Journal of Electrical and Electronic Engineering and Information Technology
type: channel
description: The Journal of Electrical and Electronic Engineering and Information Technology (JEEEIT) is a peer-reviewed scholarly journal published by the College of Electronic Technology Bani Walid (CETB). The journal is dedicated to publishing high-quality research and innovative developments in the fields of electrical engineering, electronics, and information technology. It serves as an interdisciplinary platform for researchers, academics, and industry professionals to present theoretical advances, experimental results, and practical applications that contribute to the advancement of modern engineering systems.
publisher: College of Electronic Technology, Bani Walid, Libya
language: en
publication name: Journal of Electrical and Electronic Engineering and Information Technology
issn: 3136-1579
items: Comparative Evaluation of Control Techniques for a Ball and Beam System Using LabVIEW
items: Design and Development of a Multi-Authentication Smart Door Lock System
items: Modelling, control and simulation for a Two-Wheeled Balancing Mobile Robot System
items: Data explosion of Blockchain-Based Tracking and Tracing Systems: A Review
items: Detecting Epileptic Seizures from EEG Signals Using Machine Learning Techniques: A KNN andSVM Comparative Study
items: An Intelligent Hybrid Intrusion Detection System Based on Random Forest Feature Selection and Isolation Forest Anomaly Detection
items: Deep Learning-Based CT Image Denoising Using Internal Residual Learning with DnCNN
items: Adaptive Smith Predictor with Resonance Compensator (ASP-NRC) for Time-Delay Systems with Mechanical Resonance
items: EEG-Based Brain–Computer Interface for Intelligent Wheelchair Control: A Machine Learning Approach
items: Compare the performance of Dynamic Routing protocols Based protocol Traffic Sent, Network Convergence duration and CPU Utilization using OPNET Modeler
items: Neural-Augmented Sliding Mode Control for Omnidirectional Mobile Robots: A Lyapunov-Guided Hybrid Architecture with Statistical Validation
items: Hybrid CNN-Transformer with PSD Features for EEG-Based Driver Drowsiness Detection
items: Model Predictive Control for Industrial Automation: Enhancing Efficiency and Stability in Smart Manufacturing Systems
items: Machine learning approach to address sarcopenia on skeletal muscle tissue
items: Some Inclusion Relationships of Certain Subclasses of Analytic Functions Defined by Komatu Integral Operator
items: Emitting Devices Identification Based on Variational Mode Decomposition of Captured Bluetooth Signals
items: Comparison Of An Artificial Neural Network Controller And PID Controller In On Line Of Real Time Industrial Temperature Process Control System
items: Developing Measurement System for Sea Waves Height
items: North Sea Reservoir Characterisation by Using Flow Units Technique: A Case Study
items: Design and Simulation of Rectangular Microstrip Patch Antenna Arrays Operating at Ku-band for Satellite Communication Applications
items: Fixed Backoff Contention Window (FBCW) for CSMA-CA in Ad-Hoc Underwater Acoustic Networks
items: Antenna Design and Simulation for 2x2 MIMO System for IEEE-802.11a Application
items: Performance Evaluation of a Communication Network for Digital Substation Automation System
items: Performance Analysis of SIMO-OFDM Wireless Communications Based on MRC Technique over AWGN and Frequency Selective Channels
items: Influence of Initial Backoff Contention Window on Mobile Ad-Hoc Network
items: Measuring Turbidity of Water Based Photo Voltaic Cell and Laser Light
items: Design and Implementation of Closely Spaced MIMO Antennas Zeroth-Order Resonator Antenna (ZORA) with Enhancement Isolation
items: Self-Checking Decoder Using Hardware Redundancy
items: Performance Optimization of Microstrip Patch Antenna Array for WLAN and LTE 4G Technologies
items: Provided Mathematics and Engineering Formulae sheets for exams: Good or poor Approach?

Comparative Evaluation of Control Techniques for a Ball and Beam System Using LabVIEW
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description: This paper presents a comparative study of different control strategies applied to the Ball and Beam system which is inherently nonlinear and open-loop unstable and the system was mathematically modeled and linearized to derive its transfer function and four controllers were designed and evaluated namely a PID controller using the Ziegler–Nichols method a PID controller using the Tyreus–Luyben method an Internal Model Control-based PID controller and a Fuzzy Logic Controller and all controllers were implemented and simulated in LabVIEW to ensure consistent and reliable performance evaluation and they were compared using time-domain performance indicators including rise time settling time overshoot and steady-state error and simulation results showed that conventional PID controllers could stabilize the system but exhibited high overshoot and long settling times with the Tyreus–Luyben PID outperforming the Ziegler–Nichols PID in response speed and overall performance while the IMC-PID controller achieved zero overshoot and rapid settling and the Fuzzy Logic Controller provided smooth and stable response without requiring an accurate mathematical model.
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creator: Shahed Mohammed Esmail
creator: Safa Mohammed Esmail
rights: Copyright (c) 2025 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: 36
ending page: 43

Design and Development of a Multi-Authentication Smart Door Lock System
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description: This project presents the design and implementation of a smart electronic door lock system based on the Arduino Mega microcontroller. The proposed system enhances security by integrating multiple authentication methods, including fingerprint recognition, RFID card identification, facial recognition, and password verification, providing users with flexible and reliable access control. The integration of several security techniques significantly improves system reliability, minimizes unauthorized access, and provides greater flexibility than conventional mechanical locking systems. This project demonstrates the practical application of embedded systems and smart technologies in access control and home security. The proposed design offers a low-cost, scalable, and user-friendly solution that can be further enhanced through integration with Internet of Things (IoT) technologies, mobile applications, and cloud-based monitoring systems for future smart home and smart building applications.
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creator: Abdulkarem M. A. Mohamed
creator: Akram Muntaser
rights: Copyright (c) 2025 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: 28
ending page: 35

Modelling, control and simulation for a Two-Wheeled Balancing Mobile Robot System
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description: Two-Wheeled Balancing Mobile Robots (TWBMRs) are inherently unstable systems that require an efficient control strategy to maintain balance and ensure satisfactory dynamic performance. This paper presents the optimization of a Proportional-Integral-Derivative (PID) controller using the Particle Swarm Optimization (PSO) algorithm for a TWBMR system. The mathematical model of the robot is derived based on the inverted pendulum concept, and the optimized PID controller is implemented and evaluated in the MATLAB/Simulink environment. The PSO algorithm is employed to determine the optimal PID gains by minimizing the Integral of Squared Error (ISE) performance index. The performance of the proposed PSO-PID controller is compared with the conventional Ziegler-Nichols tuning method using transient response characteristics and performance indices. Simulation results demonstrate that the proposed PSO-PID controller significantly improves the system performance, achieving a rise time of 0.0196 s, a settling time of 0.0637 s, a maximum overshoot of 9.83%, and zero steady-state error. Furthermore, the optimized controller achieves lower performance indices, with IAE = 0.0258, ISE = 0.005079, and ITAE = 0.03032, confirming superior tracking accuracy, faster transient response, and enhanced control performance compared with the conventional tuning approach. In addition, robustness analysis under ±25% system parameter variations demonstrate that the proposed controller maintains stable and satisfactory performance, highlighting its effectiveness and reliability for two-wheeled balancing mobile robot applications.
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creator: Abdulnasser Shaeban Alfirjani
creator: Mohamed Naji Muftah
creator: Abobaker Zargoun
rights: Copyright (c) 2022 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: 14
ending page: 27

Data explosion of Blockchain-Based Tracking and Tracing Systems: A Review
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description: Blockchain technology enables secure and transparent information exchange within decentralized environments. Its distributed architecture and continuous protocol improvements help streamline validation processes while supporting network scalability. In blockchain systems, transaction verification relies on digital information units recorded across distributed ledgers. However, this design inherently leads to growing data accumulation over time, as historical transactions must be preserved permanently. This data growth creates significant challenges for storage-dependent applications, particularly tracking and tracing systems, where real-time location monitoring and product authentication generate massive datasets. The resulting storage costs also affect other blockchain-enabled services, including video recognition and artificial intelligence applications, which often underperform when deployed on conventional hardware within tracking environments. This review paper examines blockchain's operational framework, exploring its fundamental concepts, classification schemes, underlying principles, and practical implementations in tracking and tracing contexts. The primary focus is addressing data proliferation issues within blockchain networks, specifically as they relate to tracking and tracing systems. Additionally, this study provides a thorough analysis of existing research contributions in this domain.
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creator: Mohamed Mostafa Montaser
creator: Rasha Ridha Alhanash
creator: Ahlam Elmghirbi
creator: Salim Tahir Alakari
creator: Maisun Alzorgani
creator: Osama Salem shtewi
creator: Mostafa Nser Brka
creator: Asad Dughman
rights: Copyright (c) 2025 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2025-12-01
publication date: 2025-12-01
starting page: 1
ending page: 13

Detecting Epileptic Seizures from EEG Signals Using Machine Learning Techniques: A KNN andSVM Comparative Study
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description: Automated detection of epileptic seizures from electroencephalogram (EEG) recordings remains a clinically important but technically challenging problem. In this paper, we present and comparatively evaluate a machine-learning pipeline for seizure detection based on the CHB-MIT Scalp EEG Database, combining Butterworth band-pass filtering, Power Spectral Density (PSD) feature extraction via Welch’s method, and classification with k-Nearest Neighbors (KNN) and Support Vector Machines (SVM). On subsets of the CHB-MIT database ranging from one healthy and one epileptic subject up to twelve of each, KNN achieved a classification accuracy of 99.3%, while SVM achieved 98.47%, with both classifiers exceeding 98% accuracy at the largest tested sample size. A direct comparison between the two methods reveals that KNN marginally outperforms SVM under the evaluated conditions, while both demonstrate competitive and robust performance. These results corroborate prior evidence that lightweight, interpretable classifiers can achieve strong performance on scalp EEG seizure detection when paired with well-chosen spectral features, and provide a structured basis for selecting between KNN and SVM in clinical or embedded EEG applications.
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creator: Hana Alfughi
creator: Asmaa Nasr Mohammed
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 61
ending page: 66

An Intelligent Hybrid Intrusion Detection System Based on Random Forest Feature Selection and Isolation Forest Anomaly Detection
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description: The rapid expansion of network infrastructure has made cybersecurity a critical concern in modern digital environments. Intrusion Detection Systems (IDS) play a vital role in identifying malicious network activities; however, traditional signature-based approaches often fail to detect novel or sophisticated attacks. This paper presents an intelligent hybrid IDS that combines supervised and unsupervised machine learning techniques to improve detection accuracy and generalizability. The proposed system is evaluated on the CICIDS2017 dataset, which contains labeled traffic records representing both benign and multiple attack categories. The preprocessing pipeline involves removing missing values, eliminating infinite values, and applying binary label encoding with MinMax normalization. SMOTE is applied exclusively to the training set to address severe class imbalance. Feature selection is performed using Random Forest Gini impurity importance, retaining the top 30 most discriminative features from an original 78. The hybrid detection model integrates an Isolation Forest for anomaly detection with a Random Forest classifier for supervised classification, combined through a logical OR voting mechanism. The system is validated using 5-Fold Cross Validation, achieving a mean accuracy of 95.5%, precision of 91.8%, recall of 99.9%, and F1-score of 95.7%, demonstrating superior attack detection over individual model approaches.
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creator: aml ellafi
creator: ABDULMALIK ALSHAYBANI
creator: Mohammed algomaity
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 52
ending page: 60

Deep Learning-Based CT Image Denoising Using Internal Residual Learning with DnCNN
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description: Image denoising is a fundamental task in image processing that aims to enhance the visual quality of images by removing unwanted noise introduced during acquisition, transmission, or storage. Noise can degrade visual content and affect image analysis tasks such as edge detection, object recognition, and feature extraction. The main challenge lies in balancing noise reduction with detail preservation. Traditional algorithms such as Gaussian and median filtering often blur important features of the images. This paper presents a deep learning scheme for denoising CT images, based on Internal Residual Learning with Deep Convolutional Neural Network (DnCNN). The model was used to suppress different levels of noise varying from 0.05 up to 0.4. The proposed model yielded very promising results compared to the classic Gaussian filter, Non-Local median (NLM), and standard DnCNN approaches.
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creator: Abdurahman E. Saleh
creator: Farag J. Zbeda
creator: Salem A. Salem
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 45
ending page: 51

Adaptive Smith Predictor with Resonance Compensator (ASP-NRC) for Time-Delay Systems with Mechanical Resonance
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description: Time delays and mechanical resonance frequently coexist in industrial servo systems such as robotic manipulators, high-speed servos, and active magnetic bearings AMBs. This paper presents an Adaptive Smith Predictor with Resonance Compensator ASP-NRC that simultaneously addresses both challenges. The architecture integrates: i. a full-gain Smith predictor λs=1 with a correctly implemented causal fractional-delay FIR filter whose bulk delay is explicitly separated; ii. a series adaptive notch filter whose zeros cancel the plant poles and whose pole -factor is adapted via an envelope-based scheduler; and iii. a rigorous modular stability analysis establishing uniform ultimate boundedness UUB of all closed-loop signals. Extensive simulations over six benchmark cases with Monte Carlo trials, colored noise, robustness to resonance-frequency mismatch, and severe simultaneous parameter uncertainties show that ASP-NRC outperforms PID, Smith predictor, and Smith + fixed-notch controllers. For the nominal case, ASP-NRC achieves 98.1% ISE reduction versus PID and maintains >5 dB resonance suppression for frequency mismatches up to ±5. Under ideal parameter matching, suppression reaches SdB=-85.18 dB i.e., 85.18 dB effective suppression at the resonance frequency. The controller remains stable under severe combined uncertainties ±20% on all parameters.
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creator: Aleisawee Alsseid
creator: Nehal A. Alsseid
creator: Abdulnasir S. Alfirjani
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-08-15
publication date: 2026-08-15
starting page: 67
ending page: 77

EEG-Based Brain–Computer Interface for Intelligent Wheelchair Control: A Machine Learning Approach
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description: Electroencephalography EEG -based motor imagery brain–computer interfaces BCIs offer a noninvasive means of control for individuals with severe motor impairments, but their translation into physically actuated systems remains challenged by the inherent uncertainty of EEG decoding. This thesis presents the design, implementation, and evaluation of an EEG-based motor imagery BCI for wheelchair control, integrating a Filter Bank Common Spatial Pattern FBCSP feature extraction pipeline with a comparative evaluation of three classifiers, Support Vector Machine SVM, k-Nearest Neighbors KNN, and Linear Discriminant Analysis LDA, on the BCI Competition IV Dataset 2a under a subject-dependent paradigm. Using five-fold stratified cross-validation, SVM achieved the highest mean accuracy 90.7 ± 2.6% and Cohen’s Kappa 0.876 ± 0.035, and was subsequently evaluated on an independent, unseen dataset via a replay based Hardware-in-the-Loop HIL methodology, achieving 85.9% accuracy. A confidence-based command validation stage further improved reliability, raising accuracy among accepted predictions to 97.6% at 60.7% coverage. The classifier output was interfaced with a physical differential-drive wheelchair prototype governed by an encoder-based closed-loop steering control scheme. A multi-tiered safety strategy, comprising confidence gating, self-terminating steering, transition braking, communication timeout supervision, and a hardware emergency cutoff, was incorporated to constrain the consequences of residual classification uncertainty. These results demonstrate that careful integration of classification, command validation, and embedded safety design can yield a robust and practical EEG-based wheelchair control framework, despite the imperfect reliability of motor imagery decoding.
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creator: Hend Eissa
creator: Abdulrauf A. Aqreerah
creator: Hasan N. Ali
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-08-29
publication date: 2026-08-29
starting page: 78
ending page: 88

Compare the performance of Dynamic Routing protocols Based protocol Traffic Sent, Network Convergence duration and CPU Utilization using OPNET Modeler
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description: This paper investigates the performance of three common dynamic routing protocols: RIP, OSPF, and EIGRP. The goal is to assist network administrators in choosing the most suitable protocol for their specific needs. Analyzes critical factors like network convergence time, scalability, memory and CPU requirements, etc.. Through a detailed simulation study using OPNET, the project compares the performance of each protocol across these parameters. The findings demonstrate that EIGRP offers faster network convergence, and better CPU and memory utilization compared to RIP and OSPF. This paper provides valuable insights for network professionals by evaluating these popular routing protocols and highlighting the key factors to consider when making implementation decisions.
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creator: Khalid Ajbarh
creator: Haytham F. Dhaw
creator: ALhadi A. ALhadi
creator: Mohammed A. abdulsalam
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 26
ending page: 36

Neural-Augmented Sliding Mode Control for Omnidirectional Mobile Robots: A Lyapunov-Guided Hybrid Architecture with Statistical Validation
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description: This paper develops a Lyapunov-guided hybrid control architecture combining sliding-mode control (SMC) with neural network residual learning for trajectory tracking of four-wheeled omnidirectional mobile robots (FOMRs). We conduct n=100 Monte Carlo simulations for three trajectories (circle, lemniscate, square) and four noise levels (σ=0,0.005,0.01,0.02) with paired t-tests and Cohen's deffect sizes. The proposed neural-network-augmented SMC (NN-SMC) achieves statistical parity with SMC on the challenging square trajectory under low noise (p=0.5499, d=0.06) and significantly outperforms SMC under high noise (p<0.001, d=0.69). In contrast, pure neural network control fails catastrophically—degrading by a factor of 1.76× under high noise—revealing a critical disturbance-rejection failure mode. Lyapunov stability verification confirms that the theoretical guaranteed uniform ultimate boundedness (GUUB) bound holds across all 12 test conditions. The quadratic convergence margin of 17.4 guarantees rapid error decay in the large-error regime. These results demonstrate that the proposed architecture provides certifiable robustness while leveraging learned residual corrections for performance improvement.
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creator: Aleisawee Alsseid
creator: Abdulnasir S. Alfirjani
creator: Nehal A. Alsseid
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 12
ending page: 25

Hybrid CNN-Transformer with PSD Features for EEG-Based Driver Drowsiness Detection
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description: Driver drowsiness is a major cause of fatal accidents worldwide. EEG signals can capture neural changes linked to fatigue before outward signs appear, but reliable detection is challenging due to high inter-subject variability and the complexity of multi-channel recordings, making robust modeling essential for effective monitoring. This paper proposes a hybrid deep model for EEG-based driver drowsiness detection: a 1-D CNN stem with sinusoidal encoding, Bahdanau-style transformer encoder attention pooling, and Power Spectral Density (PSD) feature pathway concatenated before classification, which addresses the high dimensionality and inter individual variation that make the use of multichannel a difficult task. Using the public EEG Driver Drowsiness Database 11 subjects, 30 channels with a leave-one subject-out and subject-calibration scheme, the study achieved 84.7% mean accuracy, 83.8% mean F1, and 0.912 mean AUC. A 3-limb ablation (CNN-Transformer, PSD, hybrid) shows PSD contributes most discriminative power, with the hybrid matching but not significantly exceeding PSD-only (p < 0.01) over no-calibration baseline, suggesting that PSD features are the main driver of cross-subject performance.
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creator: Asmaa Mohammed
creator: Fatima Alneqrat
creator: Hana Alfughi
creator: Hajer Aghnaya
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 37
ending page: 44

Model Predictive Control for Industrial Automation: Enhancing Efficiency and Stability in Smart Manufacturing Systems
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description: *]:pointer-events-auto R6Vx5W_threadScrollVars scroll-mb-[calc(var(--scroll-root-safe-area-inset-bottom,0px)+var(--thread-response-height))] scroll-mt-[calc(var(--header-height)+min(200px,max(70px,20svh)))]" dir="auto" data-turn-id="request-WEB:4bdbad7e-72be-4354-a6d9-16fa566c4c47-5" data-turn-id-container="request-WEB:4bdbad7e-72be-4354-a6d9-16fa566c4c47-5" data-testid="conversation-turn-12" data-scroll-anchor="false" data-turn="assistant"> Smart manufacturing systems require controllers that maintain product quality and closed-loop regularity while limiting energy demand, actuator motion, and constraint violations. This paper presents a constraint-aware Model Predictive Control (MPC) formulation for a virtual manufacturing process benchmark. The proposed controller combines tracking, control effort, actuator-smoothness, energy, terminal, and slack-penalty terms in a single receding-horizon quadratic program. The contribution is positioned as an integrated simulation-based MPC design and evaluation framework rather than as a new general stability theorem or a plant-validated digital twin. The paper specifies the continuous and discrete process models, delay implementation, disturbance and noise assumptions, energy calculation, controller constraints, tuning procedure, benchmark-controller settings, and performance metrics to improve reproducibility. The proposed controller is compared with PID, Fuzzy PID, and a standard constrained MPC under nominal set-point tracking, load-disturbance rejection, infeasible-reference constraint handling, and 20% model mismatch. In the nominal case, the proposed MPC reduced IAE from 151.3314 to 75.4142, a 50.17% reduction relative to PID. Under load disturbance and model mismatch, IAE reductions relative to PID were 57.17% and 55.62%, respectively. Across energy-reporting scenarios, total energy consumption decreased by approximately 32.65% relative to PID. In the constrained scenario, the proposed MPC eliminated output-constraint v…
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creator: Rabea Besha
rights: Copyright (c) 2026 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2026-07-15
publication date: 2026-07-15
starting page: 1
ending page: 11

Machine learning approach to address sarcopenia on skeletal muscle tissue
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description: Body weight loss (BWL) or skeletal muscle atrophy (SMA) are normal and common in elderly individuals. The satellite cells are located in the space between the basal lamina and the sarcolemma; often these cells are quiescent. There have been several attempts conducted using machine learning methods to uncover the significant age- related genes. However, these investigations have not described the impact of age on skeletal muscle mass in human. Microarray datasets involve tens of thousands of genes, but just a few genes could lead to uncover the relationship between age and muscle atrophy. The main goal of this paper is to identify age-related genes with high accuracy, the final subset of selected genes was based on Multi-filter single wrapper system (MFSWS). Microarray expression profiles, downloaded from GEO database: GSE1428 was chosen to screen the differentially expressed genes of arm tissue and to compare three age groups of both males and females. Results revealed that our approach is able to identify a subset of genes with high performance of accuracy compared to the existed system (Liu et al, 2013) [27] and MFS (2016) [28].
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creator: Dreder Dreder Abdouladeem
creator: Chambo Elferjani
creator: Hmadi Mohamed
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 32
ending page: 36

Some Inclusion Relationships of Certain Subclasses of Analytic Functions Defined by Komatu Integral Operator
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description: The authors introduce several new subclasses of analytic functions. In this paper, we recall some notations and standard definitions of analytic functions in the open unit disc. We state the definition of the Hadamard product (or convolution).We introduce and study some new subclasses of analytic functions, starlike function, convex function, close-to-convex function and quasi-convex function. We introduce and investigate some new subclasses of uniformly starlike. uniformly convex univalent functions. Also, in this paper we state the definition of Komatu integral operator and discuss the use of integral operator. After that, we explain what a new subclass of uniformly convex functions and new subclass of uniformly starlike functions are. Finally, we state the definitions and lemmas concerning the subordinations we need in our discussion. In this paper, we establish Inclusion Relationships for uniformly certain classes of analytic functions, associated with the aforementioned integral operator.
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creator: Milad Drbuk
creator: Maryam Miftah
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 18
ending page: 21

Emitting Devices Identification Based on Variational Mode Decomposition of Captured Bluetooth Signals
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description: Recently, the use of communication systems is increased therefore the security networks has become more important. Radio frequency fingerprinting (RFF) is one of the communication networks security techniques based on identification of the unique features of the RF transient signals. Transient signal detection is a very important part in the classification system. If a transient signal is not detected precisely, then the features extracted from the received signal will not show the correct unique features of the transmitting devices. For this purpose, variational mode decomposition is applied to the recorded Bluetooth (BT) signal before the transient detection process. In this paper, VMD is applied before transient detection as denoysing method in RF fingerprinting of Bluetooth device identification to increase the accuracy of transient detection and the classification rate. The method has three stages: Firstly, VMD is used to decompose the recorded BT signal into a series of band- limited modes. Then, the selected modes are added to reconstruct the original BT signal. Secondly, transient detection and different statistical features are extracted from the transients such as variance, kurtosis and skewness. Finally, a linear support vector machine (LSVM) classifier is used to identify 20 mobile phones under different SNR ranges. 20 mobile phones with 150 transients each were tested in this work. Results show that the proposed VMD identification method based on the decomposition of recorded signal outperforms the existing VMD method based on decomposition of transient signal for different ranges of SNR.
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creator: Alghannai Aghnaiya
creator: Saleh Abofana
creator: Ismael Salem
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 1
ending page: 5

Comparison Of An Artificial Neural Network Controller And PID Controller In On Line Of Real Time Industrial Temperature Process Control System
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description: The conventional PID (proportional-integral- derivative) controller is widely applied in industrial automation and process control because of its simple structure and robustness. However, it does not work well for nonlinear system, time-delayed linear system and time varying system. This paper provides a new approach of PID controller that is based on an artificial neural network and an evolutionary algorithm. An Artificial Neural Network is an effective tool for a highly nonlinear system. Neuro control algorithms are mostly implemented for the application of robotic systems and some development has occurred in process control systems. Process control systems are often nonlinear and difficult to control accurately. Their dynamic models are more difficult to derive than those used in aerospace or robotic control, and they tend to change in an unpredictable manner. This paper gives an example where a multilayered feed forward back propagation neural network is trained offline to perform as a controller for a temperature control system with no priori knowledge regarding its dynamics. The inverse dynamics model is developed by applying a variety of input vectors to the neural network. The performance of neural network based on these input vectors is observed by configuring it directly to control the process. The performance the ANN is compared to the PID controller based on set point change, effect of load disturbances and processes with variable dead time. The result shows that ANN outperforms the PID controller.
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creator: Abdulgani Albagul
creator: Mosa Abdesalam
creator: Hafed Efheij
creator: Bileid Abdulsalam
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 52
ending page: 57

Developing Measurement System for Sea Waves Height
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description: The study of underwater acoustic channels is important for applications such as telemetry between underwater vehicles. There are fundamental limitations associated with underwater communication channels in common with other communications media (i.e, spreading noise, Doppler shift of 1%, signal fading and multipath propagation). These limitations, multipath propagation caused by reflections from the sea surface and sea floor is particularly extreme. An important consideration when dealing with the multipath reflections is the movement of the sea surface, as this can affect the way in which acoustic signals travel. It is therefore necessary to have a good record of the surface conditions during experiments using acoustic communications. There are various methods and transducers that can be used to measure the surface variation. The developed system described in this paper (stepped-contact staff and a MATLAB simulation) is capable of measuring small and high frequency surface waves to a high degree of accuracy. It can operate in water with high impedance (up to 700kΩ per 5) and consists of a simple design. A DC Whetstone Bridge was used to modulate the sea surface movement, a voltage follower operational amplifier was used due to the high impedance of the output of the bridge and a TC500EV A/D converter was used with a micro-controller interfaced to a PC using its RS232 serial port. A MATLAB program simulated and plotted the variation of the depth of the wave staff in centimetres.
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creator: Omar Aldawibi
creator: Abdullatif Khrwat
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 45
ending page: 51

North Sea Reservoir Characterisation by Using Flow Units Technique: A Case Study
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description: An effective and sufficient description and characterisation of the reservoir are ultimately essential to successful reservoir engineering management. The integration of sufficient core analysis data is the primary target of reservoir description to permit identification of zones (Flow Units) with similar fluid-flow characteristics. The identification of flow units is the aim of integrated core analysis programme. The flow units technique is a method of characterising a reservoir and the route to flow unit and reservoir description is dependent on the core data available. This paper presents a practical application of the flow units technique to a classic North Sea reservoir using a statistical analysis for the flow zone indicator (FZI) to differentiate flow units. All laboratory work was conducted using 1 inch cores. Core analysis porosity-permeability data from 410 core lugs was used to work out the porosity-permeability relationship using the flow units technique. After flow unit characterisation, six flow unit groups have been selected, and sample of each individual flow unit were selected for mercury injection analysis using injection pressure up to 50000 psi. Finally, the pore size distribution and mean flow radius were calculated. In this paper, the application of this technique is discussed to examine how a better reservoir description can be achieved for a specific reservoir. This article describes a new attempt to apply this technique to a North Sea reservoir. The technique is more complex than either the depositional or layer model, but is also the most realistic because it takes account of the wide variety of geological and petrophysical characteristics present. The properties used to derive flow units in this reservoir were the core porosity-permeability and permeability measurements for small, medium and large pore- throat radii. The general porosity-permeability cross plot shows a large scatter, indicating poor overall correlation between porosity and…
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creator: Omran Al-Mahtot
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 37
ending page: 44

Design and Simulation of Rectangular Microstrip Patch Antenna Arrays Operating at Ku-band for Satellite Communication Applications
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description: Conventional microstrip patch antenna’s has a small size, but it has low gain, therefore, it not convenient for long distance communication. For conventional applications that require high gain mostly depends on parabolic antennas and arrays antennas. The objective of this paper is to design, and simulation rectangular microstrip patch array antenna to improve the gain for satellite applications working at the operating frequency in Ku_band frequency range from 12 GHz to 18 GHz. Therefore, an analysis of the performance of a single and four planar array antennas are designed at resonant frequency 12GHz using high frequency structure simulator (HFSS) simulation tools. In our simulations, RT/duirod is used as dielectric material with low relative permittivity of 2.2 and loss tangent 0.0009. Moreover, in order to improve the gain of the proposed antenna, four-element (4x1) array antenna is exploited. The simulation results confirm that the return loss is - 21.30dB, VSWR is 1.18, gain is 12.79dB, directivity is 12.89dBi, Bandwidth is 830 MHz (7.1%) at 12 GHz, efficiency 99% and beamwidth at 3dB is 32 at 0 °. As a result, these results can be used in Ku-band for satellite communication applications.
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creator: Hamza Saoud
creator: Mohamed Abdulmajid
creator: Abdulgader Abdalla
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 26
ending page: 31

Fixed Backoff Contention Window (FBCW) for CSMA-CA in Ad-Hoc Underwater Acoustic Networks
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description: Ad-Hoc underwater acoustic networks have become very important in the field of defense industry, rescue operations and etc. But this technique faces some big challenges such as high end to end delay, bandwidth limitation and battery consumptions. The performance of the backoff contention window is the main factor for CSMA-CA that determines the efficiency in sharing and utilizing the limited bandwidth and power consumption in Ad-Hoc underwater acoustic networks. In this paper , practicable distributed backoff contention algorithm, which is named Fixed Backoff Contention Window (FBCW) for CSMA-CA in Ad-Hoc underwater acoustic networks. The FBCW for CSMA-CA is presented in Ad-Hoc underwater acoustic networks. Simulation results show that the proposed technique gives remarkable improvement in terms of average end to end delay, throughput and power consumption.
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creator: Omar Aldawibi
creator: Salah Daw
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 22
ending page: 25

Antenna Design and Simulation for 2x2 MIMO System for IEEE-802.11a Application
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description: The performance and advantages of multi-input multi-output (MIMO) antennas such as offering significant increase in data throughput and link range without additional bandwidth or increased transmitted power. Primary reason to use multiple antennas is to improve link quality and reliability. This is important especially for worst channel conditions like multipath fading, shadowing, etc. MIMO techniques are the most important advancements in recent wireless systems. They are a critical part of important standards such as IEEE 802.16, 802.11 and 4G LTE Technologies. The MIMO technology has attracted attention in wireless communications. In this paper, a compact (2x2) MIMO antenna system, the reduction of mutual coupling between the two antenna elements is achieved by using a simple defected ground structure (DGS) between them to limit the surface waves between them. The distance between the two antenna elements is only 0.3?? mm. The proposed antenna works at 5.8 GHz for wireless local area network (WLAN) applications. The proposed structure has a rectangular shape using FR-4 substrate with relative permittivity of 4.4. The resulted MIMO antenna is found to have a low mutual coupling of about -20.66 dB. The antenna also has a wide relative bandwidth of 18.75%, high total efficiency of 89.5% and acceptable realized gain of about 5.10 dB. The simulation of the proposed antenna has been carried out using Ansoft HFSS and MATLAB software.
subject: Articles
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creator: Mohamed Alsahulli
creator: Sara Ali
creator: Heba Essirte
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 38
ending page: 43

Performance Evaluation of a Communication Network for Digital Substation Automation System
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description: Communications Network and Intelligent Electronic Devices (IEDs) are important functions of a substation automation system (SAS). Measuring the propagation delays and assessing the interoperability performance of IED's in an Ethernet architecture play a critical role in the operation of substation. This paper studies the application of Ethernet in Digital Substation Automation System (DSAS). Then several causes that greatly affect the performance of network are evaluated based on detailed test data. The results of such analysis proposed the key points of promoting a network in digital substation automation system.
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creator: Abdulsslalam Gumaidh
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 12
ending page: 17

Performance Analysis of SIMO-OFDM Wireless Communications Based on MRC Technique over AWGN and Frequency Selective Channels
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description: The analysis of bit error rate (BER) performance of single input multiple output (SIMO) combined with orthogonal frequency division multiplexing (OFDM) wireless communication system exploiting maximum ratio combining (MRC) technique over additive white Gaussian noise (AWGN) and frequency selective channels are studied. SIMO system can be implemented by exploiting maximum ratio combiner (MRC) at the receiver side. MRC provides full spatial receive diversity gain which improves system quality of service (QoS) and as a result combatting a fading due to multipath propagation. Moreover, OFDM offers significant advantages such as bandwidth efficiency and its robustness against multipath delay spread. The level of robustness against the multipath delay spread can be further increased by selecting the length of the cyclic prefix (CP) more than or equal to channel length (CL) (number of multipaths). Adding CP eliminates or minimizes inter-symbol-interference (ISI). In contrast, when CL greater than CP leads to error floor at high SNR. This paper presents simulation BER performance of the combination of SIMO with OFDM systems. The simulation BER performance of conventional single input single-output (SISO-OFDM) one by one wireless system compared with SIMO-OFDM systems one by two, and, four receive antennas, with quadrature phase shift keying (QPSK) digital modulation scheme, over AWGN channel and frequency selective fading channel. The results confirm that the performance of SIMO-OFDM is significantly improved compared with conventional SISO-OFDM system. Moreover, the results also confirm that when CL greater than CP leads to error floor at high SNR. Furthermore, SIMO-OFDM (1Tx, 4Rx) improves BER performance significantly and mitigates ISI effectively.
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creator: Masoud Eddaghel
creator: Mohammed Mohammed
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-12-01
publication date: 2020-12-01
starting page: 6
ending page: 11

Influence of Initial Backoff Contention Window on Mobile Ad-Hoc Network
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description: With current advances in technology, wireless networks are increasing in popularity. Mobile Ad-hoc network (MANETs) is a collection of mobile nodes connected with wireless links. MANET has no fixed topology as the nodes are moving constantly form one place to another place. In Ad-hoc networks, nodes can perform several actions like sending packets, forwarding packets, responding to routing messages, sending recommendations among others. The set of performed actions define the node’s behavior. All the nodes must cooperate with each other in order to route the packets. A routing protocol is used to find routes between mobile nodes to preserve data integrity, delivery, throughput, delay, packet loss for trust management in mobile Ad-hoc networks. This paper discusses the influence of the backoff initial contention windows algorithm and better performance based on metrics such as packet delivery ratio, throughput, average end- to-end delay and total energy consumption by using the network simulator (NS-2).
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creator: Sami Alahmar
creator: Omar Aldawibi
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 55
ending page: 58

Measuring Turbidity of Water Based Photo Voltaic Cell and Laser Light
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description: This paper presents on the design and development of laser beam to measure turbidity of water and liquids. The method is done by applying laser beam on three samples (pure water, water with some milk and water with some juice), and measuring the residual of laser beam which penetrated through the sample. This penetrated beam was measured by a photo voltaic solar which received it and produced a very small voltage as an output proportional to the penetrated beam intensity. The produced voltage was read and calibrated to give NTU reading according to a sensor (photo voltaic solar) output is considered as an input to the control program. The controller which control and monitor the turbidity of selected samples was done by using Lab VIEW and Arduino board as an interface. 18 samples were tested, and only 9 samples were calibrated. The experimental results were satisfied and the proposed method achieved the paper objects with acceptable error ± 1.4%.
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creator: Yousef Abueejela
creator: AbdAlrhman Guinauim
creator: Alhade Algitta
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 49
ending page: 54

Design and Implementation of Closely Spaced MIMO Antennas Zeroth-Order Resonator Antenna (ZORA) with Enhancement Isolation
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description: A high isolation multiple-input multiple- output (MIMO) antenna with closely spaced was presented. This antenna was designed for the purpose of MIMO wireless application. The proposed MIMO antenna consists of two antennas, each operates at 2.5 GHz. The MIMO antenna system elements on a single low-cost FR4 substrate of a compact size of 47.36 mm × 29 mm and is fed by a 50 Ω microstrip. A prototype band WiMAX antenna performance was examined. The results showed that the antenna has at 2.5 GHz a reflection coefficient better than -40 dB. As a new approach, the reduction of mutual coupling depends on current cancellation between two antennas. The proposed antenna achieved better than -30 dB isolation between the two inputs. In addition, high isolation between the antenna elements and the small spacing between antenna elements, the proposed antenna has compact size reduction of approximately 60% compared to conventional patch antennas operating at the same frequency.
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creator: Ahmed Annekaa
creator: Abdulgader Abdalla
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 44
ending page: 48

Self-Checking Decoder Using Hardware Redundancy
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description: A binary decoder is a combinational circuit that converts binary information from n input lines to maximum of 2n unique output lines. But there is no guaranty that the decoder always produce the correct output due to some types of faults. The characteristics of these types of faults render them undetectable by standard test strategies. The detection of intermittent faults requires the use of Concurrent Error Detection technique, which continuously monitors the operation of circuits and compares them with some known reference. Concurrent Error Detection is an important technique in the design of system in which dependability and data integrity are important. This can be achieved by incorporating some form of redundancy into the system. One method of implementing Concurrent Error Detection in Very Large Scale Integrated circuit is through the use of hardware redundancy. This paper investigates the use of hardware redundancy into unchecked system as a mean of incorporating Concurrent Error Detection into a self- checking binary decoder.
subject: Articles
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creator: Khadija Algheitta
creator: Amal Mahfoud
creator: Ali Maamar
creator: Khaled Alnegrat
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 35
ending page: 37

Performance Optimization of Microstrip Patch Antenna Array for WLAN and LTE 4G Technologies
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description: In this paper, array microstrip patch antenna are designed and analyzed for WLAN and LTE 4G technologies, which operating at S- band frequency. Design simulation and optimization processes are carried out with the HFSS and MATLAB software. Antenna arrays are used to achieve higher gain. The larger the number of antenna elements is better the gain of antenna array would be achieved. A propose multiple elements antenna array topology of microstrip patches for use in wireless applications is introduced in this paper. The Active element pattern technique is applied for analyzing microstrip array, which reduces analysis problem and computation. The operating frequency range is from 1 to 3 GHz. The array is mounted on a low-cost FR4 substrate and is fed by a standard 50 Ohm coaxial feed. The simulation of the proposed antenna has been carried out using Ansoft HFSS and MATLAB software.
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creator: Ismail Ammer
creator: Mohamed Alsahulli
creator: Abd Alkader Agnya
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 30
ending page: 34

Provided Mathematics and Engineering Formulae sheets for exams: Good or poor Approach?
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description: Over a very long time the debate about using Mathematics/Engineering formulae sheet/booklet as an aid during assessments, tests and exams has become an ongoing issue and there seems to be an everlasting discussion about it. Some teachers/lecturers make memorizing formulas and fact sheets obligatory and oppose any type of "aids" in any form during tests and exams. Other colleges/university/teachers do allow for the use of only complicated expressions, formulae and equations. However, students are expected to understand these formulae and their application as well as other simple and basic formulae that may not be provided during exams. After an extensive search and consulting many Mathematics/Engineering formula booklets, one has been found that could be readily adapted for use in Engineering colleges and Universities.
subject: Articles
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creator: Omran Al-Mahtot
rights: Copyright (c) 2020 Journal of Electrical and Electronic Engineering and Information Technology https://creativecommons.org/licenses/by-nc-nd/4.0
date: 2020-07-01
publication date: 2020-07-01
starting page: 27
ending page: 29