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2024 IEEE International Conference on Cluster Computing, CLUSTER 2024

作者： Zhou, Yang Wang, Fang Shi, Zhan Feng, Dan Engineering Research Center of Data Storage Systems and Technology Ministry of Education of China Wuhan National Laboratory for Optoelectronics Key Laboratory of Information Storage System Wuhan China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350358711

Modern SSDs achieve low latency and high throughput by utilizing multiple levels of SSD parallelism. Fairness is also a critical design consideration in cloud environments and has inspired great interest in recent years to study it. However, we find that excessive striving for SSD parallelism can inadvertently harm the SSD fairness due to the striped data layout. We observe from our experimental analysis that some common access patterns in cloud loads (e.g., high-intensity I/O) are not addressed by SSD parallelism, which can affect both SSD parallelism and fairness. In this paper, we analyze two address mapping policies with orthogonal characteristics from SSD parallelism and fairness perspectives. Based on extensive experiments and observations, we schedule a hybrid address mapping policy to achieve fairness of SSDs in cloud environments by distinguishing different I/O access modes and cold/hot data, while ensuring SSD performance. Experimental results on the latest block-level I/O traces show that our approach significantly improves performance and fairness by up to 77.3% and 62.8%, respectively, over the previous schemes with negligible cost. Meanwhile, it can also reduce the write amplification by 23.5% to 33.5%. © 2024 IEEE.

关键词： Cloud platforms

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An Energy-Aware UAVs Path Coverage for Critical Infrastructure Inspections 12

An Energy-Aware UAVs Path Coverage for Critical Infrastructu...

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12th International Conference on Advanced Cloud and Big data, CBD 2024

作者： Wang, Yifan Zeng, Wei Li, Guanyu Xiong, Chenglong Wang, Zicheng Mao, Yingchi College of Computer Science and Software Engineering Hohai University Nanjing China Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources Nanjing China Huaneng Lancang River Hydropower Co. CHINA HUANENG Group Kunming China Power China Kunming Engineering Co. Yunnan China

ISBN: (纸本)9798331511074

Critical infrastructures increasingly rely on unmanned aerial vehicles (UAVs) for inspection tasks. The significance of different components within these infrastructures is subject to variability and can be influenced by external factors. The principal aim of routine UAV inspections is to ensure differentiated coverage of pivotal sections with minimal energy consumption. However, extant research on UAV path coverage fails to fully account for the variability and dynamic shifts in regional significance and their impact on coverage efficacy. This paper presents an energy-aware collaborative coverage policy for UAVs, designated as ***-MATD3 employs a dynamic weight region partitioning method tailored to real-world environments and addresses the action selection challenge for UAVs using a discrete Partially Observable Markov Decision Process (Dec-POMDP). By amalgamating MATD3 with stacked LSTM, this approach mitigates redundant path overlaps and unnecessary action replication across multiple agents, thus optimizing coverage and diminishing energy usage. Simulation outcomes demonstrate that EA-MATD3 reduces energy consumption by an average of 9.65% relative to the Greedy, MADDPG, and MATD3 algorithms while sustaining a superior coverage rate. © 2024 IEEE.

关键词： Markov processes

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Immunometabolism:a new dimension in immunotherapy resistance

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Frontiers of Medicine 2023年第4期17卷 585-616页

作者： Chaoyue Xiao Wei Xiong Yiting Xu Ji’an Zou Yue Zeng Junqi Liu Yurong Peng Chunhong Hu Fang Wu Department of Oncology The Second Xiangya HospitalCentral South UniversityChangsha 410011China NHC Key Laboratory of Carcinogenesis and Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education Cancer Research InstituteCentral South UniversityChangsha 410078China Xiangya School of Medicine Central South UniversityChangsha 410013China Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha 410011China Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer The Second Xiangya HospitalCentral South UniversityChangsha 410011China Hunan Key Laboratory of Tumor Models and Individualized Medicine The Second Xiangya HospitalCentral South UniversityChangsha 410011China

Immune checkpoint inhibitors(ICIs)have demonstrated unparalleled clinical responses and revolutionized the paradigm of tumor treatment,while substantial patients remain unresponsive or develop resistance to ICIs as a single agent,which is traceable to cellular metabolic *** dysregulated metabolism has long been adjudged as a hallmark of tumor,it is now increasingly accepted that metabolic reprogramming is not exclusive to tumor cells but is also characteristic of ***,people used to pay more attention to the effect of tumor cell metabolism on immunocytes,but in practice immunocytes interact intimately with their own metabolic function in a way that has never been realized before during their activation and differentiation,which opens up a whole new frontier called *** metabolic intervention for tumor-infiltrating immunocytes could offer fresh opportunities to break the resistance and ameliorate existing ICI immunotherapy,whose crux might be to ascertain synergistic combinations of metabolic intervention with ICIs to reap synergic benefits and facilitate an adjusted anti-tumor immune ***,we elaborate potential mechanisms underlying immunotherapy resistance from a novel dimension of metabolic reprogramming in diverse tumor-infiltrating immunocytes,and related metabolic intervention in the hope of offering a reference for targeting metabolic vulnerabilities to circumvent immunotherapeutic resistance.

关键词： immune cell immunometabolism metabolic reprogramming immunotherapy resistance tumor microenvironment immune checkpoint inhibitor

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LuoJia-Explorer: Unmanned Collaborative Localization and Mapping System 1

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Wu, Weitong Chen, Chi Yang, Bisheng State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Engineering Research Center of Space-Time Data Capturing and Smart Application The Ministry of Education of P.R.C. Wuhan430079 China

ISBN: (数字)9789819710997

ISBN: (纸本)9789819710980

Over the past two decades, numerous single-robot SLAM systems have been developed and proposed. However, the problem of collaborative localization and mapping with a team of robots remains an open challenge. Collaborative localization and mapping plays a crucial role in enhancing mapping efficiency and has a wide application in search and rescue, infrastructure monitoring, extraterrestrial planetary cave exploration, etc. In this paper, we propose LuoJia-Explorer, an unmanned collaborative localization and mapping system for ground platforms. The proposed system is centralized with a main control center. Each ground platform is equipped with a multi-beam LiDAR and IMU to perform LiDAR-inertial odometry in its own coordinate system. Through mesh networking communication technology, the main control center receives the mapping result and trajectory from each platform. At the control center, global SLAM is performed, which includes loop detection, relative pose estimation and global pose graph optimization, to obtain a globally consistent mapping result. Two ground platforms were built to verify the proposed system. Field experiments have preliminarily verified the effectiveness of this system. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Mapping

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Learning Superconductivity from Ordered and Disordered Material Structures 38

Learning Superconductivity from Ordered and Disordered Mater...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Pin Peng, Luoxuan Jiao, Rui Mo, Qing Wang, Zhen Huang, Wenbing Liu, Yang Lu, Yutong National Supercomputer Center in Guangzhou School of Computer Science and Engineering Sun Yat-sen University China Dept. of Comp. Sci. & Tech. Institute for AI BNRist Center Tsinghua University China Institute for AIR Tsinghua University China Gaoling School of Artificial Intelligence Renmin University of China China Beijing Key Laboratory of Big Data Management and Analysis Methods Beijing China

Superconductivity is a fascinating phenomenon observed in certain materials under certain conditions. However, some critical aspects of it, such as the relationship between superconductivity and materials' chemical/structural features, still need to be understood. Recent successes of data-driven approaches in material science strongly inspire researchers to study this relationship with them, but a corresponding dataset is still lacking. Hence, we present a new dataset for data-driven approaches, namely SuperCon3D, containing both 3D crystal structures and experimental superconducting transition temperature (Tc) for the first time. Based on SuperCon3D, we propose two deep learning methods for designing high Tc superconductors. The first is SODNet, a novel equivariant graph attention model for screening known structures, which differs from existing models in incorporating both ordered and disordered geometric content. The second is a diffusion generative model DiffCSP-SC for creating new structures, which enables high Tc-targeted generation. Extensive experiments demonstrate that both our proposed dataset and models are advantageous for designing new high Tc superconducting candidates. © 2024 Neural information processing systems foundation. All rights reserved.

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BERD+: A Generic Sequential Recommendation Framework by Eliminating Unreliable data with Item- and Attribute-level Signals

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ACM Transactions on Information Systems 2023年第2期42卷 1-33页

作者： Sun, Yatong Yang, Xiaochun Sun, Zhu Wang, Bin School of Computer Science and Engineering Northeastern University School of Computing Macquarie University China Australia Institute of High Performance Computing Centre for Frontier AI Research A*STAR Singapore School of Computer Science and Engineering Northeastern University China National Frontiers Science Center for Industrial Intelligence and Systems Optimization China Key Laboratory of Data Analytics and Optimization for Smart Industry [Northeastern University Ministry of Education China

A preliminary work of our study was published at IJCAI’21 [47], which is substantially extended in the following aspects: (1) In Section 1, we analyze the necessity of introducing item attributes for detecting unreliable instances, together with the problems and challenges that attributes may bring in. (2) In Section 2, we add discussions about the limitations of existing attribute-aware recommender systems (Section 2.2) and denoising methods (Section 2.3) in the context of detecting unreliable instances. (3) In Section 4.2, we further conduct an in-depth analysis at the attribute level to demonstrate the capability of attributes for rectifying instance loss and uncertainty, as well as the disturbance caused by attributes. (4) We generalize BERD to a generic framework BERD+ in Section 5.1, equipped with novel modules, i.e., HU-GCN (Section 5.2) and EPE (Section 5.4), which properly incorporate item attributes while reducing their disturbance for rectifying instance uncer tainty (Section 5.5) and loss (Section 5.6). The generic BERD+ can be flexibly plugged into existing SRSs for performance enhanced recommendation via eliminating unreliable data. (5) In Section 6.2, we apply our BERD+ framework to seven state-of-the-art SRSs on five real-world datasets to illustrate its superiority. (6) To avoid unfair comparison caused by item attributes, we build and compare with the baseline that combines the original BERD and an advanced attribute-aware recommender system, KSR [19]. (7) For more comprehensive comparison, in Section 6.2.2, we compare BRED+ with two state-of-the-art denoising approaches;in Section 6.2.3, to examine the efficacy of HU-GCN and EPE, we compare HU-GCN with various attribute embedding techniques, i.e., variants of graph neural networks, and compare EPE with different attribute fusing methods, i.e., adding, concatenation, and weighted sum. (8) In Section 6.2.4, a detailed ablation study is conducted to verify the effectiveness of each module of BERD+. (

关键词： Convolution

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A Digital Twin-based Framework of Motion Control and State Monitoring for Pneumatic Muscle

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Recent Patents on Mechanical engineering 2023年第3期16卷 203-213页

作者： Xie, Shenglong Liu, Wenyuan Duan, Huiru Chen, Dijian Wan, Yanjian Key Laboratory of Intelligent Manufacturing Quality Big Data Tracking and Analysis of Zhejiang Province China Ji-liang University Zhejiang Hangzhou310018 China Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Anhui University of Technology Anhui Ma'anshan243032 China

Introduction: The current digital twin systems usually have the drawback of high cost and complex technology, and it is necessary to develop a simple solution to reduce the cost and cycle for the development of digital twin systems, especially for small projects or systems with simple structures. Objective: A low-cost patent technology of digital twin system was proposed by taking the motion control and state monitoring system (MCSMS) of pneumatic muscle as an example. Methods: The MCSMS is developed based on the browser/server architecture. The software of 3ds Max and SolidWorks are used to make the virtual model, *** and JavaScript are applied to build the browser side. data of the physical world is collected and processed on the server side firstly, and then is sent to the browser side through HTTP communication protocol to realize data interchange between the browser and server. Results: In the roaming experiment and the experiment of motion control and state monitoring of pneumatic muscle, the MCSMS can work smoothly without obvious delay and has good real-time performance, which can realize the 3D visual monitoring of the pneumatic muscle very well. Conclusion: The experimental results indicate that the proposed method possesses the ability of good feasibility and effectiveness. © 2023 Bentham Science Publishers.

关键词： Muscle

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Research on WNN Greenhouse Temperature Prediction Method Based on GA

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Phyton-International Journal of Experimental Botany 2022年第10期91卷 2283-2296页

作者： Wenbin Dai Lina Wang Binrui Wang Xiaohong Cui Xue Li College of Mechanical and Electronic Engineering China Jiliang UniversityHangzhou310018China Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province China Jiliang UniversityHangzhou310018China

Temperature in agricultural production has a direct impact on the growth of *** emergence of greenhouses has improved the impact of the original unpredictable changes in temperature,but the temperature modeling of greenhouses is still the main direction at *** network modeling relies on sufficient actual data to model greenhouses,but there is a widening gap in the application of different neural *** paper proposes a greenhouse temperature prediction model based on wavelet neural network with genetic algorithm(GA-WNN).With the simple network structure and the nonlinear adaptability of the wavelet basis function,wavelet neural network(WNN)improved model training speed and accuracy of prediction results compared with back propagation neural networks(BPNN),which was conducive to the prediction and control of short-term greenhouse temperature *** the same time,the genetic algorithm(GA)was introduced to globally optimize the initial weights of the original model,which improved the insensitivity of the model to the initial weights and thresholds,and improved the training speed and stability of the ***,simulation results for the greenhouse showed that the model training speed,prediction results accuracy and model stability of the GA-WNN in the greenhouse were improved in comparison to results obtained by the WNN and BPNN in the greenhouse.

关键词： Greenhouse temperature greenhouse modeling wavelet neural network genetic algorithm

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A Fully 3-D-Printing-Compatible E-Plane Elliptical Waveguide Junction for Power Dividing/Combining Applications

A Fully 3-D-Printing-Compatible E-Plane Elliptical Waveguide...

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2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

作者： Chen, Sicheng Li, Jin Yuan, Tao Guangdong Prov. Mobile Terminal Microwave and Millimeter-Wave Antenna Engineering Research Center College of Electronics and Information Engineering Shenzhen University China Guangdong-Hong Kong Joint Laboratory for Big Data Imaging and Communication China State Key Laboratory of Millimeter Waves China College of Electronics and Information Engineering ATR National Key Laboratory of Defense Technology Shenzhen University China

ISBN: (纸本)9798350347647

In this paper, a new class of 3-D-printing-compatible E-plane elliptical waveguide (EWG) junction is proposed for wideband power dividers/combiners. The junction is based on an EWG architecture with tailored power dividing and impedance-matching structures that are configured in a Y-shape profile. The junction is devised according to a specified orientation for 3-D printing and it features smooth and intrinsically self-supportable waveguide sidewalls. Compared to conventional rectangular waveguide junctions, the proposed EWG junction exhibits dramatically enhanced structural compatibility with additive manufacturing technology. A novel four-way EWG-junction-based power divider is demonstrated at Ka band. The power divider is prototyped monolithically by incorporating Polyjet 3-D printing and electroless copper plating processes. RF performance of the power divider shows a return loss of mostly over 20 dB, transmission coefficients of averagely -6.5 dB, and small amplitude and phase imbalances across the entire Ka band, successfully validating the wideband and low-loss characteristics of the proposed EWG junction. © 2023 IEEE.

关键词： Voltage dividers

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Intelligent elevator system based on the Internet of Things: improving elevator safety and management efficiency

Intelligent elevator system based on the Internet of Things:...

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2024 International Conference on Smart Transportation and City engineering, STCE 2024

作者： Huang, Lingbo Chen, Yihong Zhao, Kun The Internet of Things Perception and Big Data Analysis Key Laboratory of Nanchong City China West Normal University Nanchong637002 China School of Electronic Information Engineering China West Normal University Nanchong637002 China

ISBN: (纸本)9781510690585

The number of elevators in china's urbanization process has increased significantly, yet they face safety problems such as aging and insufficient maintenance. This paper introduces an intelligent IoT elevator system, comprising a data acquisition terminal and a cloud platform, utilizing a hierarchical architecture and a variety of key technologies. The system can monitor elevator operations in real time, collect and analyze large amounts of data to predict failures, and provide maintenance plans. It also features real-time alarm, rescue management, and maintenance management functions. These improvements enhance rescue efficiency, reduce maintenance costs, ensure the safe operation of elevators, and improve the efficiency and transparency of safety management. © 2025 SPIE.

关键词： Efficiency

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