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Coverage control under connectivity constraints 20

Coverage control under connectivity constraints

引用

20th International conference on Autonomous Agents and Multiagent systems, AAMAS 2021

作者： Kawajiri, Shota Hirashima, Kazuki Shiraishi, Masashi Mitsubishi Electric Corp. Information Technology R&D Center 5-1-1 Ofuna Kamakura Japan

ISBN: (纸本)9781713832621

In this paper, centralized and decentralized laws for the coverage problem under connectivity constraints are proposed. We formulated the problem as a continuous optimization task with the inequality constraint that algebraic connectivity must not be less than a small positive number, and solved the problem based on the active set method. this formulation can cause agents to be trapped in undesired local minima;to address this, we added the squared distance between the centroid of the coverage area and that of the agent system to the objective function of the coverage control. To derive the decentralized law, we employed an average consensus estimator that determines the algebraic connectivity and system centroid. When the algebraic connectivity is greater than the threshold, the proposed control laws allow agents to advance along the direction of steepest descent of the objective function. Once the connectivity is equal to the threshold, agents maintain the connectivity while decreasing the objective function by moving along the projection vector of the steepest descent in the direction in which the connectivity is constant. Simulation results confirmed the effectiveness of our proposed laws. © 2021 International Foundation for Autonomous Agents and Multiagent systems (***). All rights reserved.

关键词： optimization

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Real Time Reconstruction of Radio Environment Maps in Indoor Millimeter-Wave Beamforming with Beam Changes

Real Time Reconstruction of Radio Environment Maps in Indoor...

引用

International conference on Network and Service Management

作者： Takumi Bushi Toshiro Nakahira Shoko Shinohara Yusuke Asai Kenji Ohira Hideyuki Shimonishi Graduate School of Information Science and Technology Osaka University Osaka Japan NTT Access Network Service Systems Laboratories Nippon Telegraph and Telephone Corporation Yokosuka Japan Cybermedia Center Osaka University Osaka Japan

ISBN: (数字)9783903176669

ISBN: (纸本)9798331505158

To enable robust wireless communications towards the future Cyber Physical system by optimizing beamforming in real time, it is essential to quickly estimate changes in the radio environment map (REM) after altering the beam direction. In addition, because of the difficulty to predict detailed REMs with high accuracy, especially for millimeter waves, a probabilistic REM, which estimates the radio signal strength at any point as a probability distribution rather than as a deterministic value, is expected. In this paper, to enable fast and probabilistic REM estimation, we propose a scheme that divides the estimation formula into a linear term and a Gaussian Process Regression (GPR) term to minimize the recalculation time associated with beam adjustments. We also propose a GPR kernel that uses polar coordinates centered on the base station angle to better capture the characteristics of narrow beams like millimeter waves. We evaluated the proposed scheme using Kullback-Leibler Divergence (KLD) to compare the measured and estimated distributions of the radio signal strength. In the REM estimation after beam adjustment, an accurate distribution is estimated at 29 out of 35 points with a KLD of 0.5 or lower. the proposed method achieved approximately 50 times faster REM reconstruction compared to a simple REM using GPR, enabling dynamic beam-forming optimization in mm-wave environment.

关键词： Wireless communication Accuracy Array signal processing Millimeter wave technology Estimation Probabilistic logic Real-time systems Probability distribution Kernel optimization

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CPU and Memory Allocation optimization using Fuzzy Logic Based Clustering

CPU and Memory Allocation Optimization using Fuzzy Logic Bas...

引用

IEEE conference on Industrial Electronics and Applications (ICIEA)

作者： Eran Gur Zeev Zalevsky Dept. of Electrical Engineerign and Electronics Azrieli College of Engineering Jerusalem Israel Faculty of Engineering Bar Ilan University Ramat Gan Israel

the allocation of CPU time and memory resources, are well known problems in organizations with a large number of users, and a single mainframe. Usually, the amount of resources given to a single user is based on its own statistics, not on the entire statistics of the organization therefore patterns are not well identified and the allocation system is prodigal. In this work the authors suggest a fuzzy logic-based algorithm to optimize the CPU and memory distribution between the users based on the history of the users. the algorithm works separately on heavy users and light users since they have different patterns to be observed. the result is a set of rules, generated by the fuzzy logic inference engine that will allow the system to use its computing ability in an optimized manner. Test results on data taken from the Faculty of Engineering in Tel Aviv University, demonstrate the abilities of the new algorithm. this paper also examines the subject of system investigation using structured analysis (represented by Data Flow Diagrams - DFD), and the Object-Oriented Analysis and Design approaches (OOAD). the structured approach focuses on the flow and processing of data. the OOAD partitions the problem with respect to objects when analyzing the problem domain. When analyzing a large system or trying to reconstruct one using one of the two approaches mentioned above, there is apt to be a degree of inefficiency. this paper suggests a unique solution to this inefficiency. the optimization approach is based upon fuzzy logic inference engine clustering techniques. the study also presents the means for grading a system and creating a simple base for a computerized tool. By implementing the algorithm in a defined case study, we improved the modeling of the system coupling by 28 %, the system complexity by 20% and the system size criteria by 36%, for the structured analysis. this leads to system improvement process.

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Empowering Energy Communities by A User-Centric Model for Self-Managed Congestion via Local P2P and Flexibility Markets

Empowering Energy Communities by A User-Centric Model for Se...

引用

International conference on European Electricity Market, EEM

作者： Fernando García-Muñoz Sebasttían San Martín Josh Eichman University of Santiago of Chile (USACH) Santiago Chile Catalonia Institute for Energy Research Barcelona Spain

ISBN: (数字)9798350381740

ISBN: (纸本)9798350381757

the expected increase in distributed energy resource (DER) penetration at residential levels is promoting new local market frameworks to manage the use of these resources efficiently and improve users' and energy communities' welfare. In this regard, Peer-to-peer (P2P) energy trading and the flexibility market emerge as tentative solutions to address this purpose, empowering the users and energy communities' role in the electricity markets and in the energy transition. this article introduces a deterministic three-stage optimization model to self-manage congestion arising from the high penetration of DERs within an energy community through a local P2P and flexibility market framework. thus, under a day-ahead time framework, the initial stage considers that each user minimizes their own objective function, which is the energy bought from the grid. then, in the second stage, the DSO receives the scheduling dispatch from each user through the local market operator and solves an optimal power flow problem to identify possible congestion line issues. If any congestion appears in the second stage, it is managed in the third stage using the flexibility provided by the DERs and the P2P energy trading, considering the user's preferences derived from the first stage problem. the model has been tested in a modified version of the IEEE 33 bus system and shows the capability to mitigate congestion line issues using the flexibility from the storage and PV systems under a P2P energy trading scheme.

关键词： Privacy Profitability optimization models Stochastic processes Europe Linear programming Peer-to-peer computing

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Design and Development of Intelligent Pesticide Spraying system for Agricultural Robot 1

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20th International conference on Hybrid Intelligent systems, HIS 2020 and 12th World Congress on Nature and Biologically Inspired Computing, NaBIC 2020

作者： Deshmukh, Deepak Pratihar, Dilip Kumar Deb, Alok Kanti Ray, Hena Bhattacharyya, Nabarun Indian Institute of Technology Kharagpur India Centre for Development of Advanced Computing Kolkata India

ISBN: (数字)9783030730505

ISBN: (纸本)9783030730499

this paper presents a study and analysis of an intelligent and autonomous pesticide spraying robotic system for agricultural applications. this study aims to develop a smart pesticide spraying robotic system, which can move to infected plants in the field, identify the type of disease present in the plant, and spray appropriate pesticide. the robotic system consists of a serial manipulator mounted on a tracked vehicle, vision-based disease detection system and spraying system. the SOLIDWORKS modeling software is used for modeling and assembly of the serial manipulator, tracked vehicle, and spraying setup. the main focus of this article is towards the development of the hydraulic circuit and control system for dealing with multiple diseases present in the plants by making the decisions for regulating the flow of pesticide and switching among the pesticides to identify the most appropriate one. the fuzzy logic-based control system is developed and implemented successfully into the experimental setup with the help of MATLAB Simulink to the Arduino hardware interface. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： MATLAB

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Sustainable Control of Active systems: Decentralization and Incentive Compatibility 20th

Sustainable Control of Active Systems: Decentralization and ...

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20th IFAC conference on Technology, Culture, and International Stability (TECIS)

作者： Enaleev, A. Novikov, D. VA Trapeznikov Inst Control Sci Moscow Russia

Incentive compatible and strategy-proof mechanisms are designed for a set of Principal-agent problems under side payments. these mechanisms decompose the interaction of agents and allow the Principal to solve the incentive problem and the planning problem independently, reducing them to common optimization problems. the proposed mechanisms ensure agents communicate reliable data and execute plans. the use of these mechanisms may facilitate accounting of ethical and social aspects in organizational systems. Copyright (C) 2021 the Authors.

关键词： Active system mechanism design incentive compatibility truth-telling decentralization dominant-strategy equilibrium

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A Multi-Resolution Approach to the Assessment of Pleural Effusion in a Pig Model Using Multi-Frequency Transthoracic Bioimpedance

A Multi-Resolution Approach to the Assessment of Pleural Eff...

引用

International Workshop on Wearable and Implantable Body Sensor Networks (BSN)

作者： Jesus Antonio Sanchez-Perez Samer Mabrouk Omer T. Inan College of Engineering Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798331530143

ISBN: (纸本)9798331530150

Pleural effusion (PE) affects millions of people and is caused by a wide variety of underlying diseases. the excess of fluid in the pleural cavity leads to shortness of breath and increased risk for infections that require timely interventions. Yet, existing clinical assessments lack the temporal resolution for continuous monitoring of PE and associated respiratory symptoms. Novel wearable technologies capable of measuring multi-frequency transthoracic bioimpedance (BioZ) continuously hold promise for PE monitoring. In this study, we evaluated the feasibility of monitoring a bilateral PE in a pig model using continuous multi-frequency transthoracic BioZ obtained with a previously-validated wearable device. A novel multi-resolution approach yielded strong and significant correlations to the infused PE at the DClbaseline, respiratory windows, and breath-by-breath resolutions. A total of 1.65 L of saline was infused bilaterally, first left then right, in steps of 275 mL. the low-frequency DC resistance yielded the strongest correlation to the PE size (R 2 =O.99, −14%/L, p

关键词： Body sensor networks Fluids Correlation Biological system modeling Bioimpedance Feature extraction Wearable devices Monitoring Immune system Diseases

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Artificial Intelligence-Powered Antenna Design for 6G and Beyond Wireless Communication

Artificial Intelligence-Powered Antenna Design for 6G and Be...

引用

Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International conference on

作者： Maheswari. S N. Srividhya S. Navaneethan M. Senthil Murugan Sreelakshmy R J. Divya Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai India Department of Electronics and Communication Engineering K. Ramakrishnan College of Engineering Samayapuram Trichy India Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India Department of Electronics and Communication Engineering St. Joseph's Institute of Technology Chennai India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai India Department of Computer Science and Design R.M.K. Engineering College Chennai India

ISBN: (数字)9798331533663

ISBN: (纸本)9798331533670

Innovative antenna designs are necessary to meet the high-speed, low-latency needs of 6G and next-generation wireless networks. Because of problems with scalability, efficiency, and flexibility, the performance of standard antenna design approaches degrades in dynamic conditions. Real-time network optimization, interference, and energy usage are additional issues with these systems. the AI-driven antenna design is based on ML and DL techniques. the antenna's architecture is optimized using an AI-based system that continuously learns and adapts to the evolving behavior of the network. It optimizes antennas in real-time by using data preprocessing, feature extraction, and ML models. When compared to the newest technology, it exhibits improvements in throughput, latency, energy usage, and signal quality. these include a 35% reduction in energy consumption, a 40% reduction in latency, and a 20% increase in throughput. the results show that the proposed system can increase network performance and efficiency, which supports the proposed system's potential applicability for wireless communication in 6G and beyond.

关键词： 6G mobile communication Energy consumption Adaptation models Design methodology Computational modeling Wireless networks throughput Real-time systems Antennas optimization

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Research on Multi-source Heterogeneous Data Preprocessing Based on Improved Crow Search Algorithm

Research on Multi-source Heterogeneous Data Preprocessing Ba...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International conference on

作者： Shuai Yuan Xiaolu Pei Shulin Guo Yu Long Ke Li Beijing CLP Feihua Communication Co. Ltd Beijing China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

the integrity of multi-source heterogeneous data in vehicle-grid interaction is crucial to the security of the vehicle-grid system. Aiming at the problem that the missing of multi-source heterogeneous data can easily lead to inaccurate analysis results, which in turn affects the charging scheduling of electric vehicles and the load management of the power grid, this paper proposes a multi-source heterogeneous data filling algorithm based on the improved crow search algorithm. First, based on the characteristics of multi-source heterogeneous data in vehicle-grid interaction, a data filling model is constructed to clarify the correspondence between parameters and data filling models. Secondly, in view of the problem of insufficient search accuracy of the crow search algorithm, an optimal solution solidification mechanism and an adaptive step size strategy are proposed to improve the algorithm. then, the improved crow search algorithm is used to find the optimal solution for the data filling model. Finally, the filling model optimized by the algorithm is used to construct a heterogeneous data set. Taking accuracy as the performance index, the proposed algorithm is compared with the unimproved crow search algorithm and whale optimization algorithm, and the results show that the data accuracy of the proposed algorithm is increased by more than 20%, which effectively improves the data integrity.

关键词： Adaptation models Accuracy Stability criteria Search problems Filling Data models Whale optimization algorithms Scheduling Security Load modeling

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Scheduling of Energy Consumption in Stand-alone Energy systems Considering the Battery Life Cycle

Scheduling of Energy Consumption in Stand-alone Energy Syste...

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20th IEEE International conference on Environment and Electrical Engineering (EEEIC) / 4th IEEE Industrial and Commercial Power systems Europe conference (I and CPS Europe)

作者： Bouakkaz, Abderraouf Gil Mena, Antonio J. Haddad, Salim Ferrari, Mario Luigi Univ 20 Aout 1955 Skikda Lab Genie Mecan & Mat Bp26 Route Hada Skikda Algeria Escuela Politecn Super Algeciras Dept Elect Engn Avda Ramon Puyol S-N Cadiz 11202 Spain Univ Genoa Thermochem Power Grp TPG Genoa Italy

ISBN: (纸本)9781728174556

the aim of the present work in this paper is to propose an optimized energy management strategy that allows enhancing the life cycle of batteries through the optimal scheduling of energy consumption in a house connected to a stand-alone energy system with an energy storage system (PV, wind turbine, diesel generator, and batteries). A rain flow counting algorithm is used to calculate the number of cycles of the battery, while the optimization problem was solved using a particle swarm optimization algorithm (PSO). the optimization aims to reduce the number of cycles in the whole day by managing the charging and discharging process in order to maximize the battery life cycle. the results obtained by the simulation prove the effectiveness of the proposed strategy in the optimization of the life cycle of the battery to more than 38%.

关键词： Renewable energy Rain flow counting algorithm Batteries Number of cycles Battery life time optimization

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