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2021 International Symposium on Networks, computers and Communications, ISNCC 2021

作者： Bouras, Christos Kalogeropoulos, Rafail Sina, Ioannis Computer Technology Institute Press 'Diophantus201D Univ. Of Patras Greece Patras Greece Computer Engineering And Informatics Dept.

ISBN: (纸本)9780738113166

Machine learning is an extremely efficient technique for solving complex problems without the use of traditional programming but rather enabling machines to learn from an input of data and train them to cope with various problems. The rapid growth in the number of active mobile devices, mobile applications and services dictates an efficient utilization of mobile and wireless networking infrastructure. Communication networks need to evolve and valorize machine learning methods in order to process large volumes of data without introducing excessive time delay in these computations. Upcoming 5G systems are expected to be the first network infrastructure to support exploding mobile traffic volumes and machine learning techniques can be used in order to help manage the rise in data volumes. We present a mechanism for resource allocation in mobile and wireless networks, that effectively utilizes machine learning techniques. © 2021 IEEE.

关键词： Wireless networks

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EEG Analysis of Human Perception based on Video-Audio Stimuli 1

EEG Analysis of Human Perception based on Video-Audio Stimul...

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1st International Conference on Smart Technologies Communication and Robotics, STCR 2021

作者： Manochitra, S. Partheepan, Ravinthiran Kalasalingam Institute of Technology Faculty of Computer Science and Engineering Tamilnadu Virudhunagar India Vytautas Magnus University Faculty of Informatics Master Programme - Applied Informatics Kaunas Lithuania

ISBN: (纸本)9781665418065

Emotions plays a potential role in human computer interaction which are having an obligatory models of cognitive measures. The emotions are dominated by the human physiological communication channels. Those emotions could affect several human activities like learning, decision making, communication, perception, cognitive and so on. Also, some of the emotions are quite difficult to measure and interpret and having difficulty in incorporating them into a technology and design. On the other hand, state of the technologies has enabled us to capture the emotions and integrate them for the use of human computer interaction contexts. This paper delivers an attempt to model the emotions using electroencephalography (EEG). The video stimuli for the two representatives are based on a few negative, positive and neutral contents were shown to volunteers and EEG data was obtained. Further, EEG analysis were experimented and collected about their emotional states with subject's self reports. This study determines that the human emotions could be modelled for affect assessment module or for the usage in human computer interaction and affect based intelligent interactions. © 2021 IEEE.

关键词： Human computer interaction

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Enhancing Secure Cross-Border Collaboration among Law Enforcement Agencies for Facial Biometric Search

Enhancing Secure Cross-Border Collaboration among Law Enforc...

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Electronic Engineering, Information technology & Education (EEITE), International Conference in

作者： Kyriaki Miniadou Asterios Leonidis Georgios Th. Papadopoulos Constantine Stephanidis Institute of Computer Science (ICS) Foundation for Research and Technology - Hellas (FORTH) Heraklion Greece Department of Informatics and Telematics Harokopio University of Athens Athens Greece Department of Computer Science University of Crete Heraklion Greece

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

Addressing the growing challenge of combating international crime involves the development of secure and efficient methodologies that allow Law Enforcement Agencies to exchange information seamlessly, without being hindered by time-consuming bureaucratic processes. In this context, we present a solution centered on facial biometric search methodologies. Our approach underscores the importance of employing accurate and reliable methods to assess image data similarity, particularly in the domain of facial images, which pose unique challenges due to subtle variations. We propose a comprehensive solution that harnesses hashing techniques and homomorphic encryption. By doing so, our approach ensures secure data exchange while safeguarding confidentiality and integrity. We firmly believe that our approach will substantially improve collaboration in law enforcement efforts and make significant contributions to global security.

关键词： Data privacy Law enforcement Scalability Education Collaboration Fingerprint recognition Regulation

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Context-aware Container Orchestration in Serverless Edge Computing

Context-aware Container Orchestration in Serverless Edge Com...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Peiyuan Guan Chen Chen Ziru Chen Lin X. Cai Xing Hao Amir Taherkordi Dept. of Informatics University of Oslo Oslo Norway Dept. of Computer Science and Technology University of Cambridge Cambridge UK Dept. of Electrical and Computer Engineering Illinois Institute of Technology Chicago USA School of Information Science and Technology Northwest Univesity Xi’an China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of services. However, due to the heterogeneous nature of computing and bandwidth resources in edge networks, it is challenging to dynamically allocate different resources while adapting to the burstiness and high concurrency in serverless workloads. This article focuses on serverless function provisioning in edge networks to optimize end-to-end latency, where the challenge lies in jointly allocating wireless bandwidth and computing resources among heterogeneous computing nodes. To address this challenge, We devised a context-aware learning framework that adaptively orchestrates a wide spectrum of resources and jointly considers them to avoid resource fragmentation. Extensive simulation results justified that the proposed algorithm reduces over 95% of converge time while the end-to-end delay is comparable to the state of the art.

关键词： Wireless communication Simulation Serverless computing Bandwidth Quality of service Containers Heterogeneous networks Delays Global communication Edge computing

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Fuzzy control system design for wheel slip prevention and tracking of desired speed profile in electric trains

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Asian Journal of Control 2022年第1期24卷 388-400页

作者： Moaveni, Bijan Rashidi Fathabadi, Fatemeh Molavi, Ali Center of excellence for Modelling and Control of Complex Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Western Michigan University MI United States Institute of Robotics and Industrial Informatics Polytechnical University of Catalonia Barcelona Spain

This study proposes an anti-slip control system for electric trains based on the fuzzy logic theory, which prevents the wheels from slipping during the acceleration and simultaneously tracks the desired speed profile. To improve the control performance, the train longitudinal velocity and the slip ratio are estimated. By using a field-oriented control (FOC), the angular speed of the traction motor is controlled. The fuzzy control system determines the desired angular speed of the traction motor as the reference input of FOC to obtain the desired slip ratio and track the desired speed profile. Simulation results show the effectiveness of the control system in various wheel–rail surface conditions based on the real parameters of ER24PC locomotive. © 2020 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd

关键词： Traction motors

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Application of Parallel Signal Processing Using Reverse Blockchain technology in Conditions of Network Instability

Application of Parallel Signal Processing Using Reverse Bloc...

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Electrical, computer, Communications and Mechatronics Engineering (ICECCME), International Conference on

作者： Volodymyr Khilenko Andrii Zinchenko Oleksii Stepanov Ivan Kotuliak Michal Ries Faculty of Informatics and Information Technologies Institute of Computer Engineering and Applied Informatics Slovak University of Technology in Bratislava Bratislava Slovakia Institute of Transport Systems and Technologies National Academy of Sciences of Ukraine Dnipro Ukraine Department of Information Technologies National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Bratislava Slovakia

ISBN: (数字)9798350391183

ISBN: (纸本)9798350391190

The theses is in line with works aimed at studying the possibility of using mathematical algorithms for parallel processing of information in reverse blockchain technology. The paper examines the use of parallel signal processing algorithms to improve the speed and quality of control systems for autonomous dynamic objects using reverse blockchain technology. The use of reverse blockchain technology is due to the possibility of loss of control signals and, at the same time, the inadmissibility of loss of control in the event of changes in the conditions and parameters of the operation of the obj ect. The purpose of the work is to analyze the implementation of solutions for parallel information processing for various models of industrially produced equipment and to develop solutions to increase the efficiency of reverse blockchain technology when using parallel data processing.

关键词： Analytical models Heuristic algorithms Instruction sets Signal processing algorithms Process control Parallel processing Control systems Smart systems Data models Blockchains

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Perspective-taking for promoting prosocial behaviors through robot-robot VR task

Perspective-taking for promoting prosocial behaviors through...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Hang Chenlin Ono Tetsuo Seiji Yamada Department of Informatics The Graduate University for Advanced Studies Sokendai Kanagawa Japan National Institute of Informatics Tokyo Japan Faculty of Information Science and Technology Division of Computer Science and Information Technology Hokkaido University Sapporo Japan

Perspective-taking, which enables individuals to consider the thoughts and objectives of another, is well established to be a successful strategy for encouraging pro-social behavior in human-computer interactions. Nowadays, perspective-taking is no longer limited to text; it is now more frequently used in virtual reality (VR). However, most previous research has focused on simulating human-human interactions in the real world in VR by providing participants with experiences connected to different moral tasks. In this study, we investigated whether participants’ prosocial behaviors toward robots would change if they experienced an altruistic VR task involving robots from the perspective of different robots. Our findings show that participants who had the help-receiver-view exhibited more altruistic behaviors toward a robot than those who had the help-provider-view one in a dictator game. We believe that this work is the first attempt to investigate the relationship between perspective-taking in a VR environment and changes in prosocial behavior in human-robot interaction.

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Multi-objective VNF Placement Optimization with NSGA-III 1st

Multi-objective VNF Placement Optimization with NSGA-III

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1st International Conference on Advances in Computing Research, ACR’23

作者： Bekhit, Mahmoud Fathalla, Ahmed Eldesouky, Esraa Salah, Ahmad Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Kent Institute Australia Melbourne Australia Department of Mathematics Faculty of Science Suez Canal University Ismailia Egypt Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia College of Computers and Informatics Zagazig University Zagazig Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (纸本)9783031337420

With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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Contextual Pre-planning on Reward Machine Abstractions for Enhanced Transfer in Deep Reinforcement Learning

arXiv

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arXiv 2023年

作者： Azran, Guy Danesh, Mohamad H. Albrecht, Stefano V. Keren, Sarah Taub Faculty of Computer Science Technion Israel Institute of Technology Israel School of Computer Science McGill University Canada School of Informatics University of Edinburgh United Kingdom

Recent studies show that deep reinforcement learning (DRL) agents tend to overfit to the task on which they were trained and fail to adapt to minor environment changes. To expedite learning when transferring to unseen tasks, we propose a novel approach to representing the current task using reward machines (RMs), state machine abstractions that induce subtasks based on the current task’s rewards and dynamics. Our method provides agents with symbolic representations of optimal transitions from their current abstract state and rewards them for achieving these transitions. These representations are shared across tasks, allowing agents to exploit knowledge of previously encountered symbols and transitions, thus enhancing transfer. Empirical results show that our representations improve sample efficiency and few-shot transfer in a variety of domains. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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A Trajectory Planning Method for Automatic Water Fetching by a Robotic Arm Based on Deep Reinforcement Learning 24

A Trajectory Planning Method for Automatic Water Fetching by...

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Proceedings of the 2024 4th International Conference on Computational Modeling, Simulation and Data Analysis

作者： Yu Song Qi Li Xinyu Che Mengru Du School of Computer Science and Technology Changchun University of Science and Technology Changchun Jilin China School of Computer Science and Technology Changchun University of Science and Technology Changchun Jilin China Jilin Provincial International Joint Research Center of Brain Informatics and Intelligence Science Changchun China Zhongshan Institute of Changchun University of Science and Technology Zhongshan China

ISBN: (纸本)9798400711831

The study focuses on trajectory planning for an assistive robotic arm to autonomously fetch water, using deep reinforcement learning (DRL) algorithms to assist patients in complex environments. In real-world scenarios, the robot base is responsible for reaching a designated target location, while the robotic arm performs tasks of grasping and placing objects. Given the different precision requirements for controlling each, it is evident that the robotic arm requires continuous, precise trajectory control. Based on this, considering the motion differences between the robotic arm and its base, a combination of sparse and continuous reward strategies is employed to control the movement trajectory of the assistive robotic arm. A novel reward function is designed to aid the arm in better exploring the environment. The approach integrates the Actor-Critic algorithm with the Deep Deterministic Policy Gradient (DDPG) algorithm to train the assistive robotic arm. Ultimately, a multi-task, multi-objective assistive robotic arm system is trained using DRL, achieving the task of fetching, filling, and delivering a cup of water in a complex environment.

关键词： Actor-Criti

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