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Distributionally robust optimization based chance-constrained energy management for hybrid energy powered cellular networks

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Digital communications and networks 2023年第3期9卷 797-808页

作者： Pengfei Du Hongjiang Lei Imran Shafique Ansari Jianbo Du Xiaoli Chu The Engineering Research Center of Intelligent Air-ground Integrated Vehicle and Traffic Control Ministry of EducationXihua UniversityChengdu610039China Chongqing Key Lab of Mobile Communications Technology Chongqing University of Posts and TelecommunicationsChongqing400065China James Watt School of Engineering University of GlasgowGlasgowG128QQUK Shaanxi Key Laboratory of Information Communication Network and Security Xi'an University of Posts and TelecommunicationsXi'an710121China Electronic and Electrical Engineering University of SheffieldSheffieldS102TNUK

Energy harvesting has been recognized as a promising technique with which to effectively reduce carbon emis-sions and electricity expenses of base ***,renewable energy is inherently stochastic and inter-mittent,imposing formidable challenges on reliably satisfying users'time-varying wireless traffic *** addition,the probability distribution of the renewable energy or users’wireless traffic demand is not always fully known in *** this paper,we minimize the total energy cost of a hybrid-energy-powered cellular network by jointly optimizing the energy sharing among base stations,the battery charging and discharging rates,and the energy purchased from the grid under the constraint of a limited battery size at each base *** solving the formulated non-convex chance-constrained stochastic optimization problem,a new ambiguity set is built to characterize the uncertainties in the renewable energy and wireless traffic demands according to interval sets of the mean and *** this ambiguity set,the original optimization problem is transformed into a more tractable second-order cone programming problem by exploiting the distributionally robust optimization ***,a low-complexity distributionally robust chance-constrained energy management algo-rithm,which requires only interval sets of the mean and covariance of stochastic parameters,is *** results of extensive simulation are presented to demonstrate that the proposed algorithm outperforms existing methods in terms of the computational complexity,energy cost,and reliability.

关键词： Cellular networks Energy harvesting Energy management Chance-constrained Distributionally robust optimization

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Scalable load balancing for large-scale web server clusters

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Journal of Computational Information systems 2014年第13期10卷 5763-5771页

作者： Huang, Chuibi Wang, Jinlin Wu, Gang Chen, Jun Department of Automation University of Science and Technology of China Key Laboratory of Network Communication System and Control Hefei China Institute of Acoustics Chinese Academy of Sciences National Network New Media Engineering Research Center Beijing China

Load balancing is a fundamental technology to provide scalability for web server clusters. But in the scenarios where the web server clusters have massive amount of user accesses, a single load balancing server is unable to carry the user visits. Therefore load balancing tasks should be undertaken among a set of load balancing servers. Correspondingly the loads among these servers also need to be balanced. In this paper, we proposed a load balancing scheme that could provide scalability, availability and reliability for large-scale web server clusters. The scheme combines existing routing techniques and splits the function of load balancing into three levels that could be implemented by different devices, thereby enabling the web server cluster scales with user accesses. The experiment results have demonstrated the effectiveness of the program. © 2014 by Binary Information Press

关键词： Scalability

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A scene-aware adaptive media playout algorithm for wireless video streaming

A scene-aware adaptive media playout algorithm for wireless ...

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International Conference on Computer and Automation Engineering, ICCAE

作者： Han Hu Jian Yang Liyue Zhu Hongsheng Xi Key Laboratory of network communication system and control University of Science and Technology Hefei Anhui China Department of Automation University of Science and Technology Hefei Anhui China

ISBN: (纸本)9781424455690

This paper addresses the issue of buffer underflow in wireless multimedia service, due to both the unreliable and time-varying nature of the wireless channel. Specifically, we propose a statistical model to estimate the buffer underflow time. Based on the estimation of the underflow time, a scene-aware adaptive playout algorithm with dual-threshold to adjust the frame rate is presented. This approach adjusts the threshold dynamically according to the channel conditions and the status of the buffer, and thus regulates the frame rate timely. Moreover, the algorithm possesses scene-aware characteristics, since it adjusts the playout rate according to the motion intensity of the playout scenes to reduce the underflow probability of the buffer and provides better QoS. Simulation results demonstrate that the proposed scheme efficiently reduces the probability of the buffer underflow and provides better visual quality.

关键词： Streaming media Layout communication system control Programmable control Adaptive control Automatic control control systems Speech processing Multimedia communication TV broadcasting

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Mechatronic Design of a Human Robot Coupling Interface for Teaching by Demonstration

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IFAC-PapersOnLine 2016年第21期49卷 675-680页

作者： Liang P. Yang C. Wang N. Li Z. Li R. State Key Lab of Robotics Systems Harbin Institute of Technology Harbin China Zienkiewicz Centre for Computational Engineering Swansea University Swansea United Kingdom Centre for Robotics and Neural Systems Plymouth University United Kingdom The MOE Key Laboratory of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology Guangzhou 510640 China

In this paper, we have developed a mechatronic human-robot coupling interface for kinaesthetic guidance based human robot teaching interface, by integration of a 6-axis force sensor, a coupling mechanism and wearable electromyography (EMG) arrays. Our design aims to transfer human operator's arm kinematics, force as well as human upper limb stiffness estimated from EMG signals to robot manipulators. Experiments have been carried out to test the teaching by demonstration performance of the coupling system in two scenarios: i) human teaching a robot for lifting up task; ii) human-robot skill transfer for one joint motion. Experimental results indicated that the coupling design nearly caused no disturbance to human upper limb stiffness estimation. Moreover, human arm kinematics and force/torque in task space can be transferred to the robot in a natural way with guaranteed safety. This coupling interface design can be easily extended to other robot platforms and has great potentials in application of human robot skill transfer. © 2016

关键词： electromyography (EMG) human robot coupling teaching by demonstration

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Task-space hybrid motion/force control of bilateral teleoperation with unsymmetrical time-varying delays

Task-space hybrid motion/force control of bilateral teleoper...

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Chinese control Conference (CCC)

作者： Dehong Wang Zhijun Li Chun-Yi Su The Key Lab of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology Guangzhou Guangdong CN

The control of bilateral teleoperators is challenging due to the complexity of their nonlinear dynamics, the time delays in the communications as well as the wide range of practical real applications. In this paper, operational space adaptive control of hybrid motion/force synchronization is proposed for bilateral networked teleoperation system with asymmetric time-varying delays in communication channels. The adaptive control with parameter update mechanism is developed to deal with the different kinematics, dynamics uncertainties and external disturbances for the master robot and the slave robot. The system stability is rigorously proved using Lyapunov stability synthesis. The proposed adaptive control is robust against relative motion disturbances, parametric uncertainties and time delay, which is validated by extensive simulation studies.

关键词： Force Delay effects Synchronization Manipulator dynamics Delays

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Neural network based popularity prediction for IPTV system

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Journal of networks 2012年第12期7卷 2051-2056页

作者： Li, Jun Hong, Shuang Xia, Sha Luo, Shengmei Department of Automation Joint Lab. Of Network Communication System and Control University of Science and Technology of China Hefei Anhui 230027 China ZTE Corporation Yuhuatai Nanjing Jiangsu 210012 China

Internet protocol television (IPTV), being an emerging Internet application, plays an important and indispensable role in our daily life. In order to maximize user experience and on the same time to minimize service cost, we must take into pay attention to how to reduce the storage and transport costs. A lot of previous work has been done before to do this. There is a challenging problem in this: how to predict the popularities of videos as accurate as possible. To solve the problem, this paper presents a Neural network model for the popularity prediction of the programs in the IPTV system. And we use the actual historical logs to validate our method. The historical logs are divided to two parts, one is used to train the neural network by extract input/output vectors, and the other part is used to verify the model. The experimental results from our validation show the Neural network based method can gain better accuracy than the comparative method. © 2012 ACADEMY PUBLISHER.

关键词： IPTV

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Learning interpretable deep state space model for probabilistic time series forecasting

arXiv

引用

arXiv 2021年

作者： Li, Longyuan Yan, Junchi Yang, Xiaokang Jin, Yaohui State Key Lab of Advanced Optical Communication System and Network MoE Key Lab of Artificial Intelligence AI Institute Department of Computer Science and Engineering Shanghai Jiao Tong University China

Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We propose a deep state space model for probabilistic time series forecasting whereby the non-linear emission model and transition model are parameterized by networks and the dependency is modeled by recurrent neural nets. We take the automatic relevance determination (ARD) view and devise a network to exploit the exogenous variables in addition to time series. In particular, our ARD network can incorporate the uncertainty of the exogenous variables and eventually helps identify useful exogenous variables and suppress those irrelevant for forecasting. The distribution of multi-step ahead forecasts are approximated by Monte Carlo simulation. We show in experiments that our model produces accurate and sharp probabilistic forecasts. The estimated uncertainty of our forecasting also realistically increases over time, in a spontaneous manner. © 2021, CC BY.

关键词： State space methods

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End-to-end conversational search for online shopping with utterance transfer

arXiv

引用

arXiv 2021年

作者： Xiao, Liqiang Ma, Jun Dong, Xin Luna Martinez-Gomez, Pascual Zalmout, Nasser Zhang, Chenwei Zhao, Tong He, Hao Jin, Yaohui MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University *** Inc State Key Lab of Advanced Optical Communication System and Network Shanghai Jiao Tong University

Successful conversational search systems can present natural, adaptive and interactive shopping experience for online shopping customers. However, building such systems from scratch faces real word challenges from both imperfect product schema/knowledge and lack of training dialog data. In this work we first propose ConvSearch, an end-to-end conversational search system that deeply combines the dialog system with search. It leverages the text profile to retrieve products, which is more robust against imperfect product schema/knowledge compared with using product attributes alone. We then address the lack of data challenges by proposing an utterance transfer approach that generates dialogue utterances by using existing dialog from other domains, and leveraging the search behavior data from e-commerce retailer. With utterance transfer, we introduce a new conversational search dataset for online shopping. Experiments show that our utterance transfer method can significantly improve the availability of training dialogue data without crowd-sourcing, and the conversational search system significantly outperformed the best tested baseline. © 2021, CC BY-NC-SA.

关键词： Electronic commerce

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Robust moving object segmentation in the compressed domain for H.264/AVC video stream

Robust moving object segmentation in the compressed domain f...

引用

25th PCS: Picture Coding Symposium 2006, PCS2006

作者： Yang, Gaobo Yu, Shengfa Zhang, Zhaoyang Network and Information Security Lab School of Computer and Communication Hunan University Changsha Hunan 410082 China School of Electronic Science and Engineering National University of Defense Technology Changsha Hunan 410073 China Key Laboratory of Advanced Displays and System Application Shanghai University Ministry of Education Shanghai 200072 China

ISBN: (纸本)300018726X

Moving object segmentation in the compressed domain plays an important role in many real-time applications, e.g. video indexing, video surveillance, etc. H.264/AVC is the up-to-date video coding standard, which employs several new coding tools and provides a different video format. In this paper, a robust spatio-temporal segmentation approach to extract moving objects in the compressed domain for H.264 video stream is proposed. Coarse moving objects are firstly extracted from the motion vector field through the MRF classification process. Spatial segmentation is based on the HT coefficient, which is used to refine the object boundary of temporal segmentation results. Fusion of spatio-temporal segmentation is based on region projection based labeling technique. Further edge refinement is performed to smooth the object boundaries. The performance of the proposed approach is illustrated by simulation carried on several test sequences. Experimental results show that the proposed approach can provide the visually similar results as by using spatial domain process with much less computational complexity.

关键词： Image segmentation

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Logical Negation Augmenting and Debiasing for Prompt-based Methods

arXiv

引用

arXiv 2024年

作者： Li, Yitian Tian, Jidong He, Hao Jin, Yaohui MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China State Key Lab of Advanced Optical Communication System and Network Shanghai Jiao Tong University China

Prompt-based methods have gained increasing attention on NLP and shown validity on many downstream tasks. Many works have focused on mining these methods' potential for knowledge extraction, but few explore their ability to make logical reasoning. In this work, we focus on the effectiveness of the prompt-based methods on first-order logical reasoning and find that the bottleneck lies in logical negation. Based on our analysis, logical negation tends to result in spurious correlations to negative answers, while propositions without logical negation correlate to positive answers. To solve the problem, we propose a simple but effective method, Negation Augmenting and Negation Debiasing (NAND), which introduces negative propositions to prompt-based methods without updating parameters. Specifically, these negative propositions can counteract spurious correlations by providing "not" for all instances so that models cannot make decisions only by whether expressions contain a logical negation. Experiments on three datasets show that NAND not only solves the problem of calibrating logical negation but also significantly enhances prompt-based methods of logical reasoning without model retraining. Copyright © 2024, The Authors. All rights reserved.

关键词： Formal logic

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