International Journal of Electrical and Computer Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
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Experimental study of compressor electric current detection for a split-type air conditioner affects energy savings
Banjerd Saengchandr;
Viroch Sukontanakarn;
Kriangkrai Waiyagan
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp2660-2668
The paper presents an experimental study that aims to measure the compressor electric current of a split-type air conditioner for analyzing the various abnormal condition of the R-32 refrigerant pressure, especially for detecting compressor electric current while occurring dirt in the evaporator coil and condenser coil. The method was to install sensor devices to measure the temperature and humidity of inlet air and outlet air, and the velocity of the air outlet of the evaporator unit. In condenser unit was to measure the electric current compressor and electric power input. All data from sensors send to the Arduino board and using Parallax Data Acquisition (PLX-DAQ) Excel Macro for the record. The results show physical behavior and the changing of compressor electric current according to the abnormal condition of the refrigerant system, blocking of condenser and evaporator coil.
Residual balanced attention network for real-time traffic scene semantic segmentation
Amine Kherraki;
Shahzaib Saqib Warraich;
Muaz Maqbool;
Rajae El Ouazzani
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp3281-3289
Intelligent transportation systems (ITS) are among the most focused research in this century. Actually, autonomous driving provides very advanced tasks in terms of road safety monitoring which include identifying dangers on the road and protecting pedestrians. In the last few years, deep learning (DL) approaches and especially convolutional neural networks (CNNs) have been extensively used to solve ITS problems such as traffic scene semantic segmentation and traffic signs classification. Semantic segmentation is an important task that has been addressed in computer vision (CV). Indeed, traffic scene semantic segmentation using CNNs requires high precision with few computational resources to perceive and segment the scene in real-time. However, we often find related work focusing only on one aspect, the precision, or the number of computational parameters. In this regard, we propose RBANet, a robust and lightweight CNN which uses a new proposed balanced attention module, and a new proposed residual module. Afterward, we have simulated our proposed RBANet using three loss functions to get the best combination using only 0.74M parameters. The RBANet has been evaluated on CamVid, the most used dataset in semantic segmentation, and it has performed well in terms of parameters’ requirements and precision compared to related work.
Semi-automatic model to colony forming units counting
Jesus Emilio Pinto-Lopera;
Diana Carolina Meneses-Cabezas;
Yuliana Zapata-Serna;
Yeison Alberto Garces-Gomez
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp2761-2768
Colony forming units counting is a conventional process carry out in bacteriological laboratories, and it is used to follow the behavior of bacteria in different conditions. Currently exist different systems, automatic or semi-automatic, to counting colony forming units exits, but, in general, many laboratories continue using manual counting, which consumes considerable time and effort from researchers and laboratory employees. This paper presents a mathematical model carry out to segment the colony forming units and, in this way, counting them from a digital image of the sample. The method uses the color space information of some points in the image and shows good behavior for images with many or few colony forming units in the sample, according to manual counting. The results show efficiencies close to 98% with MacConkey agar.
Sensitivity of solar panel energy conversion at sunrise and sunset on three weather fluctuations in equatorial climate
Habib Satria;
Rahmad Syah;
Nukhe Andri Silviana;
Syafii Syafii
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp2449-2458
The high sunlight intensity in tropical and equatorial regions makes the potential for installing photovoltaic (PV) panels. However, the initial design of PV installations must be analyzed. Their implementation is carried out in buildings with load power for household electricity scale. For this reason, the panel reliability system could be efficient by designing the initial PV requirements using systematic measurements. Collecting data on fluctuating sunlight intensity (unpredictable weather) conditions needs the use of manual measuring tools, namely digital light meters and PV data with sensor integration. The research sample consists of three fluctuating hot weather conditions, namely hot-sunny, hot-cloudy and hot-rainy conditions. These weather conditions were taken because the climate of West Sumatra tends to shift clouds which sometimes cover the sun's rays. The peak PV output for direct current (DC) power generated during hot- sunny conditions reaches 1827.17 W, in sunny-cloudy weather it reaches around 1626.85 W and during sunny-rainy weather conditions the resulting output is 1161.81 W. From daily measurements, the results show that the efficiency of the PV system is strongly influenced by the prevailing weather climate.
Multivariate sample similarity measure for feature selection with a resemblance model
Tsehay Admassu Assegie;
Ayodeji Olalekan Salau;
Crescent Onyebuchi Omeje;
Sepiribo Lucky Braide
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp3359-3366
Feature selection improves the classification performance of machine learning models. It also identifies the important features and eliminates those with little significance. Furthermore, feature selection reduces the dimensionality of training and testing data points. This study proposes a feature selection method that uses a multivariate sample similarity measure. The method selects features with significant contributions using a machine-learning model. The multivariate sample similarity measure is evaluated using the University of California, Irvine heart disease dataset and compared with existing feature selection methods. The multivariate sample similarity measure is evaluated with metrics such as minimum subset selected, accuracy, F1-score, and area under the curve (AUC). The results show that the proposed method is able to diagnose chest pain, thallium scan, and major vessels scanned using X-rays with a high capability to distinguish between healthy and heart disease patients with a 99.6% accuracy.
A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability
Savari R. Sahaya Prabaharan;
Adamu Murtala Zungeru;
Bokani Mtengi;
Siluvai M. Michael
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp2482-2497
In a photovoltaic system, a stable voltage and of tolerable power equilibrium is needed. Hence, a dedicated analog charge controller for a storage system which controls energy flow to impose power equilibrium, and therefore, voltage stability on the load is required. We demonstrate here our successful design considerations employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system, incorporating a dedicated supercapacitor charge controller for the first time. Firstly, we demonstrated a photovoltaic system employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system. Secondly, we design a constant voltage maximum power point tracker (MPPT) for peak power extraction from the photovoltaic generator. Thirdly, we incorporated a supercapacitor charge controller for power equilibrium and voltage stability through a dedicated analog charge controller in our design, the first of its kind. Fourthly, we analyzed the use of supercapacitor storage to mitigate disequilibrium between power supply and demands, which, in turn, causes overvoltage or under voltage across the load. Lastly, we then went ahead to demonstrate the control of the energy flow in the system so as to maintain rated voltage across a variant demand load.
A review of hyperspectral imaging-based plastic waste detection state-of-the-arts
Owen Tamin;
Ervin Gubin Moung;
Jamal Ahmad Dargham;
Farashazillah Yahya;
Sigeru Omatu
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp3407-3419
Plastic waste issues emerged from the build-up of plastics that negatively impacts the environment. As a result, plastic waste detection is proposed in many research studies to tackle the problems. Therefore, this paper aims to review hyperspectral imaging techniques and machine learning in plastic waste detection. Hyperspectral imaging techniques are found to be effective in detecting plastic waste and microplastics as they were able to capture plastic reflectance spectral by using the near-infrared sensor. However, the review also shows that hyperspectral imaging techniques were less efficient in capturing the electromagnetic spectrum of black plastics due to carbon-black absorption properties. Carbon-black strongly absorbs light in the ultraviolet and infrared spectral range of the electromagnetic spectrum, therefore not detected by the near-infrared sensor. This paper also reviews how machine learning can alternatively detect and sort all types of waste, including plastics. Multiple studies show that the machine learning model achieved good accuracy in detecting all types of plastics based on the waste dataset. Finally, it can be seen that the spectral information of plastic can be used as feature extraction for machine learning models for better plastic detection. It is hoped that this study will contribute to more systematic research on the same topic.
Digital learning using Maktabah Syumilah NU 1.0 software and computer application for Islamic moderation in pesantren
Hamidulloh Ibda;
Aji Sofanudin;
Moh. Syafi’;
Novena Ade Fredyarini Soedjiwo;
Ana Sofiyatul Azizah;
Muhamad Arif
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp3530-3539
Digital learning through computer software and applications is rarely applied by pesantren (Islamic boarding schools) in Indonesia. So far, the application commonly used by traditional (salaf) pesantren, modern (khalaf) pesantren, and integrated pesantren is the Maktabah Syamila application. However, in Maktabah Syamila, religious radicalism, false hadiths, and texts allow the killing of innovators. Responding to this, pesantren activists developed digital learning through the application and computer program Maktabah Syumilah NU 1.0 as a comparison to Maktabah Syamila and an alternative to learning in pesantren as a counterradicalism. The research explores digital learning through Maktabah Syumilah NU 1.0 software and computer application to cultivate religious moderation in Temanggung Regency, Central Java, Indonesia. The qualitative research method with case studies on ten traditional pesantren using Maktabah Syumilah NU 1.0. The results show that digital learning through Maktabah Syumilah NU 1.0 is carried out in various activities in and outside the pesantren. The application of Maktabah Syumilah NU 1.0 is used to cultivate Islamic moderation for santri (students of pesantren). The use of Maktabah Syumilah NU 1.0 has an impact on strengthening Islamic moderation in pesantren. This research recommends that the Ministry of Religious Affairs implement Maktabah Syumilah NU 1.0 in all pesantren. Future researchers must explore digital learning more deeply through the latest applications for strengthening Islamic moderation in pesantren.
A comparative analysis between two heuristic algorithms for the graph vertex coloring problem
Velin Kralev;
Radoslava Kraleva
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp2981-2989
This study focuses on two heuristic algorithms for the graph vertex coloring problem: the sequential (greedy) coloring algorithm (SCA) and the Welsh–Powell algorithm (WPA). The code of the algorithms is presented and discussed. The methodology and conditions of the experiments are presented. The execution time of the algorithms was calculated as the average of four different starts of the algorithms for all analyzed graphs, taking into consideration the multitasking mode of the operating system. In the graphs with less than 600 vertices, in 90% of cases, both algorithms generated the same solutions. In only 10% of cases, the WPA algorithm generates better solutions. However, in the graphs with more than 1,000 vertices, in 35% of cases, the WPA algorithm generates better solutions. The results show that the difference in the execution time of the algorithms for all graphs is acceptable, but the quality of the solutions generated by the WPA algorithm in more than 20% of cases is better compared to the SC algorithm. The results also show that the quality of the solutions is not related to the number of iterations performed by the algorithms.
Horizontal trajectory based mobile multi-sink routing in underwater sensor networks
Vijayalaxmi R Patil;
Anita Kanavalli
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijece.v13i3.pp3056-3071
Scientific, commercial, exploration, and monitoring applications of underwater sensor networks have drawn the attention of researchers toward the investigation of routing protocols that are robust, scalable, and energy efficient. This has brought significant research in network layer routing protocols. Irrespective of the field of application it is desirable to increase network lifetime by reducing energy consumed by sensor nodes in the network or by balancing energy in the entire network. Energy balancing refers to the uniform distribution of the network’s residual energy such that all nodes remain alive for a long time. It requires uniform energy consumption by each sensor node in the network instead of the same node being involved in every transmission. In this paper, we discuss two routing methods for three-dimensional environments in which the water region under monitor is divided into subregions of equal height and each subregion has a sink. Nodes in the subregion send data to the sink designated for that subregion. The first method called static multi-sink routing uses static sinks and the second method called horizontal trajectory-based mobile multi-sink routing (HT-MMR) uses mobile sinks with a horizontal trajectory. Simulation results show that the proposed HT-MMR reduces average energy consumption and average energy tax by 16.69% and 16.44% respectively. HT-MMR is energy efficient as it enhances network lifetime by 11.11%.