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28,428 Article Results

Household electric monitoring IoT system

10.11591/ijeecs.v40.i1.pp85-92
Joemar Corpuz , Kristine Joy S. Dela Cruz , Joan B. Palomar , Jackielyn Tamayo , Hohn Lois C. Bongao , Mark Joseph B. Enojas , Jane E. Morgado
In dense areas in the Philippines, there are recorded cases of power theft or known to be illegally tapping power lines from another household which results to complaints because of increased electricity bills. To address the power theft problems, this work uses internet of things system for household electric monitoring and control. A transmitter and receiver set up is designed to monitor the energy consumption at both ends. When there is discrepancy with the meter reading, an alert system sends notification that there is an illegal wiretapping. The load is monitored through electric meters and the powers measured are compared. These data are being sent wirelessly through a GSM module. The meter readings for both the transmitter and receiver can be viewed in a mobile phone through a web app developed. A minimum of 3W difference between the transmitter and the receiver will mean a discrepancy and notifies illegal wiretapping. Illegal connections are cutoff when an incident of tapping occurs. Based on the results of the test, the household electricity monitoring system through internet of things (IoT) is found to be 100% reliable in detecting and cutting off illegal connections. Additionally, the system is able to compute the monthly power consumption.
Volume: 40
Issue: 1
Page: 85-92
Publish at: 2025-10-01

Distributed formation control with obstacle and collision avoidance for humanoid robot

10.11591/ijeecs.v40.i1.pp108-117
Faisal Wahab , Bambang Riyanto Trilaksnono
Formation control has become a popular research topic in recent years. A common challenge in formation control is ensuring that robots can avoid obstacles and maintain a safe distance from one another to prevent collisions while forming a formation. In this research, a distributed formation control approach for a multi-robot system (MRS) with obstacle and collision avoidance is presented. The distributed formation control architecture is based on a consensus algorithm and consists of four layers: consensus tracking, consensus-based formation control, behavior, and physical robot layers. The system was implemented and evaluated through both simulations and experiments. Humanoid robots were used as the platform for these implementations. The result of the simulations and experiments show that the distributed formation control system successfully guided the robots into desired formation while also avoiding obstacles and preventing collisions with other robots.
Volume: 40
Issue: 1
Page: 108-117
Publish at: 2025-10-01

Alzheimer’s disease stage prediction using a novel transfer learning-Alzheimer’s network architecture

10.11591/ijeecs.v40.i1.pp518-529
Pothala Ramya , Chappa Ramesh , Odugu Srinivasa Rao
The root cause of Alzheimer’s disease (AD) is unknown except for a very tiny number of family instances caused by a genetic mutation. A thorough examination of particular brain disorders’ tissues is necessary to correctly identify the circumstances using scans of magnetic resonance imaging (MRI), and specific non-brain tissues, like the neck, skin, muscle, and fat, make further investigation challenging and can be seen in MRI scans. This work aims to use the FSL-BET skull stripping tool to remove non-brain tissues and extract the significant region of the brain- deep learning (DL) techniques rather than machine learning (ML) models helpful in classification and predictions. The most frequent issue with DL models is which needs a lot of training data, causes to problems with class imbalance. To avoid imbalance issues, we used data augmentation to ensure that the samples were distributed equally among the classes. A novel transfer learning Alzheimer’s disease network (TL-AzNet) based visual geometry group-19 (VGG19) technique was developed in this study. Conducted a comparison study using the base and suggested models, comparing over data with oversampling versus non-oversampling. The novel model predicted AD with a 95% accuracy rate.
Volume: 40
Issue: 1
Page: 518-529
Publish at: 2025-10-01

Implementation of a secure system for calculating and supervising the energy consumption of electrical equipment

10.11591/ijeecs.v40.i1.pp127-136
Jarmouni Ezzitouni , Ahmed Mouhsen , Mohamed Lamhamdi , Ennajih Elmehdi , En-Naoui Ilias , Bousbaa Mohamed
With the advent of smart grids and the growing challenges associated with the production and consumption of electrical energy, it is crucial to deploy reliable systems to monitor production and consumption, as well as to improve energy efficiency. To ensure optimal decision-making in energy management and control systems, it is essential to have both efficient measurement systems for data collection and acquisition and secure information exchange. These elements are fundamental to ensuring the smooth operation of energy systems and enabling precise supervision of energy flows, thus contributing to more efficient use of available electrical resources. This article focuses on the implementation of a complete electrical energy calculation and management system for energy consumers. To achieve this, devices such as integrated digital control units and current and voltage sensors are used. The system architecture guarantees precise measurement and calculation of electrical energy and other important parameters, such as power factor in the case of inductive and capacitive loads, which have an effect on reactive energy. The data collected is stored in a secure database.
Volume: 40
Issue: 1
Page: 127-136
Publish at: 2025-10-01

Optimizing distance vector-hop localization in wireless sensor networks using the grasshopper optimization algorithm

10.11591/ijeecs.v40.i1.pp461-479
Janani Selvaraj , Hymlin Rose Sasijohn Gloryrajabai , Sivarathinabala Mariappan , Backia Abinaya Antony Samy , Sudhakar Kalairishi
In scenarios involving mobile sensors within distributed sensor systems, such as those often encountered in wireless sensor networks (WSNs) or the internet of things (IoT), the ability to ascertain the origin of sensor data holds significant importance. Range-free Monte Carlo Localization methods offer an energy-efficient solution that eliminates the need for extra hardware, as they solely rely on the radio hardware already present on sensor nodes. But there are certain disadvantages when implemented, as it occupies more amount of power and some inaccuracies might happen in accessing the data from the sensor node. In this paper, we suggest the grasshopper optimization algorithm (GOA) strategy, which incorporates the distance-vector hop (DVHop) and three-anchor methods. It displays its usefulness in terms of both overall localization accuracy and resistance to hostile attacks or malfunctioning nodes. Nonetheless, the incorporation of dead reckoning based on motion sensor data significantly enhances the precision of location estimates and bolsters the network's robustness against both faulty components and malicious agents.
Volume: 40
Issue: 1
Page: 461-479
Publish at: 2025-10-01

Analysis and evaluation about the dimmable light affect positioning-based MISO visible light communication

10.11591/ijeecs.v40.i1.pp181-188
Trang Nguyen , Dat Vuong
Visible light communication (VLC) is a new on-trend communication technology which offers high-speed data rate, great deployment potential in indoor enviroment. In VLC scenario, the positioning based on visible light communication (VLCP) has become one of interesting application of researchers. Most of existing proposed VLCP algorithms focused on mathematical analysis of multi-dimensional perspective based on the received signal strength (RSS) to enhance the accuracy without the consideration of dimming. However, regarding to physical characteristics of VLC devices and requirement of illumination, the light is increasingly dimmable along the time which leads to decrease transmitted optical power of LED as well as RSS received at the photodetector (PD)). Inspired by the above-mentioned constraints, this paper proposed the mathematical model to analyses the effect of dimming capability on the state-of-art RSS based positioning algorithms. Evaluation of the proposed model based on the metrics of RSS and position error (PE) is conducted on Matlab.
Volume: 40
Issue: 1
Page: 181-188
Publish at: 2025-10-01

Substrate thickness variation on the frequency response of microstrip antenna for mm-wave application

10.12928/telkomnika.v23i5.26731
Bello Abdullahi; Universiti Sains Malaysia Muhammad , Mohd Fadzil; Universiti Sains Malaysia Ain , Mohd Nazri; Universiti Sains Malaysia Mahmud , Mohd Zamir; Universiti Sains Malaysia Pakhuruddin , Ahmadu; Universiti Sains Malaysia Girgiri , Mohamad Faiz Mohamed; Collaborative Microelectronic Design Excellence Center (CEDEC) Omar
Substrate height (Hs) is an important parameter that influences antenna propagation. This research designed a low-profile 28 GHz microstrip antenna on a polyimide substrate with varying Hs using CST Studio software. The simulated results and MINITAB software were used to develop regression model equations, which analyzed the impact of Hs variation on the antenna performance. The proposed models’ equations have indicated an increase in average responses of resonant frequency (Fr), percentage bandwidth (% BW), gain (G), return loss (RL), and efficiency (ƞ) as the Hs decreased. The antenna achieved a BW of 3.87 GHz at Hs 0.525 mm and 5.54 GHz at 0.025 mm, a G of 3.89 dBi at Hs 0.525 mm and 3.91 dBi at Hs 0.025 mm, and an ƞ of 94.19% at Hs 0.525 mm and 98.24% at Hs 0.025 mm. The antenna was fabricated and tested, and the experimental results were validated with the models’ equations. The thinner substrate resulted in an improvement in the antenna performance.
Volume: 23
Issue: 5
Page: 1188-1200
Publish at: 2025-10-01

Optimizing nonlinear autoregressive with exogenous inputs network architecture for agarwood oil quality assessment

10.11591/ijai.v14.i5.pp3493-3502
Muhammad Ikhsan Roslan , Noor Aida Syakira Ahmad Sabri , Nur Athirah Syafiqah Noramli , Nurlaila Ismail , Zakiah Mohd Yusoff , Ali Abd Almisreb , Saiful Nizam Tajuddin , Mohd Nasir Taib
Agarwood oil is highly valued in perfumes, incense, and traditional medicine. However, the lack of standardized grading methods poses challenges for consistent quality assessment. This study proposes a data-driven classification approach using the nonlinear autoregressive with exogenous inputs (NARX) model, implemented in MATLAB R2020a with the Levenberg-Marquardt (LM) algorithm. The dataset, sourced from the Universiti Malaysia Pahang Al-Sultan Abdullah under the Bio Aromatic Research Centre of Excellence (BARCE) and Forest Research Institute Malaysia (FRIM), comprises chemical compound data used for model training and validation. To optimize model performance, the number of hidden neurons is systematically adjusted. Model evaluation uses performance metrics such as mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), coefficient of determination (R²), epochs, accuracy, and model validation. Results show that the NARX model effectively classifies agarwood oil into four quality grades which is high, medium-high, medium-low, and low. The best performance is achieved with three hidden neurons, offering a balance between accuracy and computational efficiency. This work demonstrates the potential of automated, standardized agarwood oil quality grading. Future research should explore alternative training algorithms and larger datasets to further enhance model robustness and generalizability.
Volume: 14
Issue: 5
Page: 3493-3502
Publish at: 2025-10-01

Heart disease prediction optimization using metaheuristic algorithms

10.11591/ijai.v14.i5.pp4332-4341
Zaid Nouna , Hamid Bouyghf , Mohammed Nahid , Issa Sabiri
This study explores metaheuristics hyperparameter tuning effectiveness in machine learning models for heart disease prediction. The optimized models are k-nearest neighbors (KNN) and support vector machines (SVM) using metaheuristics to identify configurations that minimize prediction error. Even though the main focus is utilizing metaheuristics to efficiently navigate the hyperparameter search space and determine optimal setting, a pre-processing and feature selection phase precedes the training phase to ensure data quality. Convergence curves and boxplots visualize the optimization process and the impact of tuning on model performance using three different metaheuristics, where an error of 0.1188 is reached. This research contributes to the field by demonstrating the potential of metaheuristics for improving heart disease prediction performance through optimized machine learning models.
Volume: 14
Issue: 5
Page: 4332-4341
Publish at: 2025-10-01

Job performance of human resource management graduates from the employers’ and graduates’ perspectives

10.11591/ijere.v14i5.31959
Dahlee Sadang-Pascua , Jennifer Montenegro-Villanueva
Graduates’ job performance reflects their academic orientation in pursuit of their degrees. Thus, academic institutions should prepare students to be competitive, match the needs of the industry, and become worthy of employment after graduation. This research determines the job performance of human resource management (HRM) graduates in terms of their job competencies, career skills, and team performance from the perception of the graduates and their employers. A quantitative research method with statistical tools such as frequency, percentage, weighted mean, and Mann-Whitney U Test was used. Findings revealed a significant difference in the respondents’ perception, specifically in conveying ideas, use of IT, values, quality work, communication skills, human relations, technical, research, leadership skills, and team performance. The result also shows that graduates perceived themselves as excellent performers, which is in contrast to their employers’ perceptions of them as good performers only regarding their job competencies, career skills, and team performance. The differences in perceptions of the performance of the graduates depicts a mismatch between the academe and the industry requirements that result in a recommendation of thorough review and revision of the HRM curriculum, the teaching methodology, and the strategy of the academic institutions to meet the needs of the industry.
Volume: 14
Issue: 5
Page: 3756-3764
Publish at: 2025-10-01

Enhancing learning outcomes through course redesign using self-assessment and inquiry models

10.11591/ijere.v14i5.32215
Fredy Martinez , César Hernández , Diego Giral
This study addresses the challenge of enhancing learning outcomes in propaedeutic education by redesigning an undergraduate deep learning course. To achieve this, the self-assessment and quality model (SQM) was combined with the community of inquiry (CoI) framework, which emphasizes cognitive, social, and teaching presence in online education. The redesigned course aligns with the guidelines of the Colombian Ministry of National Education and incorporates continuous feedback from students. Initial implementation led to improved student performance but revealed gaps in perceived learning experiences. Iterative adjustments were made to the course design based on CoI survey results, particularly focusing on increasing teacher involvement. The findings demonstrate that integrating SQM with a responsive, design-based approach can significantly improve learning outcomes and student satisfaction. This study highlights the importance of dynamic course design in higher education and offers a replicable model for other institutions.
Volume: 14
Issue: 5
Page: 3838-3845
Publish at: 2025-10-01

The educational accomplishments scale: development and validation in the context of education institutions

10.11591/ijere.v14i5.34224
Anil DCosta , Joseph Chacko Chennattuserry , Kennedy Andrew Thomas
Educational institutions play a significant role in fostering academic growth and personal development. However, there is a lack of standardized tools to assess the impact of educational accomplishments (EA), particularly integrating dimensions such as quality, value-based, integrated, and culture-enhanced education. This paper aims to create and validate a measurement tool that assesses how EA impacts students and institutions to foster academic growth, personal development, and institutional effectiveness, contributing to the overall quality of education. The data was collected from 120 participants, including religious heads, directors, principals, and coordinators of ten schools run by a specific religious congregation. The study implemented a three-stage systematic procedure in the development of the scale. Stage one consisted of item generation, literature review, and expert judgment. The second stage validated the scale and was followed by an item analysis, principal component with varimax rotation (exploratory factor analysis) using Kaiser normalization on IBM SPSS 26. The third step resulted in the final reliability and validity of the scale. A final 19-item educational accomplishments scale (EAS) is psychometrically reliable and of potential use to policymakers globally, comparing student and teacher perceptions, especially with religious congregational affiliations. This scale can particularly be used by each institution to evaluate the EA and can also be used by other researchers for further research.
Volume: 14
Issue: 5
Page: 3882-3890
Publish at: 2025-10-01

Leadership and management in early childhood: navigating contradictions and pedagogical practices to foster inclusivity

10.11591/ijere.v14i5.33061
Manoharan Nalliah , Shorouk Aboudahr , Lim Wei Huan , Esayas Teshome Taddese
Early years’ education is an important foundation for a child’s life-long learning, and leaders and managers in early childhood work settings have an important role in creating a nurturing environment that supports and enables children to learn regardless of their needs. This study investigates the challenges and contradictions leaders and managers face in early childhood education (ECE) settings. It examines how pedagogical praxis can be leveraged to foster inclusivity focusing on the tension between the intrinsic value of play and the pressure of child performativity meeting performance benchmarks. This qualitative study offers a constructive discussion on leadership practices in ECE and inclusion in Malaysia. The thematic analysis of nine interviews analyzed by N-VIVO software and showed the important considerations for enhancing leadership and management approaches, creating more inclusive spaces, and supporting the holistic development of early childhood curricula. The result offers a rich description of how leading practices are increasingly influenced by dominant trends in educational policies and society, including neoliberal agendas and narrowly conceived accountability systems that focus on measurable outcomes. It underlines the centrality of supporting the ongoing professional development of educators.
Volume: 14
Issue: 5
Page: 3765-3773
Publish at: 2025-10-01

Integrating project-based learning for enhancing higher education within an outcome-based education framework

10.11591/ijere.v14i5.31957
Radhika Bhagwat , Anagha Kulkarni
Project-based learning (PBL) has emerged as a powerful pedagogical approach within the outcome-based education (OBE) framework that is designed to align educational outcomes with the evolving demands of the 21st century. This research investigates the integration of PBL into an engineering course and focuses on its impact on the overall development of the students. Project-based approach was adapted in the artificial intelligence (AI) course, where 56 and 58 students applied AI concepts to real-world challenges in academic year 21-22 and 22-23, respectively. A structured PBL framework was implemented, systematically dividing the project into stages ensuring progressive learning. Feedback and statistical analysis, including a paired t-test, were conducted to evaluate students’ academic and interpersonal skill improvements. The statistical analysis proved a remarkable improvement in the course assessment marks. Students demonstrated improved problem-solving ability, algorithmic thinking and expertise in AI techniques. The findings exhibited enhanced communication skills, effective presentations, articulation of ideas and peer collaboration. These outcomes indicate the significance of PBL on the holistic development of higher education students, within technical disciplines by equipping students with the necessary skills, mindset, and experience to excel in their professional practice. PBL provides a comprehensive assessment of student’s abilities and fosters collaboration with industry partners thus strengthening ties between academia and industry.
Volume: 14
Issue: 5
Page: 4099-4108
Publish at: 2025-10-01

Applications of satellite information for rainwater estimation and usage: a comprehensive review

10.11591/ijece.v15i5.pp4671-4681
Laura Valeria Avendaño-García , Yeison Alberto Garcés-Gómez
Global climate change introduces significant uncertainty in water resource availability, making precipitation studies essential for societal sustainability. Satellite precipitation products (SPPs) have emerged as a vital alternative and complement to traditional meteorological station data for hydrological and climate research. This review examines scientific literature on SPP applications for daily, monthly, and annual rainfall estimations globally. Eleven widely used SPPs were identified, with the tropical rainfall measuring mission (TRMM) and climate hazards group infrared precipitation with station data (CHIRPS) standing out due to their frequent usage, high resolution, and extensive data records. A growing trend in research utilizes SPPs for hydrological studies and validates their estimates by contrasting satellite information with ground station measurements using continuous and categorical statistics. TRMM and CHIRPS, in particular, show precipitation accuracies closer to station data, influenced by local topography and climatology. Furthermore, SPP data, combined with geographic information systems (GIS), proves useful for identifying potential rainwater harvesting sites, offering an alternative information source to address water availability crises in drought-prone areas.
Volume: 15
Issue: 5
Page: 4671-4681
Publish at: 2025-10-01
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