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Channel assignment and power allocation for throughput improvement with PPO in B5G heterogeneous edge networks

Digital Communications and Networks 2024年第1期10卷 109-116页

作者： Xiaoming He Yingchi Mao Yinqiu Liu ping ping Yan Hong Han Hue The Collge of Computer and Information Hohai UniversityNanjingChina The Key Laboratory of Water Big Data Technology of Ministy of Water Resources Hohai UniversityNanjng China The School of Computer Science and Engineering Nanyang Technological UniversitySingapore The College of Textile and Clothing Engineering Soochow UniversitySuzhouChina The College of Internet of Things Nanjing University of Posts and TelecommunicationsNanjingChina

In Beyond the Fifth Generation(B5G)heterogeneous edge networks,numerous users are multiplexed on a channel or served on the same frequency resource block,in which case the transmitter applies coding and the receiver uses interference cancellation.Unfortunately,uncoordinated radio resource allocation can reduce system throughput and lead to user inequity,for this reason,in this paper,channel allocation and power allocation problems are formulated to maximize the system sum rate and minimum user achievable rate.Since the construction model is non-convex and the response variables are high-dimensional,a distributed Deep Reinforcement Learning(DRL)framework called distributed Proximal Policy Optimization(PPO)is proposed to allocate or assign resources.Specifically,several simulated agents are trained in a heterogeneous environment to find robust behaviors that perform well in channel assignment and power allocation.Moreover,agents in the collection stage slow down,which hinders the learning of other agents.Therefore,a preemption strategy is further proposed in this paper to optimize the distributed PPO,form DP-PPO and successfully mitigate the straggler problem.The experimental results show that our mechanism named DP-PPO improves the performance over other DRL methods.

关键词： B5G Heterogeneous edge networks PPO Channel assignment Power allocation Throughput

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Heat transfer enhanced inorganic phase change material compositing carbon nanotubes for battery thermal management and thermal runaway propagation mitigation

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Journal of Energy Chemistry 2024年第2期89卷 226-238,I0006页

作者： Xinyi Dai ping ping Depeng Kong Xinzeng Gao Yue Zhang Gongquan Wang Rongqi Peng Center for Offshore Engineering and Safety Technology China University of Petroleum(East China)Qingdao 266580ShandongChina College of Chemistry and Chemical Engineering China University of Petroleum(East China)Qingdao 266580ShandongChina

Developing technologies that can be applied simultaneously in battery thermal management(BTM)and thermal runaway(TR)mitigation is significant to improving the safety of lithium-ion battery systems.Inorganic phase change material(PCM)with nonflammability has the potential to achieve this dual function.This study proposed an encapsulated inorganic phase change material(EPCM)with a heat transfer enhancement for battery systems,where Na_(2)HPO_(4)·12H_(2)O was used as the core PCM encapsulated by silica and the additive of carbon nanotube(CNT)was applied to enhance the thermal conductivity.The microstructure and thermal properties of the EPCM/CNT were analyzed by a series of characterization tests.Two different incorporating methods of CNT were compared and the proper CNT adding amount was also studied.After preparation,the battery thermal management performance and TR propagation mitigation effects of EPCM/CNT were further investigated on the battery modules.The experimental results of thermal management tests showed that EPCM/CNT not only slowed down the temperature rising of the module but also improved the temperature uniformity during normal operation.The peak battery temperature decreased from 76℃to 61.2℃at 2 C discharge rate and the temperature difference was controlled below 3℃.Moreover,the results of TR propagation tests demonstrated that nonflammable EPCM/CNT with good heat absorption could work as a TR barrier,which exhibited effective mitigation on TR and TR propagation.The trigger time of three cells was successfully delayed by 129,474 and 551 s,respectively and the propagation intervals were greatly extended as well.

关键词： Inorganic phase change material Carbon nanotube Battery thermal management Thermal runaway propagation Fire resistance Encapsulation

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Improving Federated Learning through Abnormal Client Detection and Incentive

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Computer Modeling in Engineering & Sciences 2024年第4期139卷 383-403页

作者： Hongle Guo Yingchi Mao Xiaoming He Benteng Zhang Tianfu Pang ping ping College of Computer and Information Hohai UniversityNanjing211100China Key Laboratory ofWater Big Data Technology of Ministry ofWater Resources Hohai UniversityNanjing211100China

Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness.

关键词： Federated learning abnormal clients incentive credit score abnormal score detection

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Mutant rs189037 in ataxia-telangiectasia mutated gene had a negative association with metabolic syndrome but not cognitive decline in centenarians

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Genes & Diseases 2024年第3期11卷 106-108页

作者： Long Feng Hongqi Huo Qun Li Tao Yang Yali Zhao Pei Zhang ping ping Shihui Fu Department of Anesthesiology Hainan Hospital of Chinese People's Liberation Army General HospitalSanyaHainan 572013China Nuclear Medicine Department Handan Central HospitalHandanHebei056001China Department of Neurosurgery Hainan Hospital of Chinese People's Liberation Army General HospitalSanyaHainan 572013China Department of Oncology Hainan Hospital of Chinese People's Liberation Army General HospitalSanyaHainan 572013China Central Laboratory Hainan Hospital of Chinese People's Liberation Army General HospitalSanyaHainan 572013China School of Life Science Beijing Institute of TechnologyBeijing 100081China General Station for Drug and Instrument Supervision and Control Joint Logistic Support Force of Chinese People's LiberationArmyBeijing 100071China Department of Cardiology Hainan Hospital of Chinese People's Liberation Army General HospitalSanyaHainan 572013China Department of Geriatric Cardiology Chinese People's Liberation Army General HospitalBeijing 100853China

Approximately 20%-25%of adults encounter metabolic syndrome(MetS)worldwide,and MetS is a riskfactorfor cognitive decline(CD)development.Patients with MetS have an 11.48-fold increased incidence of CD compared with those without Mets.^(1) Ataxia-telangiectasia mutated(ATM)gene encodes ATM kinase,which belongs to the phosphatidylinositol 3-hydroxy kinase family.

关键词： ATM development cognitive

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Control Strategies for Digital Twin Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 170-180页

作者： Guo-ping Liu IEEE the Center for Control Science and Technology Southern University of Science and TechnologyShenzhen 518055China

With the continuous breakthrough in information technology and its integration into practical applications, industrial digital twins are expected to accelerate their development in the near future. This paper studies various control strategies for digital twin systems from the viewpoint of practical applications.To make full use of advantages of digital twins for control systems, an architecture of digital twin control systems, adaptive model tracking scheme, performance prediction scheme, performance retention scheme, and fault tolerant control scheme are proposed. Those schemes are detailed to deal with different issues on model tracking, performance prediction, performance retention, and fault tolerant control of digital twin systems. Also, the stability of digital twin control systems is analysed. The proposed schemes for digital twin control systems are illustrated by examples.

关键词： Digital twin control systems fault tolerant control model tracking performance prediction performance retention

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Strong Subgame Consistency of the Core in Stochastic Network Formation Games

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Journal of the Operations Research Society of China 2024年第1期12卷 189-213页

作者： ping Sun Elena Parilina Faculty of Applied Mathematics and Control Processes Saint Petersburg State UniversitySaint Petersburg199034Russia

We consider a model of network formation as a stochastic game with random duration proposed initially in Sun and Parilina(Autom Remote Control 82(6):1065–1082,2021).In the model,the leader first suggests a joint project to other players,i.e.,the network connecting them.Second,the players are allowed to form fresh links with each other updating the initially proposed network.The stage payoff of any player is defined depending on the network structure.There are two types of randomness in the network formation process:(i)links may fail to be formed with different probabilities although players intend to establish them,(ii)the game process may terminate at any stage or transit to the next stage with a certain probability distribution.Finally,a network is formed as a result of players’decisions and realization of random variables.The cooperative version of the stochastic game is investigated.In particular,we examine the properties of subgame consistency as well as strong subgame consistency of the core.We provide a payment mechanism or regularization of the core elements to sustain its subgame consistency and avoid the player’s deviations from the cooperative trajectory.In addition,the distribution procedure of the core elements is regularized in case there are negative payments to achieve only nonnegative payments to the players at any stage.The sufficient condition of a strongly subgame consistent core is also obtained.We illustrate our theoretical results with a numerical example.

关键词： Stochastic game Network formation Core Strong subgame consistency

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Superiority of a Convolutional Neural Network Model over Dynamical Models in Predicting Central Pacific ENSO

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Advances in Atmospheric Sciences 2024年第1期41卷 141-154页

作者： Tingyu WANG ping HUANG Center for Monsoon System Research Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China

The application of deep learning is fast developing in climate prediction,in which El Ni?o–Southern Oscillation(ENSO),as the most dominant disaster-causing climate event,is a key target.Previous studies have shown that deep learning methods possess a certain level of superiority in predicting ENSO indices.The present study develops a deep learning model for predicting the spatial pattern of sea surface temperature anomalies(SSTAs)in the equatorial Pacific by training a convolutional neural network(CNN)model with historical simulations from CMIP6 models.Compared with dynamical models,the CNN model has higher skill in predicting the SSTAs in the equatorial western-central Pacific,but not in the eastern Pacific.The CNN model can successfully capture the small-scale precursors in the initial SSTAs for the development of central Pacific ENSO to distinguish the spatial mode up to a lead time of seven months.A fusion model combining the predictions of the CNN model and the dynamical models achieves higher skill than each of them for both central and eastern Pacific ENSO.

关键词： ENSO diversity deep learning ENSO prediction dynamical forecast system

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Manipulating submolecular-scale phototautomerization

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Science China Materials 2024年第6期67卷 2048-2050页

作者： ping Zhou Hongliang Chen Stoddart Institute of Molecular Science Department of ChemistryZhejiang UniversityHangzhou 310058China Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials ZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou 311215China

A recent study on the submolecular-scale control of phototautomerization methods and the underlying reaction mechanisms was reported in Nature Nanotechnology by Guillaume and co-workers[1],elucidating how the field confinement effect generated by the scanning tunneling microscope(STM)tip precisely triggers the phototautomerization of a free-base phthalocyanine at the submolecular level and demonstrating that the reaction process can be finely controlled by adjusting either the laser excitation wavelength or the position of the tip.

关键词： tunneling excitation phthalocyanine

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Understanding Human and Machine Interaction from Decision Perspective: An Empirical Study Based on the Game of Go

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Journal of Systems Science & Complexity 2024年第2期37卷 647-667页

作者： ZHAO ping LI Xuerong WANG Shouyang Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100190China

The authors aim to interpret human and AI interactions from the decision perspective.The authors decompose the interaction analysis into the following main components in the context of interactions:Individual behavior patterns,interaction relationships,and comprehensive analysis.The authors interpret intertemporal decisions from a physical perspective and employ cross-discipline concepts and methodologies to extract the behavior characteristics of players in the empirical case study.About the individual behavior patterns,the authors find that human players prefer short-term periods to AI in decision-making.The interaction relationship analysis reveals a dynamic relationship between possible short-term co-movement and nearly counter-movement in the long run.The authors apply principal component analysis to descriptive indicators and discover a regular decision hierarchy.The main behavior pattern of players in the game of Go is switching between careful and daring behaviors.The differences in the decision hierarchies imply a discrepancy of patience between humans and AI.

关键词： Coherence analysis decision hierarchy machine behaviour multitaper spectral analysis

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Sex-biased adaptation shapes uniparental gene pools in Tibetans

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Science China(Life Sciences) 2024年第3期67卷 611-613页

作者： Min-Sheng Peng Ya-ping Zhang State Key Laboratory of Genetic Resources and Evolution Kunming Institute of ZoologyChinese Academy of SciencesKunming 650201China KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases Kunming Institute of ZoologyChinese Academy of SciencesKunming 650201China Kunming College of Life Science University of Chinese Academy of SciencesKunming 650204China State Key Laboratory for Conservation and Utilization of Bio-Resources in Yunnan School of Life SciencesYunnan UniversityKunming 650091China

During the past two decades, a series of archaeological and genetic investigations substantially improve our perception of the hominin settlement of the Tibetan Plateau(Zhang et al., 2022). In addition to the identifi... 详细信息

关键词： Tibetan Plateau altitude

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