The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to proc...The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to process the expressway road property data information, based on the current mainstream Windows operating system, this study utilizes Geographic Information System (GIS) development technology, road video processing technology, and spatial data mining method to design and develop an expressway video and road infostructure GIS data production system. The system designs a multi-layer distributed application model in accordance with the ideas and methods of GIS engineering and the characteristics of road production data. In addition, according to the characteristics and specification requirements of basic geographic data, the road production database of spatial data and attribute data integrated storage is constructed by combining database and spatial data engine. Through the development of the GIS data production system for expressway video and road infostructure, various functions such as generation of road property data, dynamic management of road infostructure, and visualization of spatial information have been realized. The system focuses on improving the production efficiency and automation level of expressway production data and meet</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> the construction requirements for modernization, informatization, and intelligence of expressways.展开更多
A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably m...A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably mixed with fluctuant and abnormal values. Models established on the basis of the data without data processing can cause misleading results, which cannot be used for the optimal design of hot rolling process. Thus, a method of industrial data processing of C-Mn steel was proposed based on the data analysis. The Bayesian neural network was employed to establish the reliable mechanical property prediction models for the optimal design of hot rolling process. By using the multi-objective optimization algorithm and considering the individual requirements of costumers and the constraints of the equipment, the optimal design of hot rolling process was successfully applied to the rolling process design for Q345B steel with 0.017% Nb and 0.046% Ti content removed. The optimal process design results were in good agreement with the industrial trials results, which verify the effectiveness of the optimal design of hot rolling process.展开更多
The reflections on data regulation in the internet of things （IoT） in this paper provide an overview of the different conceptions and legal problems of ＂data property rights.＂ Beginning with an overview of the exi...The reflections on data regulation in the internet of things （IoT） in this paper provide an overview of the different conceptions and legal problems of ＂data property rights.＂ Beginning with an overview of the existing and possible applications of the future loT （in particular, smart cars）, this paper describes the legal concerns that may arise because of increased commercialization of object-generated data. The author uses German and European Union law to illustrate the legal complexities, solutions, and shortcomings. He demonstrates how and to what extent these issues are covered by traditional data protection regulations and highlights the conceptual blind spots of these regulations. He then contrasts the data protection paradigm （de lege lata） with the idea of a general erga omnes data property right （de lege ferenda） and describes the most common understanding of such a right, that is, a data producers＇ property right. Against the background of the possible economic advantages of general data property rights, the paper discusses conceptual problems and constitutional concerns. In conclusion, the author rejects the idea of a general data property right.展开更多
The curse of high-dimensionality has emerged in the statistical fields more and more frequently.Many techniques have been developed to address this challenge for classification problems. We propose a novel feature scr...The curse of high-dimensionality has emerged in the statistical fields more and more frequently.Many techniques have been developed to address this challenge for classification problems. We propose a novel feature screening procedure for dichotomous response data. This new method can be implemented as easily as t-test marginal screening approach, and the proposed procedure is free of any subexponential tail probability conditions and moment requirement and not restricted in a specific model structure. We prove that our method possesses the sure screening property and also illustrate the effect of screening by Monte Carlo simulation and apply it to a real data example.展开更多
文摘The expressway is necessary for the development of the modern transportation industry, and the level of expressway construction reflects the overall grade of national or regional economic development. In order to process the expressway road property data information, based on the current mainstream Windows operating system, this study utilizes Geographic Information System (GIS) development technology, road video processing technology, and spatial data mining method to design and develop an expressway video and road infostructure GIS data production system. The system designs a multi-layer distributed application model in accordance with the ideas and methods of GIS engineering and the characteristics of road production data. In addition, according to the characteristics and specification requirements of basic geographic data, the road production database of spatial data and attribute data integrated storage is constructed by combining database and spatial data engine. Through the development of the GIS data production system for expressway video and road infostructure, various functions such as generation of road property data, dynamic management of road infostructure, and visualization of spatial information have been realized. The system focuses on improving the production efficiency and automation level of expressway production data and meet</span><span style="font-family:Verdana;">s</span><span style="font-family:Verdana;"> the construction requirements for modernization, informatization, and intelligence of expressways.
文摘A successful mechanical property data-driven prediction model is the core of the optimal design of hot rolling process for hot-rolled strips. However, the original industrial data, usually unbalanced, are inevitably mixed with fluctuant and abnormal values. Models established on the basis of the data without data processing can cause misleading results, which cannot be used for the optimal design of hot rolling process. Thus, a method of industrial data processing of C-Mn steel was proposed based on the data analysis. The Bayesian neural network was employed to establish the reliable mechanical property prediction models for the optimal design of hot rolling process. By using the multi-objective optimization algorithm and considering the individual requirements of costumers and the constraints of the equipment, the optimal design of hot rolling process was successfully applied to the rolling process design for Q345B steel with 0.017% Nb and 0.046% Ti content removed. The optimal process design results were in good agreement with the industrial trials results, which verify the effectiveness of the optimal design of hot rolling process.
文摘The reflections on data regulation in the internet of things （IoT） in this paper provide an overview of the different conceptions and legal problems of ＂data property rights.＂ Beginning with an overview of the existing and possible applications of the future loT （in particular, smart cars）, this paper describes the legal concerns that may arise because of increased commercialization of object-generated data. The author uses German and European Union law to illustrate the legal complexities, solutions, and shortcomings. He demonstrates how and to what extent these issues are covered by traditional data protection regulations and highlights the conceptual blind spots of these regulations. He then contrasts the data protection paradigm （de lege lata） with the idea of a general erga omnes data property right （de lege ferenda） and describes the most common understanding of such a right, that is, a data producers＇ property right. Against the background of the possible economic advantages of general data property rights, the paper discusses conceptual problems and constitutional concerns. In conclusion, the author rejects the idea of a general data property right.
基金supported by Graduate Innovation Foundation of Shanghai University of Finance and Economics of China (Grant Nos. CXJJ-2014-459 and CXJJ-2015-430)National Natural Science Foundation of China (Grant No. 71271128), the State Key Program of National Natural Science Foundation of China (Grant No. 71331006), the State Key Program in the Major Research Plan of National Natural Science Foundation of China (Grant No. 91546202)+1 种基金National Center for Mathematics and Interdisciplinary Sciences, Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences (Grant No. 2008DP173182)Innovative Research Team in Shanghai University of Finance and Economics (Grant No. IRT13077)
文摘The curse of high-dimensionality has emerged in the statistical fields more and more frequently.Many techniques have been developed to address this challenge for classification problems. We propose a novel feature screening procedure for dichotomous response data. This new method can be implemented as easily as t-test marginal screening approach, and the proposed procedure is free of any subexponential tail probability conditions and moment requirement and not restricted in a specific model structure. We prove that our method possesses the sure screening property and also illustrate the effect of screening by Monte Carlo simulation and apply it to a real data example.
