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Linear Model-Based Optimal VVC Intercoding Rate Control Scheme 1

Proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023

作者： Wei, Xuekai Zhou, Mingliang Liao, Xingran State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau 999078 China School of Computer Science Chongqing University Chongqing400044 China Department of Computer Science City University of Hong Kong Kowloon 999077 Hong Kong

ISBN: (数字)9789819958443

ISBN: (纸本)9789819958436

In this paper, we propose a rate control (RC) scheme with a linear model in versatile video coding (VVC) intercoding, our method introduces a compromise global Lagrange multiplier to minimize the distortion induced under group-of-pictures (GOP)- and frame-level bit budget constraints. To obtain the optimal solution, the corresponding problem is transformed into a convex optimization problem. Then, the Karush-Kuhn-Tucker (KKT) conditions are used to obtain the optimal quantization parameter (QP). The experimental results show that our RC algorithm achieves better coding efficiency, a better RC effect, and higher subjective quality than the default algorithm in VVC Test Model (VTM) 17.0 and other state-of-the-art algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Convex optimization

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TOPMG: Trust-Based Crowdsourcing through Multilateral Bargaining Game Theory

TOPMG: Trust-Based Crowdsourcing through Multilateral Bargai...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Panagiotis Charatsaris Adedamola Adesokan Aisha B Rahman Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Crowdsourcing plays a critical role in modern information gathering and task execution, yet it faces challenges regarding the task selection and equitable monetary incentives distribution. In this paper, we introduce the TOPMG framework, which addresses these challenges by enabling the workers to select tasks based on their historically experienced monetary incentives and the platforms’ trustworthiness. Specifically, the TOPMG framework utilizes a reinforcement learning approach based on the principles of Optimistic Q-learning with Upper Confidence Bound (OQ-UCB) algorithm, guiding the platform selection process by considering the workers’ monetary incentives, profit, and the platforms’ trustworthiness. Also, the proposed framework introduces a multilateral bargaining game to allocate the platforms’ monetary incentives to the workers by prioritizing their information contribution, fairness, and the platforms’ reputation. Simulation results demonstrate TOPMG’s operational dynamics, scalability, and efficacy, as well as its superiority over existing methodologies.

关键词： Crowdsourcing Q-learning Social networking (online) Simulation Scalability Heuristic algorithms Games Global communication Game theory Faces

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Data-Driven Adaptive Control for Frequency Perturbations in Power systems with PV-SmartParks

Data-Driven Adaptive Control for Frequency Perturbations in ...

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Computational Intelligence for Energy, Transport and Environmental Sustainability (CIETES Companion), IEEE Symposia on

作者： Ali Arzani Ganesh K. Venayagamoorthy Holcombe Department of Electrical and Computer Engineering Real-Time Power and Intelligent Systems Laboratory Clemson University SC USA Department of Electrical Electronic and Computer Engineering University of Pretoria South Africa

ISBN: (数字)9798331519681

ISBN: (纸本)9798331519698

Seamless operation of PV plants during both transient and dynamic conditions is imperative for all stakeholders including energy control centers. Fast and dampened transient response, low steady-state error, and stability are sought for power system operation with PV plants. For PV power perturbation at point of interconnection (POI), this can be further supported by deploying auxiliary fast-acting non-synchronous generation such as SmartParks (SPs). SmartParks are parking lots with a large number of electric vehicles performing bidirectional power transfers, namely, vehicle-to-grid and grid-to-vehicle. In this study, a data-driven adaptive frequency controller (DD-AFC) was developed for SPs to compensate for frequency perturbations at PV-POI. The DD-AFC was incorporated into the controller of SPs to provide a fast response for frequency perturbations caused by PV-site power perturbations. The adaptiveness of the frequency droop comes from data-driven empirical characterization of the PV plant operation at the PV-site location using time-series data analytics. The DD-AFC supports fast-frequency control response by SPs for mitigating fast power perturbation at PV-POIs. The effectiveness of the DD-AFC was illustrated via real-time simulations of a bulk power system with a 210MW p PV plant and 100MW p of SmartParks in RTDS.

关键词： Automatic frequency control Time-frequency analysis Vehicle-to-grid Transient response Data analysis Perturbation methods Power system stability Adaptive control Transient analysis Vehicle dynamics

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Intelligent Soft Robotic Gripper Enabled by Multimodal Sensors and Deep Learning 18

Intelligent Soft Robotic Gripper Enabled by Multimodal Senso...

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18th International Conference on Nano/Micro Engineered and Molecular systems, NEMS 2023

作者： Shi, Qiongfeng Sun, Zhongda Le, Xianhao Xie, Jin Lee, Chengkuo Southeast University Joint International Research Laboratory of Information Display and Visualization School of Electronic Science and Engineering Nanjing China National University of Singapore Department of Electrical and Computer Engineering Singapore Singapore Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou China

ISBN: (纸本)9798350333480

Here we report an intelligent soft robotic gripper enabled by the integration of an ultrasonic remote sensor and triboelectric sensors. Due to the noncontact distance sensing ability, the ultrasonic sensor is used to find the object's visual information including position and height by lateral scanning. The information is then used for adjusting the robotic gripper to an appropriate grasp location, after which grasp operation is performed to obtain the object's tactile information through triboelectric bending and tactile sensors. To efficiently analyze the multimodal information, a deep-learning neural network based on feature-level data fusion is constructed, which is able to achieve a high accuracy of 99.3% in classifying 14 objects, enabling the intelligent soft robotic gripper for various smart applications. © 2023 IEEE.

关键词： Classification (of information)

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Resilience of gas interchangeability in hydrogen-blended integrated electricity and gas systems:A transient approach with dynamic gas composition tracking

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iEnergy 2023年第2期2卷 143-154页

作者： Sheng Wang Hongxun Hui Pierluigi Siano State Key Laboratory of Internet of Things for Smart City University of MacaoTaipaMacao SARChina Department of Electrical and Computer Engineering University of MacaoTaipaMacao SARChina Department of Management&Innovation Systems University of SalernoFisciano 84084Italy Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg 2006South Africa

Green hydrogen can be produced by consuming surplus renewable *** can be injected into the natural gas networks,accelerating the decarbonization of energy ***,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection *** gas interchangeability may be adversely *** investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel ***,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen *** steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the ***,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability ***,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative ***,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.

关键词： Integrated electricity and gas systems gas composition hydrogen resilience renewable energy

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OSAP‐Loss:Efficient optimization of average precision via involving samples after positive ones towards remote sensing image retrieval

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1191-1212页

作者： Xin Yuan Xin Xu Xiao Wang Kai Zhang Liang Liao Zheng Wang Chia‐Wen Lin School of Computer Science and Technology Wuhan University of Science and TechnologyWuhanChina Hubei Province Key Laboratory of Intelligent Information Processing and Real‐time Industrial System Wuhan University of Science and TechnologyWuhanChina Nanyang Technological University SingaporeSingapore School of Computer Science Wuhan UniversityWuhanChina Department of Electrical Engineering Industrial Technology Research InstituteNational Tsing Hua UniversityHsinchuChina

In existing remote sensing image retrieval(RSIR)datasets,the number of images among different classes varies dramatically,which leads to a severe class imbalance *** studies propose to train the model with the ranking‐based metric(e.g.,average precision[AP]),because AP is robust to class ***,current AP‐based methods overlook an important issue:only optimising samples ranking before each positive sample,which is limited by the definition of AP and is prone to local *** achieve global optimisation of AP,a novel method,namely Optimising Samples after positive ones&AP loss(OSAP‐Loss)is proposed in this ***,a novel superior ranking function is designed to make the AP loss differentiable while providing a tighter upper ***,a novel loss called Optimising Samples after Positive ones(OSP)loss is proposed to involve all positive and negative samples ranking after each positive one and to provide a more flexible optimisation strategy for each ***,a graphics processing unit memory‐free mechanism is developed to thoroughly address the non‐decomposability of AP *** experimental results on RSIR as well as conventional image retrieval datasets show the superiority and competitive performance of OSAP‐Loss compared to the state‐of‐the‐art.

关键词： computer vision image retrieval metric learning

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Mixed Deep Reinforcement Learning Considering Discrete-continuous Hybrid Action Space for Smart Home Energy Management

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Journal of Modern Power systems and Clean Energy 2022年第3期10卷 743-754页

作者： Chao Huang Hongcai Zhang Long Wang Xiong Luo Yonghua Song IEEE State Key Laboratory of Internet of Things for Smart City University of MacaoMacao S.A.R.China School of Computer and Communication Engineering University of Science and Technology BeijingBeijing 100083China Shunde Graduate School University of Science and Technology BeijingFoshan 528399China State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of MacaoMacao S.A.R.China

This paper develops deep reinforcement learning(DRL)algorithms for optimizing the operation of home energy system which consists of photovoltaic(PV)panels,battery energy storage system,and household ***-free DRL algorithms can efficiently handle the difficulty of energy system modeling and uncertainty of PV ***,discretecontinuous hybrid action space of the considered home energy system challenges existing DRL algorithms for either discrete actions or continuous ***,a mixed deep reinforcement learning(MDRL)algorithm is proposed,which integrates deep Q-learning(DQL)algorithm and deep deterministic policy gradient(DDPG)*** DQL algorithm deals with discrete actions,while the DDPG algorithm handles continuous *** MDRL algorithm learns optimal strategy by trialand-error interactions with the ***,unsafe actions,which violate system constraints,can give rise to great *** handle such problem,a safe-MDRL algorithm is further *** studies demonstrate that the proposed MDRL algorithm can efficiently handle the challenge from discrete-continuous hybrid action space for home energy *** proposed MDRL algorithm reduces the operation cost while maintaining the human thermal comfort by comparing with benchmark algorithms on the test ***,the safe-MDRL algorithm greatly reduces the loss of thermal comfort in the learning stage by the proposed MDRL algorithm.

关键词： Demand response deep reinforcement learning discrete-continuous action space home energy management safe reinforcement learning

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Estimating stationary mass, frequency by frequency

arXiv

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arXiv 2025年

作者： Nakul, Milind Muthukumar, Vidya Pananjady, Ashwin H. Milton Stewart School of Industrial and Systems Engineering United States School of Electrical and Computer Engineering United States

Suppose we observe a trajectory of length n from an α-mixing stochastic process over a finite but potentially large state space. We consider the problem of estimating the probability mass placed by the stationary distribution of any such process on elements that occur with a certain frequency in the observed sequence. We estimate this vector of probabilities in total variation distance, showing universal consistency in n and recovering known results for i.i.d. sequences as special cases. Our proposed methodology carefully combines the plug-in (or empirical) estimator with a recently-proposed modification of the Good–Turing estimator called WingIt, which was originally developed for Markovian sequences. En route to controlling the error of our estimator, we develop new performance bounds on WingIt and the plug-in estimator for α-mixing stochastic processes. Importantly, the extensively used method of Poissonization can no longer be applied in our non i.i.d. setting, and so we develop complementary tools—including concentration inequalities for a natural self-normalized statistic of mixing sequences—that may prove independently useful in the design and analysis of estimators for related problems. © 2025, CC BY.

关键词： Stochastic systems

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Surface flashover in 50 years:Theoretical models and competing mechanisms

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High Voltage 2023年第5期8卷 853-877页

作者： Zhen Li Ji Liu Yoshimichi Ohki George Chen He Gao Shengtao Li Key Laboratory of Engineering Dielectrics and Its Application Ministry of EducationHarbin University of Science and TechnologyHarbinChina State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong UniversityXi'anChina Research Institute for Materials Science and Technology Waseda UniversityShinjuku‐kuJapan School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Surface flashover is a devastating electronic avalanche along the gas–solid interface when a high electric field is applied,which is a potential issue that threatens the safe operations of advanced power electronic,electrical,and spacecraft ***,the underlying physical mechanisms for surface flashover development are still under investigation owing to the complex charge transport processes through the gas phase,solid phase,and gas–solid *** this study,the history of surface flashover theory in the last 50 years is introduced,and several key questions are reviewed from the perspective of the competing mechanisms of charge transport:the role of each phase in a surface flashover,the origin of surface charging,and effects of traps in solid on surface ***,some suggestions involve charge transport processes in each phase,and their correlations are put forward,and a predictable‘charge transport competitive flashover model’is proposed by clarifying the competing mechanisms of charge transport processes through multiple *** study summarises the history and hot topics of physical mechanisms of surface flashover proposed based on classic and recent progress and offers promising routes for developing a more precise surface flashover theory and improving surface flashover performances.

关键词： flash transport charge

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TRUSTCACHE: Trust-based Content Caching in Information-Centric Networks

TRUSTCACHE: Trust-based Content Caching in Information-Centr...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Sean Tsikteris Aisha B Rahman Md Sadman Siraj Panagiotis Charatsaris Eirini Eleni Tsiropoulou Symeon Papavassiliou Institute of Communication and Computer Systems School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

The Information-Centric Networking (ICN) paradigm has reshaped the modern network architectures and promises efficient content delivery to the end-users. This paper introduces TRUSTCACHE, a novel framework enabling the content caching within ICNs and focusing on the trust-based ICN selection and optimal cache memory allocation to the Content Providers (CPs). The TRUSTCACHE framework incorporates the Optimistic Q-learning with Upper Confidence Bound reinforcement learning algorithm that enables the CPs to autonomously select ICNs based on their cache memory availability and trust levels. Also, TRUSTCACHE enables the CPs to jointly consider the reliability of the ICNs and their cache memory availability by integrating a novel trust model. Furthermore, TRUSTCACHE leverages the multilateral bargaining principles in order to ensure the optimal cache memory allocation among the CPs, in terms of aligning with their profit margin characteristics. Simulation-based experiments validate TRUSTCACHE’s operational efficiency across diverse CP profit margin profiles and highlight its superiority over alternative models lacking trust-based ICN selection or employing proportional fairness strategies for cache memory allocation.

关键词： Q-learning Cache memory Information-centric networking Focusing Resource management Reliability Global communication Game theory

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