At present, academic social network platforms have problems such as information overload and information asymmetry, which makes it difficult for scholars, especially those with low influence, to find contents they are interested in. At the same time, the scholars with high influence in the academic social network promote the formation of academic community and guide the scientific research of the scholars with low influence. Therefore, an Influential Scholar Recommendation Model based on Academic Community Detection (ISRMACD) was proposed to provide recommendation service for the scholars with low influence in academic social networks. First, the influential scholar group was used as the core structure of community to detect the academic community in complex network topological relationship generated by the relationship bonding — friendship among the scholars in the academic social network. Then the influences of scholars in the academic social network were calculated, and the recommendation service of influential scholars in the community was implemented. Experimental results on SCHOLAT dataset show that the proposed model achieves high recommendation quality under different influential scholar recommendation numbers, and has the best recommendation accuracy obtained by recommending 10 influential scholars each time, reaching 70% and above.

An increasing large number of services are available in the network, which plays a great role in promoting the development of service-oriented computing technology. Concerning the problems that services scale and utilization were far from initially expected, and the interactions of making the services work together were complicated, a method for constructing service network based on social network and linked data was proposed. First of all, in order to improve service scale and utilization, the concept of Service Network (SN) combining social network and linked data was proposed. Secondly, the service community in the service network was established for elevating the feasibility and effectiveness of service discovery. Then, in order to solve the problem of service interoperation, the service relationship and property were formally expressed in service network. Finally, a case study of tourism service was used to analyze the proposed method. The analysis results show that the efficiency and feasibility of the proposed method are validated to solve the problems of low service utilization and complex service relationship.

An academic paper recommendation model based on community partition was proposed according to sociability in social network. The model regarded the largest connected component in complex network as the logic unit in data processing, and divided up the largest connected component into non-intersect kernel sub-network. The labels would be established according to kernel sub-network by non-parameter control mode. Communities were divided in scholar social network through label propagation, and academic papers were recommended among the users in the communities by the results of the community partition. The proposed community partition method was compared with the classic community partition method in the experiments on artificial network. The experimental results show that the proposed method can achieve good community partition qualities on different characteristic artificial networks.

Concerning the problem that community detection algorithm based on label propagation in complex networks has a pre-parameter limit in the real network and redundant labels, a community detection model in large scale academic social networks was proposed. The model detected Utmost Maximal Cliques (UMC) in the academic social network and arbitrary intersection between the UMC is the empty set, and then let nodes of each UMC share the unique label by reducing redundant labels and random factors, so the model increased the efficiency and stability of the algorithm. Meanwhile the model completed label propagation of the UMC adjacent nodes using closeness from core node groups (UMC) to spread around, Non-UMC adjacent nodes in the network were updated according to the maximum weight of its neighbor nodes. In the post-processing stage an adaptive threshold method removed useless labels, thereby effectively overcame the pre-parameter limitations in the real complex network. The experimental results on academic social networking platform-SCHOLAT data set prove that the model has an ability to assign nodes with certain generality to the same community, and it provides support of the academic social networks precise personalized service in the future, such as latent friend recommendation and paper sharing.

The process of using the traditional WordNet Application Programming Interface (API) is based on the file operation, so each execution of API in WordNet library would lead to serious problem of time-consuming in process of text analysis and similarity calculation. Therefore, the improved solution of WordNet API was proposed. The process of constructing semantic net of WordNet concept was transferred into the computer memory; meanwhile several APIs which were convenient to calculate the similarity were added. These improvements would accelerate the process of tracking the relationship of concepts and text similarity calculation. This solution was already applied in the process of Mashup services discovery. The experimental results show that the use of improved API can effectively improve the query efficiency and recall of Mashup service.

A new method to design a 3D surface movement simulation system for A-SMGCS based on Linux operation system and FilightGear flight simulator was proposed. The simulation system was driven by real-time track data of ADS-B. An airport model was built up according to a real airport prototype by modeling of aircrafts, airport layout, terminal, tower and terrain. Because ADS-B track data had no flight attitude data, an algorithm to extract flight attitude from a space vector, which was connected by two pre and post track points, was proposed. Six degrees of freedom (6-DOF) aircraft movement simulation was realized by importing position and attitude data into FlightGear through its multiplayer interface to drive aircraft models. The simulation results show that, the system can simulate surface movement accurately and realistically. The simulation system is low-cost because it is based on free, open source software.

Many current Radio Frequency IDentification （RFID） authentication protocols cannot conform with the EPC Class 1 Gen 2 (EPC Gen2) standards or cannot meet the requirements of low-cost tags for the RFID authentication protocol. A new RFID authentication protocol based on the EPC Class 1 Gen 2 (EPC Gen2) standards was proposed and the security proof was given with BAN logic. After analyzing the security, the proposed protocol can meet the RFID security demands: information confidentiality, data integrity and identity authentication.