Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

30,376 Article Results

Comparative analysis of optimization techniques for optimal EV charging station placement

10.11591/ijpeds.v16.i4.pp2860-2867
Deepa Somasundaram , G. Prakash , N. Rajavinu , D. Lakshmi , P. Kavitha , V. Devaraj
The optimal placement of electric vehicle (EV) charging stations plays a crucial role in improving accessibility, reducing travel distances, and minimizing infrastructure costs in smart urban planning. This study presents a comparative analysis of traditional optimization techniques-such as linear programming (LP), particle swarm optimization (PSO), k-means clustering, and greedy heuristic methods-alongside a machine learning-based approach using genetic algorithms (GA). A machine learning framework is implemented to simulate EV charging demand, optimize station deployment, and incorporate real-world constraints like cost, grid capacity, and user travel penalties. The results demonstrate that GA achieves superior performance in balancing cost-efficiency and user convenience, outperforming traditional techniques in solution quality under dynamic demand conditions. PSO and LP provide faster convergence but are less adaptive to changing parameters. The study highlights the potential of integrating machine learning into infrastructure planning and provides actionable insights for urban planners and policymakers in developing resilient and intelligent EV charging networks.
Volume: 16
Issue: 4
Page: 2860-2867
Publish at: 2025-12-01

Quality of service optimization for 4G LTE upload and download throughput

10.11591/ijict.v14i3.pp1024-1033
Afrizal Yuhanef , Siska Aulia , Lefenia Indriani
Demand for mobile data services and people’s dependence on 4G LTE networks continue to increase. However, the quality of service (QoS) of this network still requires improvement, especially regarding the effect of QoS on throughput at specific frequencies. The research gap lies in the lack of indepth analysis of the impact of QoS parameters on network performance at frequencies of 2,100 MHz and 2,300 MHz. This study evaluates the effect of QoS parameters, such as delay, jitter, and packet loss, on throughput in 4G LTE networks at both frequencies. The research methodology uses an experimental approach with throughput, delay, jitter, and packet loss measurements in various network conditions. The results showed that delay (17.2174 ms to 37.0322 ms), jitter, and packet loss significantly influence throughput, ranging from 624.5 Kbps to 1,322.4 Kbps. The 2,100 MHz frequency tends to show better performance than 2,300 MHz. This study concludes that optimizing QoS parameters, especially delay and jitter, can significantly improve 4G LTE network performance. These findings provide practical contributions for mobile operators in improving network quality and customer satisfaction and open opportunities for further research on other frequencies or newer network technologies.
Volume: 14
Issue: 3
Page: 1024-1033
Publish at: 2025-12-01

Backstepping control in speed loop combined with load torque observer-ESO for IPMSM in electric vehicle

10.11591/ijpeds.v16.i4.pp2271-2279
An Thi Hoai Thu Anh , Tran Hung Cuong , Nguyen Van Hoa
Electric vehicles are gaining popularity due to their environmental friendliness and the need to conserve dwindling fossil fuel resources. In this field, interior permanent magnet (IPM) motors are considered the top choice for propulsion systems due to their high efficiency, high torque-to-current ratio, durability, and low noise. To optimize the speed control performance of IPM motors in the presence of disturbances, a nonlinear speed control algorithm for IPM systems using the backstepping method is developed in this paper. Additionally, a load torque observer using the extended state observer (ESO) method is implemented to enable the system to respond quickly and accurately to load changes while minimizing the effects of disturbances, thereby enhancing the operation and reliability of electric vehicles. The simulation results, conducted in MATLAB/Simulink, demonstrate that the combination of backstepping control and ESO offers good stability for the motor system, while mitigating the impact of disturbances and load variations. This is an important step in optimizing the control system of electric vehicles, contributing to the improvement of performance and reliability in electric vehicle applications.
Volume: 16
Issue: 4
Page: 2271-2279
Publish at: 2025-12-01

Implementation of a network intrusion detection system for man-in-the-middle attacks

10.11591/ijece.v15i6.pp3913-3927
Kennedy Okokpujie , William A. Abdulateef-Adoga , Oghenetega C. Owivri , Adaora P. Ijeh , Imhade P. Okokpujie , Morayo E. Awomoy
Intrusion detection systems (IDS) are critical tools designed to detect and prevent unauthorized access and potential network threats. While IDS is well-established in traditional wired networks, deploying them in wireless environments presents distinct challenges, including limited computational resources and complex infrastructure configurations. Packet sniffing and man-in-the-middle (MitM) attacks also pose significant threats, potentially compromising sensitive data and disrupting communication. Traditional security measures like firewalls may not be sufficient to detect these sophisticated attacks. This paper implements a network intrusion detection system that monitors a computer network to detect Address Resolution Protocol spoofing attacks in real-time. The system comprises three host machines forming the network. Using Kali Linux, a bash script is deployed to monitor the network for signs of address resolution protocol (ARP) poisoning. An email alert system is integrated into the bash script, running in the background as a service for the network administrator. Various ARP spoofing attack scenarios are performed on the network to evaluate the efficiency of the network IDS. Results indicate that deploying IDS as a background service ensures continuous protection against ARP spoofing and poisoning. This is crucial in dynamic network environments where threats may arise unexpectedly.
Volume: 15
Issue: 6
Page: 6027-6042
Publish at: 2025-12-01

Novel multilevel local binary texture descriptor for oral cancer detection

10.11591/ijict.v14i3.pp837-844
Vijaya Yaduvanshi , Raman Murugan
Categorizing texture medical images is an extensive job in most of the fields of computer vision, pattern recognition and biomedical imaging. For the past few years, the texture analysis system model, especially for biological images, has been brought to attention because of its ever-growing requirements and characteristics. This research shows its novelty by using a multilevel local binary texture descriptor (MLBTD) algorithm with support vector machine (SVM), k-nearest neighbor (KNN), and CT Classifiers to investigate the texture features of the oral cancer samples. The simulation work is done in MATLAB2021a environment by employing the MLBTD algorithm. A Mendeley dataset, containing 89 oral cavity histopathological images and 439 OSCC images in 100x magnification, is used. A statistical comparative study of local binary pattern (LBP) and MLBTD with linear SVM, KNN, CT classifier is performed in which results show the better performance of MLBTD and linear SVM with 89.94% of accuracy and by applying MLBTD algorithm over 90.57% accuracy is obtained whereas LBP algorithm only provides 86.16% of accuracy.
Volume: 14
Issue: 3
Page: 837-844
Publish at: 2025-12-01

Enhancing biodegradable waste management in Mauritius through real-time computer vision-based sorting

10.11591/ijict.v14i3.pp1119-1125
Geerish Suddul , Avitah Babajee , Nundjeet Rambarun , Sandhya Armoogum
Mauritius faces a significant waste management challenge due to the indiscriminate mixing of biodegradable and non-biodegradable waste. This practice hinders proper recycling and composting efforts, contributing to environmental pollution and resource depletion. This research proposes a computer vision-based system for real-time classification of waste into biodegradable and non-biodegradable categories. Transfer learning approach based on deep learning models, specifically DenseNet121, MobileNet, InceptionV3, VGG16 and VGG19 were evaluated with two different classifiers, the K-nearest neighbors (KNN) and support vector machine (SVM). Our experiments demonstrate that the MobileNet paired with SVM achieves a classification accuracy of 97% for detection in realtime. Compared to other studies, our results demonstrate better performance and realtime classification capabilities through the implementation of a prototype, facilitating automatic sorting of waste.
Volume: 14
Issue: 3
Page: 1119-1125
Publish at: 2025-12-01

Speed control of 3-phase induction motor with modified DTC using HTAF-ANN

10.11591/ijpeds.v16.i4.pp2197-2211
Arpita Banik , Raja Gandhi , Chandan Kumar , Achyuta Nand Mishra , Rakesh Roy
In this research paper, an artificial neural network (ANN) algorithm is implemented with modifications to enhance the performance of a direct torque controlled (DTC) induction motor drive. Since the main challenge in the conventional DTC technique is to tune the PI controller appropriately therefore in this work, an ANN technique is incorporated in place of the conventional PI controller. Sudden changes in speed and loading in induction motor drives lead to sharp fluctuations and disturb the motor performance. In order to overcome these issues, a trained ANN controller is initially used here to enhance motor drive performance. Subsequently, the performance is further improved by modifying the activation function in the ANN controller. Here, motor parameters at rated and variable speed with various loading conditions have been analyzed and compared for the DTC with a conventional PI controller with ANN, and a proposed ANN controller. Simulation of the complete model with the conventional and proposed controllers is done using MATLAB/Simulink platform to observe the various speed responses for different conditions, and the experimental setup is used to demonstrate the effectiveness and performance of the proposed system.
Volume: 16
Issue: 4
Page: 2197-2211
Publish at: 2025-12-01

Bidirectional AC/DC converter connecting AC and DC microgrids for smart grids

10.11591/ijpeds.v16.i4.pp2549-2561
Nguyen Van Dung , Nguyen The Vinh
This paper proposes a converter connecting two independent AC and DC microgrids in a flexible microgrid and smart grid system. With this converter, basic DC/DC converter types such as Flyback are used to develop the power circuit and controller for the converter that is capable of integrating the operating functions for the operation between microgrids. The converter uses bidirectional switching locking technology to simplify the control algorithm. The energy is converted in two directions, AC/DC and DC/AC, with different working principles of increasing and decreasing voltage according to the standards of the distribution grid and DC microgrid. The TDH value is significantly limited when using the recovery circuit solution. The converter is designed, simulated based on OrCAD software, and tested with a capacity in the range of 2-10 kW. The DC microgrid output voltage is 400 VDC, voltage is 220 VAC.
Volume: 16
Issue: 4
Page: 2549-2561
Publish at: 2025-12-01

Eco-friendly innovation: green energy empowered by IoT

10.11591/ijape.v14.i4.pp903-911
Nikita Amoli , Jitendra Singh , Rahul Mahala , Rajesh Singh , Anita Gehlot , Mahim Raj Gupta
Energy demand is high globally, impacting daily life and promoting sustainable modernization. Goal 9 aims to build an elastic framework for economies, while Goal 15 of the Sustainable Development Goals (SDGs) emphasizes the preservation of terrestrial environment, sustainable woodland management, and biodiversity conservation. The International Energy Agency predicts a significant increase in global renewable capacity, with solar PV being two-third of this growth. Green technology is crucial to combat global warming and Industry 4.0, a digital transformation that aims to create a strong framework for sustainable modernization. The growth of the smart grid is vital, involving energy sources, control techniques, computation, generation, transmission, distribution, and more. Supercapacitors store and deliver energy at high capacity, while green energy transforms fossil fuels into eco-friendly sources using natural resources like hydro, solar, wind, thermal, and biomass. This study explores the efficient use of microprocessors in solar and wind energy, as well as the application of actuators in the green energy sector. Green energy is a sustainable solution to increasing energy needs, reducing dependence on fossil fuels. IoT technologies, including sensors, actuators, microprocessors, and microcontrollers, are used in energy generation, transmission, distribution, and composition.
Volume: 14
Issue: 4
Page: 903-911
Publish at: 2025-12-01

Effect on saturated and unsaturated fatty acids on various vegetable oils on droplet combustion characteristic

10.11591/ijape.v14.i4.pp980-987
Dony Perdana , Muhamad Nur Rohman , Mochamad Choifin
Vegetable oils have composed of triglycerides, which one consist of 3 fatty acids combined with glycerol. Each saturated and unsaturated fatty acid has a different effect on burning characteristics. This study aimed to investigated effect of fatty acids at ceiba pentandra and jatropha oils on the flame behavior of the droplet combustion process. The combustion characteristic was observed by an ignited droplet at the junction using a thermocouple and a high-speed camera (120 fps). Results showed that a higher saturated fatty acid content resulted in long-life and steady flames. This is because more oleic and linoleic acid carbon atoms leave the droplet area and react with air. Jatropha oil produces a higher temperature of 780 °C than ceiba pentandra oil. Temperature of a vegetable oils flame is influenced by number of carbon chains, double bond, and heating value. Ceiba pentandra oil has a higher burning rate of 0.185 mm/s than jatropha oil at 0.155 mm/s. The chain content of polyunsaturated fatty acids has significant effect on rate of combustion, which is due to the weak van der Waals dispersion forces, such that heat absorption is more active and energetic. The highest flame height for ceiba pentandra oil is 55.03 mm compared to for jatropha oil it is 46.82 mm. Long-chain unsaturated double bonds and glycerol cause micro-explosions. This micro-explosion caused the shape of the flame to split and expand so that evaporation occurred faster, thus increasing the size of the flame.
Volume: 14
Issue: 4
Page: 980-987
Publish at: 2025-12-01

A recommendation system for teaching strategies according to learning styles

10.11591/ijict.v14i3.pp983-992
Juan Francisco Figueroa-Pérez , Manuel Rodríguez-Guerrero , Alan Ramírez-Noriega , Yobani Martínez-Ramírez
Teaching strategies (TS) are resources, procedures, techniques, and/or methods that teachers use as instruments to promote meaningful learning in students and that have proven to be efficient as support in classroom teaching. This paper describes a recommendation system (RS) for teaching strategies according to learning styles (RSTSLS) that helps to determine the most appropriate TS to use according to the learning style (LS) of the students based on Felder and Silverman’s learning styles model (FSLSM). A working example of the system is provided, as well as the results of its functional and non-functional tests, which were satisfactory. It is concluded that the system can be useful as a support tool for teachers, allowing them to adapt their TS according to the LS of their students.
Volume: 14
Issue: 3
Page: 983-992
Publish at: 2025-12-01

Asymmetrical nine-level hybrid multilevel inverter design and analysis for electric vehicle applications

10.11591/ijape.v14.i4.pp1023-1034
Gerri Ratnaiah , Ramya Ganesan
A novel type of single-phase hybrid multilevel inverter (HMLI) is proposed in this paper. A hybrid system is made up of a multilevel inverter coupled to an H-bridge unit and which can generate nine-level output. To synthesize an output voltage waveform with nine steps, this setup uses merely seven power switches, two diodes, and two DC supplies. A greater number of steps were achieved in output voltage through suggested circuit with a smaller number of components than other existing multilevel inverter (MLI) topologies. A finer output waveform that is closer to a sinusoidal shape is produced with less total harmonic distortion (THD) because of the greater number of steps in the output voltage. Furthermore, it prolongs the switches' lifetime and lowers the voltage stress across them, increasing reliability. In addition, the system produces fewer switches than necessary, resulting in lower power losses and increased efficiency. This guarantees the suggested system's small size and inexpensive cost. A comparison between the suggested topology and the most current MLI topologies has been conducted to highlight the key components of the proposed topology. The suggested topology has been controlled using three distinct controlling schemes are phase disposition-pulse width modulation (PD-PWM), phase opposition disposition-PWM (POD-PWM), and alternative phase opposition disposition-PWM (APOD-PWM).
Volume: 14
Issue: 4
Page: 1023-1034
Publish at: 2025-12-01

State space controller of SLCC and design analysis with MPPT approaches

10.11591/ijict.v14i3.pp791-801
Jeyaprakash Natarajan , Nivethitha Devi Manoharan , Mohanasanthosh Murugan , Karnati Venkata Lokeshwar Reddy , Thirumalaivasal Devanathan Sudhakar
Power systems with standalone properties like remote unit telecommunication network requires high negative DC supply voltage. In such remote places, solar photovoltaic (PV) are used to generate power. Maximum power point tracking techniques (MPPT) gives unregulated voltage from solar panel. This unregulated voltage is converted into regulated voltage by providing proper pulse width modulation (PWM) signal to self-lift cuk converter (SLCC). In comparison with classic cuk converter, SLCC reduces load voltage and load current ripples. This paper focuses on state space controller design and implementation of SLCC used in MPPT based PV system. The switching pulse of SLCC can be generated by perturb and observe (P&O), incremental conductance (IC) and also using fuzzy control. The simulation of SLCC has been performed using MATLAB/Simulink and its specifications in time domain has been compared.
Volume: 14
Issue: 3
Page: 791-801
Publish at: 2025-12-01

Integration and optimization of grid through ANN-based solar MPPT and battery

10.11591/ijape.v14.i4.pp988-998
Kolli Sujran , Ankala Sirisha , Ganapaneni Swapna , Malligunta Kiran Kumar , Kambhampati Venkata Govardhan Rao
Integration of solar energy into the grid is the most important aspect for achieving sustainable energy systems. This paper presents an artificial neural network-based maximum power point tracking (ANN-MPPT) system with battery storage to enhance grid efficiency. The proposed ANN-MPPT is dynamically adapted to the varying irradiance and temperature, hence ensuring optimal power extraction from the photovoltaic system. Excess energy is stored in batteries during high solar radiation and discharged when solar generation is low or grid demand is high, maintaining a stable power supply. This system enhances the grid performance in terms of supporting real-time energy exchange, load balancing, and grid stability. Efficient management of the energy fluctuations ensures reliability even at times of grid failures. Further, integration of ANN-based MPPT with battery storage reduces dependence on non-renewable sources and harmonizes solar energy utilization. It can be achieved through enabling smarter energy management and thus contributing to the resilience and efficiency of a grid for better integration of renewable energies. The proposed system can tolerate fluctuating grid demands apart from supporting the features of smart grid, hence viable for increasing stability and sustainability in the grid.
Volume: 14
Issue: 4
Page: 988-998
Publish at: 2025-12-01

Implementation of adaptive PID control for maintaining temperature stability during steady-state conditions in stirred heating tank

10.11591/ijpeds.v16.i4.pp2389-2399
Pricylia Valentina , Hendro Tjahjono , Agus Sunjarianto Pamitran , Iwan Roswandi , Putut Hery Setiawan , Arif Adtyas Budiman , Dedy Haryanto , Sanda Sanda , Kukuh Prayogo , Mulya Juarsa
Temperature stability is a crucial factor in industries such as chemicals, pharmaceuticals, and food processing, where fluctuations can damage product quality and increase energy consumption. This study aims to optimize heater power control using an adaptive proportional integral derivative (PID) control system to maintain temperature stability under steady-state conditions. The method involves applying adaptive PID control to a stirred heating tank using LabVIEW software with a national instruments controller module and a single-phase SCR to regulate heater power and adjust control parameters in real time. The results indicate that the system operates more effectively under stable conditions, with faster response times and a lower overshoot of less than 0.12%. However, under disturbed conditions, such as water drainage and replacement, the system requires more time to adjust the temperature and experiences increased energy consumption and heat loss. Despite this, the system still achieves an energy efficiency improvement, with efficiency values ranging from 77.66% to 80.03%. The implementation of adaptive PID control demonstrates significant potential in enhancing system accuracy and response to temperature changes, contributing to the development of more efficient industrial control technologies.
Volume: 16
Issue: 4
Page: 2389-2399
Publish at: 2025-12-01
1 2 3
...
2025 2026
Show 102 of 2026

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration