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15th International Renewable Energy Congress, IREC 2025

作者： Ghambirlou, Khaled Abosnina, Adel Ali Moschopoulos, Gerry Western University Dept. Electrical and Computer Engineering London Canada College of Electrical and Electronics Technology Benghazi Libya

ISBN: (纸本)9798331516772

Dealing with voltage sags during motor startup is crucial because they can delay power restoration and lead to widespread failures for industrial loads and distribution systems. A novel approach is introduced to investigate voltage sag in distribution networks using solid-state transformers (SSTs) instead of traditional ones. The induction motor startup model is employed to simulate voltage sags, accurately representing the characteristics influenced by conventional industrial loads. The inherent capabilities of SSTs are leveraged to mitigate these voltage sag issues effectively. This study focuses on analyzing voltage sags caused by the activation of induction motors in power systems, with particular emphasis on SST technology, which actively regulates voltage during motor starting by controlling reactive power. The selected distribution system is implemented and tested using MATLAB/Simulink. The results will be compared with previous research on voltage sag during motor startup, demonstrating the improvements and effectiveness of using SSTs in managing power quality issues. This study emphasizes the potential of SSTs to improve the stability and reliability of power systems during the challenging conditions of motor startup. © 2025 IEEE.

关键词： Distribution transformers

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A Comparative Study of Heart Sound Denoising Using Adaptive Line Enhancer with LMF Algorithm 12

A Comparative Study of Heart Sound Denoising Using Adaptive ...

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12th International electrical engineering Congress, iEECON 2024

作者： Pongyart, Witthawas Ongcunaruck, Wisute Faculty Of Engineering King Mongkut's University Of Technology North Bangkok Electrical And Computer Engineering Department Bangkok Thailand

ISBN: (纸本)9798350383591

This paper presents a comparative study of heart sound denoising techniques by employing the Adaptive Line Enhancer (ALE) with the Least Mean Fourth (LMF) algorithm. Three variations of the ALE using LMF are developed and evaluated. The first approach replaces the conventional Least Mean Square (LMS) algorithm with LMF in the ALE structure. The second approach adopts a transform domain framework, and a Hadamard domain LMF is developed and used for ALE. Since the transform domain LMF requires the FIR filter order to match the dimension of the transformation, a novel structure of the transform domain ALE is developed, allowing the FIR filter order to be independent of the transform dimension. The study evaluates the performance of the ALE with LMF algorithm in both domains, alongside the proposed new structure. Simulated tests, focusing on steady-state behavior as the key performance index, demonstrate the superior performance of the newly developed transform domain ALE, surpassing both the time domain ALE with LMS and LMF algorithm and the conventional transform domain approach. © 2024 IEEE.

关键词： Time domain analysis

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A novel approach to detect, analyze and block adversarial web pages

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International Journal of Information technology (Singapore) 2024年第6期16卷 3617-3622页

作者： Kumar, M. Ranjith Naik, Darshana A. Kapila, Neha Mohan, Chinnem Rama Prasad, Ch Raghava Shelke, Chetan Rao, C. V. Guru School of Computer Science and Engineering Vellore Institute of Technology Department of Computer Science and Engineering M S Ramaiah Institute of Technology Department of Electronics and Electrical Engineering Lovely Professional University Department of Computer Science and Engineering Narayana Engineering College Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Alliance College of Engineering and Design Alliance University School of CS & amp AI SR Universtity

The phenomenon of distraction is very common, and its adverse effects are seen among people. The major cause underlying this issue is the ease with which adversarial web sites and web pages can be accessed. It is of utmost importance to locate, evaluate, and actively block such web pages in an effort to comprehensively and globally solve this societal issue. Thus, the given paper proposes an extension or plug-in to detect, analyze, and block websites smartly. The proposed approach takes keywords entered by the user as input into consideration, which eventually leads to the generation of web pages and web links. The filtering of web links is done by the proposed extension, followed by the extraction of features, the utilization of support vector machines (SVM) for binary classification, and the summarization of textual data using natural language processing (NLP). Lastly, the precise results corresponding to relevant web links are presented to the users, which will increase their productivity, thereby reducing their distraction levels under all working circumstances. The performance of the proposed approach is validated against existing recent studies based on evaluation metrics such as adversarial website detection time (ms) and accuracy (%). © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adversarial web pages Distraction Natural language processing (NLP) Support vector machine (SVM) Text summarization

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Identification of nonlinear systems in the frequency domain using two-dimensional Volterra series 10

Identification of nonlinear systems in the frequency domain ...

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10th International Conference on Control, Instrumentation and Automation, ICCIA 2024

作者： Soheili, Masoud Shafieirad, Mohsen Morovati, Tahereh Ronaghi, Erfan Kouhi University of Kashan Department of Electrical and Computer Engineering Kashan Iran Iran University of Science and Technology Department of Electrical Engineering Tehran Iran Shahed University Department of Electrical and Electronic Engineering Tehran Iran

ISBN: (纸本)9798331509972

This paper presents the identification of second-order two-dimensional kernels using the Volterra series model in the frequency domain. The study focuses on nonlinear systems where the input varies over both time and spatial dimensions. The Volterra series, known for its effectiveness in modeling complex nonlinear systems, is extended to two dimensions. The kernels are computed using the least squares method, with the input defined as a product of cosine functions. By simplifying the expressions and applying the Fourier transform, accurate kernel identification is achieved. The results demonstrate the efficacy of this approach in precisely matching the estimated system with the actual system, as evidenced by the minimal identification error. This work contributes to the development of advanced techniques for nonlinear system identification in industrial and scientific applications. © 2024 IEEE.

关键词： Frequency domain analysis

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Comparative analysis of machine learning and ensemble approaches for hepatitis B prediction using data mining with synthetic minority oversampling technique

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Health and technology 2024年第1期14卷 109-118页

作者： Alizargar, Azadeh Chang, Yang-Lang Tan, Tan-Hsu Liu, Tsung-Yu Department of Electrical Engineering College of Electrical Engineering and Computer Science National Taipei University of Technology Taipei 10608 Taiwan Department of Multimedia and Game Science Lunghwa University of Science and Technology Taoyuan 333326 Taiwan

Purpose: Hepatitis B, caused by the Hepatitis B virus (HBV), can harm the liver without noticeable symptoms. Early detection is crucial to prevent transmission and enhance recovery. The main goal is to predict Hepatitis B through cost-effective lab test data, by utilizing machine learning. The primary focus is on evaluating the effectiveness of various algorithms in predicting the disease and their potential to enhance early diagnosis capabilities. Methods: Six distinct algorithms (Support Vector Machine, K-nearest Neighbors, Logistic Regression, decision tree, extreme gradient boosting, random forest) were employed alongside an ensemble model. Analysis involved two rounds: considering all features and key attributes. The Synthetic Minority Oversampling Technique (SMOTE) was employed for data imbalance. Various metrics, including the confusion matrix, precision, recall, F1 score, accuracy, receiver operating characteristics (ROC) curve, area under the curve (AUC), and mean absolute error (MAE), were utilized to assess the efficacy of each predictive technique. The National Health and Nutrition Examination Survey (NHANES) dataset was employed. Results: The experimental results demonstrate that the ensemble model attained the highest accuracy (97%) and AUC (0.997) in comparison to existing models. The analysis revealed that specific crucial features possess substantial predictive significance within this model. Conclusion: The study underscores the potential of the ensemble model as a valuable tool for medical practitioners, leveraging cost-effective and readily obtainable laboratory test data to predict Hepatitis B with remarkable accuracy. By facilitating early diagnosis and intervention, this research presents a promising avenue to enhance patient outcomes in the context of Hepatitis B. © 2023, The Author(s) under exclusive licence to International Union for Physical and engineering Sciences in Medicine (IUPESM).

关键词： Early detection Ensemble model Index terms— Hepatitis B Liver damage Machine learning SMOTE

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Enhancing Grid Resilience Through Hybrid Renewable Energy Systems: Challenges, Control Strategies, and Future Directions: A Review 33

Enhancing Grid Resilience Through Hybrid Renewable Energy Sy...

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33rd Southern African Universities Power engineering Conference, SAUPEC 2025

作者： Lumina, Sampi Denis Elvis Mnguni, Mkhululi Tshemese-Mvandaba, Nomzamo Cape Peninsula University of Technology Electrical Electronic and Computer Engineering Cape Town South Africa

ISBN: (纸本)9798331535162

Expanding renewable energy integration in a traditional grid is a vital means to strengthen the contribution of renewable resources in the energy landscape, aligning with the maintenance of adequate power systems and carbon peaking objectives, especially when power systems networks look into providing reliable, efficient and safe voltage to loads end consumption. As electricity demand keeps growing, and technologies evolve, traditional power systems are at some stage no longer able to provide sufficient power to the load. Emerging in this regard is the idea of incorporating new technology in the traditional grid to improve the generation capacity. Hybrid Renewable Energy appears to be a suitable solution for improving grid resilience and rentability, creating a primacy for power system performance benchmarking to its objectives. Thus, call to look at some contributions in the field of Hybrid Renewable Energy influence in power systems. © 2025 IEEE.

关键词： Hybrid power

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Voltage Profile Improvement and Loss Minimization in a Transmission Line Using FLC-Based UPFC at Bahir Dar Substation-II 230 kV Line 11th

Voltage Profile Improvement and Loss Minimization in a Trans...

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11th EAI International Conference on Advancement of Science and technology, ICAST 2023

作者： Birlie, Minale School of Electrical and Computer Engineering Dire Dawa University Institute of Technology Dire Dawa Ethiopia

ISBN: (纸本)9783031641503

This article examines the power flow and voltage profile of a transmission line system. A flexible alternating current transmission system (FACTS) device named unified power flow controller (UPFC) incorporating fuzzy logic controller (FLC) has been implemented to reduce power loss and enhance voltage profile after the current network analysis was completed. Utilizing Newton-Raphson load flow analysis, the weakest bus in a system is identified for the installation of UPFC. The 341-km-long, 230 kV line that runs from Bahir Dar to Alamata serves as the validation point for this controller’s operation. Therefore, to demonstrate the performance of FLC-UPFC, a comparison has been done using conventional proportional-integral (PI)-based UPFC, FLC-UPFC, and without UPFC at the same load bus. For example, receiving end voltage improves by 11% when PI-UPFC is used, while real and reactive power flows improve by 13.7% and 8.6%, respectively. Voltage rises by 14.9% when the recommended FLC-UPFC is used, while the real and reactive power flows have improved by 21.6% and 15.05%, respectively. The findings indicate that the FLC-UPFC technique, which is being proposed, performs better than the conventional PI controller. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Load flow control

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Exploring Deep Brain Stimulation Effects in a Hyperbolic-Based Computational Model of Neuronal Spiking Patterns

Exploring Deep Brain Stimulation Effects in a Hyperbolic-Bas...

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2023 Congress in computer Science, computer engineering, and Applied Computing, CSCE 2023

作者： Vakil, Ardavan Faezipour, Miad School of Engineering Technology Electrical & Computer Engineering Technology Purdue University West LafayetteIN United States

ISBN: (纸本)9798350327595

Deep brain stimulation (DBS) is a device that relies on methods to desynchronize adverse neurodegenerative activities within the brain. It is a well-known treatment method for people diagnosed with Parkinson's disease (PD). The adjustment of a precise definition of DBS signal parameters is critical to breaking the synchrony and burst of the increased neuronal activity, while preventing tissue or electrode damage, and also considering reducing the energy consumption for prolonging the battery life of the DBS device. In this research in progress, we study a pulse DBS waveform with delay between its cathodic and anodic parts to disrupt and desynchronize the firing/bursting patterns of Parkinsonian neuronal cell activities. We use a hyperbolic neuronal spiking pattern model to represent the signal activity of the brain. Specifically, we model a neuron infected with bursting behavior similar to that of PD, and apply DBS current to observe the effect, computationally. The expected output of applying the proposed pulse delayed DBS waveform is to break the bursting pattern and convert the bursting spike into a regular tonic spike. In addition, the promising results of pulse delayed waveforms in terms of eliciting action potential, desynchronization of the bursting behavior, and reduced energy consumption, can potentially enhance the performance of the applied DBS. © 2023 IEEE.

关键词： deep brain stimulation hyperbolic model neuronal spiking pattern Parkinson's Disease pulse delayed wave-form

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Design of All Textile Ultra-Wideband Monopole Antenna for Wearable Applications 12

Design of All Textile Ultra-Wideband Monopole Antenna for We...

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12th International electrical engineering Congress, iEECON 2024

作者： Thaiwirot, Wanwisa Ardhan, Jariyanee Prengsri, Saowarat Akkaraekthalin, Prayoot King Mongkut's University Of Technology North Bangkok Faculty Of Engineering Department Of Electrical And Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350383591

This paper proposes the design of all textile ultra-wideband (UWB) monopole antenna. The textile antenna structure includes of the octagonal-shaped patch and modified ground plane. Conventional rectangular ground plane is modified as curve-shaped ground plane with circular parasitic patch. By using this ground plane structure, it can shift the lowest edge of impedance bandwidth to lower frequency and enhances the directivity. The textile antenna can provide a compact size having dimension of 35 × 40 × 1 mm3. Based on simulation, the impedance bandwidth of antenna is 138% (2.36-12.78 GHz) and maximum gain is 5.19 dBi at 7 GHz. The textile antenna achieves very wide bandwidth covering ISM band and UWB which is suitable for wearable applications. © 2024 IEEE.

关键词： Slot antennas

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Real Time computer Vision Based Robotic Arm Controller with ROS and Gazebo Simulation Environment 14

Real Time Computer Vision Based Robotic Arm Controller with ...

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14th International Conference on electrical and Electronics engineering, ELECO 2023

作者： Aksoy, Egemen Çakir, Arif Dorukan Erol, Berat Alper Gumus, Abdurrahman Izmir Institute of Technology Electrical and Electronics Engineering Turkey Izmir Institute of Technology Computer Engineering Turkey

ISBN: (纸本)9798350360493

Robotic arms are widely prevalent and find utility in a variety of applications. However, a significant and widespread challenge faced by these arms is their inability to replicate the intricate functionalities of a human hand, primarily due to the distinct structure of the hand. The primary objective of this work is to create a simulation of a robotic arm that can replicate the movements and functions of a human hand in real-time. Data obtained from hand and arm gestures created with Mediapipe will be transferred in real-time to the robotic arm that is visualized and simulated on ROS and Gazebo. Thus, the hand and arm movements of the user in front of the camera will be effective in real-time on the manipulable joints. This advancement holds the potential to facilitate the construction of a robot capable of emulating both the hand and the arm of humans with high fidelity, thereby enabling comprehensive control over the robotic arm's actions in real-time. © 2023 IEEE.

关键词： Robotic arms

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