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Epoxy-impregnated aramid composites, notable for their excellent mechanical and insulation qualities, are pivotal in electrical engineering and electronics. However, their performance is severely restrained by interface issues. This research proposes an effective modification strategy for improving interface property by employing non-thermal atmospheric plasma to introduce active functional groups onto aramid paper. The modified composites demonstrated a 26 % increase in tensile strength and a 20 % enhancement in breakdown strength at best, alongside inhibited charge transport properties and reduced partial discharge under operational electric fields. Molecular simulation suggests that plasma treatment bolsters interface hydrogen bonding, restricting the chain mobility of the resin molecular, and thus augmenting inter-phase compatibility. This study offers a factual perspective on improving resin-impregnated composites, laying a theoretical foundation for advancing high-performance materials in power industries. [Display omitted] [ABSTRACT FROM AUTHOR]

The September 2023 issue of the IETE Journal of Research features 60 articles covering a wide range of topics in electrical engineering. These include communications, electromagnetics, opto-electronics, computers and computing, control engineering, electronic circuits, devices and components, instrumentation and measurements, medical electronics, and power electronics. The articles discuss ongoing research and recent advancements in these fields, presenting innovative approaches and techniques. Some specific examples include securing sensitive data in communications, improving the performance of OFDM systems through deep learning, antenna design and bandwidth enhancement in electromagnetics, and the application of artificial intelligence in the legal field. The issue also covers topics such as image data security and medical applications of electronics. Each research paper in the issue focuses on a specific problem, proposes a solution or method, and provides results and comparisons to demonstrate its effectiveness. The authors of the papers are experts in their respective fields, with extensive experience and qualifications. [Extracted from the article]

The papers address the following key areas: ' B I Applications of IoT and digital twin in electrical power systems: A comprehensive survey i b ': This research paper reviews the applications of the Internet of Things (IoT) and digital twin technology in electrical power systems. With the growth of Internet of Things (IoT) techniques, applications have become smarter, and linked gadgets allow them to be used in many parts of power systems. ' B I A new low-cost and low-power industrial Internet of Things infrastructure for effective integration of distributed and isolated systems with smart grids i b ': This research paper provides an Internet of Things (IoT) infrastructure solution based on a newly designed low-cost microcontroller-based IoT remote terminal unit (RTU) to integrate new, old, and conventional sites of existing grids with smart grids. [Extracted from the article]

This document discusses the increasing demand for high-efficient isolated DC/DC converters in renewable energy applications. It presents seventeen papers that cover various topics such as reducing switch count and current balancing, addressing voltage ringing issues, solving current unbalance problems, and optimizing converter design. The papers provide experimental results and propose innovative methods to improve the efficiency and performance of DC/DC converters in renewable energy applications. The document also includes three research papers related to power converters, including one on a prototype for NanoGrid applications, one on a new DC-DC bipolar resonance converter, and one on enhancing the stability of a DCMG cluster. The text also includes acknowledgments and biographies of the guest editors. [Extracted from the article]

The text describes the organization of a Special Issue in the Sensors journal titled "Recent Trends and Advances in Telecommunications and Sensing." The Special Issue was based on papers presented at the 17th International Conference on Telecommunications (ConTEL) held at Graz University of Technology in Austria. The conference covered various topics related to telecommunications, including optical communications, satellite communications, IoT, and security. Nine papers were accepted for publication in the Special Issue, covering subjects such as network experimentation, optical camera communications in healthcare, and anomaly detection in firewall logs. The authors of the text are Erich Leitgeb, Maja Matijašević, Wilfried Gappmair, and Mario Kušek. [Extracted from the article]

Article abstract contains maximum of 150 words and is written in the language of the article. The abstract should reflect the content of the article as precisely as possible. TECHNICAL JOURNAL is a trade journal that publishes scientific and professional papers from the domain(s) of mechanical engineering, electrical engineering, civil engineering, multimedia, logistics, etc., and their boundary areas. This document must be used as the template for writing articles so that all the articles have the same layout. [ABSTRACT FROM AUTHOR]

This paper presents a systematic literature survey on diagnostic methods used for railway materials and systems. The authors analyze various railway accident reports, focusing on the types of failures described and their causes. Previous review papers have addressed various aspects of railway systems diagnostics; however, most of the existing research focuses on specific parts of the rail vehicle or subsystems. In contrast, this survey focuses on railway diagnostic systems rather than general diagnostic methods used in mechanical and electrical engineering. The authors classify the types of failures and diagnostic methods that are used in rail transport into two categories: infrastructure and rolling stock. The purpose of this paper is to systematize the types of failure that occur in railway transport systems; identify the state-of-the-art means and methods of diagnostics in railway materials and systems, with particular focus on new research findings; and identify trends and possible research gaps in need of further development. [ABSTRACT FROM AUTHOR]

This document is a guest editorial from the journal IET Generation, Transmission & Distribution. It emphasizes the need to improve the reliability and resilience of modern power systems in the face of various threats. The editorial highlights the importance of modeling, assessing, and enhancing the reliability and resilience of power grids that are increasingly incorporating grid-edge resources. The document also provides a summary of the papers included in a special issue of the journal, which cover topics such as planning reliable energy systems, analyzing power grid operations, and enhancing service restoration and grid-support load response. Additionally, the text discusses the issue of equity in power distribution system restoration processes and proposes a model called the equity-aware power distribution system restoration model. The model aims to balance equity and resilience in restoring power after outages by focusing on fair distribution of energy resources while maintaining operational efficiency. The text also includes brief biographies of several authors who have contributed to the field of power electronics and power system reliability. [Extracted from the article]

A. Montisci, S. Cargangiu, G. Sias, B. Cannas and A. Fanni, in [[16]], present a real time bolometer tomographic reconstruction algorithm in nuclear fusion reactors based on the combination of highly correlated grid elements to yield a square coefficient matrix with sufficiently low condition number. The procedure was derived from the polynomial reproduction properties satisfied by the Hermite splines without requiring the explicit construction/evaluation of the basic functions. The paper authored by Y.E. Shao and S.C. Lin [[1]] presents an innovative time-delay neural network-based classifier to diagnose the quality variables that cause out-of-control signals for a normal multivariate process with variance shifts. It is now clear that cooperation between academia and industries is crucial for social, cultural, technological and economic progress and innovation. [Extracted from the article]

The International Journal of Electrical Engineering and Computing (IJEEC) is a recently established journal published by the Faculty of Electrical Engineering at the University of East Sarajevo, Bosnia and Herzegovina, and Academic Mind from Belgrade, Serbia. The journal aims to promote academic and professional research development in the field of electrical engineering and computing. It accepts original research papers, review papers, case studies, and short reports, which are reviewed by at least two independent reviewers. The journal is published electronically in English, with high-quality papers published twice a year. The current issue, Volume 7, Issue 2, includes five papers presented at the XXII International Symposium INFOTEH¿ JAHORINA 2023. The editorial board expresses gratitude to the authors and peer-reviewers and strives to maintain the journal's reputation in the academic community. [Extracted from the article]

The general evolution of fieldbus systems has been variously affected by both computer electrical engineering and science. First, the main contribution undoubtedly originated from network IT systems, when the Open Systems Interconnection model was presented. This reference model with seven layers was and remains the foundation for the development of numerous advanced communication protocols. In this paper, the conducted research resulted in a major contribution; specifically, it describes the mathematical model for the Modbus protocol and defines the acquisition cycle model that corresponds to incompletely defined protocols in order to provide a timestamp and achieve temporal consistency for proposed Modbus Extension. The derived technical contribution of the authors is to exemplify the functionality of a typical industrial protocol that can be decomposed to improve the performance of data acquisition systems. Research results in this area have significant implications for innovations in industrial automation networking because of increasing distributed installations and Industrial Internet of Things (IIoT) applications. [ABSTRACT FROM AUTHOR]

Introduction: Accurate prediction of line losses in distribution networks is crucial for optimizing power system planning and network restructuring, as these losses significantly impact grid operation quality. This paper proposes a novel approach that combines advanced feature selection techniques with Stacking ensemble learning to enhance the effectiveness of distribution network loss analysis and assessment. Methods: Utilizing data from 44 substations over an 18-month period, we integrated a Stacking ensemble learning model with multiple feature selection methods, including correlation coefficient, maximum information coefficient, and tree-based techniques. These methods were employed to identify the key predictors of power loss in the distribution network. Results: The proposed model achieved a Mean Absolute Percentage Error (MAPE) of 3.78% and a Root Mean Square Error (RMSE) of 1.53, demonstrating a substantial improvement over traditional linear regression-based prediction methods. The analysis revealed that historical line loss and line active power were the most influential predictive variables, while the inclusion of time-related features further refined the model's performance. Discussion: This study highlights the efficacy of combining multiple feature selection methods with Stacking ensemble learning for predicting power loss in 10 kV distribution networks. The enhanced accuracy and reliability of the proposed model offer valuable insights for electrical engineering applications, potentially contributing to more efficient and sustainable energy distribution systems. Future research could explore the applicability of this approach to other distribution network voltage levels and investigate the incorporation of additional environmental and network-specific factors to further improve power loss prediction. [ABSTRACT FROM AUTHOR]

Though theoretical knowledge is essential, there is a growing belief that when teaching applied sciences, particularly engineering, a great emphasis should be placed on the development of students’ practical skills. Therefore, some courses and curricula need to be revised to enhance the current state of education in this field. This can be achieved through the introduction of project-based learning (PBL). The PBL approach is ideal for teaching engineering disciplines because its framework promotes critical thinking and problem-solving skills, which are essential for a professional engineering career. This paper explains the implementation and comparative analysis of the PBL method in the departments of Electrical Engineering and Biomedical Engineering at King Faisal University. The challenges faced in this implementation include incorporating the PBL approach into the departments’ overall instructional technique, defining the roles of PBL coordinators, and addressing the characteristics of the PBL problems that arise in the courses offered. Furthermore, the implementation of PBL projects is evaluated based on the common courses offered in both departments. It is taken as an example and assessed based on problem-solving, teamwork skills, and the outcomes of accreditation board for engineering and technology. The results of this implementation are reported in this paper. Furthermore, we actively shared our experience managing course projects remotely during the fall semester, which COVID-19 impacted. Recommendations for future work are discussed, emphasizing the importance of having sufficient resources and fostering collaboration with industry and researchers from diverse disciplines. [ABSTRACT FROM AUTHOR]

In practical applications, the accuracy of domain terminology translation is an important criterion for the performance evaluation of domain machine translation models. Aiming at the problem of phrase mismatch and improper translation caused by word-by-word translation of English terminology phrases, this paper constructs a dictionary of terminology phrases in the field of electrical engineering and proposes three schemes to integrate the dictionary knowledge into the translation model. Scheme 1 replaces the terminology phrases of the source language. Scheme 2 uses the residual connection at the encoder end after the terminology phrase is replaced. Scheme 3 uses a segmentation method of combining character segmentation and terminology segmentation for the target language and uses an additional loss module in the training process. The results show that all three schemes are superior to the baseline model in two aspects: BLEU value and correct translation rate of terminology words. In the test set, the highest accuracy of terminology words was 48.3% higher than that of the baseline model. The BLEU value is up to 3.6 higher than the baseline model. The phenomenon is also analyzed and discussed in this paper. [ABSTRACT FROM AUTHOR]

In the field of electrical engineering, there is an increasing concern among managers and operators about the secure and cost-efficient operation of smart power systems in response to disturbances caused by physical cyber attacks and natural disasters. This paper introduces an innovative framework for the hybrid, coordinated control of Unified Power Flow Controllers (UPFCs) and Power System Stabilizers (PSSs) within a power system. The primary objective of this framework is to enhance the system's security metrics, including stability and resilience, while also considering the operational costs associated with defending against cyber-physical attacks. The main novelty of this paper lies in the introduction of a real-time online framework that optimally coordinates a power system stabilizer, power oscillation damper, and unified power flow controller to enhance the power system's resilience against transient disturbances caused by cyber-physical attacks. The proposed approach considers technical performance indicators of power systems, such as voltage fluctuations and losses, in addition to economic objectives, when determining the optimal dynamic coordination of UPFCs and PSSs—aspects that have been neglected in previous modern research. To address the optimization problem, a novel multi-objective search algorithm inspired by Harris hawks, known as the Multi-Objective Harris Hawks (MOHH) algorithm, was developed. This algorithm is crucial in identifying the optimal controller coefficient settings. The proposed methodology was tested using standard IEEE9-bus and IEEE39-bus test systems. Simulation results demonstrate the effectiveness and efficiency of this approach in achieving optimal system recovery, both technically and economically, in the face of cyber-physical attacks. [ABSTRACT FROM AUTHOR]

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This paper proposes a new neural machine translation model of electrical engineering that combines a transformer with gated recurrent unit (GRU) networks. By fusing global information and memory information, the model effectively improves the performance of low-resource neural machine translation. Unlike traditional transformers, our proposed model includes two different encoders: one is the global information encoder, which focuses on contextual information, and the other is the memory encoder, which is responsible for capturing recurrent memory information. The model with these two types of attention can encode both global and memory information and learn richer semantic knowledge. Because transformers require global attention calculation for each word position, the time and space complexity are both squared with the length of the source language sequence. When the length of the source language sequence becomes too long, the performance of the transformer will sharply decline. Therefore, we propose a memory information encoder based on the GRU to improve this drawback. The model proposed in this paper has a maximum improvement of 2.04 BLEU points over the baseline model in the field of electrical engineering with low resources. [ABSTRACT FROM AUTHOR]

Research has shown that neural machine translation performs poorly on low-resource and specific domain parallel corpora. In this paper, we focus on the problem of neural machine translation in the field of electrical engineering. To address the mistranslation caused by the Transformer model's limited ability to extract feature information from certain sentences, we propose two new models that integrate a convolutional neural network as a feature extraction layer into the Transformer model. The feature information extracted by the CNN is fused separately in the source-side and target-side models, which enhances the Transformer model's ability to extract feature information, optimizes model performance, and improves translation quality. On the dataset of the field of electrical engineering, the proposed source-side and target-side models improved BLEU scores by 1.63 and 1.12 percentage points, respectively, compared to the baseline model. In addition, the two models proposed in this paper can learn rich semantic knowledge without relying on auxiliary knowledge such as part-of-speech tagging and named entity recognition, which saves a certain amount of human resources and time costs. [ABSTRACT FROM AUTHOR]

With the growing movement of using direct current (DC) load demands, as well as DC distribution generations (DGs), the distribution system has undergone significant changes on the production and demand side. Due to alternating current (AC) and DC generators and load demands, it is not costeffective to continue in the AC distribution system. Therefore, AC/DC hybrid distribution system planning is economical despite various demands and generations. On the other hand, uncertainty in load demand and output power of DGs cause the possible behavior of the distribution system. This behavior leads to risk in the distribution system. In this paper, the AC/DC distribution system planning is discussed by considering the risk. The planning problem in the matrix laboratory and general algebraic modeling system (MATLAB/GAMS) hybrid space has been formulated and solved. Using the K-means algorithm, the uncertainty related to renewable DG output power and load demand has been modeled. To verify the proposed method, it was implemented in a sample distribution system. [ABSTRACT FROM AUTHOR]

This paper focuses on the module "Fundamentals of Electrical Engineering," in which students from different engineering disciplines often face difficulties. Despite efforts to enhance the course through digital media, the formation of study groups, and adjusted lecture and exercise materials, there is still a high failure rate in the subject, leading to potential student dropouts. The primary goal is to analyze students' challenges in solving electrical engineering problems to evaluate their grasp of the fundamentals of electrical engineering and identify varying levels of competence. The findings are based on a cross-sectional study conducted at the conclusion of a university course in Germany, involving 196 students. Through item response theory (IRT) analyses, it was determined that the assessment items demonstrated satisfactory fit values. The proficiency model delineates four levels, with only 8.2% of students achieving the highest level. At this stage, students can tackle more intricate problems using circuit analysis techniques. However, a notable portion of students (40.3%) lack a basic understanding of electrical circuits, placing them at the lowest level. [ABSTRACT FROM AUTHOR]

Appreciation/understanding of the factors that affect proximal coupling in magnetic circuits and the manifestations of the effect of coupling due to magnetic proximity are of paramount importance in electrical engineering. In this paper and in another companion paper we endeavor dealing with each of the aspects critically and putting them in one place. Mainly three aspects—factors that affect the coefficient of coupling, expressing the coefficient of coupling in terms of the design parameters—thus showing the symmetry of the inductance matrix, and the factors that contribute to the deviation of the voltage/current ratios from turns‐ratio is considered, with the introduction of a new factor—a measure of (a)symmetry between the magnetic paths seen by the associated coils. It is also attempted to counter the wide‐spread myth that the proximal coupling imperfection is because of the air‐medium and to highlight the fact that it can also arise because of and be controlled by providing controlled magnetic shunting between the associated coils—a very useful insight. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

The zero forcing number of a graph G, denoted Z(G), is a graph parameter which is based on a color change rule that describes how to color the vertices. Zero forcing is useful in several branches of science such as electrical engineering, computational complexity and quantum control. In this paper, we investigate the zero forcing number for Cartesian products of some graphs. The main contribution of this paper is to introduce a new presentation of the Cartesian product of two complete bipartite graphs and to obtain the zero forcing number of these graphs. We also introduce a purely graph theoretical method to prove Z(Kn ▢ Km) = mn − m − n + 2. [ABSTRACT FROM AUTHOR]

Undergraduate courses in electrical machines often include an introduction to the air gap magnetic field as a basic element in the energy conversion process. The students must learn the main properties of the field produced by basic winding configurations and how they relate to the winding current and frequency. This paper describes a new test equipment design aimed at helping students achieve these learning goals. The test equipment is designed based on four main elements: a modified slip ring induction machine, a winding current driver board, the DAQ boards, and a PC-based virtual instrument. The virtual instrument provides the winding current drivers with suitable current references depending on the user selected machine operational status (single- or three-phase/winding with DC or AC current) and measures and displays the air gap magnetic field for that operational status. Students' laboratory work is organized into a series of experiments that guide their achievement of these air gap field-related abilities. Student learning, assessed based on pre- and post-lab exams and end-of-semester exams, has increased significantly. The students' opinions of the relevance, usefulness, and motivational effects of the laboratory were also positive. [ABSTRACT FROM AUTHOR]