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Annual IEEE Systems Conference

作者： Kubra Aksoy Adnan Rashid Osman Hasan Sofiène Tahar Department of Electrical and Computer Engineering Concordia University Montreal Quebec Canada School of Electrical Engineering and Computer Science National University of Science and Technology Islamabad Pakistan

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

electrical circuit networks consist of various electrical components connected in different arrangements that are used to process electrical signals, such as voltages and currents. Moreover, they are widely used in many engineering and physical systems, such as control, embedded and communication systems. In this work, we propose to use higher-order-logic theorem proving for formally analyzing electrical circuit networks using network topology matrices. In particular, we formalize in the Is-abellelHOL theorem prover incidence and circuit (loop) matrices, which are widely used topology matrices. Our formalization is based on modeling the system as a network using the notion of directed graphs that are algebraically represented by matrices. Next, we use this formalization to formally analyze various network topologies, such as Δ- $Y$ and ∏ - $L$ topologies, where we perform Kirchhoff's current and voltage laws based analysis in a generic way.

关键词： Network topology Communication systems Directed graphs Bridge circuits Network analyzers Control systems Matrices Libraries Topology Integrated circuit modeling

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Radiative cooling for passive thermal management towards sustainable carbon neutrality

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National science Review 2023年第1期10卷 87-97页

作者： Jun Liang Jiawei Wu Jun Guo Huagen Li Xianjun Zhou Sheng Liang Cheng-Wei Qiu Guangming Tao Wuhan National Laboratory for Optoelectronics and Optics Valley Laboratory Huazhong University of Science and Technology Department of Electrical and Computer Engineering National University of Singapore MOE Key Laboratory of Thermo-Fluid Science and Engineering School of Energy and Power Engineering Xi'an Jiaotong University Key Laboratory of Education Ministry on Luminescence and Optical Information Technology National Physical Experiment Teaching Demonstration CenterDepartment of PhysicsSchool of Physical Science and Engineering Beijing Jiaotong University State Key Laboratory of Material Processing and Die &Mould Technology School of Materials Science and Engineering Huazhong University of Science and Technology

Photonic structures at the wavelength scale offer innovative energy solutions for a wide range of applications,from high-efficiency photovoltaics to passive cooling,thus reshaping the global energy *** cooling based on structural and material design presents new opportunities for sustainable carbon neutrality as a zero-energy,ecologically friendly cooling *** this review,in addition to introducing the fundamentals of the basic theory of radiative cooling technology,typical radiative cooling materials alongside their cooling effects over recent years are summarized and the current research status of radiative cooling materials is outlined and ***,technical challenges and potential advancements for radiative cooling are forecast with an outline of future application scenarios and development *** the future,radiative cooling is expected to make a significant contribution to global energy saving and emission reduction.

关键词： photonic structures radiative cooling energy saving and emission reduction carbon neutrality

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Advancements in Quantum Error Mitigation Strategies for Reliable Quantum Computing on IBM Simulators 6

Advancements in Quantum Error Mitigation Strategies for Reli...

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6th IEEE International Conference on Emerging Smart Computing and Informatics, ESCI 2024

作者： Sherin Beevi, L. Joe Prathap, P.M. Sudhish Reddy, D. Agnes Joshy, S. Vinil Dani, W. R.M.D. Engineering College Department of Computer Science and Engineering Kavaraipettai India Francis Xavier Engineering College Department of Information Technology Tirunelveli India St. Peter's College of Engineering and Technology Department of Electrical and Electronics Engineering India

ISBN: (纸本)9798350306613

We explore the field of quantum computing and specifically address the crucial problem of error reduction in the context of IBM simulators. Although quantum computing is a rapidly developing technology with great potential, its practical applications are severely hindered by its inherent error-proneness. We tackle this problem by introducing new developments in quantum error correction techniques designed for IBM simulators. In contrast to conventional methods that frequently depend on large matrices or pre-established error models;our technique presents a flexible and dynamic approach. By utilizing several variations of a main circuit, in which classically efficient gates are used in place of non-Clifford gates, we are able to discover the best compensation scheme from scratch for actual quantum systems. The suggested method exhibits great flexibility in handling different levels of noise and different kinds of noise, such as spatially and temporally correlated variations. It also effectively reduces errors on IBM quantum hardware as well as precisely emulated imperfect quantum computers. By offering a thorough investigation of sophisticated error mitigation techniques, this research advances the continuing quest for dependable quantum computations and opens up interesting new directions for improving both the accuracy and performance of quantum computing operations carried out on IBM simulators. © 2024 IEEE.

关键词： Adaptive Compensation Strategies IBM Quantum Simulators NISQ Quantum Computing Reliability Quantum Error Mitigation

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A New Automated Workflow for Well Monitoring Using Permanent Pressure and Rate Measurements

A New Automated Workflow for Well Monitoring Using Permanent...

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2024 SPE Norway Subsurface Conference, BERG 2024

作者： Shchipanov, A. Cui, B. Starikov, V. Muradov, K. Khrulenko, A. Zhang, N. Demyanov, V. NORCE‑Norwegian Research Centre Bergen Norway Department of Electrical Engineering and Computer Science University of Stavanger Stavanger Norway Institute of GeoEnergy Engineering Heriot-Watt University Edinburgh United Kingdom

ISBN: (纸本)9781959025344

Pressure and rate measurements are essential for the well and reservoir surveillance workflows used in petroleum, geological carbon storage, and geothermal industries. Such well monitoring data are now analyzed in manual, semi-automated and automated modes or in a combination. Automated workflows are widely adopted by the industry nowadays, enabling most efficient knowledge extraction from the data both already accumulated and being received in real-time. The paper describes a new integrated workflow for automated well monitoring using pressure and rate measurements obtained with permanent gauges and flowmeters. The workflow is based on time-lapse Pressure Transient Analysis (PTA) and integrates the following components: virtual flow-metering, transient identification, feature extraction and pattern recognition in transient pressure responses, and assessment of well performance based on PTA-metrics. The methodology behind the workflow combines different physics-informed and data-driven methods described in the paper. Application of the workflow is illustrated on a field case example from the Norwegian Continental Shelf, where changes in the well, reservoir, and well-reservoir connection performances are automatically monitored during its three-year long injection history. Reliability and accuracy of the automated monitoring results are verified via comparison with the conventional model-based time-lapse PTA. The automated workflow may be used for a variety of use cases. Being applied to the well history, the workflow enables establishing a historical performance profile and identifying trends and issues in the past. In everyday well monitoring, it may be employed to detect well performance issues early and indicate their possible reasons. Further, it may provide valuable input for in-depth model-based analysis and other reservoir engineering studies. Using the workflow unlocks knowledge hidden in abundant well-monitoring datasets available at operating companies and

关键词： Extraction

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Uncertainty-Aware Deep Neural Representations for Visual Analysis of Vector Field Data

arXiv

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arXiv 2024年

作者： Kumar, Atul Garg, Siddharth Dutta, Soumya The department of Computer Science and Engineering The Electrical Engineering department IIT Kanpur India

The widespread use of Deep Neural Networks (DNNs) has recently resulted in their application to challenging scientific visualization tasks. While advanced DNNs demonstrate impressive generalization abilities, understanding factors like prediction quality, confidence, robustness, and uncertainty is crucial. These insights aid application scientists in making informed decisions. However, DNNs lack inherent mechanisms to measure prediction uncertainty, prompting the creation of distinct frameworks for constructing robust uncertainty-aware models tailored to various visualization tasks. In this work, we develop uncertainty-aware implicit neural representations to model steady-state vector fields effectively. We comprehensively evaluate the efficacy of two principled deep uncertainty estimation techniques: (1) Deep Ensemble and (2) Monte Carlo Dropout, aimed at enabling uncertainty-informed visual analysis of features within steady vector field data. Our detailed exploration using several vector data sets indicate that uncertainty-aware models generate informative visualization results of vector field features. Furthermore, incorporating prediction uncertainty improves the resilience and interpretability of our DNN model, rendering it applicable for the analysis of non-trivial vector field data sets. © 2024, CC BY.

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Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect

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光：科学与应用（英文版） 2025年第2期14卷 307-332页

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

The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as AR/***,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size *** seriously impedes the development and application of *** this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical ***,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall ***,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED *** believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficient InGaN micro-LEDs.

关键词： technologies micro-led advanced ingan effect fabrication mitigate sidewall

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Direct ink writing of gradient shear-stiffening elastomer for enhanced toughness and impact resistance

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Journal of Industrial and engineering Chemistry 2025年 149卷 593-603页

作者： Gong, Liping Zhao, Chunyu Lu, Hongda Zhang, Qingtian Chen, Zexin Yang, Junjie Yang, Jinyu Sun, Shuaishuai Du, Haiping Li, Weihua School of Mechanical Materials Mechatronic and Biomedical Engineering University of Wollongong Wollongong2522 Australia CAS Key Laboratory of Mechanical Behaviour and Design of Materials Department of Modern Mechanics University of Science and Technology of China Hefei230027 China School of Electrical Computer and Telecommunication Engineering University of Wollongong Wollongong2522 Australia

Shear-stiffening materials have garnered significant attention due to their inherent ability to rapidly respond to changes in strain rate. However, conventional studies on these materials exhibit limited mechanical performance and insufficient structural design, hindering applications in material science and smart mechatronics. Inspired by the gradient structure of a squid beak, this study uses a direct-ink-writing (DIW) technology to develop a novel gradient shear-stiffening elastomer (GSSE). Comprehensive characterizations were conducted to optimize the printability of the shear-stiffening elastomer under various testing conditions, including rheology, compression, and tension. Additionally, the toughness and impact resistance of the elastomer were systematically investigated. It is demonstrated that the biomimetic GSSE exhibits enhanced flexibility, efficient energy dissipation, and outstanding impact resistance. Consequently, this work advances the field of shear-stiffening elastomers for diverse applications by leveraging the gradient structure design strategy to achieve superior mechanical performance under complex loading conditions. © 2025 The Author(s)

关键词： Strain rate

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WiFi Indoor Positioning System Based on OpenWRT 20

WiFi Indoor Positioning System Based on OpenWRT

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20th International Conference on Smart Technologies, EUROCON 2023

作者： Estrada, Rebeca Valeriano, Irving Aizaga, Xavier Vargas, Lourdes Vera, Nelson Zambrano, Diego Escuela Superior Politécnica Del Litoral Espol Information Technologies Center Electrical Engineering and Computer Science Department Guayaquil Ecuador

ISBN: (纸本)9781665463973

The development of indoor positioning systems is possible thanks to the availability of wireless network infrastructure. Thus, a wireless provider can determine an accurate indoor position taking into account the existing Wifi infrastructure in buildings, malls, or offices. In this work, we develop a system for indoor positioning with the use of several libraries of OpenWRT running on three access points in an office of the CTI building. We develop a server application to retrieve the performance metrics of the WiFi signal from three wireless routers of the study area and load this information to a database. Thus, this application uses the signal strength measured and stored in the database to determine the distance between the mobile devices and each access point. Then, the position of the mobile devices is estimated by averaging the estimation of three Min-Max algorithms and updated in the database. Finally, we also implemented a mobile application that shows on a map the mobile devices position in real time and the position of mobile devices in their proximity. The results show that the mobile devices locations present an average margin error of position equal to 2.43 meters enabling the development of indoor positioning applications using the existing infrastructure of the wireless networks. © 2023 IEEE.

关键词： Indoor positioning systems

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The Emergence of Artificial Intelligence in Education and its Impact on Individual Literacy in Higher Education 7

The Emergence of Artificial Intelligence in Education and it...

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7th IEEE International Conference and Workshop Obuda on electrical and Power engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Institute of Electronics and Communication Systems Kandó Kalmán Faculty of Electrical Engineering Obuda University Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

In the last three years, a new partner has emerged for teachers and educators in the field of education. The mushrooming of applications based on large language models has greatly shaped the educational development fields of the present era. The use of various AI applications has become commonplace among students and teachers alike. Many questions are being raised by researchers in this field. What does the rapid development of AI applications bring to the field of pedagogy? Should the products of such applications be compared with human performance? The form presented in this thesis seeks to answer similar questions. What is the impact of frequent use of these applications on the literacy level of individuals? In which areas do students tend to use these applications? The results indicate that half of the students believe their literacy levels will decrease with the mass emergence of AI applications, while 36% feel it will not change. However, 88 % of students have already dealt with AI-based applications, with 64 % using them several times or more, suggesting a high level of integration into their educational processes. © 2024 IEEE.

关键词： Students

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Data-Driven Diagnosis of Multi-Class Open-Circuit Switch Faults in Three-Phase Front-End Converters

Data-Driven Diagnosis of Multi-Class Open-Circuit Switch Fau...

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2024 International Conference on computer, Electronics, electrical engineering and their Applications, IC2E3 2024

作者： Ghosh, Sourabh Singh, Vikash Singh, Asheesh Kumar Hassan, Ehtesham Singh, Sri Niwas Motilal Nehru National Institute of Technology Allahabad Electrical Engineering Department Prayagraj India Kuwait College of Science and Technology Department of Computer Science and Engineering Kuwait Atal Bihari Vajpayee Indian Institute of Information Technology and Management Gwalior India

ISBN: (纸本)9798350388534

This paper analyzes the application of benchmark classification techniques for multi-class diagnosis of open-circuit switch faults (OCSFs) in three-phase front-end converters (TP-FECs). OCSFs result in harmonic distortion, secondary faults, and unscheduled shutdowns in power utilities. Moreover, due to the inherent difference between OCSFs and short-circuit switch faults, the same diagnosis techniques do not apply to both types of faults. This paper presents a detailed study on a two-level TP-FEC to generate single-, double-, and triple-switch OCSFs, resembling real-world scenarios. The single-moment fault data with 624 observations is captured through 13 distinct features to extract the fault characteristics during each of the 38 classes of OCSFs under varying load demands. Later, the paper analyzes the performance of neural networks (NNs), support vector machines (SVMs), ensemble bagged trees (EBTs), and k-nearest neighbours (KNNs) for multi-class diagnosis of OCSFs. The evaluation employed cross-validation with optimal hyperparameter combinations to train different models. Through rigorous experiments, we demonstrate the superiority of NNs in classifying multi-class OCSFs with a testing accuracy of 97.50%, achieving an improvement of 0.4%, 2.4%, and 3.8% compared to SVM, KNN, and EBT, respectively. Furthermore, our experiments underscore the efficacy of NNs and SVMs over other state-of-the-art methods for diagnosing OCSFs. © 2024 IEEE.

关键词： Harmonic distortion

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