Forthcoming and Online First Articles

International Journal of Engineering Systems Modelling and Simulation

International Journal of Engineering Systems Modelling and Simulation (IJESMS)

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International Journal of Engineering Systems Modelling and Simulation (17 papers in press)

Regular Issues

  • FPGA implementation of low complexity super resolution scaling architecture for UHD display systems   Order a copy of this article
    by Chidadala Janardhan, K.Venkata Ramanaiah, K. Babulu 
    Abstract: Ultra high definition (UHD) technology has been changing the entertainment industry significantly and its content is severely short of supply due to limited content creators or hard to access due to insufficient network bandwidth. Recent improvements in CMOS image sensor technology, multimedia applications traditional standard display (SD) systems are not sufficient to display high-quality images. Conventional FPGA-based SR methods will exhibit more complexity and requires more hardware resources to perform. This paper describes low complexity super resolution scaling architecture (SRSA) for UHD systems. In our proposed method, bi-cubic interpolation is used for reconstruction the low-frequency image to high-frequency images, these bi-cubic interpolations will have the capability to interpolate sixteen nearest neighbours of a pixel. In addition to that high-frequency patches are overlapped to construct super resolutions images with using kernel algorithm. The proposed system generates the output image at 1,600 x 1,600 sizes from 800 x 800 image size. The proposed SRSA super-resolution technique is modelled in Verilog HDL and synthesised in Xilinx Zynq-7000 series FPGA and shown the comparison of area, delay, and power. From the simulation results, the performance of the proposed method can compete over the state of the art methods.
    Keywords: image interpolation; super resolution; image resolution; field programmable gate arrays; image restoration.
    DOI: 10.1504/IJESMS.2024.10063207
     
  • Analysis of hole expansion test of aluminium alloy using finite element method simulation   Order a copy of this article
    by Yogesh Dewang, Vipin Sharma, Shashi Ranjan Mohan, Riyan Cyriac Jose 
    Abstract: The major problems associated with forming operations of metal sheets are edge failures often associated with the stretch flangeability of the material. Several ferrous and non-ferrous metals and their alloys have been studied in the recent decade to address the above mentioned issue. Stretch flangeability of a materials used in automotive applications is determined by several tests, the prominent ones being hole expansion test and uniaxial tensile test along with bending tests. The stretch flangeability of AA6016 was studied by finite element method hole expansion test. It is developed on ABAQUS/CAE 2020with implicit simulation. A finite element model is developed with appropriate material model for understanding the significance of physical parameters affecting the stretch flangeability. Simulation results provide a greater access to analyse mechanical properties acting under deformation.
    Keywords: automobile; sheet forming; hole expansion; FEM simulation; flanging; stretch frangibility.

  • Rayleigh wave in rotating thermoelastic half-space under impedance boundary conditions, two-temperature, diffusion   Order a copy of this article
    by Heena Sharma, Sangeeta Kumari, Bharti Thakur 
    Abstract: In the present work, the governing equation of Rayleigh wave is considered with rotation, diffusion, and two-temperature under impedance boundary conditions for generalised thermoelastic half-space. The surface wave technique is used to solve the governing equation of Rayleigh wave to obtain the frequency equation. It also satisfies radiation conditions. Impact of rotation, initial stress, two-temperature, magnetic field, and diffusion with impedance boundary conditions numerically calculated. The effect of different parameters against dimensionless speed is presented graphically.
    Keywords: Rayleigh wave; frequency equation; generalised thermoelasticity; relaxation time; initial stress; two-temperature; magnetic field; rotation; diffusion; impedance boundary conditions; IBCs.
    DOI: 10.1504/IJESMS.2024.10063678
     
  • DBPF pre-processing based improved ECG signal analysis in medical engineering applications   Order a copy of this article
    by Varun Gupta 
    Abstract: Bioinformatics is the essential field to capture and interpret the biomedical datasets. Among these datasets, heart is main organ which is responsible for circulation of the blood and appears in the form of electrocardiogram (ECG) signal. Unfortunately, the heart’s conduction is nonlinear in nature requiring utilisation of technological advancements. The activity of heart is signified by various small waves, viz., P-wave, QRS wave (complex), and T-wave. In this paper combination of three efficient techniques, viz., digital bandpass filtering (DBPF), Hilbert envelope, and factor analysis is used for ECG signal analysis. The analysis of ECG signal is done by estimating position of R-peaks in MIT-BIH Arrhythmia (MIT-BIH Arr) database and MIT-BIH Long-Term ECG database. The proposed technique is definitely important for medical engineering applications in estimating correct health condition.
    Keywords: bioinformatics; electrocardiogram; ECG; digital bandpass filter; Hilbert envelope; factor analysis; R-peaks.
    DOI: 10.1504/IJESMS.2024.10063747
     
  • Role of biomedical devices on surgical applications - an outlook   Order a copy of this article
    by Md. Abdul Raheem Junaidi, Ram Chandra Murthy Kalluri, Y. V. Daseswara Rao 
    Abstract: The research mainly focuses on the three different types of laparoscopic instruments such as grasping, laparoscopic forceps, and suction irrigation devices with their design modifications and robot assistance activities. Some mechanical components such as links, sliders, gears, pivots, etc. are assisted in the working mechanism of the laparoscopic instruments. Despite of its potential demand, certain complexities are faced by surgeons due to its design characteristics. From the analysis, it is clear that several researchers are focused for optimise the design of forceps and handles in laparoscopic surgery. The process of suction and irrigation contributes well to laparoscopic surgery; however, the interest toward such a process is limited by the researchers. The existing researches of laparoscopic instrumental enhancement between the year 2011 and 2020 are symbolised in this work. This research promotes direction to several surgical device designers by adopting the additional innovative methodology for designing the novel laparoscopic instruments.
    Keywords: robotic device; laparoscopic instruments; minimal invasive surgery; Grasper; suction and irrigation medical device; CFD perspectives.
    DOI: 10.1504/IJESMS.2025.10064595
     
  • Induction motor speed control performance enhancement using fractional order filters   Order a copy of this article
    by Saida Hassainia, Samir Ladaci, Sihem Kechida, Khaled Khelil 
    Abstract: This paper proposes a novel methodology for performance enhancement of simple feedback control by means of fractional order filters applied to the speed drive of an induction machine. Three performance indexes are used for this aim namely the integral square error (ISE), integral absolute error (IAE) and integral time absolute error (ITAE). A first order filter in different positions of the control loop is considered in presence of a noise source in order to design the filter configuration. Then, an optimisation of the fractional order filter is realised. Comparative simulation results are given to illustrate the superiority and robustness of the proposed control scheme with regard to integer order filters and unfiltered controllers.
    Keywords: fractional order filter; fractional order systems; induction machine; pi controller; performance index; speed control.
    DOI: 10.1504/IJESMS.2024.10064607
     
  • A versatile biomedical device employed for diverse applications in minimally invasive surgical procedures   Order a copy of this article
    by Md. Abdul Raheem Junaidi 
    Abstract: The research revolutionises to introduce a new design of an instrument that combines the functionality of Maryland forceps with that of a suction irrigation device. Currently, the above two operations have to be carried out sequentially, which adds to the amount of time and effort spent by the surgeon. Integrating both these features within the same device can ensure that both processes can take place simultaneously or one after the other as many times as required, without unnecessary removal of the device from the incision. Thus the article has modelled the instrument which can potentially benefit in all other various laparoscopic procedures.
    Keywords: laparoscopic instruments; irrigation; suction; forceps; mechanism; multi-functional.
    DOI: 10.1504/IJESMS.2024.10064909
     
  • A global thermal node model for analysing the effect of glass cover geometric parameters for no-load indirect solar dryer   Order a copy of this article
    by Ernest Léontin Lemoubou, Carine Pamela Aghogue Donchi, Hervé Thierry Tagne Kamdem, René Tchinda 
    Abstract: In this paper, a global thermal node model is developed for describing no-load indirect solar dryer with double-glass collector. The dryer is formed with drying unit and double air pass collector mounted with two absorber plates separated by confined air. The nodal model takes into account the time variations of solar flux, convection heat losses to the ambient and radiated flux from the soil surface. The mathematical model describing the transient heat transfer process is derived from the node theory, while the surface soil fluxes are approximated using the boundary layer similarity theory. The resulted equations are solved numerically using the iterative finite difference method. The results obtained indicate excellent agreement of the global node model proposed when compared predictions to experimental values of the literature. The simulation reveals significant effect of glass cover thickness and glass covers confined air thickness on the thermal behaviour of the dryer.
    Keywords: global node model; indirect solar dryer; numerical simulation; glass cover geometric parameters; boundary layer theory; dynamic conditions; thermal behaviour.
    DOI: 10.1504/IJESMS.2025.10065108
     
  • Optimisation of deep learning-based models for the diagnosis of heart disease through ODTH method   Order a copy of this article
    by Monali Gulhane, T. Sajana 
    Abstract: In middle- and low-income countries, cardiovascular illnesses (CVDs) constitute the leading cause of death, with heart attacks and strokes accounting for around 80% of CVD-related fatalities. Enabling early intervention and treatment planning, effective cardiac irregularity prediction and the design of trustworthy heart disease prediction systems eventually lower death rates. This research investigated the viability of predicting cardiac disease using tabular data and convolutional neural networks (CNN). We first retrieved pertinent data from the collection of records, which was then abridged to 14 characteristics; each record is converted into heatmaps, and PNG files of the heatmaps are stored for further CNN processing and visualisation to DenseNet121, ResNet50 and VGG19. Using 10-fold cross-validation, we discovered that DenseNet121, in addition to the optimisation method stochastic gradient descent (SGD), performed better with 97% accuracy while the other two VGG19 54.39% and ResNet50is 51.00% models, performed low as compared to DenseNet121 in addition with the use of accuracy of 54.39% and 51.00%, respectively. Our research demonstrates that deep learning models are capable to correctly forecast heart disease from tabular data. In this paper, it is concluded that tabular data can be given as input to deep learning models to achieve better accuracy and good results can be observed for further study in the field of disease prediction.
    Keywords: machine learning; deep learning;DenseNet121; ResNet50; VGG19; optimisation.
    DOI: 10.1504/IJESMS.2024.10066247
     
  • Modelling an SEIR model using saturated treatment function and analysing its stability: the effect of treating H3N2V affected patients by medicines   Order a copy of this article
    by A. Joshua Cyril Yagan, D. Jasmine 
    Abstract: Swine flu is a respiratory illness characterised by its intense spread during specific seasons, leading to concerns about the potential challenges caused by limited drug availability. This article presents a susceptible-exposed-infected-recovered (SEIR) model incorporating a saturated treatment function to address these concerns. Emphasising the crucial role of early medication in managing the infection, the model serves as a mathematical representation of the disease’s dynamics, featuring the novel inclusion of a saturated treatment function to better manage swine flu’s transmission challenges. This study emphasises early prescription medicine treatment for infected patients. A thorough methodology verifies the model’s positivity and boundedness to ensure it appropriately represents real-world disease dynamics. To better comprehend disease propagation, calculate the reproduction number and find the model’s equilibrium locations. The Gershgorin Circle theorem is used to test model stability, showing its capacity to capture disease transmission’s complicated dynamics. The essay uses numerical simulations to emphasise the need of timely and proper medicine in preventing illness development. This model-driven technique can avert swine flu pandemics by predicting pharmaceutical needs and reducing supply bottlenecks.
    Keywords: variant influenza; swine flu; H3N2; respiratory infection; pandemic; epidemic; SEIR compartmental model; saturated treatment function; reproduction number; model stability and implications.
    DOI: 10.1504/IJESMS.2024.10065300
     
  • Multi-period planning of fish breeding chains and investigation of its efficiency under demand uncertainty   Order a copy of this article
    by Sajad Moradi 
    Abstract: This article studies an issue in the fish farming industry, aiming to find the best multi-period plan for managing various chains, including spawning, breeding, harvesting, and selling trout over a given time horizon. It provides a new mixed integer linear programming model that efficiently finds the optimum solution. In the proposed model, some intermediate stages of the breeding chains that do not affect key decisions are ignored, thereby reducing the size and complexity of the proposed model without compromising the optimality of the answers. When weekly demands are considered uncertain data, by simulating weekly demand, it is shown that using the first-in, first-out policy during the selling season, the schedule provided by the deterministic model, in which average value is considered for the weekly demand, will still be effective relatively. By analysing the obtained results, some approaches are suggested to improve the proposed program.
    Keywords: fishing industry; mathematical modelling; demands uncertainty; sales management; simulation.
    DOI: 10.1504/IJESMS.2024.10066291
     
  • Fortifying cyber defence: unveiling the power of convolutional neural networks and cutting-edge data preprocessing methods for DDoS attack detection in the digital frontier   Order a copy of this article
    by Chris Harry Kandikattu, Sam Sangeeth Panguluri, Sandeep Kumar, Suneetha Bulla, Abdul Raheem Shaik 
    Abstract: With a global increase in the frequency of cyberattacks in the internet space, the digital sphere faces a significant upheaval in danger to an individual’s online presence and corporate entities. The work put forward in this paper takes advantage of deep learning techniques to improve security against DDoS attacks. The research paper provides a holistic approach to detecting DDoS attacks using convolutional neural networks (CNNs) combined with advanced data preprocessing methods. The proposed work in this research paper has been evaluated using two widely known and publicly available datasets, namely NSL-KDD and CSE-CIC-IDS208. The proposed work demonstrates that the proposed methodology consistently outperforms both datasets, achieving impressive accuracy scores of 97.46% and 98.53%. These findings underscore the promising potential of the proposed approach in enhancing the accuracy and effectiveness of intrusion detection systems.
    Keywords: distributed denial of service; DDoS; cloud attacks; cloud environment; cloud security.

  • Quantum vs. classical methods in information security, computing and machine learning domains: an empirical study   Order a copy of this article
    by Kriti Srivastava, Akshit Gabhane, Ankit Ladva, Pushkar Waykole, S. Suman Rajest 
    Abstract: The rise in big data has necessitated the development of new computing technologies that can process large volumes of data in a faster and more efficient manner. In recent years, quantum computing has emerged as a promising candidate for this purpose due to its ability to work with high dimensionality data and its potential for solving complex problems that classical computers struggle with. This research work conducts a comparative analysis of quantum computing and classical computing in the fields of information security, computing, and machine learning, which are all critical fields in the modern world. The study uses a variety of methods, including theoretical analysis, simulation, and experimental implementation to demonstrate the benefits of quantum computing. This study serves as a basis for future research in the field of quantum computing and its applications, which could lead to significant advancements in various areas of science and technology.
    Keywords: comparative analysis; Grover’s algorithm; Shor’s algorithm; quantum computing; quantum SVM; quantum CNN; information security.

  • Character classification enhancement through hybrid feature fusion in challenging scripts systems   Order a copy of this article
    by Sobia Habib, Manoj Kumar Shukla, Rajiv Kapoor 
    Abstract: One of the most intriguing research problems is to achieve high accuracy in character recognition of degraded scripts, which is essential for applications such as document digitisation, language translation, and text-to-speech systems. We aim to recognise two degraded scripts of Devanagari and Urdu languages, which have unique difficulties, mainly due to the presence of broken and merged dots. Traditional character recognition techniques, including template matching and feature-based methods, have been widely used but need to be more efficient to handle the complexities of Urdu and Devanagari scripts. We propose classifying damaged scripts using zone-based power curve fitting and a pre-trained VGG19 model that trains on script degradation patterns. Using 6,250 printed examples with distortions from damaged Devanagari and Urdu manuscripts, we fine-tune the VGG19 model. It helps the proposed model understand these characters’ intricate features and minimises overfitting. Our changes improve accuracy and strengthen the script damage detection system. Our results show that the VGG19 architecture works well across most feature extraction strategies, with accuracy scores ranging from 89.26% to 93.42%, while combining the power curve fitting methodology with VGG19 improves classification accuracy to 97.42%.
    Keywords: power curve fitting; VGG19; challenging scripts systems; broken characters; merged dots characters; deep learning features.

  • Machine learning-driven innovations for energy efficiency engineering systems empower greener technologies   Order a copy of this article
    by R. Regin, K. Selvamani, S. Kanimozhi, Pallavi Ahire, Swakantik Mishra, Sukhwinder Sharma, Sushma Rani 
    Abstract: The research investigates the role of high-energy electronics as a key player in the strength efficiency and sustainability sector. In addition, we look at recent developments in power electronics, including advanced semiconductor materials and novel topologies with machine learning-enhanced control strategies to bring technological innovations towards climate-smart technology. Our process combines a complete literature research and architectural analysis to illuminate innovative power electronics through machine learning and data-driven optimisation. Where the consequences of this study not only show substantial enhancements in power performance and sustainability, but also strengthen the case for embedding advanced energy electronics across myriad programs perfectly aligned with eco-green tech. The discussion extends to how our results may influence the integration of renewable electricity, industrial strategies, and environmental sustainability through transformational system learning-driven innovations. This paper outlines a scenario where green technology meets machine learning to usher in a new era of energy efficiency for a greener planet, highlighting power electronics’ immense potential and future direction. Current constraints are noted as side comments.
    Keywords: sustainable power systems; machine learning optimisation; advanced power electronics; renewable energy integration; energy efficiency solutions; green technology innovations; smart grid technologies; eco-friendly semiconductor materials.

  • Transforming electrical simulation and management with smart grid technologies   Order a copy of this article
    by K. Chitra, S.Silvia Priscila, Edwin Shalom Soji, R. Rajpriya, B. Gayathri, A. Chitra 
    Abstract: Electrical simulation and management are essential for ensuring reliable, efficient, and sustainable power supply to various consumers. However, the traditional power grid faces many challenges, such as ageing infrastructure, increasing demand, integration of renewable energy sources, power quality issues, and cyber-attacks. Smart grid technologies offer a promising solution to overcome these challenges and transform the electrical distribution and management system. Intelligent grid systems encompass sophisticated sensing technology, advanced metering devices, communications infrastructure, control mechanisms, data interpretation tools, and automation components. These elements facilitate two-way information and electrical power exchange between those responsible for grid management and end-users. This article reviews intelligent grid technologies’ impact on electrical distribution and operational management. A case study of a mid-sized urban region informs the article’s organised approach to creating and deploying an intelligent grid network. The findings show that intelligent grid technologies improve electrical distribution system dependability, operational efficiency, environmental sustainability, and security. This article explores the problems and opportunities of intelligent grid systems and provides guidance for future research and technology.
    Keywords: smart grid; electrical simulation; power management; smart meter and microgrid; systems’ reliability; operational efficiency; environmental sustainability; grid management.

  • Modelling and optimisation of structural parameters of main landing gear during touchdown and taxing   Order a copy of this article
    by Mantesh Basappa Khot, Abhijit Prekash, R. Gopalakrishna, Karan Nanda, Hriday Ghosh 
    Abstract: Runway irregularities induce vibrations in the fuselage of aircraft during take-off, taxiing, and landing, leading to fatigue stresses in the airframe. These vibrations impacts passenger comfort and affect the functioning of instruments. To reduce fuselage vibrations in the Fokker-70 aircraft, an optimisation of parameters is conducted, aiming to lower the peak of the frequency response at resonant conditions and minimise the time difference between the fuselage and tire stabilisation after touchdown. This prevents airframe failure due to excessive vibration at resonance. MATLAB s Nelder-Mead simplex algorithm is used for optimisation. Additionally, a PID controller is implemented in the landing gear model to further mitigate vibrations. The controller s effectiveness is tested using a runway model with various bumps, adhering to Boeing s runway roughness criteria. Results show the controller smoothens fuselage response to runway excitations, reducing vibration and enhancing the airframe s fatigue life.
    Keywords: complex modal analysis; Nelder-Mead simplex method; optimisation; Oleo pneumatic shock absorber; PID controller.