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arXiv 2022年

作者： Guarrasi, Valerio Soda, Paolo Unit of Computer Systems and Bioinformatics Department of Engineering University Campus Bio-Medico of Rome Italy Department of Computer Control and Management Engineering Sapienza University of Rome Italy

The COVID-19 pandemic has caused millions of cases and deaths and the AI-related scientific community, after being involved with detecting COVID-19 signs in medical images, has been now directing the efforts towards the development of methods that can predict the progression of the disease. This task is multimodal by its very nature and, recently, baseline results achieved on the publicly available AIforCOVID dataset have shown that chest X-ray scans and clinical information are useful to identify patients at risk of severe outcomes. While deep learning has shown superior performance in several medical fields, in most of the cases it considers unimodal data only. In this respect, when, which and how to fuse the different modalities is an open challenge in multimodal deep learning. To cope with these three questions here we present a novel approach optimizing the setup of a multimodal end-to-end model. It exploits Pareto multi-objective optimization working with a performance metric and the diversity score of multiple candidate unimodal neural networks to be fused. We test our method on the AIforCOVID dataset, attaining state-of-the-art results, not only outperforming the baseline performance but also being robust to external validation. Moreover, exploiting XAI algorithms we figure out a hierarchy among the modalities and we extract the features' intra-modality importance, enriching the trust on the predictions made by the model. Copyright © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Survey of Distributed Algorithms for Resource Allocation over Multi-Agent systems

arXiv

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arXiv 2024年

作者： Doostmohammadian, Mohammadreza Aghasi, Alireza Pirani, Mohammad Nekouei, Ehsan Zarrabi, Houman Keypour, Reza Rikos, Apostolos I. Johansson, Karl H. Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical Engineering and Computer Science Oregon State University United States Department of Mechanical Engineering University of Ottawa OttawaON Canada City University of Hong Kong China Tehran Iran Faculty of Electrical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA United States Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

Resource allocation and scheduling in multi-agent systems present challenges due to complex interactions and decentralization. This survey paper provides a comprehensive analysis of distributed algorithms for addressing the distributed resource allocation (DRA) problem over multi-agent systems. It covers a significant area of research at the intersection of optimization, multiagent systems, and distributed consensus-based computing. The paper begins by presenting a mathematical formulation of the DRA problem, establishing a solid foundation for further exploration. Real-world applications of DRA in various domains are examined to underscore the importance of efficient resource allocation, and relevant distributed optimization formulations are presented. The survey then delves into existing solutions for DRA, encompassing linear, nonlinear, primal-based, and dual-formulation-based approaches. Furthermore, this paper evaluates the features and properties of DRA algorithms, addressing key aspects such as feasibility, convergence rate, and network reliability. The analysis of mathematical foundations, diverse applications, existing solutions, and algorithmic properties contributes to a broader comprehension of the challenges and potential solutions for this domain. © 2024, CC BY.

关键词： Multi agent systems

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A Cyclic Small Phase Theorem for MIMO LTI systems*

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IFAC-PapersOnLine 2023年第2期56卷 1883-1888页

作者： Chao Chen Wei Chen Di Zhao Jianqi Chen Li Qiu Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Mechanics and Engineering Science & State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Control Science and Engineering & Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems. The underpinning of the definition lies in the matrix segmental phase which, as its name implies, is graphically based on the smallest circular segment covering the matrix normalized numerical range in the unit disk. The matrix segmental phase has the crucial product eigen-phase bound, which makes itself stand out from several existing phase notions in the literature. The proposed bound paves the way for stability analysis of a cyclic feedback system consisting of multiple subsystems. A cyclic small phase theorem is then established as our main result, which requires the loop system phase to lie between -π and π. The proposed theorem complements the celebrated small gain theorem.

关键词： Small phase theorem segmental phase cyclic feedback systems stability analysis lead-lag compensation

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Tabular Dyna-Q Algorithm for Online Calculation of LQR Gains: A Simulation Study

Tabular Dyna-Q Algorithm for Online Calculation of LQR Gains...

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International Conference on engineering and Emerging Technologies (ICEET)

作者： Kian Farooghi Mahdieh Samadi Hamid Khaloozadeh Department of Systems and Control K. N. Toosi University of Technology Tehran Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

ISBN: (数字)9798350316926

ISBN: (纸本)9798350316933

This paper presents a novel approach for the online calculation of Linear Quadratic Regulator (LQR) gains using the Tabular Dyna-Q algorithm. By leveraging Q-learning, this technique enables the determination of gains for unknown dynamic systems by using input-output data only. The proposed algorithm is particularly advantageous for situations where acquiring input-output data is expensive or time-consuming, as it effectively reduces computation time by reusing previous data. To validate the accuracy of the calculations and control scheme, a simulation example is provided. The results indicate the effectiveness of the Tabular Dyna-Q algorithm in accurately computing LQR gains and its potential application in real-world scenarios. This research contributes to advancing the field of control theory by offering an efficient and reliable method for online gain calculation in dynamic systems.

关键词： Q-learning Regulators System dynamics Heuristic algorithms Computational modeling Riccati equations Data collection

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High-Power LED Lamp Driver Modelling

High-Power LED Lamp Driver Modelling

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International Youth Conference on Radio Electronics, Electrical and Power engineering (REEPE)

作者： Igor V. Chukhraev Marina A. Sevastyanova Vladimir E. Drach Julia V. Torkunova Computer Science and Control Department Bauman Moscow State Technical University Moscow Russian Federation Department of Innovative Engineering and Digital Technologies Sochi State University Sochi Russian Federation Department of Information Technologies and Intelligent Systems Kazan State Power Engineering University Kazan Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The growing demand for energy-saving lamps highlights critical limitations in traditional LED secondary optics, which reduce energy efficiency and complicate heat dissipation — a key factor in LED lamp longevity. This study proposes an optimized circuit design for a 20-watt LED driver that addresses these issues. The proposed driver ensures effective LED control while improving thermal management and eliminating drawbacks of conventional designs. Key principles of modern LED lamp design and current challenges are identified. The electronic schematic of the high-power LED driver was simulated using LTSpice software in order to analyze and optimize the circuit's performance, resulting in a driver solution that enhances efficiency and reliability.

关键词： Thermal management of electronics Reactive power Power engineering LED lamps Power supplies Lighting Energy efficiency Software Software reliability Standards

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Investigating Role of Renewable Resources Including Wind Turbines in Energy Hub by Considering Simultaneous Demand for Electricity, Heating and Cooling

Investigating Role of Renewable Resources Including Wind Tur...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Daryoush Tavangar Rizi Mohammad Hassan Nazari Ali Maleki Seyed Hossein Hosseinian Maryam Fani Gevork B. Gharehpetian Department of Physics and Energy Engineering Amirkabir University of Technology Tehran Iran Smart Control Systems Department Niroo Research Institute (NRI) Tehran Iran School of Electrical Engineering & Computer Science Washington State University Pullman Washington Department of Electrical Engineering Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350361322

ISBN: (纸本)9798350361339

As a crucial component of multi-energy systems (MES), the energy hub significantly enhances their performance and reliability. In the energy system, the utilization of renewable energy sources (RES) can presents a significant optimization problem, capable of substantially reducing environmental pollution and lowering energy costs for users. This paper presents an optimal load dispatch model incorporating a collection of wind turbines, aimed at reducing the overall cost of operating an energy hub. It is also proposes a hub structure based on wind, natural gas, and electricity as a combined heat and power system, utilizing converters and energy storage mechanisms to obtain electricity, thermal, and cooling energy. To accomplish this, two situations are executed in the network, aiming to minimize costs by applying a problem-solving approach to the installation of wind turbines at an energy hub. After implementing energy hub management in the optimal mode, the system’s operating costs are reduced by $16 \%$, demonstrating its advantage.

关键词： Renewable energy sources Costs Electricity Wind turbines Problem-solving Trigeneration Optimization

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Analyzing the Impact of External Interventions on Water and Energy Demand: Cybersecurity’s Role in Sustainable Development

Analyzing the Impact of External Interventions on Water and ...

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Iranian Conference on Renewable Energy and Distributed Generation (ICREDG)

作者： Daryoush Tavangar Rizi Mohammad Hassan Nazari Ali Maleki Seyed Hossein Hosseinian Maryam Fani G. B. Gharehpetian Department of Physics & Energy Engineering Amirkabir University of Technology Tehran Iran Smart Control Systems Department Niroo Research Institute (NRI) Tehran Iran School of Electrical Engineering & Computer Science Washington State University Pullman Washington Department of Electrical Engineering Amirkabir University of Technology Tehran Iran

ISBN: (数字)9798350361322

ISBN: (纸本)9798350361339

The nexus of water, food, and energy constitutes a fundamental aspect of sustainable development. Furthermore, the demand for water and energy is becoming more pronounced. Moreover, there is a growing importance placed on studying cyber security within the water-energy nexus. This research investigates the interdependence of these two systems, conceptualizing them as a water-energy nexus and effort has been conducted on optimizing the economic efficiency of electricity and water systems in order to minimize operating expenses. Subsequently, external interventions, such as the simultaneous injection of false data on both water and energy demand, were addressed through an optimization process in GAMS software. The results suggest that the value of the cost objective function remains constant when inaccurate data is introduced, which hinders the accurate estimation of the system by the system operator. in this system, both water and power loads are directly impacted by these interventions. In particular, the power and water load of the system have exhibited changes ranging from 1.5% to 17.99% for electric load and 3.87% to 17.1% for water load, in comparison to the previous state.

关键词： Meters Renewable energy sources Electricity Distance measurement Software computer crime Sustainable development

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Funnel control Under Hard and Soft Output Constraints

Funnel Control Under Hard and Soft Output Constraints

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IEEE Conference on Decision and control

作者： Farhad Mehdifar Charalampos P. Bechlioulis Dimos V. Dimarogonas Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Electrical and Computer Engineering Division of Systems and Control University of Patras Patra Greece

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper proposes a funnel control method under time-varying hard and soft output constraints. First, an online funnel planning scheme is designed that generates a constraint consistent funnel, which always respects hard (safety) constraints, and soft (performance) constraints are met only when they are not conflicting with the hard constraints. Next, the prescribed performance control method is employed for designing a robust low-complexity funnel-based controller for uncertain nonlinear Euler-Lagrangian systems such that the outputs always remain within the planned constraint consistent funnels. Finally, the results are verified with a simulation example of a mobile robot tracking a moving object while staying in a box-constrained safe space.

关键词： Aerospace electronics Planning Safety Trajectory Complexity theory Mobile robots Nonlinear systems

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Consistent and Asymptotically Statistically-Efficient Solution to Camera Motion Estimation

arXiv

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arXiv 2024年

作者： Zeng, Guangyang Zeng, Qingcheng Li, Xinghan Mu, Biqiang Chen, Jiming Shi, Ling Wu, Junfeng The School of Data Science Chinese University of Hong Kong Shenzhen Shenzhen518172 China The College of Control Science and Engineering The State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou310027 China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong

Given 2D point correspondences between an image pair, inferring the camera motion is a fundamental issue in the computer vision community. The existing works generally set out from the epipolar constraint and estimate the essential matrix, which is not optimal in the maximum likelihood (ML) sense. In this paper, we dive into the original measurement model with respect to the rotation matrix and normalized translation vector and formulate the ML problem. We then propose a two-step algorithm to solve it: In the first step, we estimate the variance of measurement noises and devise a consistent estimator based on bias elimination;In the second step, we execute a one-step Gauss-Newton iteration on manifold to refine the consistent estimate. We prove that the proposed estimate owns the same asymptotic statistical properties as the ML estimate: The first is consistency, i.e., the estimate converges to the ground truth as the point number increases;The second is asymptotic efficiency, i.e., the mean squared error of the estimate converges to the theoretical lower bound - Cramer-Rao bound. In addition, we show that our algorithm has linear time complexity. These appealing characteristics endow our estimator with a great advantage in the case of dense point correspondences. Experiments on both synthetic data and real images demonstrate that when the point number reaches the order of hundreds, our estimator outperforms the state-of-the-art ones in terms of estimation accuracy and CPU time. Copyright © 2024, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Fuzzy System of IT-Project Works Priority

Fuzzy System of IT-Project Works Priority

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International Conference on Advanced computer Information Technologies (ACIT)

作者： Nadia Vasylkiv Lesia Dubchak Mikolaj Karpinski Iryna Turchenko Liubomyr Flud Tetiana Nadvynychna Department of Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine Department of Computer Engineering West Ukrainian National University Ternopil Ukraine Department of Cyber Security University of the National Education Commission Krakow Poland Department of Information Systems and Computer Modeling Ukrainian National Forestry University Lviv Ukraine Subdepartment of Psychology and Social Work West Ukrainian National University Ternopil Ukraine

ISBN: (数字)9798350350043

ISBN: (纸本)9798350350050

A fuzzy system for setting the priority of IT project work has been developed, in which a preliminary analysis of the metrics of readiness, permission and complexity of tasks is carried out, which makes it possible to determine the priority of the project work. Based on this, the business analyst can effectively make decisions about the workload of the project team. The results of the work can be successfully applied to the effective management of the implementation of IT projects and the proactive management of project teams.

关键词： Measurement Accuracy Employment Companies Software Hardware Complexity theory Information technology Fuzzy systems Business

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