Destination prediction has attracted widespread attention because it can help vehicle-aid systems recommend related services in advance to improve user driving experience.However,the relevant research is mainly based ...Destination prediction has attracted widespread attention because it can help vehicle-aid systems recommend related services in advance to improve user driving experience.However,the relevant research is mainly based on driving trajectory of vehicles to predict the destinations,which is challenging to achieve the early destination prediction.To this end,we propose a model of early destination prediction,DP-BPR,to predict the destinations by users’travel time and locations.There are three challenges to accomplish the model:1)the extremely sparse historical data make it challenge to predict destinations directly from raw historical data;2)the destinations are related to not only departure points but also departure time so that both of them should be taken into consideration in prediction;3)how to learn destination preferences from historical data.To deal with these challenges,we map sparse high-dimensional data to a dense low-dimensional space through embedding learning using deep neural networks.We learn the embeddings not only for users but also for locations and time under the supervision of historical data,and then use Bayesian personalized ranking(BPR)to learn to rank destinations.Experimental results on the Zebra dataset show the effectiveness of DP-BPR.展开更多
In order to maximize the return of investments and at the same time improve the quality in the construction industry of midrise buildings, it is very important to derive an optimal solution to the building structural ...In order to maximize the return of investments and at the same time improve the quality in the construction industry of midrise buildings, it is very important to derive an optimal solution to the building structural system, which would facilitate faster and easier construction activities with minimal quantity of construction material, while maintaining the satisfactory level of building safety and performance. This paper makes a comparative study between a ＂solid＂ and a ＂waffle＂ slab system. A typical 14-story RC building structure is selected as an example for this study purpose. The first part of this study is focused in deriving an optimal solution for a solid and waffle slab system which are later on considered as constituents of all stories of the 14-story building. In the second part, it is elaborated the effect of both slab systems over the 14-story building model. This study aims to emphasize the advantages of mid-rise buildings constituted of waffle slab system over the buildings characterized with solid types of slabs, in terms of economy, structural safety and performance.展开更多
Competitiveness is a wide concept applied to many fields, especially in economics. The study of tourism competitiveness has been focused on different factors that can enhance the prosperity of a destination. One of th...Competitiveness is a wide concept applied to many fields, especially in economics. The study of tourism competitiveness has been focused on different factors that can enhance the prosperity of a destination. One of these factors is innovation. Innovation makes destination＇s enterprises more advanced and efficient, therefore more productive. Innovation is an enhancer of competitiveness and a generator of prosperity because innovation in every aspect （technology, knowledge, organization, and processes） will provide a better quality of life for the inhabitants of the destination. The incidence of innovation on these concepts is validated by a structural equation model. We measure innovation by a range of indicators and through a factor analysis; we get the most relevant indicators of innovation for the model developed in Spain.展开更多
基金Project(2018YFF0214706)supported by the National Key Research and Development Program of ChinaProject(cstc2020jcyj-msxmX0690)supported by the Natural Science Foundation of Chongqing,China+1 种基金Project(2020CDJ-LHZZ-039)supported by the Fundamental Research Funds for the Central Universities of Chongqing,ChinaProject(cstc2019jscx-fxydX0012)supported by the Key Research Program of Chongqing Technology Innovation and Application Development,China。
文摘Destination prediction has attracted widespread attention because it can help vehicle-aid systems recommend related services in advance to improve user driving experience.However,the relevant research is mainly based on driving trajectory of vehicles to predict the destinations,which is challenging to achieve the early destination prediction.To this end,we propose a model of early destination prediction,DP-BPR,to predict the destinations by users’travel time and locations.There are three challenges to accomplish the model:1)the extremely sparse historical data make it challenge to predict destinations directly from raw historical data;2)the destinations are related to not only departure points but also departure time so that both of them should be taken into consideration in prediction;3)how to learn destination preferences from historical data.To deal with these challenges,we map sparse high-dimensional data to a dense low-dimensional space through embedding learning using deep neural networks.We learn the embeddings not only for users but also for locations and time under the supervision of historical data,and then use Bayesian personalized ranking(BPR)to learn to rank destinations.Experimental results on the Zebra dataset show the effectiveness of DP-BPR.
文摘In order to maximize the return of investments and at the same time improve the quality in the construction industry of midrise buildings, it is very important to derive an optimal solution to the building structural system, which would facilitate faster and easier construction activities with minimal quantity of construction material, while maintaining the satisfactory level of building safety and performance. This paper makes a comparative study between a ＂solid＂ and a ＂waffle＂ slab system. A typical 14-story RC building structure is selected as an example for this study purpose. The first part of this study is focused in deriving an optimal solution for a solid and waffle slab system which are later on considered as constituents of all stories of the 14-story building. In the second part, it is elaborated the effect of both slab systems over the 14-story building model. This study aims to emphasize the advantages of mid-rise buildings constituted of waffle slab system over the buildings characterized with solid types of slabs, in terms of economy, structural safety and performance.
文摘Competitiveness is a wide concept applied to many fields, especially in economics. The study of tourism competitiveness has been focused on different factors that can enhance the prosperity of a destination. One of these factors is innovation. Innovation makes destination＇s enterprises more advanced and efficient, therefore more productive. Innovation is an enhancer of competitiveness and a generator of prosperity because innovation in every aspect （technology, knowledge, organization, and processes） will provide a better quality of life for the inhabitants of the destination. The incidence of innovation on these concepts is validated by a structural equation model. We measure innovation by a range of indicators and through a factor analysis; we get the most relevant indicators of innovation for the model developed in Spain.
