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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 96 Documents
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Search results for , issue "Vol 11, No 5: October 2021" : 96 Documents clear
Identification of important features and data mining classification techniques in predicting employee absenteeism at work Amal Al-Rasheed
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4587-4596

Abstract

Employees absenteeism at the work costs organizations billions a year. Prediction of employees’ absenteeism and the reasons behind their absence help organizations in reducing expenses and increasing productivity. Data mining turns the vast volume of human resources data into information that can help in decision-making and prediction. Although the selection of features is a critical step in data mining to enhance the efficiency of the final prediction, it is not yet known which method of feature selection is better. Therefore, this paper aims to compare the performance of three well-known feature selection methods in absenteeism prediction, which are relief-based feature selection, correlation-based feature selection and information-gain feature selection. In addition, this paper aims to find the best combination of feature selection method and data mining technique in enhancing the absenteeism prediction accuracy. Seven classification techniques were used as the prediction model. Additionally, cross-validation approach was utilized to assess the applied prediction models to have more realistic and reliable results. The used dataset was built at a courier company in Brazil with records of absenteeism at work. Regarding experimental results, correlationbased feature selection surpasses the other methods through the performance measurements. Furthermore, bagging classifier was the best-performing data mining technique when features were selected using correlation-based feature selection with an accuracy rate of (92%).
Implementation of modular MPPT algorithm for energy harvesting embedded and IoT applications Krishnaveni Kommuri; Venkata Ratnam Kolluru
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3660-3670

Abstract

The establishment of the latest IoT systems available today such as smart cities, smart buildings, and smart homes and wireless sensor networks (WSNs) are let the main design restriction on the inadequate supply of battery power. Hence proposing a solar-based photovoltaic (PV) system which is designed DC-DC buck-boost converter with an improved modular maximum power point tracking (MPPT) algorithm. The output voltage depends on the inductor, capacitor values, metal oxide semiconductor field effect transistor (MOSFET) switching frequency, and duty cycle. This paper focuses on the design and simulation of min ripple current/voltage and improved efficiency at PV array output, to store DC power. The stored DC power will be used for smart IoT systems. From the simulation results, the current ripples are observed to be minimized from 0.062 A to 0.02 A maintaining the duty cycle at 61.09 for switching frequencies ranges from 300 kHz to 10 MHz at the input voltage 48 V and the output voltage in buck mode 24 V, boost mode 100 V by maintaining constant 99.7 efficiencies. The improvised approach is compared to various existed techniques. It is noticed that the results are more useful for the self-powered Embedded & Internet of Things systems.
Model reduction design for continuous systems with finite frequency specifications Miloud Koumir; Abderrahim El-Amrani; Ismail Boumhidi
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3956-3963

Abstract

This paper is concerned with the problem of model reduction design for continuous systems in Takagi-Sugeno fuzzy model. Through the defined FF H∞ gain performance, sufficient conditions are derived to design model reduction and to assure the fuzzy error system to be asymptotically stable with a FF H∞ gain performance index. The explicit conditions of fuzzy model reduction are developed by solving linear matrix inequalities. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.
Experimental study of the impact of dust on azimuth tracking solar PV in Sharjah Mohamed A. M. Abdelsalam; Fahad Faraz Ahmad; Abdul-Kadir Hamid; Chaouki Ghenai; Oussama Rejeb; Monadhel Alchadirchy; Waleed Obaid; Mamdouh El Haj Assad
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3671-3681

Abstract

Dust is one of the significant constraints in utilizing solar photovoltaic systems under harsh weather conditions in the desert regions due to creating a shadow that blocks solar irradiance from reaching solar cells and consequently, significantly reducing their efficiency. In this research, experimental study was performed to comprehend the nature of dust particles and their impact on the electrical power output that is generated from azimuth tracking solar PV modules under Sharjah environmental conditions in winter season. According to laboratory experiments, the power losses are linearly related to the dust accumulated density on the surface of the solar panel with a slope of 1.27% per g/m2. The conducted Outdoor studies revealed that the absolute reduction in output power increased by 8.46% after 41 continuous days with one low-intensity rainy day. The linear relationship obtained from indoor experiments was applied later to estimate the dust deposited density on the outdoor setup. The results showed that a regular cleaning process every two weeks is recommended to maintain the performance and to avoid the soiling loss. This work will help engineers in the solar PV plants to forecast the dust impact and figure out the regularity of the cleaning process in case of single axis tracking systems.
Offline signature recognition system using oriented FAST and rotated BRIEF Abdel-Karim Al-Tamimi; Asseel Qasaimeh; Kefaya Qaddoum
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4095-4103

Abstract

Despite recent developments in offline signature recognition systems, there is however limited focus on the recognition problem facet of using an inadequate sample size for training that could deliver reliable and easy to use authentication systems. Signature recognition systems are one of the most popular biometric authentication systems. They are regarded as non-invasive, socially accepted, and adequately precise. Research on offline signature recognition systems still has not shown competent results when a limited number of signatures are used. This paper describes our proposed practical offline signature recognition system using the oriented FAST and rotated BRIEF (ORB) feature extraction algorithm. We focus on the practicality of the proposed system, which requires only the minimum number of signatures per user to achieve a high level of fidelity. We manifest the practicality of our approach with a signature database of 300 signatures from 100 different individuals, implying that only two signatures are needed per person to train the proposed system. Our proposed solution achieves a 91% recognition rate with a median matching time of only 7 ms.
Comparative analysis of routing techniques in chord overlay network Omoruyi Osemwegie; Samuel John; Adewale Adeyinka; Etinosa Noma-Osaghae; Kennedy Okokpujie
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4361-4372

Abstract

Overlay networks are not a new field or area of study. This domain of computing will someday drive P2P systems in various application areas such as block-chain, energy trading, video multicasting, and distributed file storage. This study highlights the two widely known methods of routing information employed in one of such overlay networks called chord. In this study, simulations of both routing modes (iterative and recursive) and their variations under no-churn (leaving and joining of nodes) and churn conditions was carried out. The routing parameter (successor list size) was varied for each of the routing techniques in a simulation study. The results obtained show that semi recursive routing gives a better routing performance under churn scenarios.
Lifting dual tree complex wavelets transform Hilal Naimi; Amelbahahouda Adamou-Mitiche; Lahcène Mitiche
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4008-4015

Abstract

We describe the lifting dual tree complex wavelet transform (LDTCWT), a type of lifting wavelets remodeling that produce complex coefficients by employing a dual tree of lifting wavelets filters to get its real part and imaginary part. Permits the remodel to produce approximate shift invariance, directionally selective filters and reduces the computation time (properties lacking within the classical wavelets transform). We describe a way to estimate the accuracy of this approximation and style appropriate filters to attain this. These benefits are often exploited among applications like denoising, segmentation, image fusion and compression. The results of applications shrinkage denoising demonstrate objective and subjective enhancements over the dual tree complex wavelet transform (DTCWT). The results of the shrinkage denoising example application indicate empirical and subjective enhancements over the DTCWT. The new transform with the DTCWT provide a trade-off between denoising computational competence of performance, and memory necessities. We tend to use the PSNR (peak signal to noise ratio) alongside the structural similarity index measure (SSIM) and the SSIM map to estimate denoised image quality.
Dynamic modeling and transient stability analysis of distributed generators in a microgrid system Hamed Ahmadi; Qobad Shafiee; Hassan Bevrani
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp3692-3703

Abstract

Increasing the penetration level of distributed generation units as well as power electronic devices adds more complexity and variability to the dynamic behaviour of the microgrids. For such systems, studying the transient modelling and stability is essential. One of the major disadvantages of most studies on microgrid modelling is their excessive attention to the steady state period and the lack of attention to microgrid performance during the transient period. In most of the research works, the behaviour of different microgrid loads has not been studied. One of the mechanisms of power systems stability studies is the application of state space modelling. This paper presents a mathematical model for connected inverters in microgrid systems with many variations of operating conditions. Nonlineal tools, phase-plane trajectory analysis, and Lyapunov method were employed to evaluate the limits of small signal models. Based on the results of the present study, applying the model allows for the analysis of the system when subjected to a severe transient disturbance such as loss of large load or generation. Studying the transient stability of microgrid systems in the standalone utility grid is useful and necessary for improving the design of the microgrid’s architecture.
Software engineering based secured E-payment system Muayad Sadik Croock; Rawan Ali Taaban
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4413-4422

Abstract

Nowadays, the E-payment systems have been considered to be the safe way of money transfer in most of modern institutes and companies. Moreover, the security is important side of these systems to ensure that the money transfer is done safely. Software engineering techniques are used for guaranteeing the applying of security and privacy of such systems. In this paper, a secure E-payment system is proposed based on software engineering model and neural network technology. This system uses different proposed algorithms for applying authentication to the devices of users as mobile application. They are used to control the key management in the system. It uses the neural network back-propagation method for ensuring the security of generated keys that have sufficient random levels. The proposed system is tested over numerous cases and the obtained results show an efficient performance in terms of security and money transfer. Moreover, the generated keys are tested according to NIST standards.
MQTT-PRESENT: Approach to secure internet of things applications using MQTT protocol Imane Sahmi; Abderrahim Abdellaoui; Tomader Mazri; Nabil Hmina
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4577-4586

Abstract

The big challenge to raise for deploying the application's domain of the Internet of Things is security. As one of the popular messaging protocols in the IoT world, the message queue telemetry transport (MQTT) is designed for constrained devices and machine-to-machine communications, based on the publish-subscribe model, it offers a basic authentication using username and password. However, this authentication method might have a problem in terms of security and scalability. In this paper, we provide an analysis of the current research in the literature related to the security for the MQTT protocol, before we give a brief description of each algorithm used on our approach, to finally propose a new approach to secure this protocol based on AugPAKE algorithm and PRESENT encryption. This solution provides mutual authentication between the broker and their clients (publishers and subscribers), the confidentiality of the published message is protected twice, the integrity and non-repudiation of MQTT messages which is protected during the process of transmission.

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