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Advancement in Technology (ICONAT), International Conference for

作者： Maxim Ryzhii Victor Ryzhii Taiichi Otsuji Vladimir Mitin Michael S. Shur Department of Computer Science and Engineering University of Aizu Aizu-Wakamatsu Japan Research Institute of Electrical Communication Tohoku University Sendai Japan Department of Electrical Engineering University at Buffalo SUNY Buffalo New York USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy New York USA

The interband Zener-Klein interband tunneling in the field-effect transistors (FETs) with the graphene channels consisting of the reverse-biased p-i-n junctions enables the negative dynamic conductance associated with the electrons and hole propagation delays. This can lead to the self-excitation of plasmons in the gated p- and n-regions. For the submicrometer gate lengths, the frequency of these plasmons is in the terahertz (THz) range. The plasmon self-excitation in this regime can be used for the generation of THz radiation.

关键词： Ring oscillators Terahertz wave imaging PIN photodiodes Graphene Field effect transistors Logic gates Tunneling

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An Image Acquisition Scheme for Visual Odometry based on Image Bracketing and Online Attribute Control

An Image Acquisition Scheme for Visual Odometry based on Ima...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shuyang Zhang Jinhao He Bohuan Xue Jin Wu Pengyu Yin Jianhao Jiao Ming Liu Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong SAR China Thrust of Robotics and Autonomous Systems the Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Center for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science University College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual odometry (VO) system is challenged by complex illumination environments. Image quality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect the robustness and accuracy of the entire system. In this paper, an image acquisition scheme with image bracketing patterns is proposed. Images with different exposure levels are continuously captured to sufficiently explore the scene under varying illumination. An attribute control method is designed to adjust image exposures within the brackets online. Gaussian process regression fits the relationship between image quality metric and exposure via image synthesis technique. The optimal exposures for the next bracket are obtained directly without attempts to ensure a quick response. Experiments show our acquisition system’s effectiveness and performance improvement for VO tasks in complex illumination scenes.

关键词： Image quality Measurement Image synthesis Lighting Gaussian processes Robustness Time-domain analysis

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DERs Orchestration and Gen3 Blockchain Integration in P2P Trading Based Distribution Network

DERs Orchestration and Gen3 Blockchain Integration in P2P Tr...

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Artificial Intelligence and Machine Learning for Energy Transformation (AIE), International Workshop on

作者： Liaqat Ali M. Imran Azim Jan Peters Nabin B. Ojha M.G. Simoes S.M. Muyeen Department of Electrical Engineering Curtin University Perth Australia Electrical and Computer Systems Engineering Monash University Clayton Victoria Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Berlin Germany Department of Energy Environment and Climate Change Asian Institute of Technology Pathum Thani Thailand Department of Electrical Engineering University of Vaasa Vaasa Finland Department of Electrical Engineering Qatar University Doha Qatar

ISBN: (数字)9798350364965

ISBN: (纸本)9798350364972

This paper discusses the advantages of orchestrating distribution energy resources (DERs) within the distribution network and integrating third generation (Gen3) blockchain technology among a diverse range of customers. The implementation of peer-to-peer (P2P) energy trading aims to optimize local energy utilization, reduce energy costs for participants, and provide insights into profit margins for aggregators and the distribution system operator (DSO). The study focuses on three types of DERs, namely electric vehicles (EVs), photovoltaic (PV) systems, and battery energy storage systems (BESSs), to facilitate transparent and secure P2P energy trading. The results underscore the importance of Gen3 blockchain technology in expediting and enhancing energy trading processes, thereby benefiting a wide range of participants.

关键词： Transactive energy Photovoltaic systems Costs Distribution networks Pricing Throughput Blockchains

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Energy-Aware Task Allocation for Teams of Multi-mode Robots

arXiv

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arXiv 2025年

作者： Ito, Takumi Funada, Riku Sampei, Mitsuji Notomista, Gennaro Department of Systems and Control Engineering Institute of Science Tokyo Tokyo152-8550 Japan Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

This work proposes a novel multi-robot task allocation framework for robots that can switch between multiple modes, e.g., flying, driving, or walking. We first provide a method to encode the multi-mode property of robots as a graph, where the mode of each robot is represented by a node. Next, we formulate a constrained optimization problem to decide both the task to be allocated to each robot as well as the mode in which the latter should execute the task. The robot modes are optimized based on the state of the robot and the environment, as well as the energy required to execute the allocated task. Moreover, the proposed framework is able to encompass kinematic and dynamic models of robots alike. Furthermore, we provide sufficient conditions for the convergence of task execution and allocation for both robot models. Copyright © 2025, The Authors. All rights reserved.

关键词： Constrained optimization

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THE LAGRANGIAN METHOD FOR SOLVING CONSTRAINED MARKOV GAMES

arXiv

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arXiv 2025年

作者： Das, Soham Paternain, Santiago Chamon, Luiz F.O. Eksin, Ceyhun Department of Industrial and Systems Engineering Texas A&M University College StationTX United States Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute TroyNY United States Center for Applied Mathematics Ecole Polytechnique Palaiseau France

We propose the concept of a Lagrangian game to solve constrained Markov games. Such games model scenarios where agents face cost constraints in addition to their individual rewards, that depend on both agent joint actions and the evolving environment state over time. Constrained Markov games form the formal mechanism behind safe multiagent reinforcement learning, providing a structured model for dynamic multiagent interactions in a multitude of settings, such as autonomous teams operating under local energy and time constraints, for example. We develop a primal-dual approach in which agents solve a Lagrangian game associated with the current Lagrange multiplier, simulate cost and reward trajectories over a fixed horizon, and update the multiplier using accrued experience. This update rule generates a new Lagrangian game, initiating the next iteration. Our key result consists in showing that the sequence of solutions to these Lagrangian games yields a nonstationary Nash solution for the original constrained Markov *** Codes 93A16, 91A15 (Primary) 91A26, 49N15 (Secondary) © 2025, CC BY-NC-SA.

关键词： Lagrange multipliers

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Operational Modeling of the Nexus Between Water-Distribution and Electricity systems

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Current Sustainable/Renewable Energy Reports 2025年第1期12卷 1-16页

作者： Gu, Weiying Sioshansi, Ramteen Department of Integrated Systems Engineering The Ohio State University 1971 Neil Avenue ColumbusOH43210-1271 United States Department of Engineering and Public Policy Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213-3815 United States Carnegie Mellon Electricity Industry Center Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213-3815 United States Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213-3815 United States Wilton E. Scott Institute for Energy Innovation Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213-3815 United States

Purpose of Review: We survey operational models of water-distribution systems. Although such modeling is important in its own right, our focus is motivated by the growing desire to examine and manage the nexus between water-distribution and electricity systems. As such, our survey discusses computational challenges in modeling water-distribution systems, co-ordination dynamics between water-distribution and electricity systems, and gaps in the literature. Recent Findings: Modeling water-distribution systems is made difficult by their highly non-linear and non-convex physical properties. Co-ordinating water-distribution and electricity systems, especially with the growing supply and demand uncertainties of the latter, requires fast optimization techniques for real-time system management. Although many works suggest means of co-ordinating the two systems, practical applications are limited, due to the systems having separate and autonomous management and ownership. Nonetheless, recent works are navigating this challenge, by seeking methods to foster improved co-ordination of the two systems while respecting their autonomy. Additionally, with the backdrop of increased security threats, there is a growing need to bolster infrastructure protection, which is complicated by the intertwined nature of the two systems. Summary: By providing a steady supply of potable water to satisfy residential, commercial, agricultural, and industrial demands, water-distribution systems are pivotal components of modern society and infrastructure. The extant literature presents many models and optimization strategies that are tailored for operating water-distribution systems. Yet, there remain unexplored problems, particularly related to simplifying model computation, capturing the flexibility of water-distribution systems, and capturing interdependencies between water-distribution and other systems and infrastructures. Future research that addresses these gaps will allow greater operational

关键词： Water distribution systems

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Hybrid Multi-Strategy Aquila Optimization with Deep Learning Driven Crop Type Classification on Hyperspectral Images

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computer systems Science & engineering 2023年第10期47卷 375-391页

作者： Sultan Alahmari Saud Yonbawi Suneetha Racharla ELaxmi Lydia Mohamad Khairi Ishak Hend Khalid Alkahtani Ayman Aljarbouh Samih M.Mostafa King Abdulaziz City for Science and Technology P.O Box 6086Riyadh 11442Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of AIML Aditya Engineering CollegeSurempallemAndhra PradeshIndia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India School of Electrical and Electronic Engineering Engineering CampusUniversiti Sains Malaysia(USM)Nibong TebalPenang14300Malaysia Department of Information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia Department of Computer Science University of Central AsiaNaryn722600Kyrgyzstan Faculty of Computers and Information South Valley UniversityQena83523Egypt

Hyperspectral imaging instruments could capture detailed spatial information and rich spectral signs of observed *** spatial information and spectral signatures of hyperspectral images(HSIs)present greater potential for detecting and classifying fine *** accurate classification of crop kinds utilizing hyperspectral remote sensing imaging(RSI)has become an indispensable application in the agricultural *** is significant for the prediction and growth monitoring of crop *** the deep learning(DL)techniques,Convolution Neural Network(CNN)was the best method for classifying HSI for their incredible local contextual modeling ability,enabling spectral and spatial feature *** article designs a Hybrid Multi-Strategy Aquila Optimization with a Deep Learning-Driven Crop Type Classification(HMAODL-CTC)algorithm *** proposed HMAODL-CTC model mainly intends to categorize different types of crops on *** accomplish this,the presented HMAODL-CTC model initially carries out image preprocessing to improve image *** addition,the presented HMAODL-CTC model develops dilated convolutional neural network(CNN)for feature *** hyperparameter tuning of the dilated CNN model,the HMAO algorithm is ***,the presented HMAODL-CTC model uses an extreme learning machine(ELM)model for crop type classification.A comprehensive set of simulations were performed to illustrate the enhanced performance of the presented HMAODL-CTC *** comparison studies reported the improved performance of the presented HMAODL-CTC algorithm over other compared methods.

关键词： Crop type classification hyperspectral images agricultural monitoring deep learning metaheuristics

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Intelligent Resource Allocation in Power Grids: Leveraging Variable Neighborhood Search for Optimal Switch Allocation

Intelligent Resource Allocation in Power Grids: Leveraging V...

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IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Henrique O. Caetano Matheus de S. S. Fogliatto N. Luiz Desuó Benvindo R. Pereira J Carlos D. Maciel Marco Aiello Dept. of Electrical and Computer Engineering São Carlos School of Engineering University of São Paulo Department of Service Computing Institute for Architecture of Application Systems University of Stuttgart

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

Within the paradigm of Evolving and Adaptive Intelligent systems, the electrical Power System (EPS) represents a Critical Infrastructure demanding robust reliability metrics. This study pioneers the application of Variable Neighborhood Search (VNS) heuristic to the Optimal Switch Allocation (OSA) problem in the EPS. Adapting neighborhood structures and local search methods, we consider the joint allocation of Manual Switches and Remote-Controlled switches, addressing interdependencies. Results highlight VNS efficacy in navigating OSA challenges, showcasing its adaptability in an evolving system. Comparative analyses endorse VNS as a valuable tool for addressing EPS reliability within the dynamic landscape of evolving and adaptive intelligent systems.

关键词： Adaptive systems Uncertainty Switches Search problems Robustness Power grids Critical infrastructure

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Conformal Prediction for Distribution-free Optimal Control of Linear Stochastic systems

arXiv

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arXiv 2024年

作者： Vlahakis, Eleftherios E. Lindemann, Lars Sopasakis, Pantelis Dimarogonas, Dimos V. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Thomas Lord Department of Computer Science The Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los AngelesCA90089 United States The School of Electronics Electrical Engineering and Computer Science Queen's University Northern Ireland Belfast United Kingdom

We address an optimal control problem for linear stochastic systems with unknown noise distributions and joint chance constraints using conformal prediction. Our approach involves designing a feedback controller to maintain an error system within a prediction region (PR). We define PRs as sublevel sets of a nonconformity score over error trajectories, enabling the handling of joint chance constraints. We propose two methods to design feedback control and PRs: one through direct optimization over error trajectory samples, and the other indirectly using the S-procedure with a disturbance ellipsoid obtained from data. By tightening constraints with PRs, we solve a relaxed problem to synthesize a feedback policy. Our method ensures reliable probabilistic guarantees based on marginal coverage, independent of data size. © 2024, CC BY.

关键词： Optimal control systems

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Quantifying uncertainty in Bayesian Networks structural learning

Quantifying uncertainty in Bayesian Networks structural lear...

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IEEE Workshop on Evolving and Adaptive Intelligent systems (EAIS)

作者： Vitor O. Barth Henrique O. Caetano Carlos D. Maciel Marco Aiello Dept. of Electrical and Computer Engineering São Carlos School of Engineering University of São Paulo Department of Service Computing Institute for Architecture of Application Systems University of Stuttgart

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

The key goals in learning Bayesian networks (BNs) from data are to identify significant statistical relationships between variables and to build a Directed Acyclic Graph (DAG) that represents these relationships through Joint Probability Distributions. Most research relies on score-based or conditional test methods for model selection. However, when using real-world data, it can be challenging to identify whether the learned DAG represents the underlying relations inherent in the limited datasets, particularly when evaluating data obtained from multiple independent sources. This study presents a methodology to assess the credible interval for both the existence and direction of each edge within Bayesian networks derived from data. Furthermore, it explores the fusion of models acquired from distinct and independent datasets. This approach enables the Bayesian learning of Bayesian Networks (BNs) from data by treating the uncertainty associated with the existence and orientation of each edge as a random variable. By evaluating the probability of the orientation of each edge, it is possible to suggest the existence of a potential latent variable within the dataset. If an edge exhibits equiprobable directions and is verified to exist, it becomes a plausible hypothesis for a latent variable. The Fast Causal Algorithm, originally introduced by [1], is the foundation of this approach. Finally, by employing a maximum a posteriori estimation, the most prominent edges and their respective orientations are identified and employed to create the leading DAG. We present our findings in simulated datasets with different length sizes. By comparing the structure of the learned DAGs with existing structures and evaluating the inference capabilities of the final BN, we establish that our approach achieves results comparable to the most recent studies in the field, while offering insights into the model’s reliability and improving the use of the data.

关键词： Maximum a posteriori estimation Uncertainty Scalability Data models Probability distribution Bayes methods Random variables

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