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International Review of Progress in Applied Computational Electromagnetics (ACES)

作者： S M Sajjad Hossain Rafin Qasim Ali Osama A. Mohammed Dept. of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Florida USA Dept. of Electrical Engineering Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9781733509671

ISBN: (纸本)9798350362978

This paper presents a permanent magnet-assisted 3-layer sub-harmonic synchronous machine as a promising solution in the transportation sector. Through finite element analysis, the machine exhibits notable improvements over traditional machines, showcasing a 7.8% reduction in torque ripple and an 8.3% increase in average torque. Precise design parameters yield enhanced performance compared to five different synchronous machines. The incorporation of surface-mounted permanent magnets contributes to superior torque generation, making the machine a promising candidate for advancing in transportation applications.

关键词： Torque Windings Transportation Electromagnetic launching Motors Permanent magnets Topology

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Applying LSTM for River's Water Level Forecasting as Potential Flood Indication: A Case Study in Greece

Applying LSTM for River's Water Level Forecasting as Potenti...

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International Conference on Information, Intelligence, systems and Applications (IISA)

作者： Theodoros Tziolas Elpiniki Papageorgiou Konstantinos Papageorgiou Georgios Zardas Alexios Lekidis Papazoglou Panagiotis Dept. of Energy Systems University of Thessaly Gaiopolis Campus Larisa Greece Dept. of Electrical and Computer Engineering University of Thessaly Volos Greece Dept. of Architecture and Computer and Communication Simulation Systems National and Kapodistrian University of Athens Chalkida Greece

ISBN: (数字)9798350368833

ISBN: (纸本)9798350368840

Floods can have significant life-threatening and economic impacts on human societies. Flood forecasting with data-driven methods is a crucial aspect of disaster risk management, providing valuable insights into potential flood events and allowing for timely mitigation measures. This work illustrates the application of a Long Short-Term Memory (LSTM) neural network for short-term forecasting of a river's water level. The water treatment data used for training the LSTM models were gathered from Sperchios river, located in central Greece. Historical time-series data in a half-hour interval of the river's water level, water velocity, and area precipitation were utilized for the development of the proposed scheme. The developed model is deployed in the backend of a web application for half-hour ahead predictions of the river's water level that are visualized in the frontend. The post-analysis of the deployed forecasting model indicates that it consistently delivers forecasts with minimal error and demonstrates high accuracy in recent flood events.

关键词： Training Precipitation Biological system modeling Prevention and mitigation Neural networks Predictive models Rivers Floods Forecasting Long short term memory

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On-chip GaAs carrier lifetime investigation

arXiv

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arXiv 2025年

作者： Prayoonyong, Chawaphon Szydzik, Crispin Ren, Guanghui Corcoran, Bill Dubey, Aditya Murray, Caitlin E. Mitchell, Toby Mitchell, Arnan Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia MelbourneVIC Australia

We propose an alternative way to determine GaAs carrier lifetime using pump-probe measurement based on fibre optics and integrated waveguides. We find that our GaAs samples have the lifetime ranging from 30-80 ps, supporting the bandwidth ≥ 12.5 GHz. The platform utilised in this work could offer a cost-effective way to investigate photocarrier lifetime. Moreover, it may have the potential for high-speed switches and detectors, or could be exploited for possible all-optical modulation. © 2025, CC BY-NC-ND.

关键词： Gallium arsenide

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Derivation of Aggregated Equivalent Models for the Steady-State Analysis of Active Distribution Networks Operated Under Voltage Control Schemes

SSRN

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SSRN 2024年

作者： Pasiopoulou, Ioanna D. Kontis, Eleftherios O. Papadopoulos, Theofilos A. Papagiannis, Grigoris K. Power Systems Laboratory School of Electrical and Computer Engineering Aristotle University of Thessaloniki GR Thessaloniki54124 Greece Department of Electrical and Computer Engineering University of Thessaly Volos Greece Power Systems Laboratory Dept. of Electrical and Computer Engineering Democritus University of Thrace XanthiGR 67100 Greece

To facilitate the coordination between transmission and distribution system operators, accurate equivalent models of power system components are required. Towards this objective, in this paper, a blackbox model is proposed for developing steady-state reduced-order equivalents of active distribution networks (ADNs) that host converter-interfaced renewable energy sources (CI-RES) and operate under various voltage control schemes. Droop-based and traditional voltage control schemes, such as on-load tap changer (OLTC) control strategies and the use of shunt capacitors, are considered. The performance of the proposed model is evaluated via simulations considering various load types and CI-RES penetration levels. Comparisons against the conventional polynomial and exponential models are also conducted, demonstrating the superior performance of the proposed black-box model. © 2024, The Authors. All rights reserved.

关键词： Electric power distribution

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Dynamic Optimizations in GPU Using Roofline Model

Dynamic Optimizations in GPU Using Roofline Model

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IEEE International Symposium on Circuits and systems

作者： Winnie Thomas Suryakant Toraskar Virendra Singh Computer Architecture and Dependable Systems Laboratory Dept. of Electrical Engineering Indian Institute of Technology Bombay India

ISBN: (纸本)9781728192017;9781728192024

Massively parallel processors such as graphics processing units (GPUs) often face the challenge of resource underutilization due to varying resource proclivity of workloads. Running multiple applications on a GPU has been an efficient and known alternative to mitigate underutilization. This paper proposes a multi-application oriented framework that carries out dynamic optimizations based on the operational intensities of various applications. Our framework analyzes applications based on operational intensities to identify their bottleneck resources using Roofline model. We demonstrate that the proposed optimizations improve the utilization and system-wide throughput of the GPU co-running applications with irregular resource demands. The dynamic optimizations improve the performance by 14.8% on average and up to 72.4% over a state-of-the-art spatial multitasking technique.

关键词： Heuristic algorithms Graphics processing units Throughput Multitasking Resource management Optimization Faces

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Dual Inverter Parallel Consequent Pole PM-Assisted Two-Layer Sub-Harmonic Synchronous Machine

Dual Inverter Parallel Consequent Pole PM-Assisted Two-Layer...

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IEEE Conference on Electromagnetic Field Computation

作者： S M Sajjad Hossain Rafin Qasim Ali Osama A. Mohammed Dept. of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Florida USA Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9798350348958

ISBN: (纸本)9798350348965

A parallel consequent pole PM-assisted 2-layer subharmonic machine consisting of dual inverter topology is proposed here, which is designed to enhance torque generation and control compared to its predecessors. The stator of the sub-harmonic synchronous machine has two sets of 3-phase windings, and the dual inverter supplies current to them separately. Similarly, the rotor has two concentric windings, one for field excitation and the other for harmonic excitation. To validate the proposed model, an 8-pole, 48-slot, 2-inverter, 2-layer sub-harmonic machine is designed and simulated through 2-D finite element analysis. The results show a better torque and performance than the subharmonic and wound field synchronous machines.

关键词： Performance evaluation Torque Windings Stator windings Rotors Motors Harmonic analysis

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Stealthy Attack Detection of controlled ramp meters in freeway networks

Stealthy Attack Detection of controlled ramp meters in freew...

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IEEE Conference on Decision and Control

作者： Charalambos Menelaou Kangkang Zhang Stelios Timotheou Christos G. Panayiotou Thomas Parisini Dept. of Electrical and Computer Engineering KIOS CoE University of Cyprus Dept. of Electrical and Electronic Engineering Imperial College London London U.K. Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The increasing reliance on intelligent transportation systems (ITS) for traffic management has simultaneously heightened the potential for cybersecurity threats. Malicious cyber attacks on such systems can lead to operational inefficiencies, heightened congestion, and compromised safety. This work introduces a stealthy integrity attack tailored for ramp metered freeway systems. The attack model is conceptualized as a closed-loop dynamical system, formulated as an optimization problem based on the Cell Transmission Model. This work further proposes a distributed detection mechanism designed to identify attack residuals, which, by incorporating an adaptive threshold scheme, can detect the presence of an attack. To demonstrate the efficacy of our detection scheme, we present a scenario illustrating its application in freeway road networks.

关键词： Meters Adaptation models Roads Traffic control Safety Dynamical systems Cyberattack Optimization Intelligent transportation systems Resilience

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Meaning of the Clusters on Dimensionality Reduction by Word Clustering 12

Meaning of the Clusters on Dimensionality Reduction by Word ...

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12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

作者： Deguchi, Toshinori Seo, Sinsuke Ishii, Naohiro Dept. of Electrical and Computer Engineering Gifu College Gifu Japan Interdisciplinary Technology Development Gifu College Gifu Japan Information Systems Architecture Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (数字)9781665497558

ISBN: (纸本)9781665497558

In text mining, Latent Semantic Analysis (LSA) is the popular method to reduce the dimension of document vectors. Since LSA produces a set of topics by statistical information, the meaning of each topic is not *** proposed a method to reduce the dimension by clustering the words in the documents. This method produces a set of clusters of words instead of topics. Using Word2vec to vectorize the words, the mean vector of the cluster is calculated, which shows the meaning of the *** this paper, we show the dimensionality reduction and the meaning of the generated clusters by word cloud, on document classification problem with a subset of BBC Dataset. © 2022 IEEE.

关键词： Classification (of information)

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Methodology for Evaluating Equivalent Models for the Dynamic Analysis of Power systems

Methodology for Evaluating Equivalent Models for the Dynamic...

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Power Tech Conference

作者： Georgios A. Barzegkar-Ntovom Eleftherios O. Kontis Theofilos A. Papadopoulos Panagiotis N. Papadopoulos Dept. of Electrical and Computer Engineering Power Systems Laboratory Democritus University of Thrace Xanthi Greece Power Systems Laboratory School of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Dept. of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Dept. of Electronic and Electrical Engineering Institute for Energy and Environment University of Strathclyde Glasgow Scotland U.K.

The increasing penetration of distributed renewable energy sources drastically alters the dynamic characteristics of distribution networks (DNs). Therefore, several equivalent models have been recently proposed, to analyze more accurately the complex behavior of modern DNs. However, relatively simple models are still commonly used in practice for dynamic power system studies. In addition, dynamic equivalent models for DNs are sensitive to different operating conditions and there is lack of systematic understanding of their performance. Scope of this paper is to propose a methodology for identifying the applicability range in terms of accuracy and generalization capability of several conventional and newly developed equivalent models for the dynamic analysis of modern DNs. A set of metrics is used for the modelling accuracy assessment and a sensitivity analysis framework is introduced to fully quantify the generalization capabilities of DN equivalent models. Based on the above, guidelines and recommendations for the development of robust equivalent models for DN analysis are proposed.

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Surrogate-Assisted Multi-Class Collaborative Teaching and Learning Optimizer for High-Dimensional Industrial Optimization Problems

Surrogate-Assisted Multi-Class Collaborative Teaching and Le...

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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Bi, Jing Wang, Ziqi Yuan, Haitao Yang, Jinhong Zhang, Jia College of Computer Beijing University of Technology Beijing100124 China Beijing University of Technology Beijing Laboratory of Smart Environmental Protection Beijing100124 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Cssc Systems Engineering Research Institute Beijing China Lyle School of Engineering Southern Methodist University Dept. of Computer Science DallasTX United States

ISBN: (纸本)9781665410205

Swarm intelligence and evolutionary algorithms are widely applied in industrial scheduling, mobile edge computing, etc due to their strong robustness and fast optimization speed. However, some real-world industrial optimization problems involve numerous decision variables, known as high-dimensional problems. Current algorithms often require considerable computational resources to evaluate objective function values because of high-dimensional decision spaces. Moreover, they are also prone to be trapped in local optima. To solve the above problems, this work proposes an improved algorithm named Surrogate-assisted Multi-class Collaborative Teaching and learning optimizer (SMCT). A multi-class collaborative teaching and learning optimizer is proposed as a base optimizer to improve exploration and exploitation abilities. Furthermore, an autoencoder-assisted radial basis function is proposed as the surrogate model to replace true function evaluations, thereby saving computational resources and balancing the complexity and accuracy in fitting true models. Finally, experimental results demonstrate that SMCT surpasses its existing peers in both search accuracy and convergence speed across eight high-dimensional benchmark functions. © 2024 IEEE.

关键词： Scheduling algorithms

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