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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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Implementation of the advanced encryption standard algorithm on an FPGA for image processing through the universal asynchronous receiver-transmitter protocol Talapala Lakshmi Prasanna; Nalluri Siddaiah; Boppana Murali Krishna; Maheswara Rao Valluri
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6114-6122

Abstract

Communication among end users can be based either on wired or wireless technology. Cryptography plays a vital role in ensuring data exchange is secure among end users. Data can be encrypted and decrypted using symmetric or asymmetric key cryptographic techniques to provide confidentiality. In wireless technology, images are exchanged through low-cost wireless peripheral devices, such as radio frequency identification device (RFID), nRF, and ZigBee, that can interface with field programmable gate array (FPGA) among the end users. One of the issues is that data exchange through wireless devices does not offer confidentiality, and subsequently, data can be lost. In this paper, we propose a design and implementation of AES-128 cipher algorithm on an FPGA board for image processing through the universal asynchronous receiver transmitter (UART) protocol. In this process, the advanced encryption standard (AES) algorithm is used to encrypt and decrypt the image, while the transmitter and receiver designs are implemented on two Xilinx BASYS-3 circuits connected with a ZigBee RF module. The encrypted image uses less memory, such as LUTs (141), and also consumes less chip power (0.0291 w), I/O (0.003), block RAM (0.001 w), data, and logic to provide much higher efficiency than wired communication technology. We also observe that images can be exchanged through the UART protocol with different baud rates in run time.
Propose shot boundary detection methods by using visual hybrid features Muna Ghazi Abdulsahib; Matheel E. Abdulmunim
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp299-306

Abstract

Shot boundary detection is the fundamental technique that plays an important role in a variety of video processing tasks such as summarization, retrieval, object tracking, and so on. This technique involves segmenting a video sequence into shots, each of which is a sequence of interrelated temporal frames. This paper introduces two methods, where the first is for detecting the cut shot boundary via employing visual hybrid features, while the second method is to compare between them. This enhances the effectiveness of the performance of detecting the shot by selecting the strongest features. The first method was performed by utilizing hybrid features, which included statistics histogram of hue-saturation-value color space and grey level co-occurrence matrix. The second method was performed by utilizing hybrid features that include discrete wavelet transform and grey level co-occurrence matrix. The frame size decreased. This process had the advantage of reducing the computation time. Also used local adaptive thresholds, which enhanced the method’s performance. The tested videos were obtained from the BBC archive, which included BBC Learning English and BBC News. Experimental results have indicated that the second method has achieved (97.618%) accuracy performance, which was higher than the first and other methods using evaluation metrics.
An efficient scanning algorithm for photovoltaic systems under partial shading Mohamed Bahri; Mohamed Talea; Hicham Bahri; Mohamed Aboulfatah
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp5799-5807

Abstract

This paper proposes a new technique of maximum power point tracking (MPPT) for a photovoltaic (PV) system connected to three phase grids under partial shading condition (PSC), based on a new combined perturb and observe (P&O) with scanning algorithm. This new algorithm main advantages are the high-speed tracking compared to existing algorithms, high accuracy and simplicity which makes it ideal for hardware implementation. Simulation was carried on MATLAB/Simulink. Results showed the effectiveness in speed and accuracy of our algorithm over the existing ones either during standard condition (STC) or PSC. Furthermore, conventional direct power control (DPC) was applied to synchronize successfully the injected power with the grid, which makes our algorithm global and works efficiently under severe conditions.
A self-balancing platform on a mobile car Bushra Amer Tawfeeq; Maher Yahya Salloom; Ahmed Alkamachi
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp5911-5922

Abstract

In the last years, the self-balancing platform has become one of the most common candidates to use in many applications such as flight, biomedical fields, and industry. In this paper, the physical prototype of a proposed self-balancing platform that described the self-balancing attitude in the (X-axis, Y-axis, or biaxial) under the influence of road disturbance has been introduced. In the physical prototype, the inertial measurement unit (IMU) sensor will sense the disturbance in (X-axis, Y-axis, and biaxial). With the determined error, the corresponding electronic circuit, DC servo motors, and the Arduino software, the platform overcame the tilt angle(disturbance). Optimization of the proportional-integral-derivative (PID) controllers’ coefficients by the genetic algorithm method effectively affected the performance of the platform, as the platform system is stable and the platform was able to compensate for the tilt angle in (X-axis, Y-axis, and both axes) and overcome the error in a time that does not exceed four seconds. Therefore, a proposed self-balancing platform’s physical prototype has a high balancing accuracy and meets operational requirements despite the platform’s simple design.
Performance assessment and analysis of development and operations based automation tools for source code management Pooja Mittal; Poonam Narang
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1817-1826

Abstract

Development and operations (DevOps), an accretion of automation tools, efficiently reaches the goals of software development, test, release, and delivery in terms of optimization, speed and quality. Diverse set of alternative automation tools exist for different phases of software development, for which DevOps adopts several selection criteria to choose the best tool. This research paper represents the performance evaluation and analysis of automation tools employed in the coding phase of DevOps culture. We have taken most commonly followed source code management tools-BitBucket, GitHub actions, and GitLab into consideration. Current work assesses and analyzes their performance based on DevOps evaluation criteria that too are categorized into different dimensions. For the purpose of performance evaluation, weightage and overall score is assigned to these criteria based on existing renowned literature and industrial case study of TekMentors Pvt Ltd. On the ground of performance outcome, the tool with the highest overall score is realized as the best source code automation tool. This performance analysis or measure will be a great benefit to our young researchers/students to gain an understanding of the modus operandi of DevOps culture, particularly source code automation tools. As a part of future research, other dimensions of selection criteria can also be considered for evaluation purposes.
Fitness function X-means for prolonging wireless sensor networks lifetime Abdelrahman Radwan; Nasser Abdellatif; Eyad Radwan; Maryam Akhozahieh
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp465-472

Abstract

X-means and k-means are clustering algorithms proposed as a solution for prolonging wireless sensor networks (WSN) lifetime. In general, X-means overcomes k-means limitations such as predetermined number of clusters. The main concept of X-means is to create a network with basic clusters called parents and then generate (j) number of children clusters by parents splitting. X-means did not provide any criteria for splitting parent’s clusters, nor does it provide a method to determine the acceptable number of children. This article proposes fitness function X-means (FFX-means) as an enhancement of X-means; FFX-means has a new method that determines if the parent clusters are worth splitting or not based on predefined network criteria, and later on it determines the number of children. Furthermore, FFX-means proposes a new cluster-heads selection method, where the cluster-head is selected based on the remaining energy of the node and the intra-cluster distance. The simulation results show that FFX-means extend network lifetime by 11.5% over X-means and 75.34% over k-means. Furthermore, the results show that FFX-means balance the node’s energy consumption, and nearly all nodes depleted their energy within an acceptable range of simulation rounds. 
An automated essay evaluation system using natural language processing and sentiment analysi Vijaya Shetty Sadanand; Kadagathur Raghavendra Rao Guruvyas; Pranav Prashantha Patil; Jeevan Janardhan Acharya; Sharvani Gunakimath Suryakanth
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6585-6593

Abstract

An automated essay evaluation system is a machine-based approach leveraging long short-term memory (LSTM) model to award grades to essays written in English language. natural language processing (NLP) is used to extract feature representations from the essays. The LSTM network learns from the extracted features and generates parameters for testing and validation. The main objectives of the research include proposing and training an LSTM model using a dataset of manually graded essays with scores. Sentiment analysis is performed to determine the sentiment of the essay as either positive, negative or neutral. The twitter sample dataset is used to build sentiment classifier that analyzes the sentiment based on the student’s approach towards a topic. Additionally, each essay is subjected to detection of syntactical errors as well as plagiarism check to detect the novelty of the essay. The overall grade is calculated based on the quality of the essay, the number of syntactic errors, the percentage of plagiarism found and sentiment of the essay. The corrected essay is provided as feedback to the students. This essay grading model has gained an average quadratic weighted kappa (QWK) score of 0.911 with 99.4% accuracy for the sentiment analysis classifier.
Attention correlated appearance and motion feature followed temporal learning for activity recognition Manh-Hung Ha; The-Anh Pham; Dao Thi Thanh; Van Luan Tran
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1510-1521

Abstract

Recent advances in deep neural networks have been successfully demonstrated with fairly good accuracy for multi-class activity identification. However, existing methods have limitations in achieving complex spatial-temporal dependencies. In this work, we design two stream fusion attention (2SFA) connected to a temporal bidirectional gated recurrent unit (GRU) one-layer model and classified by prediction voting classifier (PVC) to recognize the action in a video. Particularly in the proposed deep neural network (DNN), we present 2SFA for capturing appearance information from red green blue (RGB) and motion from optical flow, where both streams are correlated by proposed fusion attention (FA) as the input of a temporal network. On the other hand, the temporal network with a bi-directional temporal layer using a GRU single layer is preferred for temporal understanding because it yields practical merits against six topologies of temporal networks in the UCF101 dataset. Meanwhile, the new proposed classifier scheme called PVC employs multiple nearest class mean (NCM) and the SoftMax function to yield multiple features outputted from temporal networks, and then votes their properties for high-performance classifications. The experiments achieve the best average accuracy of 70.8% in HMDB51 and 91.9%, the second best in UCF101 in terms of 2DConvNet for action recognition.
Supervised and unsupervised data mining approaches in loan default prediction Jovanne C. Alejandrino; Jovito Jr. P. Bolacoy; John Vianne B. Murcia
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i2.pp1837-1847

Abstract

Given the paramount importance of data mining in organizations and the possible contribution of a data-driven customer classification recommender systems for loan-extending financial institutions, the study applied supervised and supervised data mining approaches to derive the best classifier of loan default. A total of 900 instances with determined attributes and class labels were used for the training and cross-validation processes while prediction used 100 new instances without class labels. In the training phase, J48 with confidence factor of 50% attained the highest classification accuracy (76.85%), k-nearest neighbors (k-NN) 3 the highest (78.38%) in IBk variants, naïve Bayes has a classification accuracy of 76.65%, and logistic has 77.31% classification accuracy. k-NN 3 and logistic have the highest classification accuracy, F-measures, and kappa statistics. Implementation of these algorithms to the test set yielded 48 non-defaulters and 52 defaulters for k -NN 3 while 44 non-defaulters and 56 defaulters under logistic. Implications were discussed in the paper.
Bit-based cube rotation for text encryption Rihartanto Rihartanto; Didi Susilo Budi Utomo; Herny Februariyanti; Arief Susanto; Wardatul Khafidhah
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp709-717

Abstract

Today's rapid technological developments make information increasingly important. Not just its content, but the channels or media used for information distribution also need to be secured. Information security is an important aspect that requires serious attention. One of the most important parts of information security is implementation of encryption using certain methods or techniques. This study proposes bit-based cube rotation to secure a plaintext. The aim is to produce a ciphertext that satisfies the two properties of cryptography through diffusion to produce confusion. The result shows that in a normal sentence, there is a significant change in the ciphertext which has the highest avalanche effect value of 55.47% and a correlation coefficient of 0.115. This result proves that the bit-based cube rotation can produce a good ciphertext, where the encryption result is not influenced by its original text.

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