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 (155 papers in press)

Regular Issues

  • 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).
    DOI: 10.1504/IJCAET.2021.10027321
     
  • 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 BEHAVIOUR OF Al6061-ZnO(P) METAL MATRIX COMPOSITE THROUGH WIRE CUT ELECTRO DISCHARGE MACHINING USING MULTI OBJECTIVE OPTIMISATION 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.

  • 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
     
  • 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.
    DOI: 10.1504/IJCAET.2021.10026517
     
  • 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.
    DOI: 10.1504/IJCAET.2022.10027539
     
  • 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.
    DOI: 10.1504/IJCAET.2022.10026499
     
  • 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.

  • Semi-Blind Estimation of CFO and Channels for STBC-OFDM System   Order a copy of this article
    by Mokhtar BESSEGHIER, Ahmed Bouzidi DJEBBAR 
    Abstract: Space Time Block Coding-Orthogonal Frequency Division Multiplexing (STBC-OFDM) based MIMO (Multi Input Multi Output) system has been shown to be robust against non ideal operating conditions such as antenna correlation, channel estimation errors, and Doppler effects. But, the later suffers from carrier frequency offset (CFO) which makes channels estimation more challenging.rnIn this paper, we propose joint semi-blind CFO and channels estimators based on modified- multiple signal classification (M-MUSIC) algorithm for STBC-OFDM system over MIMO channels. Channels state information can be estimated at the receiver using pilot symbols embedded in each transmission block. To this end, we propose to encode pilot symbols by a Specific Space-Time Block Coder (S-STBC) while information symbols are encoded by Alamouti based space-time block coding (A-STBC). MUSIC based estimation algorithms are characterized by a high computational complexity. To overcome this drawback, we derive an iterative algorithm which leads to low complexity, high performance CFO and channels estimation. The performance of our algorithms is compared with existing approach by simulations.
    Keywords: Alamouti; CFO; Channels estimation; MUSIC; Virtual Subcarriers (VSCs); pilot symbols.

  • STABLE-PLASTIC NEURAL NETWORK, WHICH DEFINES SEVERAL SOLUTIONS AND NEW INFORMATION ON ITS INPUTS   Order a copy of this article
    by Valery Dmitrienko, Sergey Leonov, Aleksandr Zakovoroyniy 
    Abstract: Results of analysis the features of functioning discrete Hamming neural network, which can not learn in the process of functioning, not determine new information on its input layer and not recognize input black-and-white images that located at the same minimum distance from two or more reference images. The shortcomings of neural networks using the Hamming distance and solving this problem for images located on the boundaries of two or three classes of images. A modification of the Hamming neural network, which does not have the aforementioned shortcomings. Figs.: 2. Refs.: 10 titles.
    Keywords: neural network of Hamming; reference images; images on the boundaries of two or three classes; new information.

  • Reliability allocation and optimization by using Kuhn-Tucker and geometric programming for series-parallel system   Order a copy of this article
    by Ahmed Ali 
    Abstract: In this paper, two models are proposed to maximizing the lifetime stochastically of the series - parallel system\r\nby properly allocating reliabilities for each component of the\r\nsystem mentioned above. The optimization problem of reliability\r\nsystem was also used to calculate the best values for the reliability\r\nallocated to each system component and thus calculate the\r\ntotal cost.The results include: (i) a critical point in seriesparallel system is a fixed point , (ii) the first cost Tillman\r\nfunction is Euclidean convex, (iii)the optimization problem, such a\r\ncost function and constraints functions(active,inactive), associated\r\nwith polynomial of reliability, leads us to adopt an geometric\r\nprogramming method to allocate reliability and calculate total\r\ncost.
    Keywords: Reliability optimization; Redundancy allocation.

  • Power Reduction of Standard Cells by Controlling Leakage Current   Order a copy of this article
    by Suman Bhowmik 
    Abstract: Power is one of the important design criterions of VLSI circuits. Leakage power dissipation contributes to a considerable amount of total power dissipation for the circuit designed below 50 nm technology. In this paper two techniques are proposed to reduce leakage power as well as total power of logic circuits by circuit level modification. The techniques use some extra foot transistors along with capacitor to reduce leakage power. As a basic building block, NAND and NOR gate up to 4 inputs are modified accordingly for leakage reduction without violating the proper logic operation. The proposed techniques have also been extended to a larger circuit to confirm its power utility. In this case a full adder circuit has been partitioned in 4 clusters and the proposed technique has been implemented in different low power configurations. Leakage power dissipation, total power dissipation, energy and the trade-off among them of the new designs have been discussed and compared with the results of conventional CMOS circuits. Best adder configuration exhibit more than 20% saving in leakage and 28% saving in total power. In this work, the proposed technique have been implemented in standard cells only. However these techniques can be applied for leakage reduction of bigger circuits also. For circuit design and simulation virtuoso Cadence tool at 45nm technology has been used.
    Keywords: Leakage power; CMOS; Standard cells.

  • Secure Voting Scheme for Elections   Order a copy of this article
    by Gautam Srivastava, Jabbar El-Gburi, Senthilkumar Mohan 
    Abstract: In this paper, we present a novel Electronic Voting System (EVS) for political and social elections based on known Cryptographic schemes. In cryptography, the ElGamal encryption system is an asymmetric key encryption algorithm which is based on Diffie-Hellman key exchange. We use the ElGamal algorithm to generate and encrypt random keys for the voters. This scheme is designed in a way that the communication channels are anonymous and in the meantime privacy, eligibility and fairness are applied to the entire system. Encrypted receipt-free transactions are provided to the voters after they submit a vote successfully. After the voting completes the voters can check on voting online using the encrypted receipt, only to confirm their participation in the election. The voters will not be aware of the chosen candidate to prevent cheating and vote selling, common issues in elections these days. The name of the chosen candidate will be confidential. The proposed voting system efficiently gives the opportunity for people to vote via their own PCs/laptops, thus decreases the queues accumulated up at voting centers. In addition, it offers a highly dependable authentication approach by national ID or biometrically which leads to overcoming electoral fraud.
    Keywords: Secure voting; online elections; encryption; cryptography.

  • On generating random graphs with hard and soft constraints   Order a copy of this article
    by Mohamed Amine Omrani, Wady Naanaa 
    Abstract: Since its appearance in discrete mathematics, graphs have gained increasing importance due to their capacity to model and solve real-world computational problems. They even make it possible to handle fuzzy situations. The current research investigates the issue of generating random graphs using both hard and soft constraints. The aim of this paper is to suggest a constraint-based encoding of the cited problem in order to take advantage of the flurry of efficient solution algorithms available within the constraint programming framework. Experimental results obtained from a series of tests confirm the proposed method that lays the basis for further real world applications in different fields, such as analytical chemistry, telecommunication networks, and civil engineering.
    Keywords: Graph theory; constraint satisfaction problem; constraint programming; uncertain proximity relationship; induced subgraph; forbidden patterns; imposed patterns.

  • A Semi-Automatic System of Web Videos Annotation and Retrieval: Application to Events Detection in Soccer Domain   Order a copy of this article
    by Lamia Fatiha KAZI TANI, Abdelghani GHOMARI, Mohammed Yassine KAZI TANI 
    Abstract: Annotations of soccer matches from the web become the fashion area of research. Detecting objects in order to recognize events in soccer matches videos is a challenging task. In this paper, we propose to consider Deep Learning and Ontology paradigm as a complete and intelligent solution. However, the semantic gap that exists between low-level features extraction and high-level semantic interpretation exposes a serious problem. Our solution is divided into two parts, the first one concerns low-level features extraction; and the second one represents the creation of soccer ontology; this, can lead us to infer and recognize nine events in soccer matches videos. To achieve this solution, we use Deep Neural Network to extract low-level features through a complete method called Mask R-CNN based ResNet-101 architecture as a backbone. This method outputs three classes that are: boxes (all rectangles around detected objects), labels (names of detected objects) and Masks (segmentations of all detected objects). Afterwards, we create and populate complete soccer ontology in accordance to the output predictions of Mask R-CNN. In other words, we create a smart system able to learn how to detect objects and infer events in soccer matches videos. Then, we validate the effectiveness of our proposed method by the experiment tested on 40 downloaded soccer matches videos of FIFA world cup 2018 from YouTube and prove its robustness through a comparison with state of the art.
    Keywords: Soccer Video Annotation; Event recognition; Convolutional Neural Network (CNN); Mask R-CNN; Ontology; SWRL.
    DOI: 10.1504/IJCAET.2022.10026118
     
  • Augmented Reality in Education: A Systematic study on Technical and Usability issues   Order a copy of this article
    by Neha Tuli, ARCHANA MANTRI, Shivam Sharma 
    Abstract: In recent years, Augmented Reality (AR) is being used in creating distinctive learning environments for students education. Our paper gives a systematic literature review on AR in educational environments. We considered the features, advantages and challenges of using AR in educational settings. One of the main advantage of AR is that it increases students motivation thus improving their learning experiences. Technical and usability issues are reported as the challenges experienced while using AR. There are other advantages and challenges identified from the literature survey, which are discussed in this paper. The paper also reports some of the existing studies of AR for education. Furthermore, it details the present state of art and the opportunities for additional research in AR in education
    Keywords: Augmented Reality; Education; Educational Technology; Technical issues; Usability Issues; Literature Review; Technologies for Augmented Reality Systems; Advantages; Challenges; Usability studies.

  • Designing Cassegrain Antenna with Axially Corrugated Horn Feed and Investigating the Effects of the Feed Antenna Gain on Optimum Dimensions and Specifications of the Cassegrain Antenna   Order a copy of this article
    by Alireza Sharifi 
    Abstract: In this paper, geometric dimensions of Cassegrain antenna are designed in the case of the use of axially corrugated conical horn antenna as the feed antenna. The main issue in the design of the Cassegrain antenna is to calculate the dimensions of the feed antenna and the subreflector antenna so that the amount of aperture obstruction can be minimized and the radiation efficiency is increased. After presenting the design method, an illustrative design example is mentioned. Also the effects of selecting different gain values for the feed antenna, on the dimensions and characteristics of the structure is studied.
    Keywords: Cassegrain Antenna; Axially corrugated conical horn; Cross polarization; Aperture efficiency.

  • Balancing exploration and exploitation in social spider optimization using logistic chaotic map and opposition based learning with an application to data clustering   Order a copy of this article
    by RAVICHANDRAN THALAMALA, JANET B, Reddy AV 
    Abstract: Since the last two decades, nature inspired meta-heuristic algorithms have been used by researchers to solve nonlinear problems. The performance of these algorithms depends on the balance between their exploration and exploitation capabilities. A nature inspired algorithm that maintains a balance of these two capabilities will surely avoid sub optimal solutions. The randomness present in these algorithms generally contribute more to exploration. If we produce randomness systematically, it contributes to both exploration and exploitation. Chaotic maps can be used to generate random numbers systematically. Opposition based learning improves global searching capability of nature inspired algorithms and thereby improves the exploration. Social Spider Optimization (SSO) has been getting the popularity in research community because of its applicability in a wide range of applications. The chance of getting global optimum in SSO can be improved by maintaining a balance between exploration and exploitation. In this paper, we propose a new algorithm namely Logistic chaotic map and Opposition based learning SSO for Data Clustering (LOSSODC) that maintains a good balance between exploration and exploitation in the entire search process using logistic chaotic map and opposition based learning for solving data clustering problem. We compare it with other nature inspired clustering algorithms and find that it gives better clustering results with respect to both low dimensional and high dimensional datasets.
    Keywords: Social spider optimization; Logistic chaotic map; Opposition based learning; exploration; exploitation.

  • Effect of Fault Classification and Detection in Transmission Line using Wavelet Detail Coefficient   Order a copy of this article
    by Lokesh Raman, YATINDRA GOPAL, Dinesh Birla, Mahendra Lalwani 
    Abstract: This paper presents the progress of fault detection and classification analysis in transmission line using wavelet transform with high-speed protective digital relay. These techniques are applicable for real time data analysis. The MATLAB simulation model to obtained voltage and current, signals have measured in both end of the transmission line. These signals used in discrete wavelet transform to extract the original signals to measure the sharp variation of multi-resolution analysis (MRA). In transmission line to different type of faults occur with analysis fault detect, classify very quick and reliable using many protection scheme. This proposed methodology time- frequency analysis of wavelet transform. These faults classified with applied of db-4 and third level detail coefficients analyzing. These are varying fault inception angle, fault impedance and fault distance in transmission line model. This effect overcome by wavelet transforms to carry out generate time and frequency domain signal. The extensive more simulation work has been carrying to identify and classify fault are using proposed methodology more effective with suitable for high-impedance faults induced in the high-voltage transmission line. The power transmission lines are interconnected with generating station 400 kv via consumer load through 300km distance to obtain by MATLAB/SIMULINK.
    Keywords: Multi Resolution Analysis (MRA); Wavelet transform; Transient signal; Discrete wavelet transform (DWT); Fault detection.

  • Eigenvalue Fusion based Machine Learning Approach for Cooperative Spectrum Sensing in Cognitive Radio   Order a copy of this article
    by Rajendra Yelalwar, Yerram Ravinder 
    Abstract: Spectrum sensing is the most critical and fundamental function of the Cognitive Radio (CR) for dynamic spectrum usage. Machine Learning (ML) techniques that allow CRs to learn the environment adaptively are most essential in spectrum sensing. This paper proposes a novel Machine Learning based Cooperative Spectrum Sensing (CSS) technique using various ML schemes like SVM, Gaussian Naive Bayes, Gradient boosting and Extra tree to enhance the probability of detection. Here the ML classifiers used in the fusion center of the CSS schemes are trained with test statistics derived from the eigenvalues extracted from the covariance matrix of a received signal. Test statistics used are labelled with +1 for the primary user(PU) and -1 for noise. In the proposed system the classifier recognizes the received signal samples as a PU signal or a noise signal and distinguishes the PU signal from noise effectively under low SNR conditions using a threshold that possesses self learning ability. The simulation results exhibit the performance analysis of various ML algorithms for CSS under different wireless scenarios and their suitability is compared with conventional approaches.
    Keywords: Cognitive radio; Cooperative spectrum sensing; Machine learning; SVM; Gaussian Naive Bayes; Gradient boosting.

  • Optimization of Friction Stir Welding Parameters to Improve Corrosion Resistance and Mechanical Properties of AA2219 Aluminum Alloy Welds   Order a copy of this article
    by DHANAVATH BALAJI NAIK, Ch Venkata Rao, K. Srinivasa Rao, Madhusudan Reddy, G. Rambabu 
    Abstract: AA2219 Al-Cu alloy is mainly used for aerospace and defense applications. For the fabrication of lightweight structures, aluminum alloys are suitable. Welding is used in the fabrication of components made of AA2219 aluminum alloy and causes microstructural changes in fusion zone partially melted zone and heat affected zone that form during fusion welding of AA2219 alloy. These microstructural changes strongly influence the corrosion behavior and affect the corrosion resistance of the welds. Friction stir welding (FSW) is a solid-state joining method and can overcome all the problems caused by the fusion welding process. Tool pin profile is one of the important parameters that affect the microstructure and mechanical properties of friction stir welds of AA2219 aluminum alloy. The tool parameters and process of FSW plays a significant role in determining the joint strength. In this research work, the relationships between the FSW parameters (tool pin profile, rotational speed, welding speed, and axial force) and the responses (tensile strength, hardness and corrosion resistance) were studied. A mathematical model was developed to predict the welding parameters for the improvement of tensile strength, hardness and corrosion resistance of AA2219 aluminum alloy FS welds. In this work, a central composite design with four factors and five levels has been used to minimize the experimental conditions. Dynamic polarization testing was carried out to determine critical pitting potential, which is a criterion for measuring pitting corrosion resistance. Further, the response surface method (RSM) was used to develop the model. Response optimization showed that the optimum combination of tensile strength, hardness, and corrosion resistance was achieved with hexagon tool pin profile and welding parameters of rotational speed 1214 rpm, welding speed 629 mm/min and axial force 11 KN. AA2219 friction stir welds microstructural studies were carried out by using optical microscopy, scanning electron microscopy, Transmission electron microscopy and Electron backscattered diffraction for welds made with conical and hexagonal tool pin profiles and compared with base metal and found welds made with hexagonal tool pin profile superior properties than conical tool pin profile, as the number of flats are increasing from three (triangle) to six (hexagon), generation of heat during the welding also relatively more when compared to smooth type conical tool pin profile this may attributed to relatively more fine grain structure in hexagonal tool pin profile when compared to conical tool pin profile..
    Keywords: Tool pin profile; tensile strength; corrosion resistance; hardness; AA2219 aluminum alloy; FSW; SEM; TEM; EBSD and RSM.

  • Artificial Neural Network Tactic to Predict Interest in Majors in Computing   Order a copy of this article
    by Sahar Idwan, Shereen Ismail, Moh'd Sami Ashhab, Mohammed Awad, Izzeddin Matar 
    Abstract: In this paper, we will present the first study of using the neural network approach to predict aspects that influence school students in selecting an Information and Communication Technology (ICT) related major at their respective universities. A survey was distributed among school students to determine the factors towards choosing related fields in ICT. We trained the neural network algorithm with the available data. The input to the network stems from six factors: Curriculum, Extra-Curricular activities, Decision-makers, Teachers, Importance of ICT or computing-related subjects at school, and Infrastructure. The neural network predicts the school students behavior towards choosing the ICT major at the university level. Simulation results show the importance of these factors in predicting the students choice in majoring in ICT.
    Keywords: Artificial Neural Network (ANN); Artificial Intelligence; Information and Communication Technology; Computing majors.

  • A Privacy-Preserving Model for Cloud data storage through Fog Computing   Order a copy of this article
    by Rishabh Gupta, Ashutosh Kumar Singh 
    Abstract: Nowadays, most of the organizations are shifting their data to therncloud platform because of its flexibility, elasticity, on-demand services, etc.rnThe major concern of these organizations is to store the data on the cloudrnin a privacy-preserving manner as they lose the control rights and the datarncan be leaked/tempered during the transmission. This paper presents a privacy-rnpreserving scheme that uses the Advanced Encryption Standard (AES) techniquernto store the client data on the cloud via fog computing. Encryption is performedrnat the local machine as well as fog server and then data is transferred tornthe cloud. Randomly generated files are used to perform the experiments andrnencryption/decryption time is computed. The results show an improvement ofrn80% and 88% when a file of 10 MB is encrypted and decrypted respectively asrncompared to the previous work.
    Keywords: Cloud computing; Fog Computing; Cloud Storage; Privacy Protection; AES Algorithm.

  • Hybrid Renewable Energy Resources Incorporated Optimal Power Flow Using Single Phase Multi-Group Teaching Learning Based Optimizer   Order a copy of this article
    by Sundaram Pandya, Hitesh Jariwala 
    Abstract: The latest scenario of electrical system consists of conventional generating units along with the renewable energy resources. The proposed article recommends a method for the solution of optimal power flow, integrating with wind generating units, solar photovoltaic system and hybrid solar with small hydro power that is run-of-river with traditional coal-based generating stations. The irregularity of renewable sources output intensifies the complications of the optimal power flow issue. In proposed work Lognormal, Weibull and Gumble probability density functions are also utilized for predicting power outputs of those renewables, respectively. The modified IEEE-30 bus test system is used for validate the results, which is incorporated with wind-solar-small hydro generating plants. The single phase multi-group teaching learning based optimizer is used as the optimization tool and simulation results compared with newly developed algorithm.
    Keywords: Wind power units; Solar PV energy; Small hydro power; Probability Density Function.

  • Using Neural Networks to Predict Weather Patterns and Trends - Challenges and Opportunities   Order a copy of this article
    by Sandeep Mathur 
    Abstract: Weather prediction systems today are a function of a multitude of variables, which result in complicated and convoluted systems of mathematical simulations and equations. Simulating along the lines of these systems requires enormous amounts of computational power and resources, at the scale of supercomputers and super-scalar and massively parallelized architectures. There has been a recent attempt to avoid such costly and often inefficient calculations by making use of Artificial Neural Networks (ANN) to predict future weather and climate patterns at large. This paper will explore such methods of varying complexity, and review their effectiveness as compared to Numerical Weather Predictions (NWP) models.
    Keywords: Index Terms—neural networks; weather prediction; prediction models.

  • Glucose-Insulin Dynamics: A Grey-box Analogy   Order a copy of this article
    by Vincent Omwenga 
    Abstract: Regulating plasma glucose levels for both type I and type II diabetic patients is a challenging task. Understanding the effects of meals taken, the physical exercises and stress levels will contribute significantly to the overall management of the plasma glucose levels. This paper provides an extension of the Bergman Minimal model to represent twelve-compartmental models associated with meals taken, physical exercises and stress levels interactions within a semi-closed loop system using Stochastic Differential Equations (SDE). The mathematical modelling is constructed following the Grey-box model analogy as applied on an identifiable patient. Obtained results from the study demonstrates the predictive capability of the model to be good and its sensitivity is enhanced with increased dataset.
    Keywords: Glucose-Insulin dynamics; Plasma glucose levels; Stochastic differential equation; Bergman minimal model; Grey-box model.

  • PSO-SVM based novel haptic interface controller design   Order a copy of this article
    by Naveen Kumar 
    Abstract: The key performance issues in the haptic system are stability and transparency. A systems' stability, is defined as minimum oscillations & vibration in the output response as well as in the device itself, whereas, transparency, defined as minimum error between the applied force or velocity and executed in the virtual environment (VE) of haptic system. Here, when we control the stability of the system, transparency gets hamper and vice-versa. To overcome this problem, a novel optimal Haptic Interface Controller (HIC) has been designed using modern techniques (Neural Network, Support Vector Machine, and PSO optimized SVM). This optimal HIC employs the input force provided by the user and the feedback force from the haptic device. The error between the applied force and the feedback force should be minimum to maximize transparency. Moreover, there are always some differences between the theoretical model and the physical model. To ensure the working of the designed controller in the physical device, an effort also has been made to accommodate the uncertainty and delay, which makes the major difference between simulated and physical models. The result obtained using optimal HIC has been compared with the conventional method, which improvement in transparency.
    Keywords: Stability; transparency; haptic system; neural network; SVM; PSO; HIC.

  • New modelisation for create serious game for learning java language   Order a copy of this article
    by Abarkan Ali, Saaidi Abderrahim, Ben Yekhlef Majid 
    Abstract: In this article, a new model of serious game design has been proposed. In general, the design of serious games requires from the start, chooses a model of adequate design and adapted to the idea of the proposed game, to achieve a balance between the serious and playful content, and to define the intervention of employees in each d stages of design. Our proposed model integrates the teacher into the learning process by allowing him to add, modify, and adapt new parts (exercise content) in the game. Similarly, in this work, a serious game has been implemented at the base of our model. This game aims to improve the skills of the learners, in java, by offering them a learning environment based on the spirit of challenge and motivation. The results obtained, in terms of learning rates and simplicity, showed the quality of our model and game designed.
    Keywords: Serious game; learning; java; learning skills; motivation of learners; game scenario.

  • On odd harmonious labelling of even cycles with parallel chords and dragons with parallel chords   Order a copy of this article
    by V. Srividya, R. Govindarajan 
    Abstract: Labelling 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 with parallel P3 chords and the joint sum of two copies of even cycle Cn with parallel P3 chords is odd harmonious. Moreover we show that the chain of even cycles Cn (n ≥ 6) with parallel P3 chords, joining two copies of even cycles Cn by a path 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; joint sum; chain of cycles; dragons.
    DOI: 10.1504/IJCAET.2020.10029299
     
  • 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 Euclid's method and plus-minus method with variable datapath sizes. The proposed designs utilised Altera Cyclone IV FPGA family with target chip device EP4CGX-22CF19C7 along with Quartus II simulation package. Also, the proposed designs were synthesised 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 Euclid's method while reducing the total path delay by almost 50% compared to Euclid's method. However, Euclid's method listed less hardware utilisation 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; Altera Cyclone IV FPGA kit; critical path delay; FPGA thermal power dissipation; logic elements.
    DOI: 10.1504/IJCAET.2020.10029304
     
  • Fixed point theorem by altering distance technique in complete fuzzy metric spaces   Order a copy of this article
    by Vishal Gupta, R.K. Saini, Manu Verma 
    Abstract: The aim of this paper is to define the generalised 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 and Petrusel (2013) in fuzzy metric space.
    Keywords: fuzzy metric space; control function; altering distance.
    DOI: 10.1504/IJCAET.2020.10029303
     
  • Two generalised fixed point theorems in G-metric space without iterations   Order a copy of this article
    by S. Saravanan, T. Phaneendra 
    Abstract: Two generalised 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.
    DOI: 10.1504/IJCAET.2020.10029310
     
  • Inverse kinematic analysis of 5-axis hybrid parallel kinematic machine using CAD and regression analysis approach   Order a copy of this article
    by L.V. Suryam, B. Balakrishna 
    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 modelled 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; digital mockup unit; DMU; contour trajectory; regression analysis.
    DOI: 10.1504/IJCAET.2020.10029312
     
  • Multi-response optimisation in CNC turning of Al-6082 T6 using grey Taguchi method coupled with principal component analysis   Order a copy of this article
    by G. Suresh Kumar, P. Venkateshwar Reddy, D. Mohana Krishnudu 
    Abstract: The present work focuses to analyse the importance of turning parameters on the responses: machining time, surface roughness and material removal rate in CNC turning while machining of aluminium 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 optimise the response parameters simultaneously. Experiments have been conducted as per Taguchi's L9 orthogonal array. The experimental results were then analysed 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: turning; machining time; surface roughness; material removal rate; MRR; grey Taguchi; multi-response optimisation.
    DOI: 10.1504/IJCAET.2020.10029315
     

Special Issue on: Recent Trends in Computing and Engineering

  • 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, Abdelkrim Haqiq 
    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, it's 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 croker architecture; rough set theory; multi-criteria decision analysis.
    DOI: 10.1504/IJCAET.2020.10029305
     

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

  • An approach for infrared image pedestrian classification based on local directional pixel structure elements' descriptor   Order a copy of this article
    by Rajkumar Soundrapandiyan 
    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 defence 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 are compared with the existing approaches. The efficiency of the proposed approach is proven by high classification accuracy.
    Keywords: infrared image; local directional pattern; LDP; structure element descriptor; support vector machine; SVM; pedestrian classification.
    DOI: 10.1504/IJCAET.2020.10029295
     
  • An efficient image system-based grey wolf optimiser method for multimedia image security using reduced entropy-based 3D chaotic map   Order a copy of this article
    by Srinivas Koppu, V. Madhu Viswanatham 
    Abstract: Chaotic maps play an important role in information sharing. In this paper a grey wolf optimiser used with reduced entropy-based 3D chaotic map. The selection and high coefficients are selected based on the reduced entropy value to identify the optimised 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; entropy; 3D chaotic map; grey wolf optimiser.
    DOI: 10.1504/IJCAET.2020.10029297
     
  • Calibre 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 calibre 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 centre, 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 datasets DRIVE, STARE, and CHASE_DB1.
    Keywords: fuzzy c-means clustering; retinal image; self-organised map; SOM.
    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 J. Hemalatha, M.K. Kavitha Devi, S. Geetha 
    Abstract: Enlightening the processing record of a digital image is a significant problem for steganalysers and the forensic analysers. 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 neighbours. 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 of the system.
    Keywords: SVM; ensemble; higher order statistics.
    DOI: 10.1504/IJCAET.2020.10029309
     
  • Incipient knowledge in protein folding kinetics states prophecy using deep neural network-based ensemble classifier   Order a copy of this article
    by M. Anbarasi, M.A. Saleem Durai 
    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 bases 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.
    DOI: 10.1504/IJCAET.2020.10029311
     
  • Type-specific classification of bronchogenic carcinomas using bi-layer mutated particle swarm optimisation   Order a copy of this article
    by P. Balamurugan, A.M. Viswa Bharathy, K. Marimuthu, R. Niranchana 
    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 optimisation (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; particle swarm optimisation; PSO.
    DOI: 10.1504/IJCAET.2020.10029313
     
  • Effective user preference mining-based personalised movie recommendation system   Order a copy of this article
    by V. Subramaniyaswamy, R. Logesh, D. Malathi, V. Vijayakumar, 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 behaviour helps users by providing essential information without asking explicitly. Several movie recommendation systems are available to suggest movies, but often they do not do that effectively. To achieve enhanced effectiveness and efficiency, user's 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 neighbour (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; personalisation; adaptive KNN; ontology; web mining; classification.
    DOI: 10.1504/IJCAET.2020.10029314
     
  • Steganographic approach to enhance the data security in public cloud   Order a copy of this article
    by S. Prabu, 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 about delineation enigma, along with its applications as well as techniques. It moreover endeavours so that it can recognise 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 message by concealing it in a picture utilising the most ordinarily utilised least significant bit (LSB) 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; LSB; bitmap steganography; data security; cloud computing.
    DOI: 10.1504/IJCAET.2020.10029316
     

Special Issue on: ICEIEE 2019 Computational Engineering and its Applications

  • Performance Evaluation for Classifying Type 2 Diabetic Retinopathy using Deep Neural Network   Order a copy of this article
    by Sanikommu Vasavi, M. Likitha, L. Neeraz, Lin En Bing 
    Abstract: Now-a-days irrespective age and gender most of the people are being affected by retinal diseases. People with type 2 diabetes are more prone to blindness. Periodic check-up for diabetic retinopathy (DR) has become labour intensive task. Even though many methods based on computational intelligence are proposed for detecting diabetic retinopathy, are not efficient in classifying DR type. Early diagnosis and proper follow up treatment can prevent progressing to next stages of DR. This paper presents automatic disease detection that utilizes retinal image analysis and to accurately categorize the retinal problem as Normal, NPDR (Non-Proliferative Diabetic Retinopathy) and PDR (Proliferative Diabetic Retinopathy). This system uses a three step to analyze fundus images and to classify the severity grade using deep neural networks. Test results showed that our proposed system could classify the DR with 96.3 of accuracy for SVM, 95.2 accuracy for k-NN, 99.15 for ANN, and CNN scored an accuracy of 0.7998 and loss of 0.4569. ANN proved to be better when compared to existing works. Different k values are taken for k-NN and when k=5 accuracy is 95.2.
    Keywords: Type 2 Diabetic Retinopathy; Image Processing; Fundus Images; Exudates; Hemorrhages; Cotton wool spots; Lesions; Micro aneurysms.

  • Recognition of Typewritten Gurmukhi Characters   Order a copy of this article
    by Rajan Goyal, Rajesh Kumar Narula, Manish Kumar Jindal 
    Abstract: Today, extensive research has been done on data analysis and text recognition, currently numerous Optical Character Recognition (OCR) frameworks are available by various researchers. Language scripting is considered as a challenging task due to presence of degraded characters which affects the OCR performance. In Gurumukhi content old reports are inaccessible because of its delicate condition. For the most part old archives get debased which hampers their lucidness. The utmost work is done by researchers on character recognition of Gurmukhi script deals with handwritten and printed characters. The aim of this research work is to cover blind spot area of typewritten Gurmukhi script for recognition of character. To achieve this, features are extracted using projection profiles, zoning features, transition features, distance vector and neighbouring pixels and machine learning techniques like SVM (using linear and polynomial kernel) and k-NN (with value of k = 3, 5, 7 and 11) are applied to recognize the characters. It is found that SVM linear approach provides best result in our case.
    Keywords: Feature extraction; Classification; SVM; k-NN; OCR.

  • Robust segmentation model for unshaped microarray spots using fractal transformation   Order a copy of this article
    by M.A. Sayedelahl, Roushdi Farouk 
    Abstract: DNA microarray technology has permitted the analysis of global gene expression profiles in clinical diagnosis, treatment, and environmental health researches for several diseases including cancer. Microarray images analysis, processing and segmentation are decisive steps in gene expression analysis, since any errors leads to improper diagnosis. These techniques increased and enhanced over the past few years. However, the segmentation of the unshaped spots within the microarray image still a problem due to the variations of spots in shapes and sizes. Hence, we introduce a new unshaped microarray spot segmentation model. Which focuses on spots detection and segmentation regardless of their size and shape using fractal dimensions transform. rnReal microarray images from The Stanford Microarray images Database (SMD) and Universal microarray images database (UNC) are used to evaluate the efficiency of the proposed model. The numerical and visual results show that, proposed model improve the accuracy and the efficiency of the spots segmentation process. Biological researchers can used this model in their labs and Clinics, as a free priceless software instead of using expensive one like ScanAlyze, GenePix or spot software.rn
    Keywords: Unshaped segmentation; Fractal dimensions; cDNA microarray spots analysis; cDNA microarray spots segmentation.

  • A Novel Design of a 1GHz Phase Locked Loop with Improved lock time for fast Frequency Acquisition   Order a copy of this article
    by Monika Bhardwaj 
    Abstract: This paper contains a low power PLL with better lock time which involves the designing of charge pump, voltage controlled oscillator, loop filter, phase frequency detector at low power. Logical expressions are developed and analyzed for the parameters of system design. System related noise model is also presented for output and internal noise. The PLL is designed to offer high speed performance at low cost. Loop filter design is the most important block in designing low noise, low cost device which helps in improving the overall system performance. The PLL is designed using 0.18 um CMOS process in Tanner design tool and 1.8v supply. It is designed to operate in the frequency range of 200MHz-1GHz which is used to generate the clock signals where the input frequency signal is synchronized. The designed PLL can be used in variety of frequency synthesizers in the field of communication and instrumentation.
    Keywords: - Phase locked loop (PLL); VCO; charge pump (CP); phase error; phase frequency detector (PFD); channel length modulation.

Special Issue on: ISACS'19 Advances in Applied Science and Information Technology

  • A computer-aided system for monitoring quality using traceable information   Order a copy of this article
    by Abdesselam Bougdira, Ismail Akharraz, Abdelaziz Ahaitouf 
    Abstract: This paper proposes the usage of traceability data to enhance the continuous evaluation and monitoring of quality. The current study focuses on processing activities where it is difficult to detect and evaluate the possible degradation of quality. It has indeed a special interest in possible gaps that are not bridged by existing quality methods and practices, especially tasks that involve significant physical contact with manual labor. Therefore, this research introduces a computer-aided system that combines ontology-based knowledge with a fuzzy-based decision-making process. The proposed model can ensure the main traceability functions, including identifying, tracing, and tracking. Also, it can handle the various attributes associated with processing activities to assess the possible loss of quality. In case of unconformity, this monitoring function enables decision-makers to intervene appropriately. The developed system has also been illustrated through a fish canning case study.
    Keywords: Artificial Intelligence; Fuzzy Computing; Ontology; Traceability; Canning Industry.

  • Performance Analysis of WDM PON systems using PIN and APD Photodiodes   Order a copy of this article
    by HAMADOUCHE HADJIRA, MERABET Boualem, BOUREGAA Mouweffeq 
    Abstract: In this paper we study the quality(Q) factor used by the receivers of APD and PIN photodiodes in wavelength division multiplexing (WDM) system with 32 number of users and compare the efficiency of the bit-error-rate(BER).The research is conducted using avalanche photo diode (APD) P-Insulator-N and PIN photodiodes receivers of different wavelengths. Interpretation and description of the Optisystem's simulation results through the optical high debit communication system, optical fiber of different lengths, bit rate , continuous wave(cw) laser power and number of users, chosen to evaluate the APD and PIN photodiodes performances in function of Q factor and BER in order to provide new perspectives for the future transmission . The simulation values show that the performance of the APD diode and the Q and BER factor obtained from APD is better than the performance of the PIN that could be expected because APD is more sensitive than PIN.
    Keywords: WDM PON; APD; PIN; Optisystem; Bit Error Rate; Q-Factor.

  • Optimal Backstepping Controller for Trajectory Tracking of a Quadrotor UAV using Ant colony optimization algorithm   Order a copy of this article
    by Hamid HASSANI, Anass MANSOURI, Ali AHAITOUF 
    Abstract: This paper concerns the design of an optimal stabilizer/tracker for the quadrotor UAV. Firstly, kinematic and dynamic equations of the aerial vehicle are yielded through Newton-Euler formalism. Then, the backstepping (BS) technique is adopted to sustain a controllable and stable behaviors of the quadrotor attitude. However, designing a high-precision flight controller essentially necessitate an optimal selection of its internal parameters. The improper configuration of these parameters can negatively influence the flight performances, and sometimes leads the quadrotor system to the instability. Ant colony optimization algorithm (ACO) is used to configure the adopted stabilized technique, and a modified cost function is proposed to improve the response of the quadrotor system. In view to corroborate the accuracy of the suggested method, a series of numerical experiments were done and comparison with other control approaches is also given.
    Keywords: Quadrotor UAV; Backstepping technique; flight controller; ACO algorithm; modified cost function.

  • A novel face recognition approach based on strings of minimum values and several distance metrics   Order a copy of this article
    by Hicham Zaaraoui, Samir El Kaddouhi, Mustapha Abarkan 
    Abstract: This paper proposes a novel approach to face recognition using string of minimum values (SMV) as a new face feature extractor for face representation. Unlike most of the face representative methods, which focus only on micro-structures information in image analysis, by surrounding the treated pixel with a mask. The proposed descriptor uses the chains of unit vectors in four directions, by moving from the current pixel to the next one, from which to a new next pixel, and so on, in order to encode also the global appearance of the face image. Furthermore, seven distance metrics from the nearest neighbor classifier are evaluated in the classification stage. The experimental results show which metrics perform well and demonstrate the efficiency of the proposed approach in terms of recognition rate compared to the existing face recognition methods.
    Keywords: Face recognition; String of minimum values; Face descriptor; Distance metrics; Dictionary of visual words.

  • Virtual Hand Skinning Using Volumetric Shape   Order a copy of this article
    by Abderrazzak Ait Mouhou, Abderrahim Saaidi, Majid Ben Yakhlef, Khalid Abbad 
    Abstract: In this paper, we propose a skinning approach for the virtual handrndeformation. This is an implicit skinning approach based on the sphericalrnprimitives. Our approach presents a new idea of skinning, which aims to correctrnthe undesirable effects introduced by geometric skinning techniques such as LBSrn(Linear Blending Skinning) or dual quaternions. In this paper, we propose thernuse of volumetric shape as a new geometric representation to better capture thernbehavior of the skin. We present a real-time method producing a deformation ofrnthe mesh and which takes into account the contact of the skin and the simulation ofrnthe muscles swelling. Our hand mesh is approximated with a volumetric structurernwhich allows us to deform it in a plausible way while dealing with collisions andrnretaining the mesh details.
    Keywords: Character Animation; Skinning; Skeleton-Based Animation.

  • Optimized Backstepping Sliding Mode Controller with Integral Action for MPPT Based Photovoltaic System Using PSO Technique   Order a copy of this article
    by Fatima Ez-Zahra Lamzouri, El-Mahjoub Boufounas, Mounir Hanine, Aumeur El Amrani 
    Abstract: In this paper, a new Optimized Backstepping Sliding Mode Controller with Integral action (BISMC) is proposed to achieve Maximum Power Point Tracking (MPPT) for solar Photovoltaic (PV) system. The investigated PV system consists of a PV generator (PVG) as power source, a DCDC boost converter and a resistive load. Indeed, the designed controller can allow to the PV system operate around the estimated MPPT under abrupt atmospheric conditions variation. By combining the advantages of both techniques and introducing the integral action in the sliding surface, the system presents good dynamic performance. Furthermore, the proposed BISMC controller was combined with intelligent systems such swarms intelligent to improve the controller performance in terms of transition response and tracking error. Thus, in order to provide an optimal BISMC parameters, particle swarm optimization (PSO) based evolutionary algorithm was used. Moreover, asymptotic stability of the system is verified through Lyapunov stability analysis. Simulation results show that the proposed PSO-BISMC control strategy ensures better response speed and smaller steady-state error compared to the traditional SMC and BISMC control strategies.
    Keywords: photovoltaic system; maximum power point tracking; backstepping control; sliding mode control; integral action; particle swarm optimization algorithm.

  • Computational methods in aerodynamics   Order a copy of this article
    by Abdelhakim CHILLALI 
    Abstract: In the field of aerodynamics, numerical simulation is an effective way to reduce costs and design times. Numerical simulation is gaining importance thanks to the improvement of power and computing capabilities. However, computing powers are still too weak for the modelling of industrial problems (high Mach, turbulent regimes, etc.). To overcome this problem, aerodynamicists have developed methods to reduce the need for machine capacity, but by simplifying the Navier-Stokes equations, knowing that these equations accurately describe the aerodynamic flows. The objective of this research is to participate in the improvement of numerical methods in aerodynamics. Indeed, the Navier-Stokes equations are solved in conservative variables. In order to treat high Reynolds number flows, the discrete model is obtained by finite element method and a Petrov-Galerkin weighting. The developed numerical model has been used for the resolution of external two-dimensional flows around a NACA-0012 profile in the transonic and supersonic domain.
    Keywords: Navier-Stokes; finite element method; Galerkin; Petrov-Galerkin.

  • Performance Analysis of TDM PON System For 128 Users Using RZ And NRZ Modulations   Order a copy of this article
    by Hadjira HAMADOUCHE, Boualem MERABET, Mouweffeq BOUREGAA, Samir Ghouali 
    Abstract: In this paper we have compared the most important modulation formats used in optical communications, in terms of bit error rate (BER) and Q-factor, in the aim of assessing their weaknesses, advantages, and explore the functionality of these formats to meet potential network needs and tackle the growth of data traffic. Two basic formats in optical communication systems exist: non-return-to-zero (NRZ) and return-to-zero (RZ). Here, a device consisting of downstream optical fiber connectivity processing was used, and the system performance has been investigated using NRZ and RZ formats operating by varying bit rates , the length of the fiber, power of continuous wave (CW) laser and number of users. The analysis showed how exceptional the RZ modulation format compared with the conventional NRZ modulation design due to preferable inviolability to average peak power and non - linearity fiber. The results were assessed by the value of the quality (Q) factor, the bit error rate of BER and average eye opening using Optisystem.
    Keywords: TDM PON; RZ; NRZ; Optisystem; Bit Error Rate; Q-Factor.

  • STITCHED IMAGE BASED ON A REAL-TIME VIDEO CONVERSION TECHNIQUE   Order a copy of this article
    by Abderrahmane Laraqui, Kamal Azmi, Mohammed Laraqui, Faouzi Boussedra 
    Abstract: Mosaic video reconstruction is a technique of assembling a video cut into frames to provide a panoramic view of a captured scene. The resulting image of this technique provides a compact representation of the entire video. In this paper we propose a technique for creating image mosaics based video scene. This technique will be used for real-time compression of videos into mosaic images.
    Keywords: rendering; video mosaic; stitching; registration; compression; conversion; blending; matching; transformation.

  • LEARN COMPUTER CODING WITH A SERIOUS GAME: THEORETICAL FRAMEWORK AND COURSE PERFORMANCE   Order a copy of this article
    by Kamal Azmi, Abderrahmane Laraqui, Faouzi Boussedra 
    Abstract: The teaching of computer science to non-specialists, as part of Moroccan University reform perspective. So, the new purpose of the teacher/accompanying person at UCD University is to accompany the learner to be auto-effective regarding a programming language. The classic modes of teaching and the classic methodologies of researches on this topic are outdated. The present article so tells our experience in a contextualized way, our methodological repositioning before explaining the steps of a theoretical model which re-configures the phase of the production to favor an accompaniment stimulating the auto-efficacy of the learner. The Training Games and Simulation environment is a better solution for this circumstance. The scenarisation tasks in this type of game is a major issue for the development of self-efficacy; and that will be the goal of this communication.
    Keywords: task-oriented approach; auto-efficacy of the learner; programming language in the Moroccan University; theoretical model; The Training Games and Simulation.

  • An Efficient Optimization-based Design of Current Conveyor Performances   Order a copy of this article
    by Abdelaziz Lberni, Malika Alami Marktani, Abdelaziz Ahaitouf, Ali Ahaitouf 
    Abstract: Optimization algorithms are increasingly used by electronic circuit designers to optimally design and size the performance of their circuits. Multiobjective optimization algorithms have a great interest, since in most cases the problems of sizing analog, RF and mixed-signal ICs include at least two conflicting and contradictory objectives. In the present paper we present two evolutionary algorithms well known in the literature for their better performance in solving more difficult multi-objective problems (MOP). The performance of these proposed algorithms are first applied to some well known mathematical benchmark functions and then to deal with the optimal sizing of current conveyor transistors in the framework of 0.18
    Keywords: Metaheuristics; Optimization algorithms; Evolutionary algorithms; Analog IC Design; Current conveyor; Multi-objective optimization; Pareto front; CMOS technology.

Special Issue on: ISACS'19 Advances in Applied Science and Information Technology

  • Twisted Hessian curves over the ring Fq[e],e^2 = 0
    by Abdelâli Grini, Abdelhakim CHILLALI, Lhoussain ElFadil, Hakima Mouanis 
    Abstract: The goal of this work is to study some arithmetic proprieties of an twisted Hessian curves defined by a equation of type: $aX^{3}+Y^{3}+Z^{3}=dXYZ$ on the local ring $R_2=mathbb{F}_{q}[X]/(X^{2})$, where $p geq 5$ is a prime number , $q = p^d$ and $ d in mathbb{N}^{ast}$, such that $-3$ is not a square in $mathbb{F}_{q}$. It's consists of, an introduction, section, and a conclusion. In the introduction, we review some fundamental arithmetic proprieties of finite local rings $R_2$, which will be used in the remainder of this article. The section is devoted to a study the above mentioned twisted Hessian curves on these finite local rings for restriction to some specific characteristic $pgeq 5$. Using these studies, we give essential properties and we define the group $H^2_{a,d}$, these properties, the classification of these elements and a bijection between the sets $H ^{2}_{a,d}$ and $H_{a_{0},d_{0}}times mathbb{F}_{q}$, where $H_{a_{0},d_{0}}$ is the twisted Hessian curve over the finite field $ mathbb{F}_{q}$.
    Keywords: Twisted Hessian curves, Finite Ring, Cryptography

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

  • 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.

  • An efficient Automatic Generation Control for Multiple Power Systems based PI-SA Algorithm   Order a copy of this article
    by Mohammed Shahooth, Mushtaq Najeeb, Arrak Mohaisen, Maan Abdullateef Khalaf, Mohammed Kareem Mohammed 
    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.

Special Issue on: ICICT-2018 Ubiquitous Sustainable Systems

  • 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
     
  • 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
     
  • 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.
    DOI: 10.1504/IJCAET.2021.10024945
     
  • 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 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
     
  • 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: 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: 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.