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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 2: April 2024" : 111 Documents clear
Predicting churn with filter-based techniques and deep learning Quek Jia Yi, Vivian; Ying Han, Pang; Zheng You, Lim; Shih Yin, Ooi; How Khoh, Wee
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.pp2135-2144

Abstract

Customer churn prediction is of utmost importance in the telecommunications industry. Retaining customers through effective churn prevention strategies proves to be more cost-efficient. In this study, attribute selection analysis and deep learning are integrated to develop a customer churn prediction model to improve performance while reducing feature dimensions. The study includes the analysis of customer data attributes, exploratory data analysis, and data preprocessing for data quality enhancement. Next, significant features are selected using two attribute selection techniques, which are chi-square and analysis of variance (ANOVA). The selected features are fed into an artificial neural network (ANN) model for analysis and prediction. To enhance prediction performance and stability, a learning rate scheduler is deployed. Implementing the learning rate scheduler in the model can help prevent overfitting and enhance convergence speed. By dynamically adjusting the learning rate during the training process, the scheduler ensures that the model optimally adapts to the data while avoiding overfitting. The proposed model is evaluated using the Cell2Cell telecom database, and the results demonstrate that the proposed model exhibits a promising performance, showcasing its potential as an effective churn prediction solution in the telecommunications industry.
On performance analysis of non-orthogonal multiple access downlink for cellular-connected unmanned aerial vehicle relaying assisted vehicle-to-everything system Nguyen, Hong-Nhu; Nguyen, Nhat-Tien; Vo, Gia-Thinh
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.pp1634-1645

Abstract

This paper presents the unmanned aerial vehicle (UAV) relays’ assisted vehicle-to-everything (V2X) network to implement the internet of things (IoT) systems with improvement in the coverage area. Such a network benefits from many advantages of the non-orthogonal multiple access (NOMA) scheme. We have implemented a decode-and-forward (DF) scheme for these UAVs. Then, we characterize the channels as Nakagami-m fading to evaluate the performance of the system. We derive closed-form expressions of outage probability (OP), ergodic capacity (EC), and throughput. The results show that the performance of the system depends on the transmitted signal-to-noise ratio (SNR) at the base station and the heights of the UAV relays. Target rate and power allocation factors are two main parameters that can be adjusted to achieve better performance. The results also compare to the system without UAV and OMA technique that shows the advantages of deploying UAV-assisted NOMA. Therefore, the design of NOMA for UAV relay-assisted V2X systems provides sufficient demand. The simulation results verified the effectiveness of the proposed UAV network and the precision of the theoretical analysis.
Image compression and reconstruction using improved Stockwell transform for quality enhancement Babu, Padigala Prasanth; Prasad, Talari Jayachandra; Soundararajan, Kadambi
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.pp1583-1593

Abstract

Image compression is an important stage in picture processing since it reduces the data extent and promptness of image diffusion and storage, whereas image reconstruction helps to recover the original information that was communicated. Wavelets are commonly cited as a novel technique for image compression, although the production of waves proceeding smooth areas with the image remains unsatisfactory. Stockwell transformations have been recently entered the arena for image compression and reconstruction operations. As a result, a new technique for image compression based on the improved Stockwell transform is proposed. The discrete cosine transforms, which involves bandwidth partitioning is also investigated in this work to verify its experimental results. Wavelet-based techniques such as multilevel Haar wavelet, generic multiwavelet transform, Shearlet transform, and Stockwell transforms were examined in this paper. The MATLAB technical computing language is utilized in this work to implement the existing approaches as well as the suggested improved Stockwell transform. The standard images mostly used in digital image processing applications, such as Lena, Cameraman and Barbara are investigated in this work. To evaluate the approaches, quality constraints such as mean square error (MSE), normalized cross-correlation (NCC), structural content (SC), peak noise ratio, average difference (AD), normalized absolute error (NAE) and maximum difference are computed and provided in tabular and graphical representations.
Remote field-programmable gate array laboratory for signal acquisition and design verification Sum, Rithea; Suwansantisuk, Watcharapan; Kumhom, Pinit
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.pp2344-2360

Abstract

A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embedded-system design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Improved design and performance of the global rectenna system for wireless power transmission applications around 2.45 GHz En-Naghma, Walid; Halaq, Hanan; El Ougli, Abdelghani
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.pp1674-1682

Abstract

This work proposes a new conception of the global microstrip rectenna system operating around 2.45 GHz. This improved rectenna system associates a receiving antenna with a rectifier circuit. This rectenna is printed on an FR4 substrate. The proposed antenna is a 1×4 microstrip antenna patch array with pentagonal patches using the defective ground structure method and operates with circular polarization. To show the effectiveness of this array, the results obtained by the computer simulation technology microwave studio (CST MWS) software prove that this array is good in terms of high gain, high directivity, high efficiency, wideband, small volume, and well-adaptation, and all these results are confirmed by another solver high-frequency structure simulator (HFSS). The improved rectifier is a microstrip rectifier that uses an HSMS2852 Schottky diode by using a series topology. The effectiveness of this rectifier is proved by the simulation results using advanced design system (ADS) software in terms of well-matching input impedance, high efficiency, and important output direct current (DC) voltage value. The proposed rectenna system is more efficient compared with the existing works and is very appropriate for several applications of wireless power transmission to power supply electronic instruments in various fields cleanly on our planet.
Hand LightWeightNet: an optimized hand pose estimation for interactive mobile interfaces Banzi, Jamal Firmat; Leonard, Stanley
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.pp2076-2087

Abstract

In this paper, a hand pose estimation method is introduced that combines MobileNetV3 and CrossInfoNet into a single pipeline. The proposed approach is tailored for mobile phone processors through optimizations, modifications, and enhancements made to both architectures, resulting in a lightweight solution. MobileNetV3 provides the bottleneck for feature extraction and refinements while CrossInfoNet benefits the proposed system through a multitask information sharing mechanism. In the feature extraction stage, we utilized an inverted residual block that achieves a balance between accuracy and efficiency in limited parameters. Additionally, in the feature refinement stage, we incorporated a new best-performing activation function called “activate or not” ACON, which demonstrated stability and superior performance in learning linearly and non-linearly gates of the whole activation area of the network by setting hyperparameters to switch between active and inactive states. As a result, our network operated with 65% reduced parameters, but improved speed by 39% which is suitable for running in a mobile device processor. During experiment, we conducted test evaluation on three hand pose datasets to assess the generalization capacity of our system. On all the tested datasets, the proposed approach demonstrates consistently higher performance while using significantly fewer parameters than existing methods. This indicates that the proposed system has the potential to enable new hand pose estimation applications such as virtual reality, augmented reality and sign language recognition on mobile devices.
Experimental and simulation analysis for insulation deterioration and partial discharge currents in nanocomposites of power cables Thabet, Ahmed; Fouad, Mohamed
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.pp1194-1202

Abstract

Partial discharge (PD) has a well-established relationship with the lifespan of power cables. This paper has been treated the polyvinyl chloride (PVC) with specified nanoparticles for enhancing dielectric degradation and reducing partial discharge current to extending lifespan of power cables. It has been succeeded to creation new polyvinyl chloride nanocomposites that have been synthesized experimentally via using solution-gel (SOL-GEL) technique and have high featured electric and dielectric properties. The validation of nanoparticles penetration inside polyvinyl chloride during synthesis process have been constructed and tested via scanning electron microscope (SEM) images. The partial discharge current mechanisms in polyvinyl chloride nanocomposites have also been simulated in this work by using MATLAB® software. This paper has explored the characterization of partial discharge current for variant void patterns (air, water, rubber impurity) in polyvinyl chloride nanocomposites insulations of power cables to clarify the benefit of filling different nanoparticles (Clay, MgO, ZnO, and BaTiO3) with varied patterns inside power cables dielectrics. A comparative study has been done for different partial discharges patterns to propose characterization of partial discharges using nanoparticles of appropriate types and concentrations.
Hardware-in-the-loop setup for enhanced modular multi-level converter with reduced circulating currents Soomro, Jahangeer Badar; Ali, Khawaja Haider; Memon, Abdul Aziz
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.pp1448-1458

Abstract

Owing to its essential features, such as modularity and exceptional power quality, the modular multilevel converter (MMC) emerges as the optimal converter topology for high-voltage direct current (HVDC) applications. Traditionally, MMCs are controlled through a method called nearest level modulation (NLM), which generates N+1 AC output voltages, where N represents the number of sub modules (SMs) per arm. In this paper, we introduce a modified NLM technique designed to yield 2N+1 and 4N+1 levels, with a focus on efficiently controlling internal dynamics. The proposed MMC is evaluated using a hardware-in-the-loop (HIL) environment to obtain real-time simulation outcomes. This MMC topology demonstrates a reduction in circulating currents and capacitor voltage ripple.
Efficient intelligent crawler for hamming distance based on prioritization of web documents Dange, Amol Subhash; Byranahalli Eraiah, Manjunath Swamy; Rao, Manju More Eshwar; Hanumanthaiah, Asha Kethaganahalli; Ganganayaka, Sunil Kumar
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.pp1948-1958

Abstract

Search engines play a crucial role in today's Internet landscape, especially with the exponential increase in data storage. Ranking models are used in search engines to locate relevant pages and rank them in decreasing order of relevance. They are an integral component of a search engine. The offline gathering of the document is crucial for providing the user with more accurate and pertinent findings. With the web’s ongoing expansions, the number of documents that need to be crawled has grown enormously. It is crucial to wisely prioritize the documents that need to be crawled in each iteration for any academic or mid-level organization because the resources for continuous crawling are fixed. The advantages of prioritization are implemented by algorithms designed to operate with the existing crawling pipeline. To avoid becoming the bottleneck in pipeline, these algorithms must be fast and efficient. A highly efficient and intelligent web crawler has been developed, which employs the hamming distance method for prioritizing the pages to be downloaded in each iteration. This cutting-edge search engine is specifically designed to make the crawling process more streamlined and effective. When compared with other existing methods, the implemented hamming distance method achieves a high value of 99.8% accuracy.
A review on internet of things-based stingless bee's honey production with image detection framework Rohafauzi, Suziyani; Kassim, Murizah; Ja’afar, Hajar; Rustam, Ilham; Miskon, Mohamad Taib
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.pp2282-2292

Abstract

Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.

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