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IEEE Texas Power and Energy Conference (TPEC)

作者： Mingze Li Weihang Ren Lei Fan Yongpei Guan Dept. of Electrical and Computer Engineering University of Houston TX USA Engineering Technology University of Houston TX USA Dept. of Industrial and Systems Engineering University of Florida FL USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This paper presents a preprocessing method to solve the security-constrained unit commitment with AC power flows (SCUC-ACPF), which is a large scale mixed-integer non-convex, nonlinear optimization problem. We introduce clustering algorithms and local search to reduce problem complexity, and obtain local optimal solutions within limited solving time and computational capacity. The clustering algorithms group buses into manageable clusters centered around core buses, creating smaller sub-grids for efficient optimization. The local search algorithms iteratively explore and improve solution quality. Our method ensures balanced clusters that respect physical and operational constraints, significantly enhancing optimization efficiency and contributing to more effective grid management and operation.

关键词： Heuristic algorithms Clustering methods Clustering algorithms Search problems Boundary conditions Power grids Complexity theory Optimization AC power transmission

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Decomposition Algorithm for Security-Constrained Unit Commitment with AC Optimal Power Flows

Decomposition Algorithm for Security-Constrained Unit Commit...

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IEEE Texas Power and Energy Conference (TPEC)

作者： Weihang Ren Mingze Li Lei Fan Yongpei Guan Dept. of Industrial and Systems Engineering University of Florida FL USA Dept. of Electrical and Computer Engineering University of Houston TX USA Engineering Technology University of Houston TX USA

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

This paper presents a comprehensive approach to solving the security-constrained unit commitment with alternating current power flows (SCUC-ACPF) problem in contemporary power systems. We introduce algorithms that decompose the problem into subproblems suitable for specialized solvers, so that the large-scale mixed-integer nonlinear program-ming SCUC-ACPF problem can be solved. In case studies, we validate the efficiency and effectiveness of our algorithms on synthetic and industry-scale power system networks.

关键词： Runtime Scalability Power systems Planning Security Optimization AC power transmission Load flow

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Key Exchange in the Quantum Era: Evaluating a Hybrid System of Public-Key Cryptography and Physical-Layer Security 59

Key Exchange in the Quantum Era: Evaluating a Hybrid System ...

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59th Annual Conference on Information Sciences and systems, CISS 2025

作者： Staat, Paul Dorpinghaus, Meik Sheikholeslami, Azadeh Paar, Christof Fcllwcis, Gerhard Goeckel, Dennis Max Planck Institute for Security and Privacy Bochum Germany Technische Universität Dresden Vodafone Chair Mobile Communications Systems Dresden Germany Suffolk University Math and Computer Science Department Boston United States University of Massachusetts Dept. Electrical and Computer Engineering Amherst United States

ISBN: (纸本)9798331513269

Today's information society relies on cryptography to achieve security goals such as confidentiality, integrity, authentication, and non-repudiation for digital communications. Here, public-key cryptosystems play a pivotal role to share encryption keys and create digital signatures. However, quantum computers threaten the security of traditional public-key cryptosystems as they can tame computational problems underlying the schemes, i.e., discrete logarithm and integer factorization. The prospective arrival of capable-enough quantum computers already threatens today's secret communication in terms of their long-term secrecy when stored to be later decrypted. Therefore, researchers strive to develop and deploy alternative *** this work, we evaluate a key exchange protocol based on combining public-key schemes with physical-layer security, anticipating the prospect of quantum attacks: If a powerful quantum attacker cannot immediately obtain a private key, legitimate parties have a window of short-term secrecy to perform a physical-layer jamming key exchange (JKE) to establish a long-term shared secret. Thereby, the protocol constraints the computation time available to the attacker to break the employed public-key cryptography. In this paper, we outline the protocol, discuss its security, and point out challenges to be resolved. © 2025 IEEE.

关键词： Quantum computers

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The Influence of Shielding Enclosure on the Characteristics of Protection Devices Operating in Differential and Common Modes

The Influence of Shielding Enclosure on the Characteristics ...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Valerii P. Kosteletskii Alexandr M. Lakoza Evgeniya B. Chernikova dept. of Microwave and Quantum Radio Engineering Tomsk State University of Control Systems and Radioelectronics Tomsk Russian Federation

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

In this work, we used quasi-static simulation to evaluate the influence of shielding enclosure on the attenuation coefficient and per-unit-length delays of devices protecting against ultra-wideband pulses. The protection devices were 6-and 8-conductor structures, each consisting of two transmission lines with inhomogeneous dielectric filling, combined into one structure. The simulation showed that increasing the distance between the shield walls and the 6-conductor structure resulted in the same attenuation coefficients as without the shield. Therefore, the shield should be kept as far away as possible to preserve the characteristics. In the 8-conductor structure, increasing the distance to the shield walls had a non-significant influence on the attenuation coefficient in the common and differential modes. This probably happened because the active conductors were placed in the central part (inside) of the structure cross-section. The per-unit-length mode delays in both structures were not influenced by changing distances to the walls.

关键词： Performance evaluation Industries Power transmission lines Attenuation Nonhomogeneous media Electromagnetic compatibility Filling Delays Protection Ultra wideband technology

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Modeling and Simulation of Thermal Faults in Batteries for Enhanced Safety

Modeling and Simulation of Thermal Faults in Batteries for E...

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IEEE Design and Diagnostics of Electronic Circuits and systems (DDECS)

作者： Francesco Tosoni Sara Vinco Franco Fummi Department of Engineering IM University of Verona Verona Italy Dept. of Control and Computer Engineering Politecnico di Torino Turin Italy

ISBN: (数字)9798331528010

ISBN: (纸本)9798331528027

Batteries are a central component of many complex systems, including mobile devices, sensors, electric vehicles, etc. Keeping the battery working in normal conditions avoids dangerous hazards for the user or the system itself and helps extend the device’s life. The battery temperature is one of the most delicate aspects of these devices since some dangerous scenarios, like thermal runaway, could occur due to variable conditions. This paper uses a battery model of an electric vehicle from the automotive area as a case study to simulate the thermal response to normal usage. Then, thermal fault scenarios are modeled within equivalent circuital device descriptions and analyzed regarding state-of-charge, temperature, and voltage output. The findings presented offer a valuable starting point for improving the design phase of the batteries in multiple fields by testing fault scenarios already during simulation.

关键词： Temperature sensors Voltage Electric vehicles Sensor systems Batteries Thermal analysis Sensors Circuit faults Integrated circuit modeling Testing

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Cooperative Multi-Agent Assignment over Stochastic Graphs via Constrained Reinforcement Learning

arXiv

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arXiv 2025年

作者： Agorio, Leopoldo Van Alen, Sean Paternain, Santiago Calvo-Fullana, Miguel Bazerque, Juan Andres Dept. of Electrical and Computer Engineering Univ. of Pittsburgh PittsburghPA United States Dept. of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States Dept of Engineering Universitat Pompeu Fabra Barcelona Spain

Constrained multi-agent reinforcement learning offers the framework to design scalable and almost surely feasible solutions for teams of agents operating in dynamic environments to carry out conflicting tasks. We address the challenges of multi-agent coordination through an unconventional formulation in which the dual variables are not driven to convergence but are free to cycle, enabling agents to adapt their policies dynamically based on real-time constraint satisfaction levels. The coordination relies on a light single-bit communication protocol over a network with stochastic connectivity. Using this gossiped information, agents update local estimates of the dual variables. Furthermore, we modify the local dual dynamics by introducing a contraction factor, which lets us use finite communication buffers and keep the estimation error bounded. Under this model, we provide theoretical guarantees of almost sure feasibility and corroborate them with numerical experiments in which a team of robots successfully patrols multiple regions, communicating under a time-varying ad-hoc network. Copyright © 2025, The Authors. All rights reserved.

关键词： Stochastic systems

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Artificial Intelligence for Green Agriculture and Sustainable Resource Management: A Comprehensive Overview

Artificial Intelligence for Green Agriculture and Sustainabl...

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Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Eman Alduweib Waseem Alromema Essa Hezzam Dept. of Computer Science University of Petra Amman Jordan Dept. of Computer Science and Information Applied College Taibah University Medina Saudi Arabia Dept. of Information Systems College of Computer Science and Engineering Taibah University Medina Saudi Arabia

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

Artificial Intelligence (AI) is a revolutionary technology disrupting the process of finding solutions for various sustainability challenges. Specifically, AI is having a significant influence on many sectors, especially agriculture, energy, waste management, and biodiversity conservation. This paper offers a comprehensive overview of AI's applications in sustainable resource management, with a special focus on green agriculture as a case study, in which the application of AI greatly enhances the efficiency of resource use, crop yield, and environmental conservation efforts. This overview describes the potential application of AI to address performance concerns (ethical value, energy use, and data quality deficiency), and proposes the future research directions such as the explainable AI, circular economies, and the integration of AI with the Internet of Things (IoT) to guide researchers and policymakers in exploiting AI to enhance sustainability in key domains.

关键词： Waste management Ethics Explainable AI Data integrity Transforms Resource management Internet of Things Biodiversity Artificial intelligence Sustainable development

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Optimizing 3D Flight Paths for Multiple UAVs with Connectivity Management in Urban Delivery systems

Optimizing 3D Flight Paths for Multiple UAVs with Connectivi...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Yeongmin Lee Raihan Muhammad Syahran Mael Spangenberger Huigyu Yang Jiyong Oh Hyunseung Choo Dept. of Artificial Intelligence Dept. of Electrical and Computer Engineering Dept. of Informatics Télécom SudParis Évry France Convergence Research Institute Dept. of AI Systems Engineering Sungkyunkwan University Suwon S. Korea

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

The dynamic deployment of aerial vehicles in urban delivery scenarios demands precise route planning, reliable data links, and efficient use of network infrastructure. Although prior efforts have explored various aspects of unmanned navigation or communication optimization, existing approaches often overlook the combined impact of three-dimensional path selection and robust connectivity maintenance. To address this gap, this paper proposes a deep reinforcement learning framework employing Independent Proximal Policy Optimization (IPPO) to steer the flight paths of unmanned vehicles while curtailing needless interactions with base stations (BSs). By incorporating communication-specific metrics, Reference Signal Received Power (RSRP), the proposed system adapts to urban conditions and upholds resilient network links. Comprehensive performance evaluations reveal the potential of the framework to reduce excessive BS connections by up to 82.24%, preserve RSRP levels above -80 dBm, and balance handover frequencies across flight trajectories. These findings affirm the scalability and effectiveness of the method for achieving efficient aerial navigation and consistent communication in urban delivery services.

关键词： Three-dimensional displays Navigation Scalability Surveillance Handover Autonomous aerial vehicles Trajectory Resource management Vehicle dynamics Optimization

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Deep Learning for Drug Response Prediction with Gene Expression Data

Deep Learning for Drug Response Prediction with Gene Express...

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International Conference on Information Networking

作者： Sardar Jaffar Ali Muhammad Omer Duc Tai Le Syed M. Raza Hyunseung Choo Dept. of AI Systems Engineering Sungkyunkwan University Suwon South Korea Dept. of Computer Science and Engineering Sungkyunkwan University Suwon South Korea Dept. of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea James Watt School of Engineering University of Glasgow Glasgow United Kingdom

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

Accurately predicting drug responses based on individual patient profiles is a critical challenge in personalized medicine, primarily due to the complex biological variability involved. This paper presents a deep learning framework for predicting changes in gene expression, providing insights into how drugs impact cells at the molecular level. Using data from the Kaggle competition, several models have been evaluated, including LSTM, GRU, Transformer, and Autoencoder architectures. Among these, the 3 -stacked GRU with Attention demonstrated superior performance, achieving the highest sign accuracy of 79% and the lowest mean absolute error across diverse biological conditions. The robust performance of the model highlights the effectiveness of attention mechanisms in capturing critical patterns in gene expression data.

关键词： Drugs Deep learning Attention mechanisms Precision medicine Biological system modeling Autoencoders Transformers Data models Gene expression Long short term memory

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An Ising Machine-Based Hybrid Optimization Method Using Constraint Conversion and Correction

An Ising Machine-Based Hybrid Optimization Method Using Cons...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Kinya Iwata Masashi Tawada Nozomu Togawa Dept. of Computer Science and Communications Engineering Waseda University Green Computing Systems Research Organization Waseda University

ISBN: (数字)9798331521165

ISBN: (纸本)9798331521172

This paper proposes an Ising machine-based hy-brid optimization method to solve combinatorial optimization problems, which consists of an approximate formulation process, an annealing process with an Ising machine, and a correction process. The approximate formulation and correction aim to improve the performance of the Ising machine. Computational experiments were conducted on the multi-dimensional knapsack problem (MKP) using an Ising machine. We compare the results with those of the proposed method and the conventional method and demonstrate the effectiveness of the proposed approach.

关键词： Annealing Optimization methods Consumer electronics

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