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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 6,301 Documents
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Design and analysis of wideband four-port multiple input multiple output antenna using defective ground structure for 5G communication Tamminaina, Govindarao; Manikonda, Ramesh
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1646-1653

Abstract

This research work describes a compact four-port multiple input multiple output (MIMO) antenna using defective ground structure (DGS), and it perfectly supports the n77, n78, and n79 frequencies in 5G new radios (NR) bands. It can cover a wideband from 3.4 to 5.4 GHz with good impedance matching. The pair of antenna elements are orientated opposite to another pair with DGS. Due to this technique, it has minimal complexity, is less expensive, and improves isolation. It has also improved the frequency band's reflection coefficient and range using MIMO antenna with different stub lengths. Because it is less expensive, FR-4 substrate is used in the implementation of all antennas. Each antenna element has two identical stubs linked to the primary radiator. On the primary radiating element, a ''HI'' slot is created. The partial ground enhances impedance matching and radiation properties throughout the targeted band. The total dimensions of the four-port MIMO antenna are 46×30×1.6 mm3. The array elements' mutual coupling in the simulation is -14 dB. The ECC value is below 0.01, and the diversity gain (DG) is less than 10 dB. The suggested designs' measured gain ranges from 10 to 11.0 dB, and the radiation efficiency is nearly 91%.
A novel YOLOv8 architecture for human activity recognition of occluded pedestrians Rajakumar, Shaamili; Azad, Ruhan Bevi
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 5: October 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i5.pp5244-5252

Abstract

Perception is difficult in video surveillance applications because of the presence of dynamic objects and constant environmental changes. This problem worsens when bad weather, including snow, rain, fog, dark nights, and bright daylight, interferes with the quality of perception. The proposed work aims to enhance the accuracy of camera-based perception for human activity detection in video surveillance during adverse weather conditions. To identify primary human activities, including walking on the road during severe weather, transfer learning from many adverse conditions using real-time images or videos has been proposed as an improvement for you look only once v8 (YOLOv8)-based human activity recognition in poor weather conditions. We collected and sorted training rates into frames from videos depicting human walking activity, their combined forms, and other subgroups, such as running and standing, based on their characteristics. The assessment of the detection efficiency of the previously described images and subgroups led to a comparison of the training weights. The use of real-time activity images for training greatly enhanced the detection performance when comparing the proposed test results to the existing YOLO base weights. Furthermore, a notable improvement in human activity efficiency was obtained by utilizing extra images and feature-related combinations of data techniques.
Wearable with integrated piezoelectric energy harvester for geolocation of people with Alzheimer's Linder Rubiños Jimenez, Santiago; Herber Grados Gamarra, Juan; Nelson Chávez Gallegos, Eduardo; Angélica Velasquez Jimenez, Linett; Junior Grados Espinoza, Herbert; Christian Pesantes Arriola, Genaro
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.pp497-508

Abstract

Alzheimer's is a progressive disease that affects memory, causing disorientation in the patient, which causes them to lose themselves, generating anguish in families who have to resort to expensive searches. The objective of this research was to implement a device that can remotely provide the location of the Alzheimer's patient over a long period to relatives for greater security. For this, in this research, a mobile application was developed that receives information from a wearable that applies the internet of things using ong-range wide area technology to show the patient's real-time location and uses piezoelectrics for greater battery autonomy. The real-time location of the person and the radius of the safe zone in the application were obtained as results, the received signal strength indicator value where the signal was excellent or good had a value of -30 to -89 dB between 0 to 400 meters and the battery discharge time was 11 hours and 44 minutes. It was concluded that the application is interactive, that the piezoelectric system increased the autonomy of the wearable, and that the long-range wide area (LoRa) technology allowed monitoring of the patient's location with great precision at 400 meters.
Entities recommendations using contextual information Saidi, Imène; Mahammed, Nadir; Klouche, Badia; Khayra, Bencherif
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4336-4342

Abstract

Generating entities recommendations has attracted considerable interest in recent years. Most recently published works mainly focus on providing a user with the most relevant and/or personalized entity recommendations that score highly against the query and/or the user’s preference. Some works consider user side information, such as the user network, user relations, and user’s demographic information, and propose to integrate them into the framework of recommender systems. These approaches have been shown to increase the users’ satisfaction and engagement with the system. In this paper, we investigate entities recommender systems and summarize the recent efforts in this domain by categorizing approaches. The first category presents different approaches that utilize knowledge graph as side information. The second category gathers work that consider both the current query, and the users’ previous interactions with the system. These latter works have considered the full user history to personalize the ranking of recommended entities related to the query. In this review paper, we emphasize contextual information-based approaches that utilize user’s context and feedback to improve the recommendations. We accomplished a summary of the literature and synthesized the papers according to different perceptions. Finally, a comparison between approaches is provided and some drawbacks are identified.
Hierarchal attribute based cryptographic model to handle security services in cloud environment: a new model Rajarao, Banavathu; Sreenivasulu, Meruva
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.pp1102-1111

Abstract

The sharing of information in the cloud is a unique element of the environment, but there is a risk that the information may land with the wrong people. To counterattack this problem, security-associated methodologies were used to secure the information that was readily available to clients. Despite the lack of benefits, this provides productive/adaptability and dependability in access control strategies between clients in the sharing of information. The novel hierarchal attribute-based cryptographic security model (NHACSM) is being proposed to provide adaptability, versatility, and access control in sharing information in the appropriate climate. This model allows clients to share information in a hierarchal way, allowing for a productive assessment of access control strategy and improved security. The NHACSM method is used to reduce the total time values for different user instances compared to conventional approaches, for example, attribute-set-based encryption (ASBE), key-policy attribute-based encryption (KP-ABE), and ciphertext-policy attribute-based encryption (CP-ABE). With respect to 10 instances existing methods achieve 2.7, 2.5, and 2.3 respectively, and also compared to 20, 30, 40, and 50 instances, our proposed method is low. The encryption and decryption time evaluation values and performance evaluation of different approaches, ASBE, CP-ABE, were taken into account when increasing the user instance.
The social media sentiment analysis framework: deep learning for sentiment analysis on social media Rangarjan, Prasanna Kumar; Gurusamy, Bharathi mohan; Muthurasu, Gayathri; Mohan, Rithani; Pallavi, Gundala; Vijayakumar, Sulochana; Altalbe, Ali
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp3394-3405

Abstract

Researching public opinion can help us learn important facts. People may quickly and easily express their thoughts and feelings on any subject using social media, which creates a deluge of unorganized data. Sentiment analysis on social media platforms like Twitter and Facebook has developed into a potent tool for gathering insights into users' perspectives. However, difficulties in interpreting natural language limit the effectiveness and precision of sentiment analysis. This research focuses on developing a social media sentiment analysis (SMSA) framework, incorporating a custom-built emotion thesaurus to enhance the precision of sentiment analysis. It delves into the efficacy of various deep learning algorithms, under different parameter calibrations, for sentiment extraction from social media. The study distinguishes itself by its unique approach towards sentiment dictionary creation and its application to deep learning models. It contributes new insights into sentiment analysis, particularly in social media contexts, showcasing notable advancements over previous methodologies. The results demonstrate improved accuracy and deeper understanding of social media sentiment, opening avenues for future research and applications in diverse fields.
Performance analysis of 2D optical code division multiple access through underwater wireless optical medium Islam, Md. Rabiul; Islam, Md. Jahedul; Mitra, Bithi; Hossain, Md. Amzad; Islam, Jahedul; Dev, Shuvo
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp1665-1673

Abstract

The performance of a two-dimensional optical code division multiple access (2D-OCDMA) system using an underwater wireless optical (UWO) medium is assessed in this work. The optical source is an LED with a working wavelength of 532 nm, and the optical detector is a p–i–n photodiode. When calculating the bit error rate (BER), the phase-induced intensity noise (PIIN), thermal noises, and shot sounds are taken into account. The user code address is set using 2D perfect difference (2D-PD) codes. Link distance, inclination angle, beam divergence angle, transmitter power, and the number of concurrent users are all taken into account when determining the BER performance. For various water media, such as pure sea water (PSW), clear ocean water (CLOW), and coastal ocean water (CSOW), the performance of the suggested system is examined.
Network reconfiguration for improving performance system in ULP Sungguminasa considering nonlinear loads Faraby, Muhira Dzar; Rahman, Yuli Asmi; Sofyan, Sofyan; Thaha, Sarma; Lukman, Musfirah Putri; Amaliah, Asma; Mustika, Mustika; Sirad, Mochammad Apriyadi Hadi; Sonita, Anisya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6066-6075

Abstract

Network reconfiguration is a very economical technique that can improve electrical system performance. The development of semiconductor electrical equipment technology to meet human needs and work, known as nonlinear loads, has had a negative impact in the form of the spread of harmonic distortion which can accelerate the aging process and even damage equipment. In this paper, the effect of the optimization results of network reconfiguration techniques on the Sungguminasa 165-bus Executive Unit Service or Unit Layanan Pelanggan (ULP) electrical system is contaminated with harmonic distortion due to the use of nonlinear loads. This technique was optimized using the particle swarm optimization (PSO) method with a multi objective function in the form of minimizing %THDv and total losses with several limitations. Simulation results from the optimization process of several study cases are shown by activating the five tie switches from the network reconfiguration process on the Sungguminasa 165-bus ULP system which is able to improve power quality by reducing the average %THDv by 3.89% and total losses by 8.19%.
Electric vehicle and photovoltaic advanced roles in enhancing the financial performance of a manufacturing and commercial setup Nassereddine, Mohamad; Nassreddine, Ghalia; ElHassan, Tamima
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2491-2499

Abstract

Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network.
Agarwood oil quality identification using artificial neural network modelling for five grades Mohd Huzir, Siti Mariatul Hazwa; Tajuddin, Saiful Nizam; Mohd Yusoff, Zakiah; Ismail, Nurlaila; Almisreb, Ali Abd; Taib, Mohd Nasir
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 2: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i2.pp2254-2261

Abstract

Agarwood (Aquilaria Malaccensis) oil stands out as one of the most valuable and highly sought-after oils with a hefty price tag due to its widespread use of fragrances, incense, perfumes, ceremonial practices, medicinal applications and as a symbol of luxury. However, nowadays the conventional method that rely on color alone has its limitations as it yields varying results depending on individual panelists' experiences. Hence, the quality identification system of Agarwood oil using its chemical compounds had been proposed in this study to enhance the precision of the Agarwood oil grades thus addressing the shortcomings of traditional methods. This study indicates that the primary chemical compounds of Agarwood oil encompass ɤ-Eudesmol, ar-curcumene, β-dihydroagarofuran, ϒ-cadinene, α-agarofuran, allo-aromadendrene epoxide, valerianol, α-guaiene, 10-epi-ɤ-eudesmol, β-agarofuran and dihydrocollumellarin. This study employed artificial neural network analysis with the implementation of Levenberg-Marquardt algorithm to identify the Agarwood oil grades. The study's findings revealed that this modeling system of five grades got 100% accuracies with mean square error of 0.14338×10-08. Notably, this lowest mean square error (MSE) value falls within the best hidden neuron 3. These study outcomes play a pivotal role in highlighting the Levenberg Marquardt- artificial neural network (LM-ANN) modeling that contribute to the successful of Agarwood oil quality identification using its chemical compounds.

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