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31,042 Article Results

Modeling chemical kinetics of geopolymers using physics informed neural network

10.11591/ijict.v14i3.pp822-829
Blesso Abraham , Thirumalaivasal Devanathan Sudhakar
Using a physics informed neural network for the analysis of geopolymers as an alternate material for cement can be a viable approach, as neural networks are capable of modeling complex, nonlinear relationships in data, which can be beneficial for representing the dynamics of chemical properties. If you have a substantial amount of theoretical data, a neural network can learn patterns and relationships in the data, even when the underlying system dynamics are not well-defined or are difficult to model analytically. A welltrained neural network can generalize from the training data to make predictions for unseen scenarios, which can be useful for real-time analysis of the material.
Volume: 14
Issue: 3
Page: 822-829
Publish at: 2025-12-01

Comparison of the discounted costs of controlled asynchronous electric drives with matrix and with DC link frequency converters

10.11591/ijpeds.v16.i4.pp2307-2320
Viktor Petrushyn , Juriy Plotkin , Vasily Horoshko , Rostyslav Yenoktaiev , Andrii Yakimets
A quality criterion based on discounted costs is proposed, which demonstrates a significant advantage of the variable frequency asynchronous motor drive with a matrix converter over the drive with a voltage source inverter, which contains a DC link. A MATLAB software simulation was conducted to ascertain the control characteristics. In light of the control range afforded by both drives, a criterion for discounted costs is proposed that is calculated as a mid-range within a specific rotational speed control range, or is determined based on a given tachogram. The aforementioned costs include the expense of the drive, the cost of losses, maintenance costs, amortization charges, and the cost of reactive power compensation due to phase shifts of the main harmonic current and voltage. In this study, we put forth a novel proposal for the incorporation of the cost of distortion power compensation resulting from the presence of harmonic components of the input current.  The latter costs characterize the electromagnetic compatibility of the drive with the network. For the first time, a quality criterion for a regulated electric drive is proposed, which has a cost component that takes into account the electromagnetic compatibility of the drive with the network. A significant reduction in this component in a drive with a matrix converter compared to a drive with a DC link predetermines a reduction in discounted costs. For a given payback period and annual inflation rate, it was determined that the mid-range discounted costs were reduced by more than 11 times and the tachogram based discounted costs were reduced by more than 10 times for a drive with a matrix converter in comparison to a drive with a DC link.
Volume: 16
Issue: 4
Page: 2307-2320
Publish at: 2025-12-01

Support-centric PSO-based fuzzy MPPT tuning for photovoltaic systems under uniform conditions

10.11591/ijpeds.v16.i4.pp2792-2803
Amel Smaili , El-Ghalia Boudissa , M’hamed Bounekhla
Several conventional maximum power point tracking (MPPT) algorithms have been applied to harvest the optimal power of a photovoltaic (PV) system. However, the main drawbacks of these algorithms are their fluctuations around the maximum power point (MPP) and their dependence on climatic conditions variation. To overcome these issues, a fuzzy logic controller (FLC) is proposed, where the system performance depends strongly on the choice of membership functions (MFs). They are typically selected by trial and error, which may not always yield the best results. This paper seeks to enhance the efficiency of the traditional FLC method by using the particle swarm optimization (PSO) algorithm for optimizing the supports of the triangular MFs. The simulation was performed using MATLAB-Simulink environment using the "1Soltech 1STH-215-P" PV module and a single-ended primary-inductor converter (SEPIC) converter, under ideal environmental conditions of 25 °C and 1000 W/m². A comparison is established between PSO-optimized FLC and the standard FLC-based MPPT method, as well as with several other state-of-the-art approaches reported in related research. The simulation data present that the PSO-optimized FLC approach outperforms other algorithms.
Volume: 16
Issue: 4
Page: 2792-2803
Publish at: 2025-12-01

Chatbot for virtual medical assistance

10.11591/ijict.v14i3.pp914-922
Aravalli Sainath Chaithanya , Sampangi Lahari Vishista , Adepu MadhuSri
A healthy population is vital for societal prosperity and happiness. Amidst busy lifestyles and the challenges posed by the COVID-19 pandemic, individuals often neglect their health needs. To address this, we introduce a novel approach utilizing a chatbot for virtual medical assistance. Tailored for individuals confined indoors or hesitant to visit hospitals for minor ailments, our chatbot offers personalized medical support by diagnosing ailments based on user-reported symptoms and engaging in interactive conversations. Leveraging a robust dataset containing 132 symptoms, 41 diseases, and corresponding medications, our chatbot employs a systematic approach for symptom refinement, enhancing diagnostic precision. Upon identifying a disease, the chatbot promptly suggests basic medications tailored to the specific ailment. Furthermore, our system integrates user demographics to evaluate medication history and current state, allowing for personalized medication recommendations based on individual needs. Through extensive testing and validation, we demonstrate the effectiveness of our chatbot in accurately predicting ailments and providing timely treatment advice. Our study introduces a novel paradigm for medicine recommendation and disease prediction, with the potential to enhance healthcare accessibility and effectiveness.
Volume: 14
Issue: 3
Page: 914-922
Publish at: 2025-12-01

The bootstrap procedure for selecting the number of principal components in PCA

10.11591/ijict.v14i3.pp1136-1145
Borislava Toleva
The initial step in determining the number of principal components for both classification and regression involves evaluating how much each component contributes to the total variance in the data. Based on this analysis, a subset of components that explains the highest percentage of variance is typically selected. However, multiple valid combinations may exist, and the final choice is often made manually by the researcher. This study introduces a novel yet straightforward algorithm for the automatic selection of the number of principal components. By integrating ANOVA and bootstrapping with principal component analysis (PCA), the proposed method enables automatic component selection in classification tasks. The algorithm is evaluated using three publicly available datasets and applied with both decision tree and support vector machine (SVM) classifiers. Results indicate that this automated procedure not only eliminates researcher bias in selecting components but also improves classification accuracy. Unlike traditional methods, it selects a single optimal combination of principal components without manual intervention, offering a new and efficient approach to PCAbased model development.
Volume: 14
Issue: 3
Page: 1136-1145
Publish at: 2025-12-01

Attenuated-chattering global second-order sliding mode load frequency controller for multi-region linked power systems

10.11591/ijpeds.v16.i4.pp2381-2388
Phan-Thanh Nguyen , Cong-Trang Nguyen
In this study, a new chattering-free global second-order sliding mode load frequency controller (CGSOSMLFC) is proposed for multi-region linked power systems (MRLPS). Key achievements of this paper include: i) a new CGSOSMLFC is investigated utilizing only output variables; ii) a global steadiness of the MRLPS is ensured by eliminating the hitting phase in traditional sliding mode control (TSMC), and the undesirable high-frequency vacillation marvel in the control signal is efficiently lessened by utilizing the second-order sliding mode control technique. Firstly, a novel estimator is constructed to conjecture the immeasurable state variables of the MRLPS. Then, an estimator-based CGSOSMLFC is synthesized to force the states of the controlled plant into the anticipated switching surface at an instance time and attenuate the chattering phenomenon in the control indication. Additionally, the total MRLPS’s stability analysis is executed by applying the Lyapunov function theory and linear matrix inequality (LMI), confirming the practicability and reliability of the method. Lastly, simulation outcomes on a three-zone linked power system are furnished to authenticate the usefulness and advantages of the proposed technique.
Volume: 16
Issue: 4
Page: 2381-2388
Publish at: 2025-12-01

Modelling and analysis of linear DC motor with constant thrust characteristics

10.11591/ijpeds.v16.i4.pp2212-2223
Raja Nor Firdaus Kashfi Raja Othman , Siti Zulaika Mat Isa , Nor Aishah Md. Zuki , Suhairi Rizuan Che Ahmad , Fairul Azhar Abdul Shukor , Md. Nazri Othman
This paper introduces a portable and user-friendly innovation in food processing by replacing traditional molding methods with a linear DC motor (LDM). Traditional methods, which involve manual pressing, are energy-intensive and time-consuming, reducing productivity. The proposed LDM offers a simple, cost-effective, and robust solution capable of producing constant thrust, unlike conventional LDMs that require complex and expensive control methods and are limited to short displacements. The research focuses on modelling and analyzing an LDM with constant thrust characteristics for food processing applications. The primary objective is to model the thrust using the permeance analysis method (PAM), ensuring constant thrust capability. Verification was conducted using the finite element method (FEM) and measurement results, showing a percentage difference of 1.7% and 6.5%, respectively, between PAM and the other methods. The study provides valuable guidance for designing LDMs with constant thrust capabilities, enhancing the efficiency and practicality of food processing devices.
Volume: 16
Issue: 4
Page: 2212-2223
Publish at: 2025-12-01

Soil moisture prototype soil moisture sensor YL-69 for Gaharu (Aquilaria malaccensis) tree planting media

10.11591/ijict.v14i3.pp1163-1171
Rikie Kartadie , Muhammad Agung Nugroho , Adiyuda Prayitna , Adi Kusjani , Ardeana Galih Mardika
Soil moisture, defined as the amount of water present in the spaces between soil particles, plays a critical role in plant growth. Excessive soil moisture can lead to issues such as root rot, deviating from the ideal conditions required for root absorption. To address this, we developed a prototype tool using the YL-69 soil moisture sensor to monitor and control the soil moisture levels in Agarwood/Gaharu tree planting media. The prototype was designed to activate a water pump when soil moisture exceeded 80%, ensuring optimal humidity for plant growth. Once the moisture level dropped below 80%, the pump was deactivated to prevent overwatering. The YL-69 sensor demonstrated an accuracy of 88.76% under controlled conditions. This study highlights the potential of using low-cost sensors for automated soil moisture management in small-scale Gaharu cultivation.
Volume: 14
Issue: 3
Page: 1163-1171
Publish at: 2025-12-01

Design and analysis of brushless permanent magnet motor for light electrically powered two-wheeler vehicle

10.11591/ijpeds.v16.i4.pp2296-2306
How Xuan Yu , Mohd Luqman Mohd Jamil , Nurul Ain Mohd Said
This study provides a comprehensive process of designing an electric motor that will be used for a small two-wheeled electric vehicle. Due to high performance capability in term of power and torque, brushless permanent magnet topology is chosen so that a compromise between size constraint and performance can be met. For an accurate motor design sizing, the design process is initially carried out by determination of power rating that derived from vehicle dynamic calculation. Based on winding factor calculation, fractional-slot 12-slot/10-pole and 9-slot/10-pole motors equipped with non-overlapping winding are chosen and analyzed using finite element analysis (FEA) software. For an optimum electromagnetic performance, parametric optimization is included, mainly on the stator dimension. Despite the performance of both designs improved, only 9-slot motor results a convincing performance as the rated torque is 18% higher than the 12-slot design. For verification purpose, 1-D analytical solution is also included and compared with results deduced by the FEA. According to the analysis, the proposed motor designs are adequately reliable for a light electrically powered electric vehicle application.
Volume: 16
Issue: 4
Page: 2296-2306
Publish at: 2025-12-01

Scaling of Facebook architecture and technology stack with heavy workload: past, present and future

10.11591/ijict.v14i3.pp772-782
Tole Sutikno , Laksana Talenta Ahmad
Leading social media Facebook has improved its architecture to meet user needs. Facebook has improved its systems to handle millions of users with heavy workloads and large datasets using innovative architectural solutions and adaptive strategies. The study examines Facebook’s architectural and technological advances in heavy workload and big data. To understand how Facebook scaled with a growing user base and data volume, history and system architecture will be examined. It will also examine how cloud storage and high-performance computing optimize resource utilization and maintain performance during peak user activity. Facebook is managing big data and heavy workloads with new technologies like the hybrid communication model that uses PULL and PUSH strategies for real-time messaging. Facebook switched from HBase to MyRocks for message storage to improve performance as data grew. Architectural scaling and technology stack research must prioritize data storage innovations and optimized communication protocols to handle heavy workloads and big data. The messenger Sync protocol reduces network congestion and improves synchronous communication, reducing resource consumption and maintaining performance under high load. High-performance computing (HPC) and cloud storage should be studied together to support complex compute workflows. This convergence may improve large-scale application infrastructures and encourage interdisciplinary collaboration for scalable and resilient systems.
Volume: 14
Issue: 3
Page: 772-782
Publish at: 2025-12-01

Bidirectional power converter for electrical vehicle with battery charging and smart battery management system

10.11591/ijpeds.v16.i4.pp2592-2604
Bodapati Venkata Rajanna , Kondragunta Rama Krishnaiah , Ganta Raghotham Reddy , Shaik Hasane Ahammad , Mohammad Najumunnisa , Syed Inthiyaz , Gouthami Eragamreddy , Ambarapu Sudhakar , Nitalaksheswara Rao Kolukula
In electric vehicles (EVs), efficient energy management is critical for reliable power transfer between the battery and motor. This paper presents the design and implementation of a bidirectional DC-DC converter equipped with a smart battery management system (BMS). The system supports bidirectional power flow, operating in boost mode during acceleration and buck mode during regenerative braking, thereby enhancing overall energy efficiency and vehicle performance. A PIC microcontroller governs the system, performing real-time monitoring of key battery parameters such as state of charge (SOC), state of health (SOH), voltage, and temperature. Safety features include automatic cooling fan activation when the temperature exceeds 45 °C and generator startup when battery voltage falls below 23 V. Real-time data is displayed via an LCD interface to improve user interaction and system transparency. The proposed system achieved a conversion efficiency of 90-93% during experimental testing, with stable switching, reliable automation, and effective thermal protection. The embedded energy management system optimizes charging and discharging cycles while preventing overcharging, deep discharge, and thermal stress. This intelligent, automated power converter enhances battery life, improves EV reliability, and contributes to sustainable transportation by enabling features like vehicle-to-grid (V2G) energy transfer. The proposed architecture is well-suited for integration into modern EV infrastructure. Although the system architecture supports future V2G integration, V2G functionality was not implemented or tested in the present experimental setup.
Volume: 16
Issue: 4
Page: 2592-2604
Publish at: 2025-12-01

Design and development of AC motor speed controlling system using touch screen with over heat protection

10.11591/ijpeds.v16.i4.pp2429-2440
Prathipati Ratna Sudha Rani , Gouthami Eragamreddy , Syed Inthiyaz , Sivangi Ravikanth , Mohammad Najumunnisa , Bodapati Venkata Rajanna , Cheeli Ashok Kumar , Shaik Hasane Ahammad
Design and implementation of an AC motor speed control and monitoring system based on a touch screen interface with built-in overheat protection, utilizing Arduino, meets the increasing demand for efficient, user-friendly motor control in many industrial applications. This system offers an easy-to-use interface to manage the speed of an AC motor, with real-time feedback and adjustments through a touch screen display. The system employs an Arduino microcontroller, which accepts inputs from the touch screen and processes these to regulate the motor's speed through a pulse width modulation (PWM) method. The system also has an overheat protection system, which it is able to monitor the temperature of the motor via a temperature sensor. When the motor reaches a predetermined temperature, the system automatically shuts off power to avoid damage. The intuitive touch screen facilitates convenient monitoring of motor parameters like temperature, giving a smooth experience to operators. The modular design of the system provides scalability across applications, ranging from household appliances to large industrial systems, with reliability, energy efficiency, and safety in motor-driven processes.
Volume: 16
Issue: 4
Page: 2429-2440
Publish at: 2025-12-01

An artificial intelligent system for cotton leaf disease detection

10.11591/ijict.v14i3.pp950-959
Priyanka Nilesh Jadhav , Pragati Prashant Patil , Nitesh Sureja , Nandini Chaudhari , Heli Sureja
This study aims to develop a deep learning-based system for the detection and classification of diseases in cotton leaves, with the goal of aiding in early diagnosis and disease management, thereby enhancing agricultural productivity in India. The study utilizes a dataset of cotton leaf images, classified into four categories: Fusarium wilt, Curl virus, Bacterial blight, and Healthy leaves. The dataset is used to train and evaluate various CNN models such as basic CNN, VGG19, Xception, InceptionV3, and ResNet50. These models were evaluated on their accuracy in identifying the presence of diseases and classifying cotton leaf images into the respective categories. The models were trained using standard deep learning frameworks and optimized for high performance. The results indicated that ResNet50 achieved the highest accuracy of 100%, followed by InceptionV3 with 98.75%, and VGG19 and Xception both with 97.50%. The basic CNN model showed an accuracy of 96.25%. These models demonstrated strong potential for accurate multi-class classification of cotton leaf diseases. This study emphasizes the potential of deep learning in agricultural diagnostics. Future research can focus on improving model robustness, incorporating larger datasets, and deploying the system for real-time field use to assist farmers in disease management and improving cotton production.
Volume: 14
Issue: 3
Page: 950-959
Publish at: 2025-12-01

Design and implementation of IoT-based soft starter for induction motor

10.11591/ijpeds.v16.i4.pp2170-2177
Laith Najem Abood Khudhur , Amer Abdulmahdi Jabbar Chlaihawi
The practical application of the induction motor is an essential part of electrical engineering. A direct connection of the motors to the mains voltage negatively affects both the motor itself and the mains system as a whole due to high starting current values, as a result, more accidents and shortening the drive system service life. This article discusses the development of designing and implementing of soft starter single-phase IM to reduce the inrush current using the firing angle reduction technique with remote monitoring and control using the ESP32 (node MCU) and Arduino Due microcontrollers. The integration of IoT-based tools software such as VS Code, enables the remote monitoring and control of motor features. Testing shows that the system effectively facilitates remote motor control, providing a flexible and accessible learning environment with minimum starting current, solving the inrush current problem facing IMs. The proposed soft starter gives three cases of firing angle reduction that show a percentage reduction in starting current for these cases (case I, case II, and case III) are 51%, 54% and 64%, respectively. Case III has a maximum starting current is 2.2 A compared to 6.2 A for direct connecting of IM to the power supply (DOL).
Volume: 16
Issue: 4
Page: 2170-2177
Publish at: 2025-12-01

Processor-in-the-loop performance validation of a three-phase NPC three-level inverter using a novel sinusoidal PWM technique for scalar control of an induction motor

10.11591/ijpeds.v16.i4.pp2257-2270
Badr N’hili , Souhail Barakat , Abdelouahed Mesbahi , Mohamed Khafallah , Ayoub Nouaiti
This paper presents the performance of a three-phase, three-level neutral point clamped inverter driving an induction motor for variable-speed applications, compared to a two-level inverter. The studied inverter operates using a novel sinusoidal pulse width modulation technique that improves the quality of voltage and current output signals while increasing efficiency. Motor speed control is achieved using the scalar control (V/Hz) method. Experimental validation of the simulation results is performed by executing the generated C code on the F28379D DSP LaunchPad within the MATLAB/Simulink and Code Composer Studio environment, applying the processor-in-the-loop (PIL) technique.
Volume: 16
Issue: 4
Page: 2257-2270
Publish at: 2025-12-01
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