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An innovative heterogeneous transfer learning framework to enhance the scalab.lity of deep reinforcement learning controllers in buildings with integrated energy systems

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Building Simulation 2024年第5期17卷 739-770页

作者： Davide Coraci Silvio Brandi Tianzhen Hong Alfonso Capozzoli Politecnico di Torino Department of EnergyTEBE research groupBAEDA Lab.Corso Duca degli Abruzzi 24Torino10129Italy Building Technology and Urban Systems Division Lawrence Berkeley National LaboratoryOne Cyclotron RoadBerkeleyCA 94720USA

Deep Reinforcement Learning(DRL)-based control shows enhanced performance in the management of integrated energy systems when compared with Rule-Based Controllers(RBCs),but it still lacks scalab.lity and generalisation due to the necessity of using tailored models for the training *** Learning(TL)is a potential solution to address this ***,existing TL applications in building control have been mostly tested among buildings with similar features,not addressing the need to scale up advanced control in real-world scenarios with diverse energy *** paper assesses the performance of an online heterogeneous TL strategy,comparing it with RBC and offline and online DRL controllers in a simulation setup using EnergyPlus and *** study tests the transfer in both transductive and inductive settings of a DRL policy designed to manage a chiller coupled with a Thermal Energy Storage(TES).The control policy is pre-trained on a source building and transferred to various target buildings characterised by an integrated energy system including photovoltaic and battery energy storage systems,different building envelope features,occupancy schedule and boundary conditions(e.g.,weather and price signal).The TL approach incorporates model slicing,imitation learning and fine-tuning to handle diverse state spaces and reward functions between source and target *** show that the proposed methodology leads to a reduction of 10% in electricity cost and between 10% and 40% in the mean value of the daily average temperature violation rate compared to RBC and online DRL ***,online TL maximises self-sufficiency and self-consumption by 9% and 11% with respect to ***,online TL achieves worse performance compared to offline DRL in either transductive or inductive ***,offline Deep Reinforcement Learning(DRL)agents should be trained at least for 15 episodes to reach the same level of performance as the online

关键词： transfer learning reinforcement learning building control building energy management

A New Speed Limit Recognition Methodology Based on Ensemble Learning:Hardware Validation

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Computers, Materials & Continua 2024年第7期80卷 119-138页

作者： Mohamed Karray Nesrine Triki Mohamed Ksantini ESME ESME Research LabIvry Sur Seine94200France CEM Lab ENISUniversity of SfaxSfax3038Tunisia

Advanced DriverAssistance Systems(ADAS)technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the *** Sign Recognition System(TSRS)is one of themost important components *** the challengeswith TSRS is being able to recognize road signs with the highest accuracy and the shortest processing ***,this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed ***,the Speed Limit Detection(SLD)module uses the Haar Cascade technique to generate a new SL detector in order to localize SL signs within captured ***,the Speed Limit Classification(SLC)module,featuring machine learning classifiers alongside a newly developed model called DeepSL,harnesses the power of a CNN architecture to extract intricate features from speed limit sign images,ensuring efficient and precise *** addition,a new Speed Limit Classifiers Fusion(SLCF)module has been developed by combining trained ML classifiers and the DeepSL model by using the Dempster-Shafer theory of belief functions and ensemble learning’s voting *** rigorous software and hardware validation processes,the proposedmethodology has achieved highly significant F1 scores of 99.98%and 99.96%for DS theory and the votingmethod,***,a prototype encompassing all components demonstrates outstanding reliability and efficacy,with processing times of 150 ms for the Raspberry Pi board and 81.5 ms for the Nano Jetson board,marking a significant advancement in TSRS technology.

关键词： Driving automation advanced driver assistance systems(ADAS) traffic sign recognition(TSR) artificial intelligence ensemble learning belief functions voting method

Low-Complexity Integrated Super-Resolution Sensing and Communication with Signal Decimation and Ambiguity Removal

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ZTE Communications 2024年

作者： DAI Qianglong ZHOU Zhiwen XIAO Zhiqiang ZENG Yong YANG Fei CHEN Yan National Mobile Communications research lab.ratory Southeast University Purple Mountain lab.ratories Wireless Technology lab. 2012 lab Shanghai Huawei Technologies Co. Ltd

Integrated sensing and communication (ISAC) is one of the main usage scenarios for the sixth-generation (6G) wireless networks. To most efficiently utilize the limited wireless resources， integrated super-resolution sensing and communication (ISSAC) has been recently proposed to significantly improve sensing performance with super-resolution algorithms for ISAC systems， such as the Multiple Signal Classification (MUSIC) algorithm. However， traditional super-resolution sensing algorithms suffer from prohibitive computational complexity for orthogonal-frequency division multiplexing (OFDM) systems due to the large dimensions of the signals in the subcarrier and symbol domains. To address such issues， we propose a novel two-stage approach to significantly reduce the computational complexity for super-resolution range estimation. The key idea of the proposed scheme is to first uniformly decimate signals in the subcarrier domain， so that the computational complexity is significantly reduced without missing any target in the range domain. However， the decimation operation may result in range ambiguity due to pseudo peaks， which is addressed by the second stage where the total collocated subcarrier data are used for verification of the detected peaks. Compared with traditional MUSIC algorithms， the proposed scheme reduces computational complexity by two orders of magnitude， while maintaining the range resolution and unambiguity. Simulation results verify the effectiveness of the proposed scheme.

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Precise control of page cache for containers

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Frontiers of Computer Science 2024年第2期18卷 17-30页

作者： Kun WANG Song WU Shengbang LI Zhuo HUANG Hao FAN Chen YU Hai JIN National Engineering research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing Lab School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Container-based virtualization isbecoming increasingly popular in cloud computing due to its efficiency and *** isolation is a fundamental property of *** works have indicated weak resource isolation could cause significant performance degradation for containerized applications and enhanced resource ***,current studies have almost not discussed the isolation problems of page cache which is a key resource for *** leverage memory cgroup to control page cache ***,existing policy introduces two major problems in a container-based ***,containers can utilize more memory than limited by their cgroup,effectively breaking memory ***,the Os kernel has to evict page cache to make space for newly-arrived memory requests,slowing down containerized *** paper performs an empirical study of these problems and demonstrates the performance impacts on containerized *** we propose pCache(precise control of page cache)to address the problems by dividing page cache into private and shared and controlling both kinds of page cache separately and *** do so,pCache leverages two new technologies:fair account(f-account)and evict on demand(EoD).F-account splits the shared page cache charging based on per-container share to prevent containers from using memory for free,enhancing memory *** EoD reduces unnecessary page cache evictions to avoid the performance *** evaluation results demonstrate that our system can effectively enhance memory isolation for containers and achieve substantial performance improvement over the original page cache management policy.

关键词： page cache memory cgroup container isolation cloud computing

XGCN:a library for large-scale graph neural network recommendations

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Frontiers of Computer Science 2024年第3期18卷 247-249页

作者： Xiran SONG Hong HUANG Jianxun LIAN Hai JIN National Engineering research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Microsoft research Asia Beijing 100080China

1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalab.lity issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.

关键词： scaling gained operations

Answering reachability queries with ordered lab.l constraints over lab.led graphs

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Frontiers of Computer Science 2024年第1期18卷 105-117页

作者： Daoliang HE Pingpeng YUAN Hai JIN National Engineering research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science&TechnologyHuazhong University of Science and TechnologyWuhan 430074China

Reachability query plays a vital role in many graph analysis *** researches proposed many methods to efficiently answer reachability queries between vertex *** many real graphs are lab.led graph,it highly demands lab.l-Constrained Reachability(LCR)query inwhich constraint includes a set of lab.ls besides vertex *** researches proposed several methods for answering some LCR queries which require appearance of some lab.ls specified in constraints in the *** that constraint may be a lab.l set,query constraint may be ordered lab.ls,namely OLCR(Ordered-lab.l-Constrained Reachability)queries which retrieve paths matching a sequence of ***,no solutions are availab.e for ***,we propose DHL,a novel bloom filter based indexing technique for answering OLCR *** can be used to check reachability between vertex *** the answers are not no,then constrained DFS is ***,we employ DHL followed by performing constrained DFS to answer OLCR *** show that DHL has a bounded false positive rate,and it's powerful in saving indexing time and *** experiments on 10 real-life graphs and 12 synthetic graphs demonstrate that DHL achieves about 4.8-22.5 times smaller index space and 4.6-114 times less index construction time than two state-of-art techniques for LCR queries,while achieving comparable query response *** results also show that our algorithm can answer OLCR queries effectively.

关键词： graph ordered-lab.l-constrained reachability partial index bloom filter query processing

Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates

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Digital Communications and Networks 2024年第2期10卷 369-379页

作者： Héber H.Arcolezi Jean-François Couchot Bechara Al Bouna Xiaokui Xiao Inria andÉcole Polytechnique(IPP) PalaiseauFrance Femto-ST Institute Univ.Bourg.Franche-ComtéUBFCCNRSBelfortFrance TICKET lab. Antonine University Hadat-BaabdaBaabdaLebanon School of Computing National University of SingaporeSingaporeSingapore

This paper investigates the problem of collecting multidimensional data throughout time(i.e.,longitudinal studies)for the fundamental task of frequency estimation under Local Differential Privacy(LDP)*** to frequency estimation of a single attribute,the multidimensional aspect demands particular attention to the privacy ***,when collecting user statistics longitudinally,privacy progressively ***,the“multiple”settings in combination(i.e.,many attributes and several collections throughout time)impose several challenges,for which this paper proposes the first solution for frequency estimates under *** tackle these issues,we extend the analysis of three state-of-the-art LDP protocols(Generalized Randomized Response–GRR,Optimized Unary Encoding–OUE,and Symmetric Unary Encoding–SUE)for both longitudinal and multidimensional data *** the known literature uses OUE and SUE for two rounds of sanitization(***),i.e.,L-OUE and L-SUE,respectively,we analytically and experimentally show that starting with OUE and then with SUE provides higher data utility(i.e.,L-OSUE).Also,for attributes with small domain sizes,we propose Longitudinal GRR(L-GRR),which provides higher utility than the other protocols based on unary ***,we also propose a new solution named Adaptive LDP for LOngitudinal and Multidimensional FREquency Estimates(ALLOMFREE),which randomly samples a single attribute to be sent with the whole privacy budget and adaptively selects the optimal protocol,i.e.,either L-GRR or *** shown in the results,ALLOMFREE consistently and considerably outperforms the state-of-the-art L-SUE and L-OUE protocols in the quality of the frequency estimates.

关键词： Local differential privacy Discrete distribution estimation Frequency estimation Multidimensional data Longitudinal studies

Multistage guidance on the diffusion model inspired by human artists’ creative thinking

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 170-178页

作者： Wang QI Huanghuang DENG Taihao LI AI research Institute Zhejiang LabHangzhou 311121China Department of Computer Science and Technology Zhejiang UniversityHangzhou 310027China

Current research on text-conditional image generation shows parallel performance with ordinary painters but still has much room for improvement when compared to that of artist-ability paintings,which usually represent multilevel semantics by gathering features ofmultiple objects into one *** a preliminary experiment,we confirm this and then seek the opinions of three groups of individuals with varying levels of art appreciation ability to determine the distinctions that exist between painters and *** then use these opinions to improve an artificial intelligence(AI)painting system from painter-level image generation toward artistic-level image generation.

关键词： gathering ordinary artist

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collab.rative 5G networks

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Digital Communications and Networks 2024年第2期10卷 328-336页

作者： Bo Yi Jianhui Lv Xingwei Wang Lianbo Ma Min Huang College of Computer Science and Engineering Northeastern UniversityShenyang110169China Pengcheng lab. Shenzhen518055China College of Software Northeastern UniversityShenyang110819China College of Information Science and Engineering Northeastern UniversityShenyang110819China

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low ***,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content *** challenge can be eased by sinking some critical content from cloud to *** this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new *** work focuses on establishing a highly efficient content delivery framework in the IoE *** particular,the IoE environment is re-constructed as an end-edge-cloud collab.rative system,in which the concept of digital twin is applied to promote the *** on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)***,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)***,a collab.rative routing scheme is proposed to determine the way to access the content with the objective of minimizing *** experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

关键词： Digital twin IoE Content delivery Caching Routing