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31,456 Article Results

Factors influencing enrollment intention in private schools

10.11591/ijere.v14i6.35364
Lim Lee Ping , Ong Choon Hee , Tan Owee Kowang , Lim Kim Yew
The growth in private school student enrollment in Malaysia has prompted institutions to upgrade to stay competitive in the market. However, despite the increasing number of private schools, regrettably, only a few studies have focused on the factors that influence private school enrollment. This study examines the relationship between social influences (SI), school environment (SE), characteristics, parent-administration-teacher relationship (PAT), and private school enrolment intention in Malaysia. It uses a quantitative method and G*Power to determine the minimum sample size. Data was gathered from 135 respondents who have enrolled at least one child in private schools using questionnaire surveys. The statistical package for social science (SPSS) was used to analyze the data. The results showed that SI and school characteristics (SC) significantly and positively correlated with enrolment intention. The PAT was not significantly associated with enrolment intention. This study clearly shows that SI factors and SCs are crucial for enrolment intention in private schools. The management should develop and implement marketing strategies that effectively tackle current market challenges by focusing on SI and improving the SC. They can tailor the marketing strategy with electronic word-of-mouth (e-WOM) for SI and apply learning analytics for SC.
Volume: 14
Issue: 6
Page: 4509-4516
Publish at: 2025-12-01

Development of a leakage detection and alert system for liquefied petroleum gas via a mobile application

10.11591/ijaas.v14.i4.pp1099-1110
Wael A. Salah , Anees Abu Sneineh
Nowadays, ensuring the comfort and safety of house users is a top priority, and this may be accomplished by implementing smart technology to lead a convenient and safe life. Leakage of liquefied petroleum gas (LPG), which is mostly utilized in the home kitchen for cooking, is one of the frequent risks. Using a gas sensing device, a gas control system, and wireless communication units, the goal of this study is to create an LPG gas leakage warning and management system to prevent the gas from exploding by detecting the leak. When LPG gas is brought near the sensor, it detects the leakage and the buzzer is activated by activating the audio-visual alarm and closing the gas cylinder valve. The system also generates alert messages and sends them to the fire station when the LPG gas leakage has reached a critical level. Testing results of the proposed LPG leakage system show a satisfactory performance of the developed device with a quick response to LPG gas leakage. In addition, powerful audio and visual alarms are activated. An immediate message was sent to homeowners and the fire station department regarding the leakage incident to prevent the risk of gas leakage.
Volume: 14
Issue: 4
Page: 1099-1110
Publish at: 2025-12-01

Tailoring collaborative learning with jigsaw and VARK: a case study in teaching physics with environmental protection

10.11591/ijere.v14i6.32823
Ngan Hai My Le , Anh Thi Kim Nguyen
Collaboration is a crucial 21st century skill, requiring learning environments that foster teamwork while leveraging students’ individual strengths. This study aimed to enhance collaboration using the jigsaw strategy, which was adapted to students’ learning styles based on the model: visual, aural, read/write, and kinesthetic (VARK). The study involved 27 tenth-grade students in Ho Chi Minh City and focused on the topic “physics with environmental protection.” Students were initially grouped by learning styles into expert groups and later reorganized into mixed jigsaw groups to collaboratively address tasks related to environmental issues. A quasi-experimental design was employed, utilizing pre- and post-test self-assessment surveys, video observations, and group discussions to assess collaborative performance. Quantitative data were analyzed using the Wilcoxon signed rank test, while qualitative data provided deeper insights. Results demonstrated a significant improvement in team support (p=0.030), suggesting that aligning learning tasks with students’ styles foster group cohesion. However, participation and contribution showed minimal improvement, with students preferring reading/writing styles facing challenges in adapting to group activities. While the integration of jigsaw and VARK proved effective in enhancing collaboration, the study underscores the need to develop strategies to accommodate diverse learning preferences. Future research should involve larger sample sizes and consider teachers’ perspectives to optimize the practical implementation of learning styles in collaborative learning environments.
Volume: 14
Issue: 6
Page: 4364-4374
Publish at: 2025-12-01

Integration of ultra-wideband elliptical antenna with frequency selective surfaces array for performance improvement in wireless communication

10.11591/ijece.v15i6.pp5515-5523
Saleh Omar , Chokri Baccouch , Rhaimi Belgacem Chibani
The integration of frequency selective surfaces (FSS) with antennas has gained significant attention due to its ability to enhance key radio frequency (RF) performance parameters such as gain, directivity, and bandwidth, making it highly beneficial for modern wireless communication systems. In this work, we propose and investigate an ultra-wideband (UWB) elliptical antenna operating within the 5.2 to 10 GHz frequency range. To further improve its performance, we integrate the antenna with a 13×13 FSS array. The impact of the FSS on the antenna’s characteristics is analyzed, showing a remarkable gain enhancement from 2.6 dBi (without FSS) to 10.05 dBi (with FSS). These results confirm the effectiveness of FSS integration in optimizing UWB antenna performance, making it a promising approach for advanced wireless communication applications.
Volume: 15
Issue: 6
Page: 5515-5523
Publish at: 2025-12-01

Geometrical determination of the focal point of parabolic solar concentrators

10.11591/ijece.v15i6.pp5055-5066
Bekzod Maxmudov , Sherzod A. Korabayev , Nosir Yu. Sharibaev , Abror Abdulkhaev , Xulkarxon Mahmudova , Sh A. Mahsudov
Parabolic solar concentrators play a crucial role in harnessing solar energy by focusing sunlight onto a single focal point, enhancing efficiency in solar thermal applications. However, accurately determining the focal point remains a significant challenge, affecting energy efficiency, stability, and operational costs. This study presents a novel approach to determining the focal point of parabolic solar concentrators using two distinct geometric and mathematical methods. The first method applies standard parabolic equations to derive the focal point, while the second method introduces a geometric approach based on the properties of straight-line tangents and angular measurements. Experimental validation was conducted by comparing the proposed method against laser-based focal point determination. The results demonstrate that the proposed method enhances heat collection efficiency and stability, leading to improved energy output. The findings of this study contribute to optimizing solar concentrator designs, reducing energy losses, and promoting sustainable energy applications.
Volume: 15
Issue: 6
Page: 5055-5066
Publish at: 2025-12-01

Improving time-domain winner-take-all circuit for neuromorphic computing systems

10.11591/ijece.v15i6.pp5173-5182
Son Ngoc Truong , Tu Tien Ngo
With the rapid advancements of information processing systems, winner- take-all (WTA) circuits have emerged as essential components in a wide range of cognitive functions and decision-making applications. Neuromorphic computing systems, inspired by the biological brain, utilize WTA circuits as selective mechanisms that identify and retain the strongest signal while suppressing all others. In this study, we present an effective time-domain WTA circuit with optimized multiple-input NOT AND (NAND) gate and delay circuit for neuromorphic computing applications. The circuit is evaluated using sinusoidal current inputs with varying phase delays, which successfully demonstrating precise winner selection. When applied to neuromorphic image recognition task, the enhanced time-domain WTA achieves an improvement of 0.2% in precision while significantly reducing power consumption, yielding a low figure of merit (FoM) of 0.03 µW/MHz, compared to the previous study with FoM of 0.25 µW/MHz. The optimized WTA circuit is highly promising for large-scale neuromorphic applications.
Volume: 15
Issue: 6
Page: 5173-5182
Publish at: 2025-12-01

Improving network security using deep learning for intrusion detection

10.11591/ijece.v15i6.pp5570-5583
Mohammed Al-Shabi , Anmar Abuhamdah , Malek Alzaqebah
As cyber threats and network complexity grow, it is crucial to implement effective intrusion detection systems (IDS) to safeguard sensitive data and infrastructure. Traditional methods often struggle to identify sophisticated attacks, necessitating advanced approaches like machine learning (ML) and deep learning (DL). This study explores the application of ML and DL algorithms in IDS. Feature selection techniques, such as correlation and variance analysis, were employed to identify key factors contributing to accurate classification. Tools like WEKA and MATLAB supported data pre-processing and model development. Using the UNSW-NB15 and NSL-KDD datasets, the study highlights the superior performance of random forest (RF) and multi-layer perceptron (MLP) algorithms. RF ensemble decision trees and MLP multi-layered architecture enable accurate attack detection, demonstrating the potential of these advanced techniques for enhanced network security.
Volume: 15
Issue: 6
Page: 5570-5583
Publish at: 2025-12-01

Data transmission technologies for the development of a drilling rig control and diagnostic system

10.11591/ijece.v15i6.pp5506-5514
Irina Rastvorova , Sergei Trufanov
This article examines telecommunication technologies used in automatic control and diagnostics systems and discusses key aspects of using telecommunication solutions for monitoring and controlling the operation processes of the electrical complex of a drilling rig, including remote access, data transmission and real-time information analysis. It provides a comprehensive overview of such communication technologies as Bluetooth, Wi-Fi, ZigBee, global system for mobile communication (GSM), RS-232, RS-422, RS-485, universal serial bus (USB), Ethernet, narrowband internet of things (NB-IoT), long range wide area network (LoRaWAN), and power line communication (PLC). Technologies that will be most effective for use in control and diagnostics systems of a drilling rig complex are proposed. The possibility of using machine learning to process a large amount of data obtained during the drilling process to optimize the controlled drilling parameters is investigated.
Volume: 15
Issue: 6
Page: 5506-5514
Publish at: 2025-12-01

Low-power and reduced delay in inverter and universal logic gates using Hvt-FinFET technology

10.11591/ijece.v15i6.pp5193-5204
Veerappa Chikkagoudar , G. Indumathi
The rapid scaling of conventional complementary metal–oxide– semiconductor (CMOS) metal–oxide–semiconductor field-effect transistors (MOSFETs) led to significantly increasing power dissipation, delay, and short channel effects (SCEs). Fin field-effect transistor (FinFET) technology is a better alternative to MOSFETs with superior electrostatic control, low power, and reduced leakage current. FinFETs have been chosen for their efficiency in overcoming these issues. This work focuses on the design of high-threshold voltage fin field-effect transistor (Hvt-FinFET) 18 nm technology-based inverter with optimized parameters and implementing universal gates NAND and NOR in Cadence Virtuoso tool. These three gates are basic building blocks for any complex digital system design. The results demonstrate significant improvement in power and reduced propagation delay in comparison with conventional CMOS technology. The Hvt-FinFET inverter obtained power dissipation and delay reduction of 13.63% and 33.33%, respectively. Power and delay optimization of 29.10% and 11.8% have been obtained in the NAND gate and 31.28% and 29.08% in the NOR gate when compared to conventional CMOS circuits. The results demonstrate significant improvements in power savings, reduced propagation delay, and superior energy efficiency, validating the effectiveness of Hvt-FinFET technology for next-generation very large scale integration (VLSI) applications.
Volume: 15
Issue: 6
Page: 5193-5204
Publish at: 2025-12-01

Design and performance analysis of an NSFET-based biosensor for the early detection of dengue

10.11591/ijece.v15i6.pp5183-5192
Tulasi Radhika Patnala , Madhavi Tatineni
Healthcare industry is changing due to technological breakthroughs that spur creative methods for diagnosing and treating illnesses. This study examines the development of nanowire-based stacked field-effect transistor (NSFET) biosensors for the early detection of dengue virus. Dengue fever is severe threat to public health and a flavivirus spread by mosquitoes. About half of the global population is at risk due to an endemic illness in tropical and subtropical regions, which affects approximately 100 million individuals annually in 130 countries. The virus has four antigenically distinct serotypes, and there may be a fifth. These serotypes induce variety of clinical symptoms. This can include benign infections that go away on their own or extremely serious, potentially fatal consequences like organ failure, plasma leakage, and bleeding. While many techniques are now used to diagnose dengue fever in the laboratory, no single technique satisfies the optimum standards for speed, economy, sensitivity, specificity. To close this gap in dengue diagnosis, newer detection technologies are desperately needed. This ultrasensitive label-free electrical device can detect the dengue virus (DENV) early on and prevent severe additional harm to humans. To detect various DENV concentrations in human blood and demonstrate potential for eventual point-of-care (POC) detection, NSFET constructed and simulated in this work.
Volume: 15
Issue: 6
Page: 5183-5192
Publish at: 2025-12-01

Impact of outlier detection techniques on time-series forecasting accuracy for multi-country energy demand prediction

10.11591/ijece.v15i6.pp5067-5079
Shreyas Karnick , Sanjay Lakshminarayanan , Madhu Palati , Prakash R
Accurate energy demand prediction is crucial for efficient grid management and resource optimization, particularly across multiple countries with varying consumption patterns. However, real-world energy demand data often contains outliers that can distort forecasting accuracy. This study evaluates the impact of five outlier detection techniques—Z-Score, density- based spatial clustering of applications with noise (DBSCAN), isolation forest (IF), local outlier factor (LOF), and one-class support vector machine (SVM)—on the performance of three time-series forecasting models: long short-term memory (LSTM) networks, convolutional neural network (CNN) Autoencoders, and LSTM with attention mechanisms. The models are tested using energy demand data from four European countries— Germany, France, Spain, and Italy—derived from real-time consumption records. A comparative analysis based on root mean squared error (RMSE) demonstrates that incorporating outlier detection significantly enhances model robustness, reducing forecasting errors caused by anomalous data. The findings emphasize the importance of selecting appropriate outlier detection strategies to improve the accuracy and reliability of energy demand forecasting. This research provides valuable insights into the trade-offs involved in outlier removal, with implications for policy and operational practices in energy management.
Volume: 15
Issue: 6
Page: 5067-5079
Publish at: 2025-12-01

SGcoSim: a co-simulation framework to explore smart grid applications

10.11591/ijece.v15i6.pp5106-5118
Abdalkarim Awad , Abdallatif Abu-Issa , Peter Bazan , Reinhard German
Under the smart grid concept, new novel applications are emerging. These applications make use of information and communication technology (ICT) to help the electrical grid run more smoothly. This paper introduces SGcoSim, a co-simulation framework that integrates power system modeling and data communication to enhance smart grid applications. The framework utilizes OpenDSS for simulating power distribution components and OMNeT++ for communication modeling, enabling real-time peer-to-peer interactions via wireless sensor network (WSN) techniques. Virtual cord protocol (VCP) is deployed for efficient routing and data management within the field area network. SGcoSim’s functionality is demonstrated through two case studies: a phasor measurement unit (PMU)-based wide-area monitoring system and an integrated volt/VAR optimization with demand response (IVVO-DR) application. Results indicate significant reductions in energy consumption and power losses, highlighting the capabilities of SGcoSim.
Volume: 15
Issue: 6
Page: 5106-5118
Publish at: 2025-12-01

Intrusion detection based on image transformations and data augmentation

10.11591/ijece.v15i6.pp5594-5603
Nada Ali Abood , Asghar A. Asgharian Sardroud
The increasing growth of users and communication networks in different platforms has led to the emergence of various types of network attacks. intrusion detection systems (IDS) are one of the important solutions to cope with these problems. An IDS determines whether incoming traffic is intrusive or normal. IDSs often achieve high efficiency with methods based on deep neural networks. However, one of the shortcomings of these methods is the lack of sufficient attention to the spatial features in the data. This research presents an intrusion detection method based on image transformations and data augmentation is presented. In the proposed method, the intrusion detection process is performed by transforming the traffic vector into an image using a convolutional neural network (CNN). Also, we use data augmentation and dimension reduction techniques to increase accuracy and reduce complexity in the proposed method. Simulation results on network security laboratory - knowledge discovery and data mining (NSL-KDD) show that the proposed IDS can classify intrusion traffic with an accuracy of 97.58%.
Volume: 15
Issue: 6
Page: 5594-5603
Publish at: 2025-12-01

A telemedicine platform empowered by 5G mobile networks for Tunisian rural places

10.11591/ijece.v15i6.pp5433-5442
Ibrahim Monia , Dadi Mohamed Bechir , Rhaimi Belgacem Chibani
A telemedicine platform needed to be developed to address the various challenges faced by patients in rural areas, such as the lack of specialist doctors, the distance to healthcare and the time spent accessing it, which can present a risk to their lives, especially for those with chronic illnesses. For its realization, we used Laravel 11, a framework that offers powerful features for building modern, high-performance applications. To enable seamless real-time communication, we integrated Laravel reverb, a robust package supporting live interactions, updates, and notifications. The database uses MySQL 8 in combination with PHP 8.2, ensuring performance, scalability, and reliability. The strengths of our systems compared with existing Tunisian platforms are real-time interaction between patient and doctor thanks to 5G, ensuring the transfer of data and access at the same time, real- time communications such as video and audio calls, live notifications and instant messaging.
Volume: 15
Issue: 6
Page: 5433-5442
Publish at: 2025-12-01

Design and implementation of a modern modulation technique for modular multilevel converters

10.11591/ijece.v15i6.pp5249-5257
Kishore Parapelly , Mahalakshmi C. , Venu Madhav Gopala
The phase opposition disposition (POD) modulation technique is a sophisticated control strategy employed in modular multilevel converters (MMCs) to achieve high-quality output waveforms with minimized harmonic distortion. POD modulation employs numerous triangular carrier signals, positioned such that carriers above the zero-reference point are in phase, while those below are 180 degrees out of phase. This unique arrangement reduces even-order harmonics and enhances the overall power quality. By comparing a common sinusoidal reference signal with these phase-opposed carriers, pulse width modulation (PWM) signals are generated to control the insertion and bypassing of sub modules within the MMC. The modular structure and balanced switching pattern of POD modulation ensure efficient thermal management and reduced electrical stress on the components, significantly improving the reliability and lifespan of the converter. The technique’s inherent scalability and flexibility make it particularly suitable for renewable energy integration, HVDC systems, and industrial motor drives. This paper explores the principles, implementation, and advantages of the POD modulation technique in enhancing the performance and efficiency of MMCs in modern power electronics.
Volume: 15
Issue: 6
Page: 5249-5257
Publish at: 2025-12-01
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