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Resource discovery strategy is an important part of mobile peer-to-peer network. How to response the users' query rapidly and effectively is related to the efficiency and the performance of the mobile P2P system. In this survey, we give an overview of the background and the characteristics of mobile P2P networks. We also provide a classification for mobile P2P networks, and review the corresponding various search algorithms. At last, we conclude this paper and point out the future research directions.

The deficiency of measures which are used for the safe operation of power cables is analyzed in this paper, and then the fuzzy decision trees is applied to the field. This paper introduces the fuzzy ID3 algorithm and proposes the method of power cable insulation condition assessment based on fuzzy decision tree. What's more, a model based on original data monitored on 35kv cable in Jilin power system is created, and the experimental results show that this method could judge the state of the cable insulation effectively so as to provide the basis of cable maintenance for the maintenance personel.

Building Virtual Tour is an emerging field of virtual reality applications, the research analyses the framework of roaming system and gives the implementation of the system. The article also researches the issues about the establishing and optimization of the three-dimensional scene model, collision detection, and the realization of human-computer real-time interaction.

At present, there are two different research in the forefront of studying the virtual campus roaming, they are geometric model-based virtual reality technology and image-based virtual reality technology [1]. Based on geometric model-based virtual reality technology, the paper has designed and realized a desktop virtual campus cruising system that has real-time interactivity, immersion and telepresence by using the combination of VRML and 3ds MAX in the computer environment. The paper also gives the detailed description of scene modeling, roaming implementation, the realization of human-computer interaction function, and collision detection.

This paper fully studied in the Collaborative Filtering Recommendation Algorithm and k-means clustering algorithm, on this basis, Proposed the establishment of recommendation system based on the collaborative Filtering Recommendation Algorithm of k-means clustering algorithm. This can significantly reduce the seeking time of algorithm to find the nearest neighbor time, so as to raise the speed of the E-commerce recommendation system.