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检索条件"任意字段=2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021"

共 950 条记录，以下是71-80 订阅

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Online Automatic Service Composition for Mobile and Pervasive computing 20

Online Automatic Service Composition for Mobile and Pervasiv...

引用

20th ieee international conference on Trust, Security and Privacy in computing and Communications (ieee TrustCom)

作者： Wang, Zhaoning Cheng, Bo Chen, Junliang China United Network Commun Corp Res Inst Beijing 100048 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

ISBN: (纸本)9781665416580

In the mobile and pervasive computing environment, automatic service composition faces the challenges of the highly dynamic network structure and limited computation resources. Existing approaches create service flows under the assumption that network context changes are slower than the time required to plan the composite service which is no longer set up in the mobile and pervasive computing environment. In this paper, we propose an online automatic service composition approach to dynamically construct service flows and interleave the planning and executing processes. Particularly, it introduces a novel distributed heuristic searching algorithm to determine solutions with limited knowledge bases and execute them in real time. Simulation results show that our proposed online approach reduces the composition time and performs faster composition time and higher composition success rates than state-of-the-art approaches in mobile computing environments.

关键词： Pervasive computing mobile computing online planning service composition heuristc search

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computing the positioning error of an upper-arm robotic prosthesis from the observation of its wearer's posture

Computing the positioning error of an upper-arm robotic pros...

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ieee international conference on robotics and Automation (ICRA)

作者： Poignant, Alexis Legrand, Mathilde Jarrasse, Nathanael Morel, Guillaume Sorbonne Univ CNRS INSERM Inst Intelligent Syst & Robot ISIR Paris France

ISBN: (纸本)9781728190778

When the arm prosthesis worn by an amputated Human being is not adequately configured with respect to the end-effector task, body compensations are often observed. Namely, to compensate for a wrong joint positioning on the robotic distal side, a subject trying to reach a desired position/orientation of his/her hand mobilizes his/her proximal joints, thus exploiting the redundancy of the human+robot kinematic chain. In this paper, we explore the possibility of exploiting this well-known behavior to reverse the causality: if we observe the posture of an amputated subject wearing a prosthesis during a hand positioning task, to what extent can we infer the positioning error of the prosthesis? To answer this question, we make the assumption that the adequate, or natural posture for a given task is one that optimizes a postural score. The proposed approach then consists in i) measuring the joint posture of the subject fitted with the prosthesis;ii) search for an alternative posture that optimizes a postural score within the null space of the human+robot kinematic chain and iii) compute the position error for the robot joints between the initial and the optimized posture. An experimental evaluation is provided with non amputated subjects who emulate erratic positioning of their distal joints during hand positioning tasks. Results show that joint errors are estimated with a precision that seems compatible with the implementation of a real time control algorithm.

关键词： Wrist Ergonomics Wearable computers Redundancy Null space Training data Kinematics

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EdgePS: Selective Parameter Aggregation for Distributed Machine Learning in Edge computing 14

EdgePS: Selective Parameter Aggregation for Distributed Mach...

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ieee 14th international conference on Cloud computing (CLOUD)

作者： Zhao, Yangming Hou, Yunfei Qiao, Chumming Univ Sci & Technol China Sch Comp Sci & Technol Hefei Peoples R China Univ Buffalo Dept Comp Sci & Engn Buffalo NY 14260 USA Calif State Univ San Bernardino San Bernardino CA 92407 USA

ISBN: (纸本)9781665400602

In this paper, we propose EdgePS, an advanced parameter server approach for distributed machine learning in edge computing scenarios. Different from the Conventional Parameter Server (CPS) approach, which performs parameter aggregation after every local training epoch, EdgePS synchronizes the parameters of all workers only when the local training cannot improve the global model performance. We first analyze how the local training will impact the performance of the global model, and then design algorithms to determine when the best time is to perform the parameter aggregation. Both real testbed experiments and extensive large scale simulations demonstrate that EdgePS can train a practical machine learning model, e.g., VGG-16, with up to 59.28% less time compared with the CPS approach. With the same training time, EdgePS can improve model accuracy by up to 30.19% compared with the state-of-the-art distributed machine learning algorithm designed for edge computing scenarios.

关键词： Training Cloud computing Machine learning algorithms Costs Computational modeling Machine learning Servers

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5G and Edge computing Enabling Experience Delivery Network (XDN) for Immersive Media 22

5G and Edge Computing Enabling Experience Delivery Network (...

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ieee 22nd international conference on High Performance Switching and Routing (ieee HPSR)

作者： Shen, Gang Dai, Jianhui Moustafa, Hassnaa Zhai, Lei Intel Corp Hillsboro OR 97124 USA Intel Corp Shanghai Peoples R China Intel Corp Santa Clara CA USA

ISBN: (纸本)9781665440059

With 5G and Edge computing, media services observe a very big revolution nowadays. LTE led to media services evolution through enabling video streaming anytime, anywhere, and to any connected mobile device. CDN offered HTTP-based solutions for media streaming services, however real-time communication (RTC) and interactive traffic are not fully supported. 5G and Edge computing are now enabling new experience through an Experience Delivery Network (XDN), where content creation is in real-time, on the fly and equally uses upstream and downstream links. real-time Communication (RTC) with 5G and Edge computing allows negligible latency between the communicating parties and is promising not only for immersive media, but also for Cloud Gaming and Telehealth applications. In this paper, we present a 360 Immersive Media solution using Intel-incubated Open WebRTC Toolkit (OWT) and edge computing platforms, while allowing media ingestion over 5G networks from multiple cameras, media control and 360 media distribution over 5G networks. Microservices architecture is used for media ingestion, control, and distribution functions, allowing the solution deployment across multiple edge computing clusters and sites. We implemented a prototype for our solution, and we present a performance evaluation showing the gain in terms of bandwidth and latency besides the modular deployment.

关键词： 5G Edge computing Immersive Media real-time Communication WebRTC Experience Delivery Network

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The Estimation Method of Regression Model and Its Comparisons

The Estimation Method of Regression Model and Its Comparison...

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2021 ieee international conference on robotics, Automation and Artificial Intelligence, RAAI 2021

作者： Cao, Keyi Communication University of China School of Computing Beijing100024 China

ISBN: (纸本)9781665425322

Machine learning is one of the current development trends of computer technology, and regression algorithm is an important algorithm in machine learning. For the accuracy of the algorithm, it is essential to select good evaluation indicators. This paper proposes a curve for evaluating the regression equation, which has similar characteristics to the Receiver-Operating Curve. This article describes the calculation and drawing method of the curve. Compared with other regression equation evaluation indicators, this curve can more intuitively reflect the sensitivity and specificity of the model. The area under the curve can be used to compare the performance between different models, and it has stronger robustness. However, it can be further optimized in terms of accuracy and time cost, and it may be combined with other evaluation indicators in the future to improve its accuracy. ©2021 ieee

关键词： Machine learning

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real-time 3D HAND-OBJECT POSE ESTIMATION FOR MOBILE DEVICES

REAL-TIME 3D HAND-OBJECT POSE ESTIMATION FOR MOBILE DEVICES

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ieee international conference on Image Processing (ICIP)

作者： Yin, Yue McCarthy, Chris Rezazadegan, Dana Swinburne Univ Technol Dept Comp Sci & Software Engn Melbourne Vic Australia

ISBN: (纸本)9781665441155

Interest in 3D hand pose estimation is rapidly growing, offering the potential for real-time hand gesture recognition in a range of interactive VR/AR applications, and beyond. Most current 3D hand pose estimation models rely on dedicated depth-sensing cameras and/or specialised hardware support to handle both the high computation and memory requirements. However, such requirements hinder the practical application of such models on mobile devices or in other embedded computing contexts. To address this, we propose a lightweight model for hand and object pose estimation specifically targeting mobile applications. Using RGB images only, we show how our approach achieves real-time performance, comparable accuracy, and an 81% model size reduction compared with state-of-the-art methods, thereby supporting the feasibility of the model for deployment on mobile platforms.

关键词： 3D hand pose estimation mobile computing gesture recognition virtual reality augmented reality

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Edge computing based Multi-channel Active Noise Control System with Virtual-sensing Function for ICU Patient Bed

Edge Computing based Multi-channel Active Noise Control Syst...

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ieee international conference on Systems, Man, and Cybernetics (SMC)

作者： Liu, Lichuan Bi, Congzhi Maeda, Reo Northern Illinois Univ De Kalb IL 60115 USA Kansai Univ Suita Osaka Japan

ISBN: (纸本)9781665442077

The purpose of this research is to reduce high noise level for patients in intensive care unit (ICU) environments. The study has designed and developed the auxiliary filter based virtual sensing (AF-VS) active noise control (ANC) system. Filtered x least mean square (FxLMS) algorithm is used to reduce the interfering noise around ICU patients' heads. A multi-channel feedforward AF-VS ANC algorithm has been implemented in real-time using a digital signal processing system based on edge computing (TMS320C6713). This noise control system has been tested in a real patient bed with recorded ICU noise. The experiment setup has been presented. The real-time experiment results show that AF-VS ANC is a promising solution to solve high noise level problem inside ICU for patients.

关键词： Intensive care units

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CooLSM: Distributed and Cooperative Indexing Across Edge and Cloud Machines 37

CooLSM: Distributed and Cooperative Indexing Across Edge and...

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37th ieee international conference on Data Engineering (ieee ICDE)

作者： Mittal, Natasha Nawab, Faisal UC Santa Cruz Santa Cruz CA 95064 USA

ISBN: (纸本)9781728191843

We tackle one of the fundamental data management challenges in edge-cloud computing, the problem of data indexing. We propose Cooperative LSM (CooLSM), a distributed Log-Structured Merge Tree that is designed to overcome the unique challenges of edge-cloud indexing such as machine and workload heterogeneity and the communication latency asymmetry between the edge and the cloud. To tackle these challenges, CooLSM deconstructs the LSM tree [23] into its basic parts. This deconstruction allows a better distribution and placement of resources across edge and cloud devices. For example, append-specific functionality is managed at the edge to ensure appending and serving data in real-time, whereas resource-intensive operations such as compaction and querying is managed at the cloud where more compute resources are available.

关键词： data indexing edge computing cloud computing

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English real-time Speech Recognition Based on Hidden Markov and Edge computing Model 3

English Real-time Speech Recognition Based on Hidden Markov ...

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3rd international conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Wu, Juan Sichuan Top It Vocational Institute Sichuan Chengdu611743 China

ISBN: (纸本)9780738146270

This paper is based on the hidden Markov model and edge computing to recognize English speech in real time. This article first analyzes the preprocessing process of the voice signal, and proposes the use of dual-threshold method to detect the voice signal endpoint. Then, two characteristic parameter extraction methods are analyzed in detail, including linear prediction cepstral coefficient and Mel cepstral coefficient. Finally, this paper focuses on the real-time recognition algorithm of English speech based on HMM and edge computing. Experiments have proved the effectiveness and feasibility of this algorithm. © 2021 ieee.

关键词： Speech recognition

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Edge computing Based Data Center Monitoring 5

Edge Computing Based Data Center Monitoring

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5th ieee international conference on Edge computing (ieee EDGE) / ieee World Congress on Services (ieee SERVICES)

作者： Yan, Long-Chuan Li, Yan Song, Hu Zou, Hao-Dong Wang, Li-Jun State Grid Informat & Telecommun Branch Beijing Peoples R China State Grid Jiangsu Elect Power Co Ltd Informat & Telecommun Branch Nanjing Peoples R China State Grid Elect Power Res Inst Nanjing Peoples R China

ISBN: (纸本)9781665400626

With the increase of data center scale, monitoring the status of its internal running devices has become the basis of automatic operations. Traditional environmental monitoring is often based on fixed sensors with limited server racks to collect temperature and humidity data, which cannot be effectively combined with the server task scheduling and resource allocation system. In order to provide reliable services to users, a reliable and low-power data center environmental data monitoring system is needed to collect and analyze data such as temperature, humidity and smoke. This paper presents a data center monitoring system based on edge computing, which uses edge computing and wireless sensor network technology to monitor the running status of the data center. The edge device collects the environmental data in real time, and then obtains the real-time running state parameters of the server through Intelligent Platform Management Interface. By analyzing the environmental data of the data center, the energy consumption and operating parameters of the server can be monitored and adjusted.

关键词： edge computing data center monitor system wireless sensor network ZigBee

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