System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a ...System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.展开更多
With the eruption of big data,practical recommendation schemes are now very important in various fields,including e-commerce,social networks,and a number of web-based services.Nowadays,there exist many personalized mo...With the eruption of big data,practical recommendation schemes are now very important in various fields,including e-commerce,social networks,and a number of web-based services.Nowadays,there exist many personalized movie recommendation schemes utilizing publicly available movie datasets(e.g.,MovieLens and Netflix),and returning improved performance metrics(e.g.,Root-Mean-Square Error(RMSE)).However,two fundamental issues faced by movie recommendation systems are still neglected:first,scalability,and second,practical usage feedback and verification based on real implementation.In particular,Collaborative Filtering(CF)is one of the major prevailing techniques for implementing recommendation systems.However,traditional CF schemes suffer from a time complexity problem,which makes them bad candidates for real-world recommendation systems.In this paper,we address these two issues.Firstly,a simple but high-efficient recommendation algorithm is proposed,which exploits users1 profile attributes to partition them into several clusters.For each cluster,a virtual opinion leader is conceived to represent the whole cluster,such that the dimension of the original useritem matrix can be significantly reduced,then a Weighted Slope One-VU method is designed and applied to the virtual opinion leader-item matrix to obtain the recommendation results.Compared to traditional clusteringbased CF recommendation schemes,our method can significantly reduce the time complexity,while achieving comparable recommendation performance.Furthermore,we have constructed a real personalized web-based movie recommendation system,MovieWatch,opened it to the public,collected user feedback on recommendations,and evaluated the feasibility and accuracy of our system based on this real-world data.展开更多
Modem surface mines, either mono-system or multi-systems, need a large fleet of equipment consisting of excavators, loaders, haulers and auxiliary machines. Presently, the complexity of the system, the interference be...Modem surface mines, either mono-system or multi-systems, need a large fleet of equipment consisting of excavators, loaders, haulers and auxiliary machines. Presently, the complexity of the system, the interference between sub-systems and the lag in management skills has been a bottle neck for improving productivity of the system. Based on the fact that the traditional tools for safety analysis have been insufficient to evaluate systematically and dynamically the safety risks, this paper tries to create a virtual reality tool consisting of human, machine and mines, using Pro/E and the 3D MAX software in order to evaluate visually the operations of typical mining equipment, such as the bucket wheel excavator （BWE）, the shovel, the truck and the dragline. Within this virtual world, the behavior of the system, such as interaction, interference and potential risk can be replayed and reviewed visually. The objective of the study is to identify the critical safety issues of the system and to provide a convenient and powerful tool for safety training and safety management.展开更多
文摘System optimization plays a crucial role in developing VR system after 3D modeling, affecting the system's Immersion and Interaction performance enormously. In this article, several key techniques of optimizing a virtual mining system were discussed: optimizing 3D models to keep the polygon number in VR system within target hardware's processing ability; optimizing texture database to save texture memory with perfect visual effect; optimizing database hierarchy structure to accelerate model retrieval; and optimizing LOD hierarchy structure to speed up rendering.
文摘With the eruption of big data,practical recommendation schemes are now very important in various fields,including e-commerce,social networks,and a number of web-based services.Nowadays,there exist many personalized movie recommendation schemes utilizing publicly available movie datasets(e.g.,MovieLens and Netflix),and returning improved performance metrics(e.g.,Root-Mean-Square Error(RMSE)).However,two fundamental issues faced by movie recommendation systems are still neglected:first,scalability,and second,practical usage feedback and verification based on real implementation.In particular,Collaborative Filtering(CF)is one of the major prevailing techniques for implementing recommendation systems.However,traditional CF schemes suffer from a time complexity problem,which makes them bad candidates for real-world recommendation systems.In this paper,we address these two issues.Firstly,a simple but high-efficient recommendation algorithm is proposed,which exploits users1 profile attributes to partition them into several clusters.For each cluster,a virtual opinion leader is conceived to represent the whole cluster,such that the dimension of the original useritem matrix can be significantly reduced,then a Weighted Slope One-VU method is designed and applied to the virtual opinion leader-item matrix to obtain the recommendation results.Compared to traditional clusteringbased CF recommendation schemes,our method can significantly reduce the time complexity,while achieving comparable recommendation performance.Furthermore,we have constructed a real personalized web-based movie recommendation system,MovieWatch,opened it to the public,collected user feedback on recommendations,and evaluated the feasibility and accuracy of our system based on this real-world data.
基金Project 2002CB412705 supported by the Major State Basic Research Development Program (973) of China
文摘Modem surface mines, either mono-system or multi-systems, need a large fleet of equipment consisting of excavators, loaders, haulers and auxiliary machines. Presently, the complexity of the system, the interference between sub-systems and the lag in management skills has been a bottle neck for improving productivity of the system. Based on the fact that the traditional tools for safety analysis have been insufficient to evaluate systematically and dynamically the safety risks, this paper tries to create a virtual reality tool consisting of human, machine and mines, using Pro/E and the 3D MAX software in order to evaluate visually the operations of typical mining equipment, such as the bucket wheel excavator （BWE）, the shovel, the truck and the dragline. Within this virtual world, the behavior of the system, such as interaction, interference and potential risk can be replayed and reviewed visually. The objective of the study is to identify the critical safety issues of the system and to provide a convenient and powerful tool for safety training and safety management.
