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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 13, No 2: April 2023" : 111 Documents clear
Assessing contributor features to phishing susceptibility amongst students of petroleum resources varsity in Nigeria Rume Elizabeth Yoro; Fidelis Obukohwo Aghware; Bridget Ogheneovo Malasowe; Obinna Nwankwo; Arnold Adimabua Ojugo
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.pp1922-1931

Abstract

In this observational quasi-experimental study, we recruited 200 participants during the Federal University of Petroleum Resources Effurun’s (FUPRE) orientation, who were exposed to socially engineered (phishing) attacks over nine months. Attacks sought to extract participants’ data and/or entice them to click (compromised) links. The study aims to determine phishing exposure and risks among undergraduates in FUPRE (Nigeria) by observing their responses to socially-engineered attacks and exploring their attitudes to cybercrime risks before and after phishing attacks. The study primed all students in place of cybercrime awareness to remain vigilant to scams and explored the various scam types with their influence on gender, age, status, and their perceived safety on susceptibility to scams. Results show that contrary to public beliefs, these factors have all been found to be associated with scam susceptibility and vulnerability of the participants.
Node classification with graph neural network based centrality measures and feature selection Asmaa M. Mahmoud; Abeer S. Desuky; Heba F. Eid; Hoda A. Ali
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.pp2114-2122

Abstract

Graph neural networks (GNNs) are a new topic of research in data science where data structure graphs are used as important components for developing and training neural networks. GNN always learns the weight importance of the neighbor for perform message aggregation in which the feature vectors of all neighbors are aggregated without considering whether the features are useful or not. Using such more informative features positively affect the performance of the GNN model. So, in this paper i) after selecting a subset of features to define important node features, we present new graph features’ explanation methods based on graph centrality measures to capture rich information and determine the most important node in a network. Through our experiments, we find that selecting certain subsets of these features and adding other features based on centrality measure can lead to better performance across a variety of datasets and ii) we introduce a major design strategy for graph neural networks. Specifically, we suggest using batch renormalization as normalization over GNN layers. Combining these techniques, representing features based on centrality measures that passed to multilayer perceptron (MLP) layer which is then passed to adjusted GNN layer, the proposed model achieves greater accuracy than modern GNN models.
Designing smart pulse flow meters using diversion analysis Pavel S. Micheev; Konstantin A. Muraviev; Elena V. Rezchikova; Kirill V. Selivanov
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.pp1338-1345

Abstract

The operation of modern housing infrastructure is characterized by a constant increase in the cost of the limited resources used. This necessitates the priority implementation in the concept of a smart home of elements aimed at resource saving and their rational management. The study provides an overview of the implementation architectures of the internet of things (IoT) concept in the construction of home automation systems and the requirements they impose on the implementation of smart primary meters of controlled physical quantities. Based on a diversion analysis, a promising smart water meter was developed. The prototype is ergonomic and has a structural form factor convenient for further integration. The designed model of the electronic module of the water flow monitoring system implements, in addition to typical tasks, additional functionality: transfer of recorded indicators and technical information to the cloud storage, warning the user about an emergency situation, accumulation of current data in non-volatile memory. It is possible to use the accumulated statistics for training the predictive analysis module. The proposed architecture option will allow creating energy-efficient elements of home automation systems in the future.
Software aging prediction – a new approach Shruthi Parashivamurthy; Nagaraj Girish Cholli
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.pp1773-1781

Abstract

To meet the users’ requirements which are very diverse in recent days, computing infrastructure has become complex. An example of one such infrastructure is a cloud-based system. These systems suffer from resource exhaustion in the long run which leads to performance degradation. This phenomenon is called software aging. There is a need to predict software aging to carry out pre-emptive rejuvenation that enhances service availability. Software rejuvenation is the technique that refreshes the system and brings it back to a healthy state. Hence, software aging should be predicted in advance to trigger the rejuvenation process to improve service availability. In this work, the k-nearest neighbor (k-NN) algorithm-based new approach has been used to identify the virtual machine's status, and a prediction of resource exhaustion time has been made. The proposed prediction model uses static thresholding and adaptive thresholding methods. The performance of the algorithms is compared, and it is found that for classification, the k-NN performs comparatively better, i.e., k-NN showed an accuracy of 97.6. In contrast, its counterparts performed with an accuracy of 96.0 (naïve Bayes) and 92.8 (decision tree). The comparison of the proposed work with previous similar works has also been discussed.
Active vibration control of flexible beam system based on cuckoo search algorithm Aida Nur Syafiqah Shaari; Muhamad Sukri Hadi; Abdul Malek Abdul Wahab; Rickey Ting Pek Eek; Intan Zaurah Mat Darus
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.pp2289-2298

Abstract

A flexible beam is recognized as a lightweight structure that is prone to excessive vibration, resulting in poor performance. Thus, controlling unwanted vibration is necessary to maintain the system’s performance. Therefore, this study presents a technique to suppress undesired vibration in a flexible beam structure by introducing active vibration control (AVC). However, to develop an effective controller, an appropriate flexible beam model must first be obtained. In recent times, one of the best methods employed to model a flexible beam structure is system identification via a swarm intelligence algorithm. In this study, an intelligent algorithm acknowledged as cuckoo search (CS) was acquainted. The capability of the proposed algorithm was verified using three robustness techniques which were correlation test, pole-zero diagrams and mean square error (MSE). The simulation result showed that the CS algorithm achieved superior performance by achieving the lowest MSE of 6.1547x10-9, a correlation test between a 95% confidence level and high stability. Next, a proportional-integral-derivative (PID) controller tuned by the Ziegler-Nichols method was developed using the transfer function accomplished from the CS model. Two types of interference, namely single and multiple sine waves were introduced to validate the effectiveness of the controller. The controller successfully achieved a 30.2 dB of attenuation level for both disturbances.
Performance evaluation of dynamic source routing protocol with variation in transmission power and speed Saad Elsayed; Mohammed Ibrahim Youssef
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.pp1795-1802

Abstract

Mobile ad-hoc network (MANET) is a set of mobile wireless nodes (devices) which is not rely on a fixed infrastructure. In MANETs, each device is responsible for routing its data according to a specific routing protocol. The three most common MANET routing protocols are: dynamic source routing protocol (DSR), optimized link state routing protocol (OLSR), and ad-hoc on-demand distance vector (AODV). This paper proposes an efficient evaluation of DSR protocol by testing the MANETs routing protocol with variation in transmission power at different speeds. The performance analysis has been given using optimized network engineering tools (OPNET) modeler simulations and evaluated using metrics of average end to end delay and throughput. The results show that the throughput increases as the transmission power increases up to a certain value after which the throughput decreases, also the network work optimally at a certain transmission power which varied at different speed.
A lightweight and secure multilayer authentication scheme for wireless body area networks in healthcare system Mohammad Fareed; Ali A. Yassin
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.pp1782-1794

Abstract

Wireless body area networks (WBANs) have lately been combined with different healthcare equipment to monitor patients' health status and communicate information with their healthcare practitioners. Since healthcare data often contain personal and sensitive information, it is important that healthcare systems have a secure way for users to log in and access resources and services. The lack of security and presence of anonymous communication in WBANs can cause their operational failure. There are other systems in this area, but they are vulnerable to offline identity guessing attacks, impersonation attacks in sensor nodes, and spoofing attacks in hub node. Therefore, this study provides a secure approach that overcomes these issues while maintaining comparable efficiency in wireless sensor nodes and mobile phones. To conduct the proof of security, the proposed scheme uses the Scyther tool for formal analysis and the Canetti–Krawczyk (CK) model for informal analysis. Furthermore, the suggested technique outperforms the existing symmetric and asymmetric encryption-based schemes.
Experimental review of an improving system on wireless power transfer via auto tuning of frequency Kazuya Yamaguchi; Ryusei Okamura; Haruto Terada; Kenichi Iida
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.pp1314-1319

Abstract

Wireless power transfer for electric vehicles is focused because these vehicles cannot run long distance without frequently charging. If these vehicles are charged from outside wirelessly, for example an alternating current (AC) power supply is embed under road, the problem is going to be solved. However, efficiency of wireless power transfer depends on various factors, therefore many contrivances should be considered to realize optimal transfer. In this paper, we focused on frequency of inverter, and created auto tuning system of it in response to the distance of inductors. On this system, frequency was modified automatically by a microcontroller and sensor at the same time position of a load changed. Finally, we confirmed that voltage of light emitting diode (LED) was improved by utilizing our system compared with non-tuning frequency.
A novel hybrid deep learning approach for tourism demand forecasting Houria Laaroussi; Fatima Guerouate; Mohamed Sbihi
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.pp1989-1996

Abstract

This paper proposes a new hybrid deep learning framework that combines search query data, autoencoders (AE) and stacked long-short term memory (staked LSTM) to enhance the accuracy of tourism demand prediction. We use data from Google Trends as an additional variable with the monthly tourist arrivals to Marrakech, Morocco. The AE is applied as a feature extraction procedure to dimension reduction, to extract valuable information and to mine the nonlinear information incorporated in data. The extracted features are fed into stacked LSTM to predict tourist arrivals. Experiments carried out to analyze performance in forecast results of proposed method compared to individual models, and different principal component analysis (PCA) based and AE based hybrid models. The experimental results show that the proposed framework outperforms other models.
Landslide early warning systems: a perspective from the internet of things Vladimir Henao-Céspedes; Yeison Alberto Garcés-Gómez; María Nancy Marín Olaya
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.pp2214-2222

Abstract

Populations located in the vicinity of slopes and soils derived from volcanic ash are constantly at risk due to the possibility of landslides. Such is the case of the city of Manizales, Colombia, which, due to its geomorphological characteristics, has experienced a significant number of landslides that have caused human and economic losses. The Internet of things (IoT) has allowed important technological advances for monitoring, thanks to the low cost and wide coverage of IoT-based systems. Slope monitoring and the development of landslide early warning systems (EWS) have been positively impacted by IoT developments, which shows a relationship. The objective of this article is to review, from the scientific production, the relationship between IoT and EWS. For this purpose, a fragmenting-deriving-combining methodology is applied to focus on a research trends analysis of the subject, from macro-areas such as IoT and EWS to micro areas such as EWS by IoT-based landslides. Finally, the analysis concluded that the conceptual models of IoT and EWS for landslides have some correspondence in some of their layers.

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