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23,598 Article Results

A novel distributed generation integrated MFUPQC for active-power regulation with enhanced power quality features

10.11591/ijeecs.v36.i1.pp26-40
Moturu Seshu , Kalyana Sundaram , Maddukuri Venkata Ramesh
The distributed generation (DG) scheme has become significant and advanced energy generation corridor for present power distribution system. This advanced DG scheme offers several merits such as flexible active power transfer, low transmission losses, maximize power efficiency, reduce transmission cost, expanding grid capacity, so on. It is motivated that, integration of such DG system in to multi-parallel feeder distribution system with enhanced power-quality features is considered as major problem statement. The proposed multi-functional unified power-quality conditioner (MFUPQC) device has robust design, reliable performance; specifically for addressing the voltage-current affecting PQ issues, regulation of active-power in multi-parallel distribution system. The fundamental goal of the MFUPQC device has been to operate as both a PQ improvement device and a DG integration device by implementing a new universal fundamental vector reference (UFVR) control algorithm. The suggested innovative control algorithm extracts the fundamental voltage and current reference signals with low computational response delay, simple mathematical formulations and without additional transformations which are also major problems identified in classical control schemes. This work focuses on design, operation and performance of MFUPQC device has been evaluated in both PQ and DG operations in a multi-parallel feeder distribution system through MATLAB/Simulink computing platform. The simulation results are illustrated with possible interpretation and analysis.
Volume: 36
Issue: 1
Page: 26-40
Publish at: 2024-10-01

Development of diagnostic competencies of educational psychologist in professional training

10.11591/ijere.v13i5.29522
Ryszhamal Aralbaeva , Khapiza Naubaeva , Nurlan Abishev , Zhumagul Taszhurekova , Zhadra Zhexembayeva
In the era of globalization, enhancing the development of diagnostic competencies among educational psychologists in Kazakhstan is a crucial aspect of improving higher education quality. The purpose of the study is to substantiate and implement the methodology for the development of diagnostic competencies of future educational psychologists in higher educational institutions of Kazakhstan as a guarantee of their readiness to carry out professional activities. The methodological approach involves developing methods for fostering diagnostic competencies, employing empirical techniques such as comparison, systematization, classification, and generalization of theoretical data, conducting surveys, testing, and modeling training methods for future educational psychologists. An experimental study conducted on the premises of Zhetysu University named after I. Zhansugurov has developed methodological tools to increase the readiness of future educational psychologists for the development of diagnostic competencies in professional training, namely: the implementation of readiness components with selected methods for their formation. After conducting an experimental study, promising areas for improving the methodology of readiness of future educational psychologists for the development of diagnostic competencies in Kazakhstan were established.
Volume: 13
Issue: 5
Page: 3393-3401
Publish at: 2024-10-01

Video explainer, e-module, or both: which is better to improve statistics performance of graduate students?

10.11591/ijere.v13i5.28945
Roberto G. Sagge Jr , Salvador P. Bacio Jr
Technology is an essential component of modern education, and teachers use various types of technology to improve classroom performance. Meanwhile, statistics is one of the seemingly difficult courses according to students across levels. This study experimental aimed to determine if video explainer and e-module improve students’ performance in statistics. There were 78 graduate school students participated and used video explainer, e-module, or both as an intervention. A 100-item performance test in statistics was used. The statistical techniques employed were mean, standard deviation and analysis of covariance (ANCOVA). Results revealed that students’ pre-test performance was “average”. Additionally, their posttest performance was “high”, regardless of the intervention utilized. Significant differences emerged between groups who utilized both video explainer and e-module and those who used simply video explainer or e-module. Video explainer and e-modules should be integrated carefully into the instruction, helping graduate students develop a solid understanding of statistics. The results of the study suggest that studying statistics is more successful when one uses these interventions because it integrates visuals, audio, real-world applications, accessibility and flexibility towards various learning styles. Learning stakeholders should cooperate to ensure seamless integration of these materials into the curriculum and provide ample support to educators in generating and managing content.Technology is an essential component of modern education, and teachers use various types of technology to improve classroom performance. Meanwhile, statistics is one of the seemingly difficult courses according to students across levels. This study experimental aimed to determine if video explainer and e-module improve students’ performance in statistics. There were 78 graduate school students participated and used video explainer, e-module, or both as an intervention. A 100-item performance test in statistics was used. The statistical techniques employed were mean, standard deviation and analysis of covariance (ANCOVA). Results revealed that students’ pre-test performance was “average”. Additionally, their posttest performance was “high”, regardless of the intervention utilized. Significant differences emerged between groups who utilized both video explainer and e-module and those who used simply video explainer or e-module. Video explainer and e-modules should be integrated carefully into the instruction, helping graduate students develop a solid understanding of statistics. The results of the study suggest that studying statistics is more successful when one uses these interventions because it integrates visuals, audio, real-world applications, accessibility and flexibility towards various learning styles. Learning stakeholders should cooperate to ensure seamless integration of these materials into the curriculum and provide ample support to educators in generating and managing content.
Volume: 13
Issue: 5
Page: 3194-3201
Publish at: 2024-10-01

Moroccan pre-service elementary teachers: attitudes toward STEM education and mobile devices

10.11591/ijere.v13i5.28205
Aziz Amaaz , Abderrahman Mouradi , Moahamed Erradi , Ali Allouch
The purpose of this study was to explore Moroccan pre-service elementary teachers' attitudes toward integrated science, technology, engineering, and mathematics (STEM) education and the use of mobile devices in integrated STEM education. The research sample was selected using convenience sampling. Data were collected from 226 pre-service teachers in the Bachelor of Education Elementary Specialty (BEES) using a 28-item questionnaire. The validity of the items was tested by factor analysis using the extraction method of principal component analysis with varimax rotation. Reliability tests for the different constructs were conducted by calculating Cronbach's alpha. Frequency, mean, standard deviation and Mann-Whitney tests were used to analyze the data. The results revealed that pre-service elementary teachers have generally neutral attitudes toward integrated STEM education, and they also showed that pre-service teachers' attitudes toward integrated STEM education do not depend on gender or grade level. However, these attitudes are dependent on pre-university studies. Pre-service teachers with a scientific background have significantly more positive attitudes toward integrated STEM education than their counterparts with a literary background. Furthermore, the results of this study also revealed that pre-service teachers have positive attitudes toward the use of mobile devices in integrated STEM education, and these attitudes are not dependent on gender, grade level, or pre-university studies.
Volume: 13
Issue: 5
Page: 3270-3283
Publish at: 2024-10-01

Career-focused teaching and its effects on students’ biology-technical-vocational-fused skills

10.11591/ijere.v13i5.29131
Joelash R. Honra , Sheryl Lyn C. Monterola , Rosanelia T. Yangco
The K to 12 program in the Philippines, initiated in 2012, brought about challenges like job mismatch among senior high school (SHS) graduates. Addressing this issue requires integrating technical-vocational-livelihood (TVL) skills with core subject skills, particularly in biology. This study explores how the career-focused teaching approach (CFTA) nurtures biology-technical-vocational-fused skills (BTVFS). Using a pretest-posttest quasi-experimental design, two grade 11 classes (35 students each) participated-one exposed to CFTA and the other to conventional teaching. Quantitative data from a researcher-made BTVFS questionnaire were analyzed with an independent samples t-test, revealing significant differences in all BTVFS subcomponents; t(68)=3.670, p<0.036. Qualitative data from reflective journals aligned with BTVFS subskills (metacognition, communication, problem-solving, and collaboration). CFTA proved instrumental in enhancing the BTVFS of students, emphasizing its importance in the curriculum across SHS core subjects to mitigate job mismatch for K to 12 graduates.
Volume: 13
Issue: 5
Page: 3427-3434
Publish at: 2024-10-01

Factors that influence global literacy: what is the most dominant?

10.11591/ijere.v13i5.28903
Anggi Tias Pratama , Ahmad Kamal Sudrajat , Rizqa Devi Anazifa , Atik Kurniawati
Global literacy is a crucial ability to maintain the world’s peace. Several studies show that demographic factors influence the development of a person’s competence. However, the influence of demographic factors on global literacy has not yet been explored, especially in high school students. This research was conducted to determine the factors that most influence students’ global literacy in biology learning. The factors used in this research are gender, school profile (public or private school), and interest in learning biology. This study used a cross-sectional survey design with 2,759 students participating. Students’ global literacy was analyzed from a questionnaire of four aspects: exploration, communication, using the internet, and act for society. This study found that all the proposed factors influence students’ global literacy, but the factor that has the most dominant influence is the school profile. This research provides a new view regarding the influence of demographic factors on students’ global literacy. The government and related parties can use these results to design effective learning innovations to develop students’ global literacy.
Volume: 13
Issue: 5
Page: 2989-2995
Publish at: 2024-10-01

Mechatronic system to classify plastic and metal bottles using capacitive and inductive sensors

10.11591/ijece.v14i5.pp4970-4976
Napoly Melo , Abigail Sanchez Gonzales , Ernesto Paiva-Peredo
The problem addressed in this article focuses on the management of plastic waste, which has experienced a significant increase in recent years, posing challenges in its management and recycling. In addition, the concentration of microplastics in water and their impact on health and the food chain is highlighted. The proposed solution consists of developing a mechatronic system for sorting plastic and metal bottles using capacitive and inductive sensors, respectively. The system demonstrated efficiency in tests, achieving 100% sorting for plastic and metal bottles. The need for bottles to be properly positioned for optimal performance was identified. This work highlights the importance of automation in mechatronic systems and the effectiveness of capacitive and inductive sensors in sorting materials.
Volume: 14
Issue: 5
Page: 4970-4976
Publish at: 2024-10-01

Model predictive control with finite constant set for five-level neutral-point clamped inverter fed interior permanent magnet synchronous motor drive of electric vehicle

10.11591/ijece.v14i5.pp5038-5047
Tran Hung Cuong , An Thi Hoai Thu Anh
This paper uses the five-level neutral-point clamped (NPC) inverter to feed an electric vehicle's traction motor-interior permanent magnet synchronous motor (IPMSM). The model predictive control method controls the energy conversion process according to the model with two prediction steps. The advantage of this method is its fast response, which increases the ability to operate the converter with good voltage quality. Model predictive control (MPC) control is a closed-loop strategy with much potential when integrating multiple control objectives; the calculation process is compact without complex modulation. Within the scope of this article, the MPC strategy will be implemented with two control goals for NPC, including output load current and capacitor voltage balance with low switching frequency. The simulation results on MATLAB/Simulink software were performed to verify the proposed algorithm's effectiveness in minimizing the grid current's harmonics and ensuring an uninterrupted power supply.
Volume: 14
Issue: 5
Page: 5038-5047
Publish at: 2024-10-01

Detection and classification of breast cancer types using VGG16 and ResNet50 deep learning techniques

10.11591/ijece.v14i5.pp5481-5488
Ashwini P. , Suguna N. , Vadivelan N.
Breast cancer has become a major worldwide health issue, accounting for a large portion of the mortality rate among women. As a result, the need for early detection techniques to enhance prognosis is increasing. Many techniques are being used to detect breast cancer early, and treatment outcomes are frequently favorable when the disease is detected early. Mammography is a commonly used and very successful method for identifying breast cancer among these modalities. Through additional image processing operations like resizing and normalizing, this technology allows the detection of malignant spots from mammography pictures of the affected area. The goal of our research is to improve breast cancer detection and diagnosis speed and accuracy. In this study, we investigate the use of deep learning methods, particularly the visual geometry group (VGG16) and ResNet50 models, for mammography-based breast cancer detection. We assess the performance of the VGG16 and ResNet50 models by training and testing on a mammogram dataset that consists of 322 images from the mammographic image analysis society (MIAS) dataset. The suggested models aim to classify these images into normal, benign, and malignant groupings. Our results show better performance when compared to existing approaches. The proposed methods VGG16 and ResNet50 show promising results, achieving a classification accuracy of 91.23% and 99.01% respectively.
Volume: 14
Issue: 5
Page: 5481-5488
Publish at: 2024-10-01

Solar-based aerator with water quality monitoring in vannamei shrimp pond

10.11591/ijece.v14i5.pp5048-5054
I Putu Eka Widya Pratama , Friska Aprilia Kusuma , Safira Firdaus Mujiyanti , Romana Schirhagl , Tepy Lindia Nanta
The water quality is vital for the vannamei shrimp pond's productivity. Manual monitoring at Gunung Anyar's vannamei shrimp pond is time-consuming, ineffective, and potentially harmful. In this research, we developed a real-time monitoring system for the water quality of the vannamei shrimp pond. This monitoring system is integrated with a solar-based aerator. To address this, water quality monitoring in a solar-based aerator system tracks the degree of acidity (pH), temperature, and total dissolved solids (TDS) remotely using a website and real-time mobile phone Android application with 98.57% accuracy and 1.43% error. Seven days of data revealed the degree of acidity between 6.92 and 7.34 is indicated poor conditions of the pond While the temperatures from 23.59 °C to 38.32 °C, and TDS from 628.65 to 652.34 ppm indicate the good condition of the shrimp pond. This real-time monitoring system can help vannamei shrimp farmers monitor the actual conditions of their ponds.
Volume: 14
Issue: 5
Page: 5048-5054
Publish at: 2024-10-01

Effect of Na-EDTA on electrical characteristics NaCl electrolyte battery charging solar panels

10.11591/ijece.v14i5.pp4846-4855
Dina Maizana , Moranain Mungkin , Habib Satria , Syafii Syafii , Muhammad Fadlan Siregar
This research investigates the problem of Cu-Zn electrode batteries with NaCl electrolyte. Previous studies have indicated problems with the electrolyte and electrodes after charging, such as turbidity and deposits in the electrolyte, as well as corrosion on the electrodes. Consequently, the battery can only be used once due to a decline in its electrical characteristics after the initial charging. Through this research, improvements were made to the electrical characteristics of the battery by adding Na-EDTA to enhance usage efficiency. The research method involved mixing NaCl solution with the highest electrical conductivity, using six pairs of Cu-Zn electrodes arranged in series. The physical conditions of the electrolyte and electrodes were observed, and electrical characteristics were measured. The research results indicate that the use of NaCl+Na-EDTA electrolyte produces a battery voltage of 4.20 volts with a current of 2 Ah and can be used twice. Charging with solar panels can be done in 1 hour, but the frequency is limited to two times.
Volume: 14
Issue: 5
Page: 4846-4855
Publish at: 2024-10-01

Detection of elements of personal safety for the prevention of accidents at work with convolutional neural networks

10.11591/ijece.v14i5.pp5824-5833
Maria Claudia Bonfante , Ivan Hernandez , Juan Contreras Montes , Eugenia Arrieta Rodríguez , Alejandro Cama-Pinto
The task of recognizing personal protective elements in workplace environments in real time is fundamental to protecting the employees in case of any accidents. This can be achieved by deploying a convolutional neural network (CNN) algorithm that can efficiently detect protective elements through surveillance devices. Therefore, this work proposes the construction of a model, implementing the you only look once (YOLO) detector, whose architecture has been one of the most tested according to literature review. YOLOv5 and YOLOv7 versions were used and a dataset of 2,000 images for four classes considered. This dataset was collection from various sources and labelled by the authors, of which 80% was used for training, 15% for testing and 5% for model validation. The most important metrics are presented, making a comparison between the models, and finally it was identified that YOLOv7 achieved a higher success rate, which could be considered a more complete solution for occupational health and safety management in companies.
Volume: 14
Issue: 5
Page: 5824-5833
Publish at: 2024-10-01

A fuzzy logic scheme based on spread rate and population for pandemic vaccine allocation

10.11591/ijece.v14i5.pp5941-5948
Abdul Kareem , Varuna Kumara
This paper deals with a novel decision-making scheme for inferring the allocation of vaccines to the provincial health care authorities by the central health care authority of a country in pandemic scenarios. This novel scheme utilizes a fuzzy logic-based inference scheme that utilizes the spread rate and population of a province as inputs to infer the vaccination rate. The proposed scheme is evaluated on the coronavirus disease (COVID-19) data from six southern states of India during the first week of October 2020, collected from the database maintained by the Government of India. The findings demonstrate that the suggested plan, which takes population and spread rate into account, makes sure that enough vaccination doses are distributed to the provinces with a larger spread rate with a higher priority, and that immunizations are not delayed in provinces with controlled spread rates. Also, in due course, all territories will appropriately distribute enough vaccine supply to control the spread. Therefore, this plan strengthens the efforts to control the pandemic outbreaks by ensuring the proper and balanced delivery of vaccines in a timely, efficient, and objective manner.
Volume: 14
Issue: 5
Page: 5941-5948
Publish at: 2024-10-01

Photovoltaic power prediction using deep learning models: recent advances and new insights

10.11591/ijece.v14i5.pp5926-5940
Basma Saad , Asmaa El Hannani , Abdelhak Aqqal , Rahhal Errattahi
Artificial intelligence (AI) and its application across various domains have sparked significant interest, with each domain presenting distinct characteristics and challenges. In the renewable energies sector, accurate prediction of power output from photovoltaic (PV) panels using AI is crucial for meeting energy demand and facilitating energy management and storage. The field of data analysis has grown rapidly in recent years, with predictive models becoming increasingly popular for forecasting and prediction tasks. However, the accuracy and reliability of these models depend heavily on the quality of data, data preprocessing, model learning and evaluation. In this context, this paper aims to provide an in-depth review of previous research and recent progress in PV solar power forecasting and prediction by identifying and analyzing the most impacting factors. The findings of the literature review are then used to implement a benchmark for PV power prediction using deep learning models in different climates and PV panels. The aim of implementing this benchmark is to gain insights into the challenges and opportunities of PV power prediction and to improve the accuracy, reliability and explainability of predictive models in the future.
Volume: 14
Issue: 5
Page: 5926-5940
Publish at: 2024-10-01

Indonesian vocational college students’ attitudes towards project-based learning in English courses

10.11591/ijere.v13i5.28406
Ira Mutiaraningrum , Sri Wuli Fitriati , Issy Yuliasri , Mursid Saleh
Following the mandatory adoption of project-based learning (PjBL) in Indonesian vocational education, there has been a revival in popularity as a prevalent instructional approach in higher education. However, no research on students' attitudes toward mandatory PjBL in Indonesia has raised concerns about its acceptance. This article describes Indonesian vocational college students’ attitudes toward PjBL in English language courses. The study specifically focuses on cognitive, affective, and behavioral attitudes and how students perceive the advantages of PjBL for their English skills and career aspirations. This quantitative study included 336 Indonesian vocational students from twelve state and private colleges in Indonesia. The results of this study revealed that students had a positive attitude toward PjBL in their English courses. Students’ cognitive, affective, and behavioral attitudes indirectly influenced their career aspirations, with English skill benefits acting as mediators. This study proves that how students feel, think, and behave affects their future career goals by shaping how they perceive improvement in their English language skills.
Volume: 13
Issue: 5
Page: 3177-3184
Publish at: 2024-10-01
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