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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Romphoyen, Dineenath Panmala, Nattapon Suwanasri, Thanapong Suwanasri, Cattareeya King Mongkut's University of Technology North Bangkok The Sirindhorn International Thai-German Graduate School of Engineering EPE Program Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangsue Bangkok Thailand

ISBN: (纸本)9798350344585

In this paper, the overall health index of underground cable system is determined using Fuzzy Logic and Scoring and Weighting Average methods. The relevant data of 73 feeders has been collected in the prepared evaluation forms, divided into five major component groups: cable, joint, termination, manhole, and ductbank. In each component, various testing methods and diagnostic techniques are applied, and then the numerical score is determined according to the technical criteria for condition assessment. Subsequently, the obtained overall health index is multiplied with the conditional factor to incorporate the differences in installation type and configuration as well as the operating and environmental conditions. Finally, the overall health index based on these two methods is compared to verify the accuracy of the obtained results to properly plan the preventive and condition-based maintenance and to improve the reliability of the underground cable system. © 2023 IEEE.

关键词： Fuzzy logic

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A Time-Domain Thin-Sheet Volume Integral Equation for Non-Dispersive Bi-Isotropic Media

A Time-Domain Thin-Sheet Volume Integral Equation for Non-Di...

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European Conference on Antennas and Propagation, EuCAP

作者： S. Celis Sierra R. Zhao M. Khamitova H. Bagci Electrical and Computer Engineering (ECE) Program Computer Electrical and Mathematical Science and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia School of Electronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu China

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

Bi-isotropic and bi-anisotropic materials are expected to revolutionize wireless communications through the extended use of metasurfaces. This paper proposes a time-domain integral equation solver to simulate non-dispersive biisotropic materials under the thin-sheet approximation. Thin-sheet approximation is used to convert the time-domain volume integral equation for non-dispersive bi-isotropic media into a surface integral equation. This surface equation is discretized in space using Rao-Wilton-Glisson (RWG) basis functions for the tangential components of the electric and magnetic fluxes and pulse basis functions for their normal components (relative to the surface of the thin sheet). In time, shifted Lagrange polynomials are used for discretization. Applying Galerkin testing in space and point matching in time yields a matrix system. This matrix system is solved for the unknown basis expansion coefficients at each time step via time-marching. Numerical results demonstrate the accuracy of the proposed method. Future work includes extending this solver to dispersive bi-anisotropic media and use it in the simulation of metasurface represented by generalized sheet transition conditions (GSTCs).

关键词： Wireless communication Accuracy Integral equations Media Metasurfaces Polynomials Time-domain analysis Dispersion Method of moments Testing

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Investigation of Lightning Overvoltage on 220 kV Transmission Lines in Bhutan Using ATP-EMTP

Investigation of Lightning Overvoltage on 220 kV Transmissio...

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2023 International Conference on Power, Energy and Innovations, ICPEI 2023

作者： Samten Suwanasri, Thanapong Suwanasri, Cattareeya Panmala, Nattapon King Mongkut's University of Technology North Bangkok The Sirindhorn International Thai-German Graduate School of Engineering EPE Program Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangsue Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangsue Bangkok Thailand

ISBN: (纸本)9798350344585

This paper provides an examination of the impact of lightning strikes on a 220 kV double circuit (D/C) high voltage transmission line in Bhutan. The study employs the ATP-EMTP software to identify the leading causes of transmission line faults, which are primarily attributed to lightning strikes. Since the transmission lines run through areas in Bhutan that are prone to severe weather conditions and lightning strikes, they are vulnerable to damage, leading to an unreliable power supply. To address this issue, the author proposes several solutions, such as enhancing the tower footing resistance and installing line surge arresters. The author also created models of different transmission towers and analyzed an 18 km stretch of the transmission line that is highly susceptible to lightning strikes. © 2023 IEEE.

关键词： Electric lines

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A Discontinuous Galerkin Time-Domain Scheme to Model Lasing Dynamics in Four-Level Two-Electron Atomic Systems

A Discontinuous Galerkin Time-Domain Scheme to Model Lasing ...

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European Conference on Antennas and Propagation, EuCAP

作者： Ming Dong Liang Chen Ran Zhao Hakan Bagci Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia School of Electronic Science and Engineering Univesirty of Electronic Science and Technology of China (UESTC) Chengdu China

A discontinuous Galerkin time-domain scheme is formulated and implemented to analyze three-dimensional transient lasing dynamics. The proposed scheme solves a coupled system of the Maxwell and the rate equations. The atomic transitions through different energy levels are quantum-mechanically described by a four-level two-electron model, while the electro-magnetic interactions are treated using the Maxwell equations. The resulting solver accounts for the Pauli Exclusion Principle and permits robust simulation of lasing dynamics under optical pumping. Numerical results are presented to demonstrate the applicability and the accuracy of the proposed scheme.

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Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filtering

arXiv

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arXiv 2024年

作者： Mashkova, Olga Zhapa-Camacho, Fernando Hoehndorf, Robert Computer Science Program Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Ontology embeddings map classes, relations, and individuals in ontologies into Rn, and within Rn similarity between entities can be computed or new axioms inferred. For ontologies in the Description Logic EL++, several embedding methods have been developed that explicitly generate models of an ontology. However, these methods suffer from some limitations;they do not distinguish between statements that are unprovable and provably false, and therefore they may use entailed statements as negatives. Furthermore, they do not utilize the deductive closure of an ontology to identify statements that are inferred but not asserted. We evaluated a set of embedding methods for EL++ ontologies based on high-dimensional ball representation of concept descriptions, incorporating several modifications that aim to make use of the ontology deductive closure. In particular, we designed novel negative losses that account both for the deductive closure and different types of negatives. We demonstrate that our embedding methods improve over the baseline ontology embedding in the task of knowledge base or ontology completion. © 2024, CC BY.

关键词： Ontology

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Optimizing 3D Clothing Models for VR: A Deep Learning Approach to Triangle Count Reduction

Optimizing 3D Clothing Models for VR: A Deep Learning Approa...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Surasachai Doungtap Varinya Phanichraksaphong Jenq-Haur Wang International Graduate Program of Electrical Engineering and Computer Science National Taipei University of Technology Taipei Taiwan Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

This study presents a deep learning framework optimizing 3D clothing models for VR, using a CNN to significantly reduce the triangle count of models from DeepFashion3D and CAP-UDF datasets. Achieving a balance between efficiency and detail, it cuts triangle count from over 160,000 to below 4,000, maintaining high DPI. The approach automates optimization, promising scalability and efficiency in VR fashion, setting a foundation for future 3D content development, enhancing virtual garment realism and interactivity.

关键词： Deep learning Solid modeling Three-dimensional displays Scalability Clothing Optimization Consumer electronics

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Towards Automated Functional Equation Proving: A Benchmark Dataset and A Domain-Specific In-Context Agent

arXiv

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arXiv 2024年

作者： Buali, Mahdi Hoehndorf, Robert Computer Science Program Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

Automated Theorem Proving (ATP) faces significant challenges due to the vast action space and the computational demands of proof generation. Recent advances have utilized Large Language Models (LLMs) for action selection in ATP, but these methods often require substantial computational resources. This study introduces the Functional Equation Automated Solver (FEAS), an agent that builds on the COPRA in-context learning framework within the Lean environment. FEAS innovates by refining prompt generation and response parsing mechanisms, integrating domain-specific heuristics for functional equations, and introducing the FunEq dataset—a rigorously curated collection of functional equation problems categorized into three difficulty levels. The agent’s performance is evaluated against established baselines using this dataset, demonstrating improvements in theorem proving accuracy, particularly with the integration of functional equation-specific heuristics. Our results highlight the effectiveness of FEAS in generating and formalizing high-level proof strategies into Lean proofs, emphasizing the potential of tailored approaches in domain-specific ATP challenges. © 2024, CC BY.

关键词： Theorem proving

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Smart Home Security System Using Face Recognition Based on IoT- CNN 2

Smart Home Security System Using Face Recognition Based on I...

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2nd International Conference on Information technology Research and Innovation, ICITRI 2023

作者： Febriantono, M. Aldiki Zuhair, Alvin Khaeruddin School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia University of Islam Blitar Electrical Engineering Department Blitar Indonesia University of Muhammadiyah Malang Diploma III Electronic Technology Vocational Study Program Malang Indonesia

ISBN: (纸本)9798350324945

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning computer Vision holds tremendous benefits for homeowners. © 2023 IEEE.

关键词： Face recognition

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Alleviate sidewall damage of InGaN green micro-LEDs by atomic layer etching

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Optics letters 2025年第11期50卷 3756-3759页

作者： Zhiyuan Liu Haicheng Cao Tingang Liu Yi Lu Xiao Tang Zixian Jiang Na Xiao Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering Program CEMSE Division King Abdullah University of Science and Technology (KAUST) Thuwal 23955-6900 Saudi Arabia

In this work, atomic layer etching (ALE) technology is demonstrated to alleviate the sidewall damage generated during the mesa etching process of InGaN micro-LEDs. TEM images verify the existence of the sidewall damage and its mitigation after 200-cycle ALE sidewall treatment. The defect-related leakage current density significantly decreases from 3 × 10 to 7 × 10 A/cm at -20 V bias through sidewall treatment. InGaN green micro-LEDs (11 µm) with ALE sidewall treatment show a more than 10% enhancement in external quantum efficiency compared to untreated reference devices. This work provides a new, to our knowledge, perspective on addressing the sidewall effect in micro-LEDs, aiding the realization of high-efficiency InGaN micro-LEDs in the near term.

关键词： Atomic force microscopy Indium gallium nitride Indium tin oxide Light extraction Quantum efficiency Surface layers

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Classifying Tweet Sentiment Analysis on Airlines using Random Forest Classifier, Naïve Bayes Classifier and K-Nearest Neighbors Classifier Algorithm

Classifying Tweet Sentiment Analysis on Airlines using Rando...

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2023 International Conference on Artificial Intelligence Robotics, Signal and Image Processing, AIRoSIP 2023

作者： Alexander, Ivan Heryadi, Yaya Lukas Suparta, Wayan Sonata, Ilvico Bina Nusantara University Binus Graduate Program Computer Science Computer Science Departement Jakarta11480 Indonesia Universitas Katolik Indonesia Atma Jaya Cognitive Engineering Research Group Faculty of Engineering Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350327472

Opinion has always affected businesses and individuals especially from the Public. People react through social media and spread it incompletely. The situation was then accepted as public opinion. There are three categories of opinion i.e., positive, negative, and neutral. To investigate public opinion on a particular issue of interest, sentiment analysis might be employed. By offering a solution to the text classification challenge, this experiment focuses on the perception of airline tweets among the American public. We offer a method to classify tweets as positive, negative, or neutral using three machine learning classifiers: Random Forest Classifier, Naive Bayes Classifier, and K-Nearest Neighbors Classifier. We examined the performance of three machine learning classifiers in terms of accuracy, average precision, average recall, and average f-1 score. The results demonstrate that the Random Forest Classifier, which produces 82% accuracy, 80% average precision, 82% average recall, and 80% average f1-score, performs the best among the machine learning classifiers. © 2023 IEEE.

关键词： Tweets

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