Aiming at the energy efficiency and scene adaptability problems of synchronization topology， a Greedy Synchronization Topology algorithm based on Formal Concept Analysis for traffic surveillance based sensor network （GST-FCA） was proposed. Firstly， scene adaptability requirements and energy efficiency model of the synchronization topology in traffic surveillance based sensor network were analyzed. Secondly， correlation analysis was performed on the adjacent features of sensor nodes in the same layer and adjacent layers by using Formal Concept Analysis （FCA）. Afterward， Broadcast Tuples （BT） were built and synchronization sets were divided according to the greedy strategy with the maximum number of neighbors. Thirdly， a backtracking broadcast was used to improve the broadcast strategy of layer detection in Timing-synchronization Protocol of Sensor Network （TPSN） algorithm. Meanwhile， an upward hosting mechanism was designed to not only extend the information sharing range of synchronous nodes but also further alleviate the locally optimal solution problem caused by the greedy strategy. Finally， GST-FCA was verified and tested in terms of energy efficiency and scene adaptability. Simulation results show that compared with algorithms such as TPSN， Linear Estimation of Clock Frequency Offset （LECFO）， GST-FCA decreases the synchronization packet overhead by 11.54%， 24.59% and 39.16% at lowest in the three test scenarios of deployment location， deployment scale and road deployment. Therefore， GST-FCA can alleviate the locally optimal solution problem and reduce the synchronization packet overhead， and it is excellent in energy efficiency when the synchronization topology meets the scene adaptability requirements of the above three scenarios.

Concerning the privacy disclosure in Social Networking Service (SNS), the usability of the privacy control in domestic SNS was studied. From the users' point of view, with the method of experiment and interview, usability testing and comparative analysis on the privacy control in Renren and Pengyou were handled. The result indicates that the privacy control in Pengyou is better than that in Renren, but there is no significant difference between the two sites. Both of them need some improvements. Renren needs to improve its centralized navigation of privacy control and the centralized privacy setting interface. Pengyou should improve its decentralized navigation of privacy control and the blacklist function.

A new method for solving the permutation problem in the frequency-domain Blind Source Separation (BSS) was presented. This new method divided the whole frequency-domain into three sections and applied different permutation algorithms to different sections. The neighboring frequency correlation and harmonic frequency correlation coefficient of signal amplitudes were used together for the low-frequency section, the direction of arrival estimation for speech sources for the mid-frequency section, and the combination of correlation coefficient comparison and direction estimation for the high-frequency section, respectively. Experimental results show that the new method provides a more robust and precise solution to the permutation problem than the algorithm only with interfrequency correlation coefficient of signal amplitudes or only with direction of arrival estimation for sources.