Xuan Shen

Bio: Xuan Shen is an academic researcher from Nanjing University of Posts and Telecommunications. The author has contributed to research in topics: Tuple & Ranking SVM. The author has co-authored 3 publications.

A ranking algorithm based on contents and non-key attributes for object-level keyword search over relational databases

Abstract: Keyword search technique over relational databases is a research hot-spot in database field. At present, there have been many ranking correlation algorithms for object-level keyword search over relational databases. Object-level keyword search can better integrate information scattered in various tuples. OCS(Object-level Correction Sort) algorithm cannot rank results in keyword search accurately as was expected. This paper foucuses on the problems of ranking results in keyword search system for object-level over relational databases and proposes a new ranking algorithm SOCA(Sort of Correction Algorithm) which takes into consideration the content information of key attributes, and the correlation of non-key attributes. We use Weight to evaluate the content information of key attributes, and Correlation to assess the correlation of non-key attributes Finally, we give a score function about contents Correlation and Weight. Experiments demonstrate that this algorithm can effectively rank results and verify its reasonableness and effectiveness.

Study on object transaction based on networked RFID systems

Abstract: Radio Frequency IDentification(RFID) is a novel technology of automated identification. The use of RFID, however, raises great concerns due to the serious security issue. In this paper, we at first propose a Secure Transaction Frame(STF) and a flow of object transaction based on networked RFID systems. Then, it is worth mentioning that the authentication technology in Secure Transaction Frame(STF) is able to verify the ownership of electric tags in order to deal with common attacks in the networked RFID system. Meanwhile, this paper presents an encryption scheme to protect the information stored in electric tags from being illegally used. After collecting relevant statistics and analyzing cases based on networked RFID systems, this paper also researches the mass requests for the information stored in the electric tags by the reader and eventually, gives a cache mechanism to solve that problem.

Perfect power visualization-performance optimization with Java

Abstract: Visualization is critical in power systems engineering since the gigantic amount of data generated by power systems is difficult, and at times impossible, to be analyzed numerically. Therefore, the need for powerful visualization software has been increasingly acute due to the growth in size of power system models. To improve PPV's performance in order to accompany larger systems, this paper focuses on the development of PPV (Perfect Power Visualization), a 2-D power system visualization software program that processes and converts numerical data to graphic symbols based on their types, positions and states. The goal of PPV is to let operators visualize and interact with large-scale power systems in a consumer lever personal computer in real time. Also, it was optimized again with smarter data management systems, refinement of overall structure, and a newer platform that enables GPU acceleration, all of which further increased the performance of PPV by a factor of ten times that of its initial capabilities.