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IEEE Conference on Decision and Control

作者： Dejan Milutinović Alexander Von Moll Satyanarayana G. Manyam David W. Casbeer Isaac E. Weintraub Meir Pachter Dept. University of California Santa Cruz Electrical and Computer Engineering Santa Cruz CA USA Control Science Center Aerospace Systems Directorate Air Force Research Laboratory Dayton OH USA DCS Corporation Dayton OH USA Dept. of Electrical Engineering Air Force Institute of TechnologyWright-Patterson AFB OH USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In planar pursuit-evasion differential games considering a faster pursuer and slower evader, the interception points resulting from equilibrium strategies lie on the Apollonius circle. This property is instrumental for leveraging geometric approaches for solving multiple pursuit-evasion scenarios in the plane. Here, we study a pursuit-evasion differential game on a sphere and generalize the planar Apollonius set to the spherical domain. We find that the interception point from the equilibrium strategies can leave the Apollonius set boundary and present a condition to keep the intercept point on the boundary. This condition allows for generalizing planar pursuitevasion strategies to the sphere.

关键词： Geometry Instruments Differential games Games

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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Learning Goal-based Movement via Motivational-based Models in Cognitive Mobile Robots

arXiv

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arXiv 2023年

作者： Berto, Letícia Costa, Paula Simões, Alexandre Gudwin, Ricardo Colombini, Esther Laboratory of Robotics and Cognitive Systems Institute of Computing University of Campinas Brazil Dept. of Computer Engineering and Industrial Automation School of Electrical and Computer Engineering University of Campinas Brazil Dept. of Control and Automation Engineering Institute of Science and Technology São Paulo State University Sorocaba Brazil University of Campinas Brazil

Humans have needs motivating their behavior according to intensity and context. However, we also create preferences associated with each action’s perceived pleasure, which is susceptible to changes over time. This makes decision-making more complex, requiring learning to balance needs and preferences according to the context. To understand how this process works and enable the development of robots with a motivational-based learning model, we computationally model a motivation theory proposed by Hull. In this model, the agent (an abstraction of a mobile robot) is motivated to keep itself in a state of homeostasis. We added hedonic dimensions to see how preferences affect decision-making, and we employed reinforcement learning to train our motivated-based agents. We run three agents with energy decay rates representing different metabolisms in two different environments to see the impact on their strategy, movement, and behavior. The results show that the agent learned better strategies in the environment that enables choices more adequate according to its metabolism. The use of pleasure in the motivational mechanism significantly impacted behavior learning, mainly for slow metabolism agents. When survival is at risk, the agent ignores pleasure and equilibrium, hinting at how to behave in harsh scenarios. Copyright © 2023, The Authors. All rights reserved.

关键词： Metabolism

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Pursuit-Evasion on a Sphere and When It Can Be Considered Flat

arXiv

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arXiv 2024年

作者： Milutinović, Dejan Von Moll, Alexander Manyam, Satyanarayana G. Casbeer, David W. Weintraub, Isaac E. Pachter, Meir Electrical and Computer Engineering Dept. University of California Santa Cruz Santa CruzCA United States The Control Science Center Aerospace Systems Directorate Air Force Research Laboratory DaytonOH45435 United States DCS Corporation DaytonOH United States Dept. of Electrical Engineering Air Force Institute of Technology Wright-Patterson AFB OH United States

In classical works on a planar differential pursuit-evasion game with a faster pursuer, the intercept point resulting from the equilibrium strategies lies on the Apollonius circle. This property was exploited for the construction of the equilibrium strategies for two faster pursuers against one evader. Extensions for planar multiple-pursuer single-evader scenarios have been considered. We study a pursuit-evasion game on a sphere and the relation of the equilibrium intercept point to the Apollonius domain on the sphere. The domain is a generalization of the planar Apollonius circle set. We find a condition resulting in the intercept point belonging to the Apollonius domain, which is the characteristic of the planar game solution. Finally, we use this characteristic to discuss pursuit and evasion strategies in the context of two pursuers and a single slower evader on the sphere and illustrate it using numerical *** Codes 58E10, 86A30, 37D40, 91A23, 49L12, 49Q10 © 2024, CC BY-NC-ND.

关键词： Spheres

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Pneumonia Classification using deep learning: a comparative study

Pneumonia Classification using deep learning: a comparative ...

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International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Mohamed Lakhdar Tiar Nadjiba Terki Juan Jose Dominguez-Jimenez IL3CUB Laboratory University of Mohamed Khider Biskra Algeria Electrical Engineering Department University of Mohamed Khider Biskra Algeria Dept. Computer Languages and Systems University of Cadiz Escuela Superior de Ingenieria Cadiz Spain

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Pneumonia is an infectious disease of the lungs, caused by viruses, bacteria or fungi. Pneumonia is distinguished by acute inflammation of the lung tissue, causing the consolidation of the terminal bronchioles and alveoli. According to the WHO (the World Health Organization), this disease causes about 4 million deaths. Among the methods of diagnosing pneumonia uses a chest X-ray. This is widely used to visualize pulmonary abnormalities. This work aims at the detection and characterization of pneumonia by the development of computer-assisted diagnosis systems (DAOC). We use deep learning algorithms and chest X-ray images from a pneumonia database to examine the classification of pneumonia. To improve the accuracy, we compare several deep learning models. This research contributes to meeting the growing demand for medical personnel by addressing the global incidence of chest disorders.

关键词： Deep learning Visualization Pneumonia Lung Signal processing algorithms Medical services Signal processing

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A Novel Non-Mirrored Buck-Boost Flying Capacitor Multilevel DC-DC Converter Topology

A Novel Non-Mirrored Buck-Boost Flying Capacitor Multilevel ...

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IEEE Annual Southern Power Electronics Conference (SPEC)

作者： Samantha Coday David Menzi Jonas Huber Johann W. Kolar ETH Zurich Power Electronic Systems Laboratory Switzerland Dept. of Electrical Engineering and Computer Sciences University of California Berkeley U.S.A

Enabling future electrification of air and ground transportation requires flexible, compact, and highly efficient power converters. Four-switch non-inverting bidirectional buck-boost dc-dc converters allow for wide and overlapping input and output voltage ranges, enabling integration of fuel cells and batteries whose voltages vary with state of charge and operating conditions. In this work, we propose a novel non-mirrored buck-boost (N-MBB) Flying Capacitor Multilevel (FCML) dc-dc converter. The proposed topology integrates the conventionally separated buck and boost bridge-legs, which is enabled by novel monolithic bidirectional GaN transistors featuring bipolar voltage blocking capability. Compared to the conventional mirrored buck-boost FCML converter, the proposed topology shows a higher inductor vol-ume but advantageously a lower component count, better utilization of the installed chip area and flying capacitors, and lower conduction losses. Finally we introduce a topology variant with reduced induc-tor volume, the return-path-inductor (RPI) N-MBB FCML, and a direct non-isolated single-phase dc-ac N-MBB FCML inverter.

关键词： Economic indicators Capacitors Voltage DC-DC power converters Inverters Topology Transistors

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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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IEEE International Conference on systems, Man and Cybernetics

作者： Jing Bi Ziqi Wang Haitao Yuan Jinhong Yang Jia Zhang College of Computer Beijing University of Technology Beijing China Beijing Laboratory of Smart Environmental Protection Beijing University of Technology Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Lyle School of Engineering Southern Methodist University Dallas TX USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

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.

关键词： Accuracy Processor scheduling Computational modeling Education Autoencoders Collaboration Search problems Space exploration Particle swarm optimization Optimization

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The DEVStone Metric: Performance Analysis of DEVS Simulation Engines

arXiv

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arXiv 2023年

作者： Cárdenas, Román Henares, Kevin Arroba, Patricia Risco-Martín, José L. Wainer, Gabriel A. Integrated Systems Laboratory Universidad Politécnica de Madrid Madrid Spain Dept. of Systems and Computer Engineering Carleton University OttawaON Canada Dpt. of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain Center for Computational Simulation Universidad Politécnica de Madrid Madrid Spain

The DEVStone benchmark allows us to evaluate the performance of discrete-event simulators based on the DEVS formalism. It provides model sets with different characteristics, enabling the analysis of specific issues of simulation engines. However, this heterogeneity hinders the comparison of the results among studies, as the results obtained on each research work depend on the chosen subset of DEVStone models. We define the DEVStone metric based on the DEVStone synthetic benchmark and provide a mechanism for specifying objective ratings for DEVS-based simulators. This metric corresponds to the average number of times that a simulator can execute a selection of 12 DEVStone models in one minute. The variety of the chosen models ensures we measure different particularities provided by DEVStone. The proposed metric allows us to compare various simulators and to assess the impact of new features on their performance. We use the DEVStone metric to compare some popular DEVS-based simulators. © 2023, CC BY-SA.

关键词： Discrete event simulation

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Secure the 5G and Beyond Networks with Zero Trust and Access Control systems for Cloud Native architectures

Secure the 5G and Beyond Networks with Zero Trust and Access...

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ACS/IEEE International Conference on computer systems and Applications

作者： Hisham A. Kholidy Keven Disen Andrew Karam Elhadj Benkhelifa Mohammad A. Rahman Atta-Ur Rahman Ibrahim Almazyad Ahmed F. Sayed Rakia Jaziri Dept. of Networks and Computer Security College of Engineering SUNY Polytechnic Institute Utica NY USA Dept. of Networks and Comp. Security SUNY Polytechnic Institute Utica NY USA The Air Force Research Laboratory (AFRL RIGB) Rome NY USA Smart Systems AI and Cybersecurity Research Centre Staffordshire Univ. UK Dept of Electrical and Computer Engineering Florida International University USA Dept. of Computer Science Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Dept. of Electrical and Computer Engineering Univ. of Arizona Tucson AZ USA Transmission Dept. Telecom Egypt Fayoum Egypt Paragraphe Research Lab. Univ. of Paris VIII France

5G networks are highly distributed, built on an open service-based architecture that requires multi-vendor hardware and software development environments, all of which create a high attack surface in the 5G networks than other proprietary fixed-function networks. Besides that, cloud-native architectures also present new security challenges. Cloud-native separates monolithic virtual machines into microservice pods, resulting in higher volumes of signaling and communication flowing through and between microservices. In addition, secure connections in monolithic applications have been replaced by untrusted communication between microservice pods, requiring additional cybersecurity capabilities. Access control systems were created to provide reliability and limit access to an organization’s assets. However, due to technology's constant evolution and dynamicity, these conventional security systems lack the security to protect an organization’s information because they were created to address access control for known users. For 5G based cloud native technology, these access controls need to be taken further by implementing a Zero Trust model to secure one’s essential assets for all users within the system. Zero Trust is implemented in an access control system under the concept "Never Trust, Always Verify". In this paper, we implement zero trust as a factor within access control systems by combining the principles of access control systems and zero-trust security by factoring in the user’s historical behavior and recommendations into the mix.

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Feedback control in RF photonic transversal filter systems based on optical microcombs

Feedback control in RF photonic transversal filter systems b...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

作者： Li, Yang Wu, Jiayang Sun, Yang Ren, Guanghui Tan, Mengxi Xu, Xingyuan Corcoran, Bill Chu, Sai Tak Little, Brent E. Morandotti, Roberto Mitchell, Arnan Moss, David J. Optical Sciences Centre Swinburne University of Technology HawthornVIC3122 Australia Integrated Photonics and Applications Centre School of Engineering RMIT University MelbourneVIC3000 Australia School of Electronic and Information Engineering Beihang University Beijing100191 China State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Photonic Communications Laboratory Dept. Electrical and Computer Systems Engineering Monash University ClaytonVIC Australia Department of Physics City University of Hong Kong Hong Kong QXP Technology Inc. Xi'an China INRS - Énergie Matériaux et Télécommunications VarennesQCJ3X 1S2 Canada

We propose and experimentally demonstrate four different feedback control methods employed in microcomb-based RF photonic transversal filter systems to enhance their accuracy and stability. Detailed characterizations ... 详细信息

关键词： Transversal filters

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