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31,456 Article Results

A convex hull based geofencing system to eradicate COVID

10.11591/ijece.v15i2.pp1817-1825
Parul Arora , Suman Deswal
The World Health Organization (WHO) has identified coronavirus disease (COVID-19), as a global pandemic due to its quick global spread to more than 183 countries. Many countries have used movement control orders (MCO) and high alert levels to halt the spread. The primary goal of this research is to provide a geofencing architecture that is specially tailored to the MCO's standard requirement for monitoring an individual's whereabouts during a lockdown. Whenever an individual tests Corona positive, Geofencing uses technology to notify an anticipated network of people who may be affected and to enable traceability for potential patients. Computational techniques such as Delaunay triangulation (inpolygon) and triangle weight characterization (inside polygon) are applied to analyze the geographical boundary in which the patient is isolated. Convex hull, on the other hand, is a better technique than computational algorithms. It is considered the best mathematical technique because it takes the least amount of time (0.014985 sec) to detect the patient within the geofence layer and has the lowest standard deviation when compared with the other computational techniques.
Volume: 15
Issue: 2
Page: 1817-1825
Publish at: 2025-04-01

Exploring university students’ engagement and motivation: critical factors

10.11591/ijere.v14i2.30300
Reham Ghanem , Hoda Abdelhameed , Mona Abdulmonem , Rawan Alfrehat , Reem Altaisan , Mona Soliman , Hager Abdel Hameed , Rania Abduljawad , Yousef Alrashed , Nahed Nasr
The study aimed to investigate the critical factors for success students' motivation and their engagement in their learning of Jordan's universities. The quantitative method was employed using a survey questionnaire as the research method to measure students' evaluation of factors. Simple sampling was used to obtain a group of university students. The questionnaire was distributed to 265 university students in Jordan. Data analysis was performed using several analyses such as descriptive analysis, Pearson correlation and regression analysis. The results of the study partially supported several factors influencing students' motivation. The results evidenced that assessment, teaching/learning strategy and students attitudes significantly influenced students learning motivation. The results of this have implications to literature, academicians and decision makers to review and discover the proper methods to invest the necessary tools that can enhance the quality of students learning in the higher education institutions.
Volume: 14
Issue: 2
Page: 1323-1330
Publish at: 2025-04-01

Enhancing spatiotemporal weather forecasting accuracy with 3D convolutional kernel through the sequence to sequence model

10.11591/ijece.v15i2.pp2022-2030
Renaldy Fredyan , Karli Eka Setiawan , Kelvin Asclepius Minor
Accurate weather forecasting is important when dealing with various sectors, such as retail, agriculture, and aviation, especially during extreme weather events like heat waves, droughts, and storms to prevent disaster impact. Traditional methods rely on complex, physics-based models to predict the Earth's stochastic systems. However, some technological advancements and the availability of extensive satellite data from beyond Earth have enhanced meteorological predictions and sent them to Earth's antennae. Deep learning models using this historical data show promise in improving forecast accuracy to enhance how models learn the data pattern. This study introduces a novel architecture, convolutional sequence to sequence (ConvSeq2Seq) network, which employs 3D convolutional neural networks (CNN) to address the challenges of spatiotemporal forecasting. Unlike recurrent neural network (RNN)--based models, which are time-consuming due to sequential processing, 3D CNNs capture spatial context more efficiently. ConvSeq2Seq overcomes the limitations of traditional CNN models by ensuring causal constraints and generating flexible length output sequences. Our experimental results demonstrate that ConvSeq2Seq outperforms traditional and modern RNN-based architectures in both prediction accuracy and time efficiency, leveraging historical meteorological data to provide a robust solution for weather forecasting applications. The proposed architecture outperforms the previous method, giving new insight when dealing with spatiotemporal with high density.
Volume: 15
Issue: 2
Page: 2022-2030
Publish at: 2025-04-01

Assessing the user experience of marker-based 3D WebAR applications using user experience questionnaire

10.11591/ijict.v14i1.pp31-41
Nooralisa Mohd Tuah , Wan Nooraishya Wan Ahmad , Ryan MacDonell Andrias , Dg. Senandong Ajor , Suaini Sura , Ahmad Rizal Ahmad Rodzuan
Marker-based 3D web-based augmented reality (WebAR) applications are an emerging field that merges web technologies with augmented reality. WebAR has gained popularity because of its ability to provide users with a reliable and autonomous platform. Yet, a limited investigation has verified its application and user perspective on its ability to function. This study is designed to evaluate the user experiences of marker-based 3D WebAR applications using the user experience questionnaire (UEQ). This study assesses various elements of the user experience, including attractiveness, clarity, engagement, efficiency, and innovation, utilizing the UEQ. This study aims to analyze user perceptions and interaction patterns thoroughly to get useful insights into the usability and user satisfaction aspects of marker-based 3D WebAR apps. The findings reveal that the WebAR app is both appealing and efficient, instilling confidence in its users. This underscores the pivotal role of user experience in shaping the effectiveness and reception of WebAR applications. This research has the potential to influence the creation of more user-focused and engaging marker-based 3D WebAR experiences, improving user engagement and immersion in web-based augmented reality environments.
Volume: 14
Issue: 1
Page: 31-41
Publish at: 2025-04-01

Vehicle side control of a wireless power transfer charger using optimized artificial neural network

10.11591/ijece.v15i2.pp1487-1498
Marouane El Ancary , Abdellah Lassioui , Hassan El Fadil , Anwar Hasni , Yassine El Asri , Zakariae El Idrissi
This paper investigates a new approach to control a wireless power transfer (WPT) charger for electric vehicles (EVs) employing an optimized artificial neural network (ANN). Enhancing the efficiency and robustness of such systems is crucial, and integrating artificial intelligence (AI)-based solutions has introduced innovative approaches in this field. The proposed method enables precise regulation of battery charging voltage even under challenging conditions, such as coil misalignment or shared grounding assemblies for multiple EVs. To assess the stability and robustness of the proposed controller, its performance was evaluated under scenarios of coil misalignment and shared grounding assemblies for EVs with varying battery voltages. The controller effectively eliminated overshoot and significantly reduced residual output voltage ripple by 4.33% compared to a conventional proportional-integral (PI) controller, demonstrating the superior performance and reliability of the ANN-based control approach.
Volume: 15
Issue: 2
Page: 1487-1498
Publish at: 2025-04-01

Teaching learning based optimization algorithm for effective analysis of power quality using dynamic voltage restorer

10.11591/ijict.v14i1.pp268-275
Soumya Ranjan Das , Surender Reddy Salkuti
In this study, the load voltage is dynamically restored utilising the dynamic voltage restorer (DVR) using the voltage injection approach. The injected voltage is generated using a voltage-source inverter (VSI), which is necessary to correct for the utility network's sag and swell characteristics voltage. The restoration process is dependent on the condition and quality of the utility system, i.e., it injects energy into the external system for the duration of voltage sag, and during voltage swell, energy is absorbed by the compensator from the external system, causing an rise in dc link voltage, which is connected across the VSI. In this study two different controllers are employed based on a learning based optimized algorithm. The simulation results are shown using two different controllers and the performance of the proposed controller is found to be a better one.
Volume: 14
Issue: 1
Page: 268-275
Publish at: 2025-04-01

A novel one-dimensional chaotic map with improved sine map dynamics

10.11591/ijece.v15i2.pp2128-2137
Mohamed Htiti , Ismail Akharraz , Abdelaziz Ahaitouf
These days, keeping information safe from people who should not have access to it is very important. Chaos maps are a critical component of encryption and security systems. The classical one-dimensional maps, such as logistic, sine, and tent, have many weaknesses. For example, these classical maps may exhibit chaotic behavior within the narrow range of the rate variable between 0 and 1and the small interval's rate variable. In recent years, several researchers have tried to overcome these problems. In this paper, we propose a new one-dimensional chaotic map that improves the sine map. We introduce an additional parameter and modify the mathematical structure to enhance the chaotic behavior and expand the interval's rate variable. We evaluate the effectiveness of our map using specific tests, including fixed points and stability analysis, Lyapunov exponent analysis, diagram bifurcation, sensitivity to initial conditions, the cobweb diagram, sample entropy and the 0-1 test.
Volume: 15
Issue: 2
Page: 2128-2137
Publish at: 2025-04-01

A ten-year bibliometric study on mathematical ability

10.11591/ijere.v14i2.30313
Meria Ultra Gusteti , Edwin Musdi , Indang Dewata , Ahmad Fauzan , I Made Arnawa , Amran Md. Rasli
Mathematical ability is a crucial aspect of modern life as it influences various fields such as economics, technology, and science. This study, spanning 2014-2023, examines articles on mathematical ability in leading journals. Using the bibliometric methods, it includes article searches in Scopus and Google Scholar via Publish or Perish (PoP), classification for bibliometric analysis, metadata checks, and bibliometric analysis using VOSviewer. The research shows a consistent trend in publications on mathematical ability, with minimal fluctuations and significant citation patterns. High-citation articles underscore the field’s importance in knowledge advancement. Key terms are ‘ability’, ‘mathematical ability’, and ‘student’, indicating research focus areas. However, limited author collaboration suggests potential for increased interdisciplinary synergy and knowledge sharing. These findings highlight opportunities for enhancing cross-disciplinary collaborations and research networks. They offer insights for policymakers, educators, and researchers in understanding trends, developing effective learning strategies, and encouraging further research in mathematical ability. In summary, this bibliometric study provides a comprehensive overview of the significance of mathematical ability in research, emphasizing the need for collaborative, innovative educational and research practices. It underscores the importance of further research to deepen understanding and application of mathematical ability, promoting an integrative approach in this essential field.
Volume: 14
Issue: 2
Page: 1273-1285
Publish at: 2025-04-01

Flipped classroom approach of language education: a systematic review

10.11591/ijere.v14i2.31718
Rohaida Mazlan , Zamri Mahamod , Khairul Azhar Jamaludin
The flipped classroom approach has emerged as an innovative pedagogical model in language education, transforming traditional teaching methods by reversing the conventional sequence of instruction and homework. The objectives of this systematic literature review are to examine the impact of various technological enhancements on the effectiveness and student engagement in flipped classrooms. Secondly, to explore the perceptions and attitudes of students and teachers towards flipped classroom methodologies across different educational contexts. Thirdly, to assess the effects of flipped classroom approaches on students’ academic performance and critical thinking skills across various disciplines. This study conducted an extensive search of scholarly articles from reputable databases such as Scopus and Web of Science, focusing on studies published from 2021 until 2024. The flow of the study is based on the PRISMA framework. The database search identified 35 final primary studies that were analyzed. The findings were divided into three themes: i) technological enhancements in flipped classrooms, which were found to significantly improve student engagement and learning outcomes; ii) student and teacher perceptions of flipped classrooms, which were generally positive, with many highlighting increased interaction and autonomy in learning; and iii) outcomes and effectiveness of flipped classroom approaches, showing a positive impact on students’ academic performance and critical thinking skills. In conclusion, the flipped classroom approach holds considerable promise for language education, offering a more effective and engaging alternative to traditional instruction. This review provides valuable insights for educators and policymakers seeking to adopt innovative teaching strategies in language education.
Volume: 14
Issue: 2
Page: 1235-1245
Publish at: 2025-04-01

Nonlinear regression analysis to predict mandibular landmarks on panoramic radiographs

10.11591/ijece.v15i2.pp2098-2108
Nur Nafiiyah , Ayu Ismi Hanifah , Edy Susanto , Eha Renwi Astuti , Chastine Fatichah , Ramadhan Hardani Putra , Agus Subhan Akbar
An automatic system for determining mandibular landmark points on panoramic radiography can reduce errors due to differences in expert professionalism and save time. Previous research has shown that the linear regression method is ineffective at predicting condyle and gonion landmark points in panoramic radiography. So, this research proposes an analysis of nonlinear regression methods (support vector machine (SVM) kernel=‘polynomial’, polynomial regression, ensemble regression) for predicting condyle and gonion landmark points. There are four predicted landmark points, namely the right condyle, left condyle, right gonion, and left gonion. The nonlinear regression methods used are SVM, polynomial regression, and ensemble regression. The Dental and Oral Hospital, within the Faculty of Dentistry at Universitas Airlangga, provides the research data. The research encompasses 119 patients between the ages of 19 and 70, dividing 103 into training and 16 into testing. The research results show that the SVM method is only good at predicting the right condyle point with a mean radial error (MRE) of 4,724 pixels. Meanwhile, to predict the left condyle, right gonion, and left gonion points, it is better to use the polynomial regression method and ensemble regression with an order of success detection rate (SDR) of 37.5%, 18.75%, and 12.5%, respectively.
Volume: 15
Issue: 2
Page: 2098-2108
Publish at: 2025-04-01

High speed space division multiplexing based integrated fiber transmission system and its impact on atmospheric conditions

10.11591/ijece.v15i2.pp1745-1753
Kakarla Phaneendra Kumar , T. Sreenivasulu Reddy
With several advantages over traditional wireless and fiber optic cables, free space optical communication is becoming more and more popular because of its high speed and bandwidth applications. In particular, the high transmission capacity of free space optics (FSO) communication systems makes them preferred, which enables them to handle the growing amount of internet traffic. Because FSO has no regulatory limitations, operates over large distances with high levels of security, and transmits data faster than radio frequency communication technologies are widely utilized. However, given different atmospheric conditions, the availability and capacity of FSO optical bands represent a major concern. For next-generation information transmission networks to satisfy end users high-capacity demands, the transmission technology known as space-division multiplexing (SDM) has become essential. Hence in this work, High speed space division multiplexing based integrated fiber/FSO transmission system and its impact on atmospheric conditions is presented. The SDM transmission system developed in this study is based on an integrated multimode fiber (MMF)/ FSO link with linear polarized (LP) spatial modes. This approach takes into consideration extreme climate conditions like snow and turbulence while evaluating performance. Utilizing bit error rate (BER) and received optical power (ROP) are the performance of FSO is evaluated in different weather conditions.
Volume: 15
Issue: 2
Page: 1745-1753
Publish at: 2025-04-01

Markov processes in Bayesian network computation

10.11591/ijece.v15i2.pp2181-2191
Assem Shayakhmetova , Nurbolat Tasbolatuly , Ardak Akhmetova , Assel Abdildayeva , Marat Shurenov , Anar Sultangaziyeva
The article examines the influence of Markov processes on computations in Bayesian networks (BN), an important area of research within probabilistic graphical models. The concept of Bayesian Markov networks (BMN) is introduced, an extension of traditional Bayesian networks with the addition of a Markov constraint, according to which the probability in a node can only depend on the state of neighboring nodes. This constraint makes the model more realistic for many practical tasks, as most graphical models that reflect real-world processes possess the Markov property. The article also discusses that Bayesian networks, in the absence of evidence, actually exhibit the Markov property. However, when evidence (additional information) is introduced into the model, challenges arise that require more complex computational methods. In response, the article proposes algorithms adapted for working with Bayesian Markov networks in the presence of evidence. These algorithms are aimed at optimizing computations and reducing computational complexity. Additionally, a comparative analysis of calculations in Bayesian networks without Markov constraints and with them is conducted, highlighting the advantages and disadvantages of each approach. Special attention is paid to the practical applications of the proposed methods and their effectiveness in various scenarios.
Volume: 15
Issue: 2
Page: 2181-2191
Publish at: 2025-04-01

Planar hexagonal patch multiple input multiple output 4x4 antenna for UWB applications

10.11591/ijict.v14i1.pp174-181
Nasrul Nasrul , Firdaus Firdaus , Nurraudya Tuz Zahra , Maulidya Rachmawati
The combination of Multiple Input Multiple Output (MIMO) antennas and Ultra-Wideband (UWB) technology offers several advantages, including reduced interference, improved isolation, and optimized dual paths. These benefits extend the range and enhance signal quality. However, designing UWB-MIMO antennas presents challenges, such as achieving low mutual coupling for high isolation and creating small-sized antennas suitable for portable devices while being effective for UWB frequencies in a MIMO configuration. The proposed antenna is a 4x4 planar MIMO antenna with a hexagon-shaped patch, a partial ground plane featuring an inverted L-stub on the left side, and a plus-shaped slot in the centre ground. It has dimensions of 32 x 32 x 1.6 mm³ and is capable of achieving a wide bandwidth of 3-12.5 GHz. The antenna's performance measurements are impressive: return loss below -10 dB at frequencies of 3-12.5 GHz, mutual coupling below -16.5 dB, Envelope Correlation Coefficient (ECC) bellow 0.005, Diversity gain of more than 9.97, Total Active Reflection Coefficient (TARC) below -10 dB. Based on these results, the proposed antenna offers excellent performance for UWB applications, featuring high efficiency, minimal interference between antenna elements, and optimal diversity performance.
Volume: 14
Issue: 1
Page: 174-181
Publish at: 2025-04-01

Novel features extraction: pigment epithelial detachment detection using machine learning algorithms

10.11591/ijece.v15i2.pp1572-1583
Sheeba Thankappan Mercy , Albert Antony Raj Saminathan , Anand Murugadhas , Anshy Princella Anand Sheeba
The majority of the retinal diseases have visual symptoms. Any area of the retina, a delicate layer of tissue on the interior the posterior wall of the human eye, can be impacted by retinal disorders. Optical coherence tomography (OCT) is the utmost commonly used imaging procedure for diagnosing retinal disorders such as age-related macular degeneration (ARMD), diabetic retinopathy, pigment epithelial detachment (PED), macular holes, and more. In this study, we put forth a brand-new technique for accurately extracting features from OCT images to identify PED diseases. For the preprocessing step, we examined the wiener filtering method. After that, we segmented the retinal pigment epithelium (RPE) layer used to the thresholding method, extracted the features from the RPE layer, and then gave the features to machine learning (ML) classifiers like the support vector machine (SVM), logistic regression (LR), k-nearest neighbors (KNN), decision tree (DT), random forest (RF), naive Bayes (NB), and artificial neural network (ANN). The total dataset about 200 images among 100 is normal and 100 is PED, we trained the dataset as an unbalanced and balanced group. The RF is the best outcome in comparison of other classifiers. The overall outcome of random forest is 100% accuracy.
Volume: 15
Issue: 2
Page: 1572-1583
Publish at: 2025-04-01

The integration of discrete contourlet transform in OFDM framework for future wireless communication

10.11591/ijict.v14i1.pp182-194
Mohamed Hussien Mohamed Nerma , Adam Mohamed Ahmed Abdo
In the upcoming era, the forthcoming sixth-generation (6G) wireless communication network will demand highly efficient technology to support extensive capacity, ultra-high speeds, low latency, scalability, and adaptability. While the current fifth-generation (5G) wireless communication system relies on OFDM technology, the evolution towards a beyond 5G wireless communication system necessitates a new OFDM framework. This study introduces a novel OFDM system that integrates the discrete Contourlet transform. A comparative analysis has been conducted among the proposed system, conventional OFDM, and curvelet-based OFDM systems. The results indicate that the proposed system offers improvements in bit error rate (BER), reduced computational complexity, decreased peak-to-average power ratio (PAPR), and enhanced power spectrum density (PSD) when contrasted with both the traditional and curvelet-based systems.
Volume: 14
Issue: 1
Page: 182-194
Publish at: 2025-04-01
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