Fuzzy Pi Controller For Frequency Control Of A Diesel-Pv-Battery-Based Islanded Ac Microgrid,
2026
Process Control Technology Dept., Faculty of Technology and Education, Beni-Suef University, Beni-Suef, Egypt
Fuzzy Pi Controller For Frequency Control Of A Diesel-Pv-Battery-Based Islanded Ac Microgrid, M. S. Elborlsy, Ramadan M. Mostafa, Hossam E. Keshta, Mohamed A. Ghalib
Mansoura Engineering Journal
Effective management of modern electrical grids requires intelligent and adaptable control mechanisms to effectively balance power supply and demand, particularly in times of significant disturbances. Microgrids predominantly harness renewable energy sources (RES), which are inherently variable, for electricity generation. However, due to these fluctuations, conventional control systems often struggle to optimize performance under diverse operational conditions. This study addresses the need for improved frequency regulation in isolated AC microgrids (MGs) by proposing a fuzzy PI (FPI) controller capable of dynamically adjusting control strategies to accommodate disturbances such as three-phase faults, sudden changes in load, and variations in solar irradiance. A …
Developing A Collaborative Tool To Foster Communication In Sustainability Research,
2026
Department of Electrical and Electronic Engineering, Munster Technological University, Cork, Ireland
Developing A Collaborative Tool To Foster Communication In Sustainability Research, Nina Hunter, Noëlle-Laetitia Perret, Martin Klepal
Electrical & Electronic Engineering
Climate change necessitates urgent responses based on knowledge produced by teams that transcend disciplinary boundaries, and with members whose work focuses on the generation of knowledge and on the application of knowledge, with some integrating both. Almost a third of Europe’s building stock consists of heritage buildings requiring renovation that is ideally sustainable as part of an energy transition response. The European transdisciplinary CALECHE study team with use-cases in France, Italy, Sweden and Switzerland aims to support decision-making on the sustainable renovation of heritage buildings, via research that employs co-design. However, team members are from various disciplines, with different skillsets …
Cover And Contents,
2026
TÜBİTAK
Cover And Contents
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Exploitation Prioritization And Residual Risk Assessment Based On Hybrid Mcdm Model,
2026
College of Computer Science & Technology Harbin Institute of Technology at Weihai, Weihai, China
Exploitation Prioritization And Residual Risk Assessment Based On Hybrid Mcdm Model, Zibo Wang, Yaofang Zhang, Sicai Lv, Yingzhou Wang, Hongri Liu, Bailing Wang
Turkish Journal of Electrical Engineering and Computer Sciences
Exploitation is one of the most significant ways to launch attacks using vulnerabilities. The increasing number of vulnerabilities and limited allocation of security resources make it impossible to eliminate all exploitations. Because not every vulnerability can be fixed, it is necessary to rank exploitations and subsequently assess the residual risk, which is defined as the remaining threat potential after each elimination. In this paper, a structured and flexible decision support framework based on a hybrid multicriteria decision-making model is proposed for prioritizing exploitations and assessing residual risk. Metrics are treated as criteria in the model. The hybrid model is developed …
A Deep Learning-Based Real-Time No-Reference Image Decolorization Network With Perceptual Preservation,
2026
TÜBİTAK
A Deep Learning-Based Real-Time No-Reference Image Decolorization Network With Perceptual Preservation, Mengjuan Zhao, Yitao Liang, Weiya Shi, Juan Xia
Turkish Journal of Electrical Engineering and Computer Sciences
Currently, grayscale images are preferred as input data for some specific vision tasks. Decolorization is the transformation of a color image into a grayscale image. Efficient decolorization algorithms can improve the overall task efficiency, while perceptual preservation in decolorization can provide more information for further processing. In recent research, traditional methods focus on preserving contrast or detail information with little attention to perceptual features. Deep-learning methods are beginning to consider perceptual preservation, but they run inefficiently. In addition, the decolorization methods lack the optimal target grayscale images for reference. Therefore, we propose a new deep learning-based real-time no-reference decolorization network …
Noninvasive Condition Monitoring For Eccentricity Fault Detection In Large Hydro Generators,
2026
TÜBİTAK
Noninvasive Condition Monitoring For Eccentricity Fault Detection In Large Hydro Generators, Atena Tazikeh Lemeski, Di̇dem Tekgün, Ozan Keysan, Kemal Leblebi̇ci̇oğlu, Murat Göl
Turkish Journal of Electrical Engineering and Computer Sciences
Eccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in Türkiye. The effects of DE faults on the SPSG’s magnetic equivalent circuit parameters are then examined under various fault severities. A …
A Deep Learning Model For Accurate Tomato Leaf Disease Identification,
2026
Bahria Univerisy, Islamabad E-8, Pakistan
A Deep Learning Model For Accurate Tomato Leaf Disease Identification, Maheen Shahzad, Muhammad Abdullah Javed, Erum Ashraf, Hafiz Ishfaq Ahmad, Sabeen Masood
Turkish Journal of Electrical Engineering and Computer Sciences
Recent advances in machine learning and deep learning have greatly improved how we detect plant diseases, making diagnoses more accurate, faster, and easier to scale. However, many existing solutions depend on large, pretrained models that need powerful hardware, which limits their use in the field, especially in areas with limited resources. To tackle this, we designed a custom lightweight convolutional neural network (CNN) built from scratch using 20,000 carefully selected images from the PlantVillage tomato dataset. Our model uses Squeeze-and-Excitation (SE) blocks and Swish activation functions to boost performance, reaching an accuracy of 97.7% while using far fewer computing resources …
Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond,
2026
TÜBİTAK
Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond, Sadiq Ur Rehman, Jawwad Ahmed, Muhammad Zubair, Syed Sajjad Hussain Rizvi
Turkish Journal of Electrical Engineering and Computer Sciences
Nonorthogonal multiple access (NOMA) communication presents a promising solution to the limitations of traditional orthogonal multiple access techniques, offering potential improvements in achievable rates. Multiple-input multiple-output (MIMO), when combined with NOMA (MIMO-NOMA), further enhances these benefits by leveraging the diversity advantages of multiple antennas. Looking ahead, the future of wireless communication hinges on deploying heterogeneous networks (HetNets), facilitating the coexistence of various wireless access networks in a hierarchical fashion. However, the advent of 5G and 6G communications brings shorter channel coherence times, rendering channel reciprocity unreliable. Consequently, conventional channel estimation methods relying on uplink (UL) pilots for downlink (DL) transmission …
A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control,
2026
TÜBİTAK
A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control, Zülal Hi̇lal Yildiz Budak, Seyi̇t Alperen Çeltek, Aki̇f Durdu
Turkish Journal of Electrical Engineering and Computer Sciences
Traffic signal management is a critical challenge due to its environmental, economic, and public health impacts. The maximum weighted flow method (MaxWeightedFlow) was developed to optimize traffic flow at isolated and coordinated urban intersections. This study proposes a new method, the novel MaxWeightedFlow, which includes two key strategies to enhance the classical approach. The first strategy reduces computational burden by estimating vehicle approach times based on instantaneous speeds, improving real-time performance. The second employs regression analysis to optimize the alpha parameter, representing the vehicle waiting coefficient. The proposed approach, the novel MaxWeightedFlow, was evaluated using real-world traffic data from Kilis, …
Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis,
2026
TÜBİTAK
Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis, Mehmet Taci̇ddi̇n Akçay, Abdurrahi̇m Akgündoğdu
Turkish Journal of Electrical Engineering and Computer Sciences
In this study, a dataset comprising 3600 discrete operational snapshots (rather than continuous time-series data) derived from real-field operations is used to obtain a high-accuracy driving profile equation using a second-degree Polynomial Regression method. This equation demonstrates the model’s interpretability. The performance metrics obtained with the second-degree polynomial regression model’s equation are as follows: a coefficient of determination (R2) of 0.84, a Pearson Correlation Coefficient of 0.91, and an RMSE of 11.13. These results indicate the effectiveness of artificial intelligence-based approaches in improving the efficiency of the railway signaling system. The same dataset is also utilized with other machine learning …
Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets,
2026
TÜBİTAK
Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets, Rani Kumari, Bhukya Krishna Naick
Turkish Journal of Electrical Engineering and Computer Sciences
Maintaining reliable and high-quality power delivery becomes increasingly complex with expanding power grids. The lack of protection coordination poses a significant threat, compromising overall system reliability. This research addresses this challenge by proposing a method for coordinating protective devices within the distribution system, specifically during network faults. The proposed approach utilizes a stochastic timed Petri net (STPN) based methodology to model protective device coordination across various fault scenarios. This technique effectively captures the dynamic behavior and interactions of protective equipment, allowing for the anticipation of potential disturbances. This proactive insight facilitates preventative measures to address prewarning situations, thereby preventing cascading …
Proposed Methodology For Correcting Fourier-Transform Infrared Spectroscopy Field-Of-View Scene-Change Artifacts,
2026
Center for Technical Intelligence Studies and Research, Air Force Institute of Technology
Proposed Methodology For Correcting Fourier-Transform Infrared Spectroscopy Field-Of-View Scene-Change Artifacts, Kody A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz
Faculty Publications
Fourier-transform spectrometers are widely used for spectral measurements. Changes in the field of view during measurement introduce oscillations into the measured spectra known as scene-change artifacts. Field-of-view changes also introduce uncertainty about which target the measured spectrum represents. Though scene-change artifacts are often present in dynamic data, their significance is disputed in the current literature. This work presents a theoretical framework and experimental validation for scene-change artifacts. Field-of-view changes introduce variable interferogram offsets, which standard processing techniques assume are constant. The error between the interferogram offset and its estimate is Fourier-transformed, yielding scene-change artifacts, often confused with noise, in the …
Exploring Runtime Sparsification Of Yolo Model Weights During Inference,
2026
Utah State University
Exploring Runtime Sparsification Of Yolo Model Weights During Inference, Tanzeel-Ur-Rehman Khan, Sanghamitra Roy, Koushik Chakraborty
Electrical and Computer Engineering Student Research
In the pursuit of real-time object detection with constrained computational resources, the optimization of neural network architectures is paramount. We introduce novel sparsity induction methods within the YOLOv4-Tiny framework to significantly improve computational efficiency while maintaining high accuracy in pedestrian detection. We present three sparsification approaches: Homogeneous, Progressive, and Layer-Adaptive, each methodically reducing the model’s complexity without compromising its detection capability. Additionally, we refine the model’s output with a memory-efficient sliding window approach and a Bounding Box Sorting Algorithm, ensuring precise Intersection over Union (IoU) calculations. Our results demonstrate a substantial reduction in computational load by zeroing out over 50% …
Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing,
2026
Missouri University of Science and Technology
Robust And High-Efficiency Demodulation Of Ultra-Weak Fbg Arrays In Ofdr-Based Distributed Sensing, Zhaopeng Zhang, Yuxuan Cao, Xu Liu, Dingcheng Wang, Bo Liu, Chen Zhu
Electrical and Computer Engineering Faculty Research & Creative Works
A robust and high-efficiency demodulation scheme for optical frequency domain reflectometry (OFDR) based ultra-weak fiber Bragg grating (UWFBG) array detection system, originating from the Buneman frequency estimation (BFE) algorithm, is proposed and experimentally demonstrated. Due to the current limitations and imperfections of FBG inscription technology, the quasi-continuous inscription approach, along with its less-than-ideal outcomes, gives rise to problems of grating spectrum splitting and spectral distortion during the grating demodulation process. This renders the traditional approach of directly applying the BFE algorithm for grating demodulation ineffective, despite its significant enhancement of demodulation efficiency. To address this issue, we propose utilizing the …
Temperature Dependent High Frequency Performance Of A 62% Algan Channel Hemt,
2026
University of South Carolina
Temperature Dependent High Frequency Performance Of A 62% Algan Channel Hemt, Jiahao Chen, Abdullah Al Mamun Mazumder, Parthasarathy Seshadri, Dheekshinn Nandakumar, Ruixin Bai, Rafael Andrew Choudhury, M. Asif Khan, Chirag Gupta
Faculty Publications
This article reports on the temperature dependent performance of a HEMT with an Al0.62Ga0.38N channel layer and an Al0.84Ga0.16N barrier layer grown by metal–organic chemical vapor deposition. The device in this report was measured at room temperature and elevated temperatures of 100–150 °C. The sheet resistance increased from 3.5 kΩ/sq (25 °C) to 5.4 kΩ/sq (150 °C), while the contact resistance remained nominally similar. For a device with 160 nm gate length and 2 µm source-to-drain length, excellent electrical characteristics have been achieved when the device was operated at 150 °C with …
Optimized Resnet-18 Architecture For Multi-Class Oral Diseases Classification,
2026
Department of Computer Networks and Internet, College of Information Technology, Ninevah University, Mosul 41002, Iraq.
Optimized Resnet-18 Architecture For Multi-Class Oral Diseases Classification, Ahmed Ahmed
Karbala International Journal of Modern Science
In recent years, the classification of oral diseases has gained significant attention due to its influence on public health and the necessity for early and accurate diagnosis. Traditional diagnosis depends on manual clinical assessment, which can be slow and subjective. An optimized and subsequently quantized model is required to provide a faster and more consistent diagnostic support tool. This paper proposes an optimized ResNet-18 architecture for the classification of six oral diseases. The optimization process is based on removing the Rectified Linear Unit (ReLU), Batch Normalization (BN), and convolutional layers from the base ResNet-18 blocks that contain 128 filters. This …
Model-Based Investigation Of The Influence Of Environmental Conditions On The Energy Supply Of Multirotor Uavs,
2026
Flensburg University of Applied Sciences
Model-Based Investigation Of The Influence Of Environmental Conditions On The Energy Supply Of Multirotor Uavs, Morten Roßberg, Hanna Dibbern, Claudia Werner
Journal of Aviation Technology and Engineering
Flight time of unmanned aerial vehicles (UAVs) is limited by available energy, which is affected by the mission profile and external factors, such as environmental conditions. Two main environmental conditions that need to be considered are the impact of wind and ambient temperature on the UAV and its energy supply. The purpose of this study is to examine the effects of wind and ambient temperature to conduct a preliminary evaluation of flight performance and flight limitations. For this reason, three locations in the United States—New York City, Miami, and Fairbanks—are selected and the impact of the considered environmental conditions of …
Research Progress On Generating Perfect Vortex Beams Based On Metasurfaces,
2026
China Jiliang University, Hangzhou
Research Progress On Generating Perfect Vortex Beams Based On Metasurfaces, Xiujuan Liu, Manna Gu, Ying Tian, Mingfeng Zheng, Bo Fang, Zhi Hong, Chee Leong Tan, Xufeng Jing
Electrical and Computer Engineering Faculty Publications and Presentations
This article reviews the latest advances in the generation and control of perfect vector beams using metasurfaces. In recent years, metasurfaces have garnered increasing interest due to their simple fabrication and easy integration. Perfect vortex beams (PVBs), as a type of vector beams, exhibit complex polarization states that require the superposition of multiple phases for their generation. The use of metasurfaces provides a compact platform for the generation of perfect vortex beams and enables more complex vortex beam control tasks, which are quite challenging for traditional optics. This paper begins by introducing the principle of perfect vortex beam generation using …
Universal Sound Separation: Distance-Aware Mixture Simulation, Co-Occurrence Conditioning, And Chain-Of-Inference,
2026
University of Texas at Arlington
Universal Sound Separation: Distance-Aware Mixture Simulation, Co-Occurrence Conditioning, And Chain-Of-Inference, Wonjun Park
Computer Science and Engineering Theses - Archive
Universal Sound Separation (USS) -- the task of disentangling arbitrary sound sources from a single-channel acoustic mixture -- remains an open challenge due to the ill-posed nature of the problem and the distributional gap between synthetic training data and real-world recordings. This thesis addresses three distinct bottlenecks in the USS pipeline: training data realism, inference strategy, and conditioning richness. We first present two knowledge-guided approaches to sound source separation. The first is a distance-aware mixing strategy that leverages Large Language Models (LLMs) to assign plausible loudness relationships between audio sources during training data synthesis. By querying an LLM about the …
Study Of Clustering Technique And Communication Topologies For Cooperative Control-Based Volt-Var Optimization,
2026
University of Kentucky
Study Of Clustering Technique And Communication Topologies For Cooperative Control-Based Volt-Var Optimization, Gaurav Yadav, Yuan Liao, Dan M. Ionel
Electrical and Computer Engineering Faculty Publications
Introducing renewable distributed generation (DG) in the power distribution system causes rapid voltage fluctuations due to its intermittency. This intermittency renders conventional voltage regulation devices such as on-load tap changers (OLTCs) and capacitor banks (CBs) inefficient to regulate rapid voltage changes and leads to reduced equipment lifetime and high operation and maintenance costs. Hence, this calls for non-conventional methods to mitigate such voltage fluctuations. This paper presents a cooperative control-based method aimed to optimally control the reactive power of DG inverters to mitigate the voltage deviations by establishing communication among the DG nodes, and between DG and non-DG nodes. This …
