International Journal of Electrical and Computer Engineering (IJECE)

Journal Information
ISSN / EISSN : 2088-8708 / 2088-8708
Total articles ≅ 4,515
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SCOPUS
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Latest articles in this journal

, Oluwamayowa Abimbola
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5214-5225; https://doi.org/10.11591/ijece.v12i5.pp5214-5225

Abstract:
Cement is one of the most common building materials in the construction industry. Simultaneously, its price fluctuation can affect the success or failure of the construction project's performance. The study aimed to develop a web-based platform that uses machine learning algorithms on historical data of cement prices, petrol prices, diesel prices, interest rate, and exchange rate to predict future prices of cement products. The web-based learning platform was developed using hypertext markup language (HTML), cascading style sheet (CSS), MySQL, and hypertext preprocessor (PHP). For building a reliable machine learning model, python language was used to train the system. The front end, the back end, and the machine learning model were integrated with a flask python framework. A system block diagram was designed to show the web-based learning platform's interfaces. The web-based learning platform's system implementation led to the login page, the home page, database page, and cement price analytics interface. In training the machine learning model to make reliable cement price predictions, the study obtained an 80% fitted model in the linear regression. The web-based machine learning platform was able to predict the prices of cement. The rationale behind the machine learning prediction shown by the scatter plot diagram revealed that the cement increases by 250 naira biannually.
Mohammed Al-Shabi, Abdulrahman Al-Qarafi
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5619-5629; https://doi.org/10.11591/ijece.v12i5.pp5619-5629

Abstract:
Due to its uniquely suited to the knowledge era, the blockchain technology has currently become highly appealing to the next generation. In addition, such technology has been recently extended to the internet of things (IoT). In essence, the blockchain concept necessitates the use of a decentralized data operation system to store as well as to distribute data and the transactions across the net. Therefore, this study examines the specific concept of the blockchain as a decentralized data management system in the face of probable protection threats. Furthermore, it discusses the present solutions that can be used to counteract those attacks. The blockchain security enhancement solutions are included in this study by summarizing the key points of these solutions. Several blockchain systems and safety devices that register security defenselessness can be developed using such key points. At last, this paper discusses the pending matters and the outlook research paths of blockchain-IoT systems.
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5055-5062; https://doi.org/10.11591/ijece.v12i5.pp5055-5062

Abstract:
Image segmentation consists of partitioning the image into different objects of interest. For a biological image, the segmentation step is important to understand the biological process. However, it is a challenging task due to the presence of different dimensions for cells, intensity inhomogeneity, and clustered cells. The marker-controlled watershed (MCW) is proposed for segmentation, outperforming the classical watershed. Besides, the choice of markers for this algorithm is important and impacts the results. For this work, two foreground markers are proposed: kernels, constructed with the software Fiji and Obj.MPP markers, constructed with the framework Obj.MPP. The new proposed algorithms are compared to the basic MCW. Furthermore, we prove that Obj.MPP markers are better than kernels. Indeed, the Obj.MPP framework takes into account cell properties such as shape, radiometry, and local contrast. Segmentation results, using new markers and illustrated on real Drosophila dataset, confirm the good performance quality in terms of quantitative and qualitative evaluation.
Christian Manuel Moreno Rocha, , Willian Fernando Arguello Rodríguez, Arley Jesús Fontalvo Ballesteros,
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 4521-4528; https://doi.org/10.11591/ijece.v12i5.pp4521-4528

Abstract:
This article quantifies the development of photovoltaic solar energy in Colombia and its current development prospects. The high demand for electricity in Colombia is increasing since there is a large population, industrial, and business increase, which brings a higher energy consumption and consequently economic, social, and environmental problems. Faced with this situation, a possible solution is proposed, using solar energy, to supply the increase in demand and mitigate the problems caused by current electricity generation because Colombia has high levels of solar radiation in almost the entire territory. The objective of this research is based on the analysis of the behavior of the projects on photovoltaic solar systems presented to the mining-energy planning unit (UPME) in the last 14 years until September 30, 2020, as well such as the study of the areas with the most effective implementation of this technology and their respective radiation indices. In addition, a synthesis is made of the regulations, laws, and tax incentives that exist for the implementation of this technology and the different stages of execution of the projects approved and in performance.
Ramana Reddy Gujjula, Chitra Perumal, Prakash Kodali, Bodapati Venkata Rajanna
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 4935-4943; https://doi.org/10.11591/ijece.v12i5.pp4935-4943

Abstract:
In this paper, the design and analysis of dual-mode numerically controlled oscillators (NCO) based controlled oscillator frequency Modulation is implemented. Initially, input is given to the analog to digital (ADC) converter. This will change the input from analog to digital converter. After that, the pulse skipping mode (PSM) logic and proportional integral (PI) are applied to the converted data. After applying PSM logic, data is directly transferred to the connection block. The proportional and integral block will transfer the data will be decoded using the decoder. After decoding the values, it is saved using a modulo accumulator. After that, it is converted from one hot residue (OHR) to binary converter. The converted data is saved in the register. Now both data will pass through the gate driver circuit and output will be obtained finally. From simulation results, it can observe that the usage of metal oxide semiconductor field effect transistors (MOSFETs) and total nodes are very less in dual-mode NCO-based controlled oscillator frequency modulation.
Kannattha Chaisriya, Lester Gilbert, Ratchada Suwangerd, Sasithorn Rattanarungrot
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5272-5278; https://doi.org/10.11591/ijece.v12i5.pp5272-5278

Abstract:
Digital games are a powerful tool for the presentation of food cultural heritage. A digital game was designed and developed to raise and enhance young people’s interest in and knowledge of Thai food cultural heritage, currently an under-researched field. The platform game was played on a mobile device and required the collection of food ingredients appropriate to popular cuisine in four Thai regions while overcoming obstacles. A sample (N=61) of young people (mean age=19 years) played the game, and the differences in their pre and post-test knowledge of and interest in Thai food and its cultural heritage were analyzed. The findings showed a highly significant increase in interest in and knowledge of Thai food cultural heritage, and did so despite the opinion of some participants that learning games were less interesting than conventional games, or that games were not a good way of raising interest in cultural heritage.
Hatim Jbari, Rachid Askour, Badr Bououlid Idrissi
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 4903-4914; https://doi.org/10.11591/ijece.v12i5.pp4903-4914

Abstract:
This paper presents a fuzzy logic controller (FLC) based energy management strategy (EMS), combined with power filtering for a pure electric vehicle. The electrical power supply is provided by a hybrid energy storage system (HESS), including Li-Ion battery and supercapacitors (SCs), adopting a fully active parallel topology. The vehicle model was organized and constructed using the energetic macroscopic representation (EMR). The main objective of this work is to ensure an efficient power distribution in the proposed dual source, in order to reduce the battery degradation. To evaluate the impact of the developed design and the efficiency of the developed EMS, the proposed FLC strategy is compared to a classical EMS using SCs-filtering strategy and architecture based on battery storage model. To validate the proposed topology, simulation results are provided for the new European driving cycle (NEDC) using MATLAB/Simulink environment.
Novie Ayub Windarko, Evi Nafiatus Sholikhah, , Eka Prasetyono, , Moh. Zaenal Efendi,
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 4571-4585; https://doi.org/10.11591/ijece.v12i5.pp4571-4585

Abstract:
Due to natural randomness, partial shading conditions (PSCs) to photovoltaic (PV) power generation significantly drop the power generation. Metaheuristic based maximum power point tracking (MPPT) can handle PSCs by searching PV panels’ global maximum power point (GMPP). However, trapped at local maxima, sluggishness, continuous power oscillations around GMPP and inaccuracy are the main disadvantages of metaheuristic algorithm. Therefore, the development of algorithm under complex PSCs has been continuously attracting many researchers to yield more satisfying results. In this paper, several algorithms including conventional and metaheuristic are selected for candidate, such as perturb and observe (P&O), firefly (FF), differential evolution (DE), grey wolf optimizer (GWO) and Seagull optimizer (SO). From the preliminary study, SO has shown best performance among other candidates. Then, SO is improved for rapid global optimizer. Modified variable step sizes perturb and observe (MVSPO) is applied to enhance the accuracy tracking of SO. To evaluate the performances, high complexity multipeak partial shading is used to test the algorithms. Statistical results are also provided to analyze the trend of performances. The proposed method performances are shown better fast-tracking time and settling time, high accuracy, higher energy harvesting and low steady-state oscillations than other candidates.
Doni Setyawan, , Moh Edi Wibowo,
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5036-5048; https://doi.org/10.11591/ijece.v12i5.pp5036-5048

Abstract:
Malaria is a disease caused by plasmodium parasites transmitted through the bites of female anopheles-mosquito that infect the human red blood cell (RBC). The standard malaria diagnosis is based on manual examination of a thick and thin blood smear, which heavily depends on the microscopist experience. This study proposed a system that can identify the life stages of plasmodium falciparum in human RBC. The image preprocessing process was done by illumination correction using gray world assumption, contrast enhancement using shadow correction, extraction of saturation component, and noise filtering. The segmentation process was applied using Otsuthresholding and morphological operation. The test results showed that the use of artificial neural network (ANN) using a combination of texture and morphological features gives better results when compared to the use of only texture or morphology features. The results showed that the proposed feature achieved an accuracy of 82.67%, a sensitivity of 82.18%, and a specificity of 94.17%, thus improving decision-making for malaria diagnosis.
, Trung Hai Trinh, Duc-Hien Nguyen, , Tran Anh Kiet, Phan Hieu Ho, Nguyen Thanh Thuy
International Journal of Electrical and Computer Engineering (IJECE), Volume 12, pp 5580-5588; https://doi.org/10.11591/ijece.v12i5.pp5580-5588

Abstract:
With the advancement of the internet, individuals are becoming more reliant on online applications to meet most of their needs. In the meantime, they have very little spare time to devote to the selection and decision-making process. As a result, the need for recommender systems to help tackle this problem is expanding. Recommender systems successfully provide consumers with individualized recommendations on a variety of goods, simplifying their duties. The goal of this research is to create a recommender system for farmers based on tree data structures. Recommender system has become interesting research by simplifying and saving time in the decision-making process of users. We conducted although a lot of research in various fields, there are insufficient in the agriculture sector. This issue is more necessary for farmers in Quangnam-Danang or all Vietnam countries by severe climate features. Storm from that, this research designs a system based on tree data structures. The proposed model combines the you only look once (YOLO) algorithm in a convolutional neural network (CNN) model with a similarity tree in computing similarity. By experiments on 400 samples and evaluating precision, accuracy, and the value of the predictive test as determined by its positive predictive value (PPV), the research proves that the proposed model is feasible and gain better results compared with other state-of-the-art models.
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