This is the first of two-part paper that investigates the multi-mode sequential flocking with application to multiple non-holonomic mobile robot motion control. To provide a new procedure to avoid collisions and obstacles in the process of multi-robot's sequential flocking, this paper presents the design of a multi-model flocking control for multiple mobile robots in terms of behaviour-based robotics. Some nature-imitating behaviour modes are integrated into the new sequential flocking strategy, including single-robot potential-based behaviour, singlerobot wall-following behaviour, multi-robot rigid-body bouncing behaviour, multi-robot pathtracking behaviour and their fusion state. In this way, the efficient collision and obstacle avoidance in flocking motion can be achieved.

This study is a productivity review on the literature gleaned from SSCI, SCIE databases concerning trust analysis in social network community research. The result indicates that the number of literature productions on trust analysis in social network community is still growing. The main research development country is the United States, and from the analysis of the distribution of language, English is the most popular language. Moreover the research focuses on are mainly empirical research, computational model and recommendation system, we analyze these typical references in detail, also limitations and future research.

Cell Nerve Network (CNN) has been used to process the cloudy radar image. And then we use mathematic to diagnose the cloudy is hail or not. Veins is useful in diagnose the hail cloudy in weather forecast. The veins of the radar image have been picking up according the CNN. And then find the regular polynomial to processed radar image .Then analysis the image with polynomial fitting. We enlarge eight times of the key part of the radar image, and then detect the edge of the image. Dug some data as information .At last we find some regular to distinguish the cloud with hail or not. We find those are useful way for forecasting of hail.

Abstract. This paper studies on the prediction of the hail. First, Cellular Neural Network method acts on the cloud radar images to extract their edge, The cloud's contour feature would be more clear; and then, the edge detection would be processed by wavelet transform. Five different coefficients would be found; At last we construct hail cloud life feature vector matrix, explain the problem by matrix form, so as to find the corresponding rules through the five coefficients, after seeking to rules, through the simulation experiment, to achieve the purpose of hail forecast.

This study is a productivity review on the literature gleaned from SSCI, SCIE databases concerning social network analysis in knowledge management research. The result indicates that the number of related literature is still growing especially in recent two years. The main research development country is the United States, then England and German, and from the analysis of the subject area, Information Science & Library Science is the most popular subject. Concerning source title, Knowledge Management Research & Practice is in the priority. Moreover the research focuses on this topic are mainly in close relationship with knowledge network. Typical references were analyzed in detail, including limitations and future research.