by SRINIVAS KOPPU, Madhu Viswanatham V 
    Abstract: Chaotic maps plays an important role in information sharing. In this paper a Grey Wolf Optimizer used with reduced entropy based 3D chaotic map. The selection and High coefficients are selected based on the reduced entropy value to identify the optimized parameters to get unpredictable random values. Time complexity, Autocorrelation of V, H and D elements, Histogram of original and cipher images, Peak signal to noise ratio and NPCR and UACI values are computed from the cipher image. The empirical results show the proposed method provides good, better imperceptibility and defends various attacks. To prove this accomplishment of the method, several experiments were conducted and compared the results with existing systems.
    Keywords: Encryption/Decryption; Chaos; 3D Choatic map; Entropy; Grey Wolf Optimizer.

  • Caliber fuzzy c-means algorithm applied for retinal blood vessel detection   Order a copy of this article
    by Gowri Jeyaraman, Janakiraman Subbiah 
    Abstract: Retinal blood vessel detection employs a vital role in finding of Retinal diseases like diabetic retinopathy and glaucoma. This paper presents an innovative unsupervised retinal blood vessel detection technique. First step is to generate a vessel enhanced image, then using Caliber Fuzzy C-means (CFCM) technique, first cluster the Retinal image; next the clustered image is passed to the canny edge operator and finally post process the retinal image. CFCM clustering method for blood vessel detection is based on the choice of the number of clusters value. By using CFCM clustering function, compute the cluster center, which commonly divides the image into four clusters. The proposed technique is obviously forceful into the modification of fuzzy c-means with canny algorithm. The proposed algorithm accomplishes an accuracy of about 95% of retinal images from three data sets DRIVE, STARE, and CHASE_DB1.
    Keywords: fuzzy c-means clustering; retinal image; self organized map.
    DOI: 10.1504/IJCAET.2021.10020685
     
  • Effective Image Stego Intrusion Detection System using Statistical Footprints of the Steganogram and Fusion of Classifiers   Order a copy of this article
    by Hemalatha J 
    Abstract: Enlightening the processing record of a digital image is a significant problem for steganalyzers and the forensic analyzers. In the present day, the most precise steganalysis techniques are built as supervised classifiers by extracting the feature vectors from the digital media. This paper presents an ensemble classification method for effective image stego intrusion detection system on JPEG images consists of two step process. In the first step the features are engineered as higher-order statistics for blind steganalysis. In the second step ensemble classifier is used by fusing the classifiers such as support vector machine, neural networks, k-nearest neighbors. By applying the mentioned classifiers to these features, the steganogram and the clear (unadultered) carrier signals are effectively discriminated. For generating the image dataset, images are undergone with six embedding schemes with different payload. Experimental results show that the proposed approach remarkably improve the metrics such as specificity, sensitivity and accuracy (94%) of the system.
    Keywords: SVM; Ensemble; Higher order statistics.

  • Incipient Knowledge in Protein Folding Kinetics States Prophecy Using Deep Neural Network based Ensemble Classifier   Order a copy of this article
    by ANBARASI M, SALEEM DURAI M. A 
    Abstract: In this paper, we focus on incipient knowledge in the prediction of protein folding kinetics states using deep neural network based stacking technique in ensemble classifier. Protein folding procedure is highly crucial for deciding the molecular function. The protein folding kinetic states check whether particle stimulus structure has done with the intermediary or not. Folding structure can be done with the stable intermediary (3S/3States) and without stable intermediary (2S/2State). Furthermore, there is a vast number of proteins in PDB still unfolding mechanism are found unknown. In this paper, we proposed stacking with the deep neural network for predicting protein folding kinetics states. In first level learning, we have used five base classifier, i.e., naive bayesian, decision tree, random forest, support vector machine and neural network and in the second level meta-learning we have used the rule based method and deep neural network based stacking in ensemble classifier for increasing the accuracy.
    Keywords: protein folding; two states; multi states; deep neural network; stacking; ensemble classifier;.

  • TYPE-SPECIFIC CLASSIFICATION OF BRONCHOGENIC CARCINOMAS USING BI-LAYER MUTATED PARTICLE SWARM OPTIMIZATION   Order a copy of this article
    by Balamurugan P, Viswa Bharathy AM, Marimuthu K, Niranchana R 
    Abstract: The cancer disease is posing a big challenge in the field of pathological diagnosis. The feature selection of cells is highly important in isolating the affected cells. The classification of cancer cells is gaining importance among clinical researchers. Gene Expression Profile (GEP) is used in better classifying genes in a cell or tissue. Gene Expression Data (GED) differs for every gene from which cell or tissue it is originated. Based on the GED the cancer cells can be classified into seven categories from which cell or tissue it was born. The infected cells can be graded from level one to four based on its growth and difference from other unaffected cells. Many techniques have been developed in the past for classifying cancer affected genes. In this paper we propose a modified classification algorithm Bi-Layer Mutated Particle Swarm Optimization (BLMPSO). The microarray dataset used for testing the method is Affymetrix Human Genome U95Av2 Array. The simulation results showed that the proposed technique performs better in terms of classification based on GED than the other existing methods.
    Keywords: cancer cells; feature selection; classification; gene expression; mutation; PSO.

  • Steganographic approach to Enhance the Data Security in Public Cloud   Order a copy of this article
    by Prabu S, Gopinath Ganapathy 
    Abstract: Steganography is the claim to fame of disguising how correspondence is happening, by hiding information in other information. As picture encryption is a quickly creating innovation in the field of picture preparing, it can be portrayed as the strategy for encoding messages and data especially to such an extent that it can be gotten to ensured elements as it were. The paper manages an overview which deals with delineation enigma, along with its applications as well as techniques. It moreover endeavors so that it can recognize the essentials of a respectable enigma figuring as well as swiftly considers the steganography procedures that are better suitable for specific applications. Information transmission crosswise over systems is a typical practice according to the advancement of Internet and sight and sound advances that develops exponentially today. The paper displayed about the mystery sharing of the message by concealing it in a picture utilizing the most ordinarily utilized LSB (Least Significant Bit) method. Here, steganography went for concealing the information imperceptibly inside any media (picture, sound, and video) so it ought to be unnoticeable to the unintended individual and in this manner accomplishing secured applications.
    Keywords: Encryption; Decryption; Least Significant Bit; Bitmap Steganography; Data Security; Cloud Computing.

Special Issue on: Ubiquitous Sustainable Systems

  • Gender Classification using PSO based Feature Selection and Optimized BPNN in Forensic Anthropology   Order a copy of this article
    by Nurul Liyana Hairuddin, Lizawati Mi Yusuf, Mohd Shahizan Othman, Dewi Nasien 
    Abstract: The development of biological profile allows gender classification which is a crucial task in most forensic cases. A biological profile is developed by the anthropologists to assist in the identification process of an individual. In most forensic anthropology cases, skeleton remains are employed in the process of producing a biological profile. There are different parts of human skeleton available for the process of gender classification. Every part of skeleton contains different types of features and this benefits toward gender classification. However, not all the features can contribute toward gender classification because some features do not carry any information on gender and some data may have redundant information. Hence, this article proposed Particle Swarm Optimization (PSO) based feature selection and optimized BPNN model as a gender classification framework. Initially, PSO functions to select the most significant features that lead to an accurate classification process. While BPNN process, the parameter tuning based on cross-validation technique is applied where the model able to find a good combination of learning rate and momentum. The main scope of this article is to develop a framework that able to conduct a proper feature selection process and parameter optimization for accurate gender classification in forensic anthropology field. This article utilized three different sets of data which are Goldman Osteometric dataset, Clavicle collection, and George Murray Black collection. The result shows that the accuracy of gender classification is improved for every dataset via the proposed framework.
    Keywords: Gender classification; forensic anthropology; feature selection; particlernswarm optimization; backpropagation neural network; parameter tuning.