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International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics 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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 111 Documents
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Search results for , issue "Vol 14, No 1: February 2024" : 111 Documents clear
Reinforcement learning strategies using Monte-Carlo to solve the blackjack problem Srinivasaiah, Raghavendra; Biju, Vinai George; Jankatti, Santosh Kumar; Channegowda, Ravikumar Hodikehosahally; Jinachandra, Niranjana Shravanabelagola
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp904-910

Abstract

Blackjack is a classic casino game in which the player attempts to outsmart the dealer by drawing a combination of cards with face values that add up to just under or equal to 21 but are more incredible than the hand of the dealer he manages to come up with. This study considers a simplified variation of blackjack, which has a dealer and plays no active role after the first two draws. A different game regime will be modeled for everyone to ten multiples of the conventional 52-card deck. Irrespective of the number of standard decks utilized, the game is played as a randomized discrete-time process. For determining the optimum course of action in terms of policy, we teach an agent-a decision maker-to optimize across the decision space of the game, considering the procedure as a finite Markov decision chain. To choose the most effective course of action, we mainly research Monte Carlo-based reinforcement learning approaches and compare them with q-learning, dynamic programming, and temporal difference. The performance of the distinct model-free policy iteration techniques is presented in this study, framing the game as a reinforcement learning problem.
Robust automotive radar interference mitigation using multiplicative-adaptive filtering and Hilbert transform Asmaur Rohman, Budiman Putra; Suryadi Satyawan, Arief; Kurniawan, Dayat; Indrawijaya, Ratna; Bin Ali Wael, Chaeriah; Armi, Nasrullah
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp326-336

Abstract

Radar is one of the sensors that have significant attention to be implemented in an autonomous vehicle since its robustness under many possible environmental conditions such as fog, rain, and poor light. However, the implementation risks interference because of transmitting and/or receiving radar signals from/to other vehicles. This interference will increase the floor noise that can mask the target signal. This paper proposes multiplicative-adaptive filtering and Hilbert transform to mitigate the interference effect and maintain the target signal detectability. The method exploited the trade-off between the step-size and sidelobe effect on the least mean square-based adaptive filtering to improve the target detection accuracy, especially in the long-range case. The numerical analysis on the millimeter-wave frequency modulated continuous wave radar with multiple interferers concluded that the proposed method could maintain and enhance the target signal even if the target range is relatively far from the victim radar.
Sensing complicated meanings from unstructured data: a novel hybrid approach Shastri, Shankarayya; Teligi Math, Veeragangadhara Swamy; Siddalingappa, Patil Nagaraja
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp711-720

Abstract

The majority of data on computers nowadays is in the form of unstructured data and unstructured text. The inherent ambiguity of natural language makes it incredibly difficult but also highly profitable to find hidden information or comprehend complex semantics in unstructured text. In this paper, we present the combination of natural language processing (NLP) and convolution neural network (CNN) hybrid architecture called automated analysis of unstructured text using machine learning (AAUT-ML) for the detection of complex semantics from unstructured data that enables different users to make understand formal semantic knowledge to be extracted from an unstructured text corpus. The AAUT-ML has been evaluated using three datasets data mining (DM), operating system (OS), and data base (DB), and compared with the existing models, i.e., YAKE, term frequency-inverse document frequency (TF-IDF) and text-R. The results show better outcomes in terms of precision, recall, and macro-averaged F1-score. This work presents a novel method for identifying complex semantics using unstructured data.
Optimal load management of autonomous power systems in conditions of water shortage Rahimov, Firdavs; Kirgizov, Alifbek; Safaraliev, Murodbek; Zicmane, Inga; Sergeev, Nikita; Matrenin, Pavel
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp99-109

Abstract

The issues of optimizing the operation of micro hydropower plants in conditions of water scarcity, performed by additional connection to the grid of an energy storage system and wind power turbine, as well as optimal load management, are considered. It is assumed that the load of the system is a concentrated autonomous power facility that consumes only active power. The paper presents a rigorous mathematical formulation of the problem, the solution of which corresponds to the minimum cost of an energy storage system and a wind turbine, which allows for uninterrupted supply of electricity to power facilities in conditions of water shortage necessary for the operation of micro hydropower plants (under unfavorable hydrological conditions). The problem is formulated as a nonlinear multi-objective optimization problem to apply metaheuristic stochastic algorithms. At the same time, a significant part of the problem is taken out and framed as a subproblem of linear programming which will make it possible to solve it by a deterministic simplex method that guarantees to find the exact global optimum. This approach will significantly increase the efficiency of solving the entire problem by combining metaheuristic algorithms and taking into account expert knowledge about the problem being solved.
Controlling temperature using proportional integral and derivative control algorithm for hybrid forced convection solar dryer Arifin, Mohammad Aldrin; Pangaribuan, Porman; Pramudita, Brahmantya Aji; Megantoro, Prisma
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp239-247

Abstract

Drying is one of the crucial processes in agricultural production, especially in grain processing. The drying process can improve grain quality and affect the grain content. However, maintaining the temperature is a challenge in the drying process. Because it can influence the drying performance and produce a low-efficiency reduction of water content, in this study, the hybrid drying system is proposed to improve the performance of the forced convection dryer system. The proposed system used a proportional integral and derivative (PID) control system to obtain the optimal temperature. The proposed system was compared with natural drying and forced convection methods. The experimental result showed that the proposed system performed excellently for three performance evaluations. The average temperature was obtained as the highest of the other methods, with 54.68 °C and 54.55 °C for coffee and cocoa beans. The water content can be reduced by an average of 27.38% and 42.67% for coffee and cocoa beans. Then, the proposed system also had the highest reduction efficiency of water content than the other methods, with 62.71% and 36.94% reductions for coffee and cocoa beans, respectively. The results indicate that the proposed hybrid system performs better than the other methods.
Affective e-learning approaches, technology and implementation model: a systematic review Adebiyi, Marion Olubunmi; Adebiyi, Abayomi Aduragba; Olaniyan, Deborah; Orenyi, Bajeh Amos
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp631-644

Abstract

A systematic literature study including articles from 2016 to 2022 was done to evaluate the various approaches, technologies, and implementation models involved in measuring student engagement during learning. The review’s objective was to compile and analyze all studies that investigated how instructors can gauge students’ mental states while teaching and assess the most effective teaching methods. Additionally, it aims to extract and assess expanded methodologies from chosen research publications to offer suggestions and answers to researchers and practitioners. Planning, carrying out the analysis, and publishing the results have all received significant attention in the research approach. The study’s findings indicate that more needs to be done to evaluate student participation objectively and follow their development for improved academic performance. Physiological approaches should be given more support among the alternatives. While deep learning implementation models and contactless technology should interest more researchers. And, the recommender system should be integrated into e-learning system. Other approaches, technologies, and methodology articles, on the other hand, lacked authenticity in conveying student feeling.
Detecting anomalies in security cameras with 3D-convolutional neural network and convolutional long short-term memory Mahareek, Esraa A.; ElSayed, Eman K.; ElDesouky, Nahed M.; ElDahshan, Kamal A.
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp993-1004

Abstract

This paper presents a novel deep learning-based approach for anomaly detection in surveillance films. A deep network that has been trained to recognize objects and human activity in movies forms the foundation of the suggested approach. In order to detect anomalies in surveillance films, the proposed method combines the strengths of 3D-convolutional neural network (3DCNN) and convolutional long short-term memory (ConvLSTM). From the video frames, the 3DCNN is utilized to extract spatiotemporal features,while ConvLSTM is employed to record temporal relationships between frames. The technique was evaluated on five large-scale datasets from the actual world (UCFCrime, XDViolence, UBIFights, CCTVFights, UCF101) that had both indoor and outdoor video clips as well as synthetic datasets with a range of object shapes, sizes, and behaviors. The results further demonstrate that combining 3DCNN with ConvLSTM can increase precision and reduce false positives, achieving a high accuracy and area under the receiver operating characteristic-area under the curve (ROC-AUC) in both indoor and outdoor scenarios when compared to cuttingedge techniques mentioned in the comparison.
Development of energy conversion and lightning strike protection simulation for photovoltaic-wind turbine on grid Satria, Habib; Mungkin, Moranain; Dayana, Indri; Ramdan, Dadan; Maizana, Dina; Syafii, Syafii
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp66-74

Abstract

Photovoltaic (PV) installations and wind turbines that are installed on the rooftops of buildings need to be protected because the layout is in a high position and there is a risk of being struck by lightning. Therefore, a more effective protection system is designed to anticipate electronic damage and fire on all materials in the distribution network, especially the addition of PV and wind turbine installations on building roofs. The purpose of this study is to simulate a lightning protection system on the distribution network and the results of on-grid PV energy conversion using electrical transient analyzer program (ETAP) software. Feeder relay delay times and cascade coordination patterns between outgoing and incoming relays do not overlap. the delay time of the relay working on the feeder is 0.31 s and the coordination pattern of the outgoing relay and incoming relay does not touch each other, so the delay time for the incoming relay is 2.73 s. Then testing the results of PV energy conversion connected to the grid using MATLAB Simulink monitoring obtained data reaching 1.600 Wp at peak power with sun conditions parallel to the PV installation layout.
Graph embedding approach to analyze sentiments on cryptocurrency Moudhich, Ihab; Fennan, Abdelhadi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp690-697

Abstract

This paper presents a comprehensive exploration of graph embedding techniques for sentiment analysis. The objective of this study is to enhance the accuracy of sentiment analysis models by leveraging the rich contextual relationships between words in text data. We investigate the application of graph embedding in the context of sentiment analysis, focusing on it is effectiveness in capturing the semantic and syntactic information of text. By representing text as a graph and employing graph embedding techniques, we aim to extract meaningful insights and improve the performance of sentiment analysis models. To achieve our goal, we conduct a thorough comparison of graph embedding with traditional word embedding and simple embedding layers. Our experiments demonstrate that the graph embedding model outperforms these conventional models in terms of accuracy, highlighting it is potential for sentiment analysis tasks. Furthermore, we address two limitations of graph embedding techniques: handling out-of-vocabulary words and incorporating sentiment shift over time. The findings of this study emphasize the significance of graph embedding techniques in sentiment analysis, offering valuable insights into sentiment analysis within various domains. The results suggest that graph embedding can capture intricate relationships between words, enabling a more nuanced understanding of the sentiment expressed in text data.
Enhancing healthcare services through cloud service: a systematic review Guo, Bo; Shukor, Nur Syufiza Ahmad; Ishak, Irny Suzila
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1135-1146

Abstract

Although cloud-based healthcare services are booming, in-depth research has not yet been conducted in this field. This study aims to address the shortcomings of previous research by analyzing all journal articles from the last five years using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) systematic literature review methodology. The findings of this study highlight the benefits of cloud-based healthcare services for healthcare providers and patients, including enhanced healthcare services, data security, privacy issues, and innovative information technology (IT) service delivery models. However, this study also identifies challenges associated with using cloud services in healthcare, such as security and privacy concerns, and proposes solutions to address these issues. This study concludes by discussing future research directions and the need for a complete solution that addresses the conflicting requirements of the security, privacy, efficiency, and scalability of cloud technologies in healthcare.

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