This paper describes the function,structure and working status of the data buffer unitDBU,one of the most important functional units on ITM-1.It also discusses DBU’s supportto the multiprocessor system and Prolog lan...This paper describes the function,structure and working status of the data buffer unitDBU,one of the most important functional units on ITM-1.It also discusses DBU’s supportto the multiprocessor system and Prolog language.展开更多
Artificial intelligence is a new technological science that researches and develops theories,methods,technologies and application systems for simulating,extending and expanding human intelligence.It simulates certain ...Artificial intelligence is a new technological science that researches and develops theories,methods,technologies and application systems for simulating,extending and expanding human intelligence.It simulates certain human thought processes and intelligent behaviors(such as learning,reasoning,thinking,planning,etc.),and produces a new type of intelligent machine that can respond in a similar way to human intelligence.In the past 30 years,it has achieved rapid development in various industries and related disciplines such as manufacturing,medical care,finance,and transportation.展开更多
Land cover map can accurately characterize the spatial distribution of natural and artificial surface features.However,large-scale land cover products with submeter resolution are still scarce.To address this gap,this...Land cover map can accurately characterize the spatial distribution of natural and artificial surface features.However,large-scale land cover products with submeter resolution are still scarce.To address this gap,this study proposes an innovative data annotation engine,called initial and expanded labeling,to generate reliable labels for high-resolution imagery.The engine takes imagery and historical products as input,generates a small number of labels using weight voting in the first stage,and iteratively expands the labels in the second stage.The proposed method can effectively deal with the insufficiency of training labels in large-scale submeter land cover mapping.Based on the datasets generated by this engine,we have produced the first large-scale submeter land cover map covering the urban areas of 42 major cities in China,called EcoVision.It has a spatial resolution of about 0.5 m with 8 representative urban land cover categories.The product has been validated with 23,850,000 randomly sampled validation pixels in 42 cities and has an overall accuracy of 83.6%.Compared with 5 existing land cover maps,EcoVision shows superior performance in spatial resolution,accuracy,and details.The product has been made public,providing high-precision data support for urban sustainable development research and territorial spatial planning.展开更多
OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and a...OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and analysis of data on 3970 sub-mentally healthy individuals selected from 13385 relevant question naires.METHODS: The strategic tree algorithm was used to identify the main mani festations of the state of sub-mental health. The backpropogation artificial neural network was used to analyze the main mani festations of sub-healthy mental states of three different degrees. A sub-mental health evaluation model was then established to achieve predictive evaluationresults.RESULTS: Using classifications from the Scale of Chinese Sub-healthy State, the main manifestations of sub-mental health selected using the strate gictree were F1101(Do you lack peace of mind?),F1102(Are you easily nervous when something comes up?), and F1002(Do you often sigh?). The relative intensity of manifestations of sub-mental health was highest for F1101, followed by F1102,and then F1002. Through study of the neural network, better differentiation could be made between moderate and severe and between mild and severe states of sub-mental health. The differentiation between mild and moderate sub-mental health states was less apparent. Additionally, the sub-mental health state evaluation model, which could be used to predict states of sub-mental health of different individuals, was established using F1101, F1102, F1002, and the mental self-assessment totals core.CONCLUSION: The main manifestations of the state of sub-mental health can be discovered using data mining methods to research and analyze the latent laws and knowledge hidden in research evidence on the state of sub-mental health. The state of sub-mental health of different individuals can be rapidly predicted using the model established here.This can provide a basis for assessment and intervention for sub-mental health. It can also replace the relatively outdated approaches to research on sub-health in the technical era of information and digitization by combining the study of states of sub-mental health with information techniques and by further quantifying the relevant information.展开更多
推荐系统已经被越来越频繁地应用到电子商务网站与一些社交网站,在提高用户满意度的同时也带来了巨大的商业利益.然而,当前的推荐算法由于原始数据的不完整性以及算法本身处理数据的特殊性,导致推荐效果不理想.例如,某些推荐系统会产生...推荐系统已经被越来越频繁地应用到电子商务网站与一些社交网站,在提高用户满意度的同时也带来了巨大的商业利益.然而,当前的推荐算法由于原始数据的不完整性以及算法本身处理数据的特殊性,导致推荐效果不理想.例如,某些推荐系统会产生冷启动、复杂兴趣推荐困难、解释性差等问题.为此,该文提出一种基于标签权重评分的推荐系统模型(Label-Weight Rating based Recommendation,LWR),旨在使用一种较为简洁的方式——标签权重评分来获取用户最准确的评价和需求,并通过改进当前的一些推荐算法来处理标签权重评分数据,从而生成对用户的推荐,最后以标签权重评分的形式向用户展示推荐结果并作出合理的解释.扩展实验中,通过电影推荐实验,证明了该文技术的有效性和可行性.展开更多
1 Introduction.With the rapid development of emerging technologies such as the Internet of Things(IoT)and artificial intelligence(AI),data has become an indispensable key asset and core resource across various industr...1 Introduction.With the rapid development of emerging technologies such as the Internet of Things(IoT)and artificial intelligence(AI),data has become an indispensable key asset and core resource across various industries[1].Data trading as an emerging business model,relies on high-quality data products for its healthy development[2,3].展开更多
ESCAP/WMO Typhoon Committee Members are directly or indirectly affected by typhoons every year.Members have accumulated rich experiences dealing with typhoons'negative impact and developed the technologies and mea...ESCAP/WMO Typhoon Committee Members are directly or indirectly affected by typhoons every year.Members have accumulated rich experiences dealing with typhoons'negative impact and developed the technologies and measures on typhoon-related disaster risk forecasting and early warning in various ways to reduce the damage caused by typhoon.However,it is still facing many difficulties and challenges to accurately forecast the occurrence of typhoons and warning the potential impacts in an early stage due to the continuously changing weather conditions.With the development of information technology(IT)and computing science,and increasing accumulated hydro-meteorological data in recent decades,scientists,researchers and operationers keep trying to improve forecasting models based on the application of big data and artificial intelligent(AI)technology to promote the capacity of typhoon-related disaster risk forecasting and early warning.This paper reviewed the current status of application of big data and AI technology in the aspect of typhoon-related disaster risk forecasting and early warning,and discussed the challenges and limitations that must be addressed to effectively harness the power of big data and AI technology application in typhoon-related disaster risk reduction in the future.展开更多
As the energy transition is upon us,the replacement of combustion engines by electrical ones will imply a greater stress on the electrical grid of different countries.Therefore,it is of paramount importance to simulat...As the energy transition is upon us,the replacement of combustion engines by electrical ones will imply a greater stress on the electrical grid of different countries.Therefore,it is of paramount importance to simulate a great number of hypothetical multi-variant scenarios to correctly plan the roll-out of new grids.In this paper,we deploy Generative Adversarial Networks(GANs)to swiftly reproduce the non-Gaussian and multimodal distribution of real energy-related samples,making GANs a valuable tool for data generation in the field.In particular,we propose an original dataset deriving from the aggregation of two European providers including hourly electric inland generation from several European countries.This dataset also comes along with the corresponding season,day of the week,hour of the day and macro-economic variables aiming at unequivocally describing the country’s energetic profile.Finally,we evaluate the performance of our model via dedicated metrics capable of grasping the non-Gaussian nature of the data and compare it with the state-of-the-art model for tabular data generation.展开更多
Modern data-centric applications,such as artifical artificial intelligence(AI)workloads,graph data analysis,IoT and mobile systems,have emerged and been widely used in our daily life.These applications keep raising th...Modern data-centric applications,such as artifical artificial intelligence(AI)workloads,graph data analysis,IoT and mobile systems,have emerged and been widely used in our daily life.These applications keep raising the requirements of large capacity,high performance,low power consumption,and high reliability for the whole memory hierarchy,which may be difficult to be satisfied by traditional memory architectures and systems.On the other hand,with the rapid advancement of memory technologies,various emerging memory technologies have been proposed to mitigate the problems mentioned above.These emerging memory technologies have the advantages of high density,low standy power,etc.However,they also face the challenges of programming overhead,limited lifetime,and reliablility issues.Thus,to leverage the uniques features and handle the limitations of these emerging memory technologies,we are expecting innovations in memory architecture and system designs.展开更多
基金the High Technology Research and Development Programme of china.
文摘This paper describes the function,structure and working status of the data buffer unitDBU,one of the most important functional units on ITM-1.It also discusses DBU’s supportto the multiprocessor system and Prolog language.
文摘Artificial intelligence is a new technological science that researches and develops theories,methods,technologies and application systems for simulating,extending and expanding human intelligence.It simulates certain human thought processes and intelligent behaviors(such as learning,reasoning,thinking,planning,etc.),and produces a new type of intelligent machine that can respond in a similar way to human intelligence.In the past 30 years,it has achieved rapid development in various industries and related disciplines such as manufacturing,medical care,finance,and transportation.
基金supported by the National Key Research and Development Program of China(grant number 2024YFF1306102)the National Natural Science Foundation of China(grant numbers 42271328 and 42471391).
文摘Land cover map can accurately characterize the spatial distribution of natural and artificial surface features.However,large-scale land cover products with submeter resolution are still scarce.To address this gap,this study proposes an innovative data annotation engine,called initial and expanded labeling,to generate reliable labels for high-resolution imagery.The engine takes imagery and historical products as input,generates a small number of labels using weight voting in the first stage,and iteratively expands the labels in the second stage.The proposed method can effectively deal with the insufficiency of training labels in large-scale submeter land cover mapping.Based on the datasets generated by this engine,we have produced the first large-scale submeter land cover map covering the urban areas of 42 major cities in China,called EcoVision.It has a spatial resolution of about 0.5 m with 8 representative urban land cover categories.The product has been validated with 23,850,000 randomly sampled validation pixels in 42 cities and has an overall accuracy of 83.6%.Compared with 5 existing land cover maps,EcoVision shows superior performance in spatial resolution,accuracy,and details.The product has been made public,providing high-precision data support for urban sustainable development research and territorial spatial planning.
基金Supported by Chinese"Disease"Sub-health Medicine Research and Intervention of the Eleventh Five-Year Science and Technology Support Project of China(No.2006BAI13B01)Financial Support Case Studies of Traditional Chinese Medicine Treatment of Disease and Health Management Ideas of Shanghai Health Bureau(No.2010227)+2 种基金Scientific Innovation Research Funds of Shanghai Municipal Education Commission(No.14YZ061)Teacher Academic Community Fund of Shanghai University of Traditional Chinese Medicine(No.2013JXG03)Chinese Culture and Its Core Value System Modernization Transformation of the National Social Science Funds(No.12AZD094)
文摘OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and analysis of data on 3970 sub-mentally healthy individuals selected from 13385 relevant question naires.METHODS: The strategic tree algorithm was used to identify the main mani festations of the state of sub-mental health. The backpropogation artificial neural network was used to analyze the main mani festations of sub-healthy mental states of three different degrees. A sub-mental health evaluation model was then established to achieve predictive evaluationresults.RESULTS: Using classifications from the Scale of Chinese Sub-healthy State, the main manifestations of sub-mental health selected using the strate gictree were F1101(Do you lack peace of mind?),F1102(Are you easily nervous when something comes up?), and F1002(Do you often sigh?). The relative intensity of manifestations of sub-mental health was highest for F1101, followed by F1102,and then F1002. Through study of the neural network, better differentiation could be made between moderate and severe and between mild and severe states of sub-mental health. The differentiation between mild and moderate sub-mental health states was less apparent. Additionally, the sub-mental health state evaluation model, which could be used to predict states of sub-mental health of different individuals, was established using F1101, F1102, F1002, and the mental self-assessment totals core.CONCLUSION: The main manifestations of the state of sub-mental health can be discovered using data mining methods to research and analyze the latent laws and knowledge hidden in research evidence on the state of sub-mental health. The state of sub-mental health of different individuals can be rapidly predicted using the model established here.This can provide a basis for assessment and intervention for sub-mental health. It can also replace the relatively outdated approaches to research on sub-health in the technical era of information and digitization by combining the study of states of sub-mental health with information techniques and by further quantifying the relevant information.
文摘推荐系统已经被越来越频繁地应用到电子商务网站与一些社交网站,在提高用户满意度的同时也带来了巨大的商业利益.然而,当前的推荐算法由于原始数据的不完整性以及算法本身处理数据的特殊性,导致推荐效果不理想.例如,某些推荐系统会产生冷启动、复杂兴趣推荐困难、解释性差等问题.为此,该文提出一种基于标签权重评分的推荐系统模型(Label-Weight Rating based Recommendation,LWR),旨在使用一种较为简洁的方式——标签权重评分来获取用户最准确的评价和需求,并通过改进当前的一些推荐算法来处理标签权重评分数据,从而生成对用户的推荐,最后以标签权重评分的形式向用户展示推荐结果并作出合理的解释.扩展实验中,通过电影推荐实验,证明了该文技术的有效性和可行性.
基金supported by the Ministry of Education Humanities and Social Science Project(No.21YJCZH197)Shanxi Provincial Research Foundation for Basic Research(No.202303021221184).
文摘1 Introduction.With the rapid development of emerging technologies such as the Internet of Things(IoT)and artificial intelligence(AI),data has become an indispensable key asset and core resource across various industries[1].Data trading as an emerging business model,relies on high-quality data products for its healthy development[2,3].
文摘ESCAP/WMO Typhoon Committee Members are directly or indirectly affected by typhoons every year.Members have accumulated rich experiences dealing with typhoons'negative impact and developed the technologies and measures on typhoon-related disaster risk forecasting and early warning in various ways to reduce the damage caused by typhoon.However,it is still facing many difficulties and challenges to accurately forecast the occurrence of typhoons and warning the potential impacts in an early stage due to the continuously changing weather conditions.With the development of information technology(IT)and computing science,and increasing accumulated hydro-meteorological data in recent decades,scientists,researchers and operationers keep trying to improve forecasting models based on the application of big data and artificial intelligent(AI)technology to promote the capacity of typhoon-related disaster risk forecasting and early warning.This paper reviewed the current status of application of big data and AI technology in the aspect of typhoon-related disaster risk forecasting and early warning,and discussed the challenges and limitations that must be addressed to effectively harness the power of big data and AI technology application in typhoon-related disaster risk reduction in the future.
文摘As the energy transition is upon us,the replacement of combustion engines by electrical ones will imply a greater stress on the electrical grid of different countries.Therefore,it is of paramount importance to simulate a great number of hypothetical multi-variant scenarios to correctly plan the roll-out of new grids.In this paper,we deploy Generative Adversarial Networks(GANs)to swiftly reproduce the non-Gaussian and multimodal distribution of real energy-related samples,making GANs a valuable tool for data generation in the field.In particular,we propose an original dataset deriving from the aggregation of two European providers including hourly electric inland generation from several European countries.This dataset also comes along with the corresponding season,day of the week,hour of the day and macro-economic variables aiming at unequivocally describing the country’s energetic profile.Finally,we evaluate the performance of our model via dedicated metrics capable of grasping the non-Gaussian nature of the data and compare it with the state-of-the-art model for tabular data generation.
文摘Modern data-centric applications,such as artifical artificial intelligence(AI)workloads,graph data analysis,IoT and mobile systems,have emerged and been widely used in our daily life.These applications keep raising the requirements of large capacity,high performance,low power consumption,and high reliability for the whole memory hierarchy,which may be difficult to be satisfied by traditional memory architectures and systems.On the other hand,with the rapid advancement of memory technologies,various emerging memory technologies have been proposed to mitigate the problems mentioned above.These emerging memory technologies have the advantages of high density,low standy power,etc.However,they also face the challenges of programming overhead,limited lifetime,and reliablility issues.Thus,to leverage the uniques features and handle the limitations of these emerging memory technologies,we are expecting innovations in memory architecture and system designs.
