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检索条件"任意字段=Proceedings of the 12th ACM International Conference on Distributed and Event-based Systems"

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international Winter conference on Brain-Computer Interface, BCI

International Winter Conference on Brain-Computer Interface,...

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12th international Winter conference on Brain-Computer Interface, BCI 2024

ISBN: (纸本)9798350309430

the proceedings contain 55 papers. the topics discussed include: sample dominance aware framework via non-parametric estimation for spontaneous brain-computer interface;a signal acquisition approach for implantable brain-machine interface system;improving generalization of drowsiness state classification by domain-specific normalization;enhancing neural decoding with large language models: a GPT-based approach;revolutionizing intrusive neural interfaces: vascular stent-based neural electrodes;decoding EEG-based workload levels using spatio-temporal features under flight environment;influence of video dynamics on EEG-based single-trial video target surveillance system;temporal convolutional network-based multi-view sleep staging;and a distributed inference system for detecting task-wise single trial event-related potential in stream of satellite images.

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12th international conference on Networked systems, NETYS 2024

12th International Conference on Networked Systems, NETYS 20...

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12th international conference on Networked systems, NETYS 2024

ISBN: (纸本)9783031673207

the proceedings contain 17 papers. the special focus in this conference is on Networked systems. the topics include: Challenger: Blockchain-based Massively Multiplayer Online Game Architecture;Agent-Driven BFS Tree in Anonymous Graphs with Applications;some New Results With k-Set Agreement;a Domain Specific Language for Testing distributed Protocol Implementations;Tool Augmented LLMs for Big Data Analysis;static Data Race Detection via Lazy Sequentialization;Algebraic Computations in Anonymous VANET;federated Learning for Enhanced Medical Image Analysis;towards Stronger Blockchains: Security Against Front-Running Attacks;distributed Station Assignment through Learning;Short Paper: An Efficient Framework for Supporting Nested Transaction in STMs;enhancing Cost and Latency Efficiency through Service Placement in Containerized Fog-Cloud Computing Environments;towards Generating a Dataset for Failure Prediction in Microservices Applications;Dynamic Resource Allocation for 5G Device-to-Device Communication based on Expected SARSA;BeRGeR: Byzantine-Robust Geometric Routing.

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A Collection of Standards-based Recommendations for Sustainable, Social, Accessible Robots and systems in Public Spaces - A Systematic Review and Derivation of Unified Equality Requirement Descriptions 24

A Collection of Standards-based Recommendations for Sustaina...

引用

12th international conference on Human Agent Interaction

作者： Kubullek, Ann-Kathrin van Ledden, Sebastian Doganguen, Ayseguel Ruhr West Univ Appl Sci Mulheim Germany

ISBN: (纸本)9798400711787

the development of social robots for public spaces is challenging as they need to be accessible and socially acceptable for diverse user groups. Although current standards and guidelines contain numerous requirements, there is still a lack of comprehensive analysis and a compendium of these accessibility requirements, especially for social robots. therefore, the aim of this paper is to derive a set of requirements and recommendations based on existing standards and guidelines. this is intended to promote the development of socially sustainable, accessible robots in public spaces and ensure that the specific needs of different user groups are taken into account. For this purpose, we conducted a systematic review of 31 international, European, and German standards and guidelines relevant to the design of socially sustainable robotics in public spaces. the review focused on aspects of accessibility, usability, design, safety requirements, and risk management in relation to robots, considering the heterogeneity of use by different target groups. In particular, we emphasized the equality requirements essential for the development of socially sustainable robots. We then categorized these requirements and recommendations according to different user needs using text mining techniques. Our analysis led to the creation of an illustrative catalog of 83 equality requirements and recommendations. these requirements and recommendations are intended to guide the design process, development, implementation, and use of sustainable and equality-oriented social robots in public spaces. this catalog provides comprehensive insights into promoting accessibility and social sustainability in the design of social robotics, addressing the challenges and requirements in developing such systems, and ensuring that these systems meet the needs of a heterogeneous user group.

关键词： European-Standards social robots accessibility accessible systems

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Resource Allocation for Multi-Cell Semantic Communication systems based on DRL 12

Resource Allocation for Multi-Cell Semantic Communication Sy...

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12th international conference on Information systems and Computing Technology

作者： Jia, Xia Wang, Xiaoming Zhang, Yongjia Sheng, Mingyue Cheng, Guang Nanjing Univ Posts & Telecom Sch Commun Engn Tongda Coll Yangzhou 225127 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Sch Commun & Informat Engn Nanjing 210003 Peoples R China

ISBN: (纸本)9798350379860;9798350379877

To improve user service satisfaction level (SSL), this paper investigates a resource allocation method for multi-cell semantic communication systems with multi-service hybrid transmission mode. For the coexistence of textual semantic communication service and ultra-high reliability and low latency (URLLC) service, we utilize a deep reinforcement learning (DRL) method to solve dynamic sub-channel assignment and power allocation optimization problem. then, we design an event triggering control mechanism (ETC) and a centralized training and distributed execution (CTDE) method for the multi-agent DRL-based resource allocation network, to reduce transmission delay of the multi-cell semantic communication system. Simulation results illustrate that the proposed algorithm can achieve better service satisfaction level performance with lower time cost compared with existing methods.

关键词： Semantic communication resource allocation multi-service coexistence deep reinforcement learning ultra-high reliability and low latency

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Agent-based Orchestration on a Swarm of Edge Devices 23

Agent-based Orchestration on a Swarm of Edge Devices

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17th acm international conference on distributed and event-based systems, DEBS 2023

作者： Anuraj, Banani University of Applied Sciences and Arts Western Switzerland HES-SO Sierre Switzerland

ISBN: (纸本)9798400701221

the proliferation of smart devices, sensors, autonomous robots, drones, and other similar instruments have profoundly changed the way of implementing and deploying systems in industrial and home environments, for diverse scenarios such as smart agriculture, healthcare, or manufacturing. Devices in these settings are not limited to simply observe and acquire data for monitoring, but they are also equipped with actuation capabilities, as well as the possibility of autonomously processing the incoming data through various techniques. However, given their intrinsic limitations regarding the capacity to store and process computations, it is often necessary to delegate some of these processing tasks to intermediary edge nodes in the network. these nodes, given their unique position can act as orchestrators guiding the decentralized work of the interconnected autonomous devices. Beyond static and pre-defined organization structures, in this work we propose the usage of agent and multi-agent-based models for designing and implementing swarms of edge nodes, conceived to dynamically orchestrate other devices, while meeting quality of service conditions. Allowing the control of intelligent edge nodes as conveyors and orchestrators on swarms of devices, we aim at providing intelligence to the self-organization of edge nodes, which may interchange streaming data, and represent their own capabilities through semantic models. Swarm-inspired behavioral patterns would guide the collaborative distribution of their computational tasks. Finally, we will implement and demonstrate the proposed technologies in an elderly home environment powered with a host of edge computing, sensing, and actuating devices. © 2023 Owner/Author(s).

关键词： Sensor networks

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Text-based Multi-pair Contrastive Learning Bidirectional Transformer for Sequential Recommendation 12

Text-based Multi-pair Contrastive Learning Bidirectional Tra...

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12th international conference on Advanced Cloud and Big Data, CBD 2024

作者： He, Tao Liu, Xuejun Xing, Zhuoya Wang, Yitian College of Computer and Information Engineering Nanjing Tech University Nanjing China

ISBN: (纸本)9798331511074

Sequential recommendation aims to capture the dynamic changes in user interests by leveraging their historical behavior sequences for making recommendations. Existing methods often rely on explicit item IDs or generic textual features, but they struggle with cold start scenarios and adapting to new datasets. In this paper, we propose a novel approach called Text-based Multi-pair Contrastive Learning Bidirectional Transformer for Sequential Recommendation (TMCBiT). this method takes sequences of users' historical interactions in the form of key-value text pairs as input, enhancing representation capability through multi-layer embeddings. It employs a bidirectional Transformer model with a long-range attention mechanism, integrating random masking training with multi-pair contrastive learning for joint optimization. Experimental results demonstrate that our proposed method effectively alleviates issues related to cold starts and new dataset adaptation, significantly improving recommendation performance. this study provides a viable path for enhancing model performance in recommendation systems using deep learning techniques, offering valuable guidance for developing more intelligent, accurate, and personalized recommendation systems. © 2024 IEEE.

关键词： Contrastive Learning

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ICCPR 2023 - proceedings of the 2023 12th international conference on Computing and Pattern Recognition

ICCPR 2023 - Proceedings of the 2023 12th International Conf...

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12th international conference on Computing and Pattern Recognition, ICCPR 2023

ISBN: (纸本)9798400707988

the proceedings contain 85 papers. the topics discussed include: entity attribute alignment method based on attribute value distribution;solving the lunar lander problem with multiple uncertainties using a deep Q-learning based short-term memory agent;sentiment analysis of Weibo text using a deep combination model;an ontology-enhanced knowledge graph embedding method;Chinese event extraction algorithm of multi-information semantic enhancements;comparative analysis of classification methods for diagnosing myasthenia gravis based on lumbar electromyography;rare association rule mining based on reinforcement learning;research on identification and prediction of financial fraud of listed companies based on machine learning;using process enhancement to predict organizational citizenship behavior via the role of sustainable training practices;self-supervised contrastive few-shot learning for motor imagery brain-computer interfaces;and a wearable brain-computer interface system for fatigue detection in driving.

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Deep Reinforcement Learning-based distributed Collaborative Service Caching in Edge Computing 12

Deep Reinforcement Learning-Based Distributed Collaborative ...

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12th international conference on Advanced Cloud and Big Data, CBD 2024

作者： Yang, Wei Chu, Yi Chen, Chao Jiao, Shengming Xu, Xiaolong Xue, Shengjun School of Software Nanjing University of Information Science and Technology Nanjing China Jiangsu Meteorological Information Center Nanjing China School of Computer Science and Technology Silicon Lake College Suzhou China

ISBN: (纸本)9798331511074

As the Internet of things (IoT) continues to evolve, smart devices increasingly depend on edge computing for services characterized by low latency and high efficiency. the rapid proliferation of smart devices and the diversification of service requests impose greater demands on the quality of edge service provision. Traditional caching strategies based on service request volumes, which neglect the geographic distribution of devices and the randomness of requests, fail to meet the dual requirements of accuracy and response speed, resulting in inefficient resource allocation and caching. To tackle these challenges, this paper introduces ECPG, a novel distributed collaborative service caching strategy leveraging deep reinforcement learning. By modeling the service caching issue as a Markov Decision Process (MDP) and optimizing it through the Deep Deterministic Policy Gradient (DDPG) algorithm, this strategy facilitates independent yet collaborative caching decisions by devices based on real-time data and environmental conditions. this approach significantly improves service response times and overall system efficiency. Experimental results demonstrate ECPG's superior performance in reducing service latency and increasing cache hit rates, underscoring its practicality and efficacy in contemporary edge computing environments. © 2024 IEEE.

关键词： Deep reinforcement learning

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An Adaptive Online Few-shot Network Intrusion Detection System based on Meta-Learning 12

An Adaptive Online Few-shot Network Intrusion Detection Syst...

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12th international conference on Advanced Cloud and Big Data, CBD 2024

作者： Ding, Shiru Wang, Zhen Lu, Yifei School of Electrical and Automation Engineering Nanjing Normal University China School of Computer Science and Engineering Nanjing University of Science and Technology China

ISBN: (纸本)9798331511074

Previous deep learning-based Network Intrusion Detection systems (NIDS) require a sufficient number of labeled samples to train deep neural network models. However, in certain scenarios of the Internet of things (IoT), such as zero-day attacks, abnormal data is scarce and cannot meet the training conditions for neural network models. thus, there is a need for a NIDS capable of few-shot learning. Additionally, previous online network intrusion detection systems did not comprehensively consider the significant impact of data feature drift and catastrophic forgetting on the performance of online models. In order to solve these two problems, we designed an adaptive online few-shot network intrusion detection system based on meta-learning. We evaluated the proposed system using the public datasets CIC-IDS2017, and the results show that our system can effectively handle the challenge of small samples while continuously adapting to new data with minimal catastrophic forgetting. © 2024 IEEE.

关键词： Zero-shot learning

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proceedings of 2023 IEEE 12th Data Driven Control and Learning systems conference, DDCLS 2023

Proceedings of 2023 IEEE 12th Data Driven Control and Learni...

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12th IEEE Data Driven Control and Learning systems conference, DDCLS 2023

ISBN: (纸本)9798350321050

the proceedings contain 347 papers. the topics discussed include: fault estimation for nonlinear systems with time delay based on iterative learning scheme;a variational Bayesian dictionary learning for process monitoring;tuning method for parameters in fractional-order PID controllers based on neural networks with improved Borges derivative;distributed online convex optimization with adaptive event-triggered scheme;water supply network optimization based on improved sparrow search algorithm;time series generator adversarial network with stochastic process for the degradation generation and prediction;trajectory tracking by an adaptive controller for high-speed train based on neural network and sliding mode control;graph context target attention graph neural network for session-based recommendation;novel virtual sample generation using Gibbs sampling integrated with GRNN for handling small data in soft sensing;Hammerstein system identification using robust estimator based on quantized observation;group consensus for second-order linear multi-agent systems with intermittent control;a new deep learning-based food recognition system for mobile terminal;and study on genetic algorithm optimization of ultrasonic echo peak value thickness measurement algorithm.

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