Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By...Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things （IoT）, continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine （SVM） to Aarhus smart city traffic data is presented for a more detailed exploration.展开更多
Since the reform and opening up,with the digital network science change rapidly development,China＇ s digital animation industry has been rapid development of corresponding.Effects of digital animation industry of Ch...Since the reform and opening up,with the digital network science change rapidly development,China＇ s digital animation industry has been rapid development of corresponding.Effects of digital animation industry of China＇ s national economy is more and more strong,and in the entire national economy proportion is also growing.Digital animation industry as one of the most promising future industry, its development potential is very great,and it should cause our enough attention,which must not regard as unimportant.The development of digital industry can drive software and hardware technology, telecommunications industry and other industries progress.However, at present our country digital animation industry development is not satisfactory, and there are still many problems,also,the problems existed in the development of China＇s digital animation industry problem for detailed analysis,and it puts forward some countermeasures to solve the problem.展开更多
Public stadiums is the hardware foundation for the development of sports enterprise, the operating status and the degree of perfection of public stadiums in a country or a region, not only reflects the level of develo...Public stadiums is the hardware foundation for the development of sports enterprise, the operating status and the degree of perfection of public stadiums in a country or a region, not only reflects the level of development of sports of the countries in the region, but also it is an important symbol of modernization. However, the operation and management problems of public sports venues, are still worldwide problem, and stadiums in China face the same problem.展开更多
With the decrease of the device size,soft error induced by various particles becomes a serious problem for advanced CMOS technologies.In this paper,we review the evolution of two main aspects of soft error-SEU and SET...With the decrease of the device size,soft error induced by various particles becomes a serious problem for advanced CMOS technologies.In this paper,we review the evolution of two main aspects of soft error-SEU and SET,including the new mechanisms to induced SEUs,the advances of the MCUs and some newly observed phenomena of the SETs.The mechanisms and the trends with downscaling of these issues are briefly discussed.We also review the hardening strategies for different types of soft errors from different perspective and present the challenges in testing,modeling and hardening assurance of soft error issues we have to address in the future.展开更多
文摘Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things （IoT）, continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine （SVM） to Aarhus smart city traffic data is presented for a more detailed exploration.
文摘Since the reform and opening up,with the digital network science change rapidly development,China＇ s digital animation industry has been rapid development of corresponding.Effects of digital animation industry of China＇ s national economy is more and more strong,and in the entire national economy proportion is also growing.Digital animation industry as one of the most promising future industry, its development potential is very great,and it should cause our enough attention,which must not regard as unimportant.The development of digital industry can drive software and hardware technology, telecommunications industry and other industries progress.However, at present our country digital animation industry development is not satisfactory, and there are still many problems,also,the problems existed in the development of China＇s digital animation industry problem for detailed analysis,and it puts forward some countermeasures to solve the problem.
文摘Public stadiums is the hardware foundation for the development of sports enterprise, the operating status and the degree of perfection of public stadiums in a country or a region, not only reflects the level of development of sports of the countries in the region, but also it is an important symbol of modernization. However, the operation and management problems of public sports venues, are still worldwide problem, and stadiums in China face the same problem.
基金supported by the National Natural Science Foundation of China(Grant No.11175138)the Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20100201110018)+1 种基金the Key Program of the National Natural Science Foundation of China(Grant No.11235008)the State Key Laboratory Program(Grant No.20140134)
文摘With the decrease of the device size,soft error induced by various particles becomes a serious problem for advanced CMOS technologies.In this paper,we review the evolution of two main aspects of soft error-SEU and SET,including the new mechanisms to induced SEUs,the advances of the MCUs and some newly observed phenomena of the SETs.The mechanisms and the trends with downscaling of these issues are briefly discussed.We also review the hardening strategies for different types of soft errors from different perspective and present the challenges in testing,modeling and hardening assurance of soft error issues we have to address in the future.
