检索结果-南通市图书馆

The importance of data assimilation components for initial conditions and subsequent error growth

维普期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

Science China Earth Sciences 2024年第1期67卷 105-116页

作者： zhongrui wang Haohao SUN Lili LEI Zhe-Min TAN Yi ZHANG Key Laboratory of Mesoscale Severe Weather Ministry of Educationand School of Atmospheric SciencesNanjing UniversityNanjing 210023China Frontiers Science Center for Critical Earth Material Cycling Nanjing UniversityNanjing 210023China

Despite a specific data assimilation method,data assimilation(DA)in general can be decomposed into components of the prior information,observation forward operator that is given by the observation type,observation error covariances,and background error *** a classic Lorenz model,the influences of the DA components on the initial conditions(ICs)and subsequent forecasts are systematically investigated,which could provide a theoretical basis for the design of DA for different scales of *** forecast errors undergo three typical stages:a slow growth stage from 0 h to 5 d,a fast growth stage from 5 d to around 15 d with significantly different error growth rates for ensemble and deterministic forecasts,and a saturation stage after 15 *** strategies that provide more accurate ICs can improve the *** assimilation is superior to offline assimilation,and a flow-dependent background error covariance matrix(Pf)provides better analyses than a static background error covariance matrix(B)for instantaneous observations and frequent time-averaged observations;but the opposite is true for infrequent time-averaged observations,since cycling simulation cannot construct informative priors when the model lacks predictive skills and the flow-dependent Pf cannot effectively extract information from low-informative observations as the static *** observations contain more information than time-averaged observations,thus the former is preferred,especially for infrequent observing ***,ensemble forecasts have advantages over deterministic forecasts,and the advantages are enlarged with less informative observations and lower predictive-skill model priors.

关键词： Data assimilation Atmospheric predictability Background error covariances Ensemble forecasts

Programming Supramolecular Hydrogels by Constructing a Multibranch Selection Structure

在线全文

学校读者我要写书评

暂无评论

CCS Chemistry 2024年第8期6卷 1951-1964页

作者： zhongrui wang Ting Zhao Shenghao Yang Yuwen Meng Xu wang National Engineering Research Center for Colloidal Materials School of Chemistry and Chemical EngineeringShandong UniversityJinanShandong 250100 Key Laboratory of Colloid and Interface Chemistry of the Ministry of Education School of Chemistry and Chemical EngineeringShandong UniversityJinanShandong 250100

Developing chemical systems capable of executing multipath nonequilibrium processes provides valuable insights into the study of multistage dissipative structures in living ***,we report a nonequilibrium multipath evolution in a three-state supramolecular system,which is clarified by associating it with a multibranch selection *** system is constructed by synergistically combining an assembly-induced sol-gel transition with the color change of an acid-base *** on the initial condition and chemical fuel composition,this system can execute five distinct nonequilibrium *** addition,the set of structured programming can be replayed by repeatedly introducing the chemical *** is further utilized to explore the applications of information encryption and establish its *** findings offer novel avenues for future transient material design and may make significant contributions to systems chemistry.

关键词： supramolecular hydrogels nonequilibrium processes programmable self-assembly chemical fuels multibranch selection structure

In-materio reservoir computing based on nanowire networks:fundamental,progress,and perspective

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Materials Futures

Materials Futures 2023年第2期2卷 79-93页

作者： Renrui Fang Woyu Zhang Kuan Ren Peiwen Zhang Xiaoxin Xu zhongrui wang Dashan Shang State Key Laboratory of Fabrication Technologies for Integrated Circuits Institute of Microelectronics of Chinese Academy of SciencesBeijing 100029People’s Republic of China Department of Electrical and Electronic Engineering The University of Hong KongHong Kong 999077People’s Republic of China University of Chinese Academy of Sciences Beijing 100049People’s Republic of China

The reservoir computing(RC)system,known for its ability to seamlessly integrate memory and computing functions,is considered as a promising solution to meet the high demands for time and energy-efficient computing in the current big data landscape,compared with traditional silicon-based computing systems that have a noticeable disadvantage of separate storage and *** review focuses on in-materio RC based on nanowire networks(NWs)from the perspective of materials,extending to reservoir devices and *** common methods used in preparing nanowires-based reservoirs,including the synthesis of nanowires and the construction of networks,are firstly systematically *** physical principles of memristive and memcapacitive junctions are then ***,the dynamic characteristics of nanowires-based reservoirs and their computing capability,as well as the neuromorphic applications of NWs-based RC systems in recognition,classification,and forecasting tasks,are explicated in ***,the current challenges and future opportunities facing NWs-based RC are highlighted,aiming to provide guidance for further research.

关键词： reservoir computing nanowire networks short-term memory dynamic characteristics neuromorphic computing

CMN: a co-designed neural architecture search for efficient computing-in-memory-based mixture-of-experts

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(Information Sciences) 2024年第10期67卷 100-114页

作者： Shihao HAN Sishuo LIU Shucheng DU Mingzi LI Zijian YE Xiaoxin XU Yi LI zhongrui wang Dashan SHANG Department of Electrical and Electronic Engineering The University of Hong Kong ACCESS-AI Chip Center for Emerging Smart Systems InnoHK Centers Key Lab of Fabrication Technologies for Integrated Circuits Chinese Academy of Sciences Laboratory of Microelectronics Devices and Integrated Technology Institute of MicroelectronicsChinese Academy of Sciences University of Chinese Academy of Sciences School of Microelectronics Southern University of Science and Technology

Artificial intelligence(AI) has experienced substantial advancements recently, notably with the advent of large-scale language models(LLMs) employing mixture-of-experts(MoE) techniques, exhibiting human-like cognitive skills. As a promising hardware solution for edge MoE implementations, the computing-in-memory(CIM) architecture collocates memory and computing within a single device, significantly reducing the data movement and the associated energy consumption. However, due to diverse edge application scenarios and constraints, determining the optimal network structures for MoE, such as the expert's location,quantity, and dimension on CIM systems remains elusive. To this end, we introduce a software-hardware co-designed neural architecture search(NAS) framework, CIM-based MoE NAS(CMN), focusing on identifying a high-performing MoE structure under specific hardware constraints. The results of the NYUD-v2 dataset segmentation on the RRAM(SRAM) CIM system reveal that CMN can discover optimized MoE configurations under energy, latency, and performance constraints, achieving 29.67×(43.10×) energy savings,175.44×(109.89×) speedup, and 12.24× smaller model size compared to the baseline MoE-enabled Visual Transformer, respectively. This co-design opens up an avenue toward high-performance MoE deployments in edge CIM systems.

关键词： mixture-of-experts computing-in-memory neural architecture search resistive random-access memory static random-access memory

同方期刊数据库

Structural plasticity-based hydrogel optical Willshaw model for one-shot on-the-fly edge learning

在线全文

学校读者我要写书评

暂无评论

InfoMat 2023年第4期5卷 48-59页

作者： Dingchen wang Dingyao Liu Yinan Lin Anran Yuan Woyu Zhang Yaping Zhao Shaocong wang Xi Chen Hegan Chen Yi Zhang Yang Jiang Shuhui Shi Kam Chi Loong Jia Chen Songrui Wei Qing wang Hongyu Yu Renjing Xu Dashan Shang Han Zhang Shiming Zhang zhongrui wang Department of Electrical and Electronic Engineering The University of Hong KongHong Kongthe People's Republic of China ACCESS-AI Chip Center for Emerging Smart Systems InnoHK CentersHong Kong Science ParkHong Kongthe People's Republic of China School of Computer Science and Engineering Faculty of Innovation EngineeringMacao University of Science and TechnologyMacaothe People's Republic of China Key Laboratory of Microelectronics Devices and Integrated Technology Institute of MicroelectronicsChinese Academy of SciencesBeijingthe People's Republic of China Collaborative Innovation Center for Optoelectronic Science Technology International Collaborative Laboratory of 2D Materials for OptoelectronicsScience and Technology of Ministry of EducationInstitute of Microscale OptoelectronicsShenzhen UniversityShenzhenthe People's Republic of China School of Microelectronics Southern University of Science and TechnologyShenzhenthe People's Republic of China Microelectronics Thrust Function Hub of the Hong Kong University of Science and Technology(Guangzhou)Guagndongthe People's Republic of China

Autonomous one-shot on-the-fly learning copes with the high privacy,small dataset,and in-stream data at the *** such learning on digital hardware suffers from the well-known von-Neumann and scaling *** optical neural networks featuring large parallelism,low latency,and high efficiency offer a promising ***,ex-situ training of conventional optical networks,where optical path configuration and deep learning model optimization are separated,incurs hardware,energy and time overheads,and defeats the advantages in edge ***,we introduced a bio-inspired material-algorithm co-design to construct a hydrogel-based optical Willshaw model(HOWM),manifesting Hebbian-rule-based structural plasticity for simultaneous optical path configuration and deep learning model optimization thanks to the underlying opto-chemical *** first employed the HOWM as an all optical in-sensor AI processor for one-shot pattern classification,association and *** then leveraged HOWM to function as a ternary content addressable memory(TCAM)of an optical memory augmented neural network(MANN)for one-shot learning the Omniglot *** HOWM empowered one-shot on-the-fly edge learning leads to 1000boost of energy efficiency and 10boost of speed,which paves the way for the next-generation autonomous,efficient,and affordable smart edge systems.

关键词： associative memory hydrogel one-shot learning optical neural network structural plasticity Willshaw model

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

激情犯罪他评检查表的编制与信效度

北京大学学报（自然科学版） 2023年第6期59卷 1035-1042页

作者：王中瑞黄鑫周颖钟杰西华大学心理健康教育中心成都610039 行为与心理健康北京市重点实验室北京大学心理与认知科学学院北京100871

梳理激情犯罪的操作性定义和评估要素,编制适用于服刑人员的《激情犯罪他评检查表》,并检验其信效度。样本1招募40名狱警,评定15份典型暴力卷宗,探索该检测表的评定准确率、因子结构以及内部一致性。样本2招募14名狱警,评定275份罪犯卷... 详细信息

梳理激情犯罪的操作性定义和评估要素,编制适用于服刑人员的《激情犯罪他评检查表》,并检验其信效度。样本1招募40名狱警,评定15份典型暴力卷宗,探索该检测表的评定准确率、因子结构以及内部一致性。样本2招募14名狱警,评定275份罪犯卷宗,将UPPS冲动性量表等作为校标,测量对应的服刑人员,检验该检测表的关联效度、评定阈值、重测和评定者信度。结果表明,激情犯罪组得分高于对照组;探索性因素分析结果支持单因素模型,该量表的内部一致性信度、评定者信度和重测信度均达到心理测量学要求,同时体现出较好的汇聚和区分效度;该检查表具有较强的检测效力,经过接收者操作特征(ROC)曲线分析,确定其阈值为10.5,可作为筛查激情犯罪服刑人员的有效工具。

关键词：激情犯罪检查表他评信度效度

基于氨储能技术的电转氨耦合风–光–火综合能源系统双层优化调度

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

中国电机工程学报 2023年第18期43卷 6992-7002页

作者：袁文腾陈亮王春波王中瑞华北电力大学能源动力与机械工程学院河北省保定市071003

针对高风光渗透率的风-光-火综合能源系统弃能问题,提出利用电转氨和火电机组掺氨燃烧相结合的技术以提高风光利用率,改善我国以煤为主的能源系统安全性与环保性。首先提出电转氨耦合综合能源系统构型,并为燃煤机组出力、风光消纳和电... 详细信息

针对高风光渗透率的风-光-火综合能源系统弃能问题,提出利用电转氨和火电机组掺氨燃烧相结合的技术以提高风光利用率,改善我国以煤为主的能源系统安全性与环保性。首先提出电转氨耦合综合能源系统构型,并为燃煤机组出力、风光消纳和电转氨运行的经济性和稳定性的综合评价定义风-光-火-氨系统协调运行指标;进而构建以协调运行指标最大为上层目标、电转氨耦合风-光-火综合能源系统运行成本最小为下层目标的双层优化调度模型;最后,通过多场景下不同模型的对比验证了所提模型的有效性。结果表明,在冬季、过渡季和夏季典型日场景下,对于不含电转氨的综合能源系统,采用双层优化调度模型后,在燃煤机组的稳定性和安全性得到改善的同时,系统的总成本均降低。引入电转氨后,风光消纳率得到提升,总成本分别进一步降低1.06%、1.74%和0.59%;碳排放量分别降低2.11%、2.81%和1.95%。可见电转氨对综合能源系统的经济、低碳运行具有较好的改善作用。

关键词：综合能源系统电转氨掺氨燃烧协调运行双层优化模型

在线全文

学校读者我要写书评

暂无评论

海温异常对江淮流域入梅的影响

应用气象学报 2005年第2期16卷 193-204页

作者：王钟睿钱永甫南京大学大气科学系南京210093

通过对江淮流域入梅期与海温场的相关分析,以及对海温异常年大气环流的合成分析,研究了海温异常对江淮流域入梅的影响。结果表明,太平洋、印度洋和大西洋的海温异常对江淮流域的入梅期有较大影响,前一年11月至当年6月西太平洋暖池的海... 详细信息

通过对江淮流域入梅期与海温场的相关分析,以及对海温异常年大气环流的合成分析,研究了海温异常对江淮流域入梅的影响。结果表明,太平洋、印度洋和大西洋的海温异常对江淮流域的入梅期有较大影响,前一年11月至当年6月西太平洋暖池的海温偏高(低)时,江淮流域入梅早(晚)。2～5月中太平洋的海温偏高时,江淮流域入梅偏晚。5～6月,马斯克林高压附近的海温对入梅期有较好的指示意义,高海温对应早入梅,而低海温对应晚入梅。2～4月以及2～5月西太平洋暖池附近的海温对江淮流域的入梅也有较好的指示意义。6月,台湾以东以及南大西洋的海温异常对入梅期有较大影响。

关键词：江淮流域海温异常西太平洋暖池梅马斯克林高压指示意义相关分析合成分析大气环流中太平洋南大西洋海温场异常年印度洋偏高

印度洋、南海和东南沿海海温异常影响江淮流域6～7月降水量的分析及数值模拟

在线全文

学校读者我要写书评

暂无评论

应用气象学报 2005年第4期16卷 527-538页

作者：王钟睿钱永甫南京大学大气科学系南京210093

利用统计分析和CCM3数值模式研究了印度洋、南海和东南沿海同期海温异常对江淮梅雨的影响。统计分析结果表明:印度洋、南海和东南沿海的正(负)海温异常对应于江淮流域的多(少)雨。对OLR资料分析表明:当印度洋OLR为正(负)距平时,江淮流域... 详细信息

利用统计分析和CCM3数值模式研究了印度洋、南海和东南沿海同期海温异常对江淮梅雨的影响。统计分析结果表明:印度洋、南海和东南沿海的正(负)海温异常对应于江淮流域的多(少)雨。对OLR资料分析表明:当印度洋OLR为正(负)距平时,江淮流域OLR也为正(负)距平,但南海和东南沿海OLR多为负(正)距平。数值模拟结果表明:当印度洋为正海温异常时,中高纬地区的阻高偏强,江淮流域为多雨区;印度洋为负海温异常时,东亚沿海出现江淮流域旱年的环流形势,与统计事实相符合。

关键词：海温异常江淮流域雨量数值模拟江淮流域东南沿海印度洋南海月降水量 OLR资料统计分析