Time-Ordered Collaborative Filtering for News Recommendation

Faced with hundreds of thousands of news articles in the news websites,it is difficult for users to find the news articles they are interested in.Therefore,various news recommender systems were built.In the news recommendation,these news articles read by a user is typically in the form of a time sequence.However,traditional news recommendation algorithms rarely consider the time sequence characteristic of user browsing behaviors.Therefore,the performance of traditional news recommendation algorithms is not good enough in predicting the next news article which a user will read.To solve this problem,this paper proposes a time-ordered collaborative filtering recommendation algorithm(TOCF),which takes the time sequence characteristic of user behaviors into account.Besides,a new method to compute the similarity among different users,named time-dependent similarity,is proposed.To demonstrate the efficiency of our solution,extensive experiments are conducted along with detailed performance analysis.

A novel denoising method for infrared image based on bilateral filtering and non-local means

This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used to effectively preserve the edge and detail of the image. And compared with classical methods, bilateral filtering method has a better performance in denosing for the reason that the weight includes the geometric closeness factor and the intensity similarity factor. We combine the geometric closeness factor with the weight of non-local means, and construct a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.

Rapid discovery and identification of 68 compounds in the active fraction from Xiao-Xu-Ming decoction(XXMD) by HPLC-HRMS and MTSF technique

Xiao-Xu-Ming decoction（XXMD） was a traditional Chinese prescription and first recorded in ＂Bei Ji Qian Jin Yao Fang＂.It has been widely used to treat theoplegia and the sequel of theoplegia in China.In the present work,high-performance liquid chromatography coupled with high resolution mass spectrometry（HPLC-HRMS） combined with the mass spectral tree similarity filter technique（MTSF）was used to rapidly discover and identify the compounds of the active fraction of XXMD.A total of 3362 compounds were automatically detected by HPLC-HRMS,and final 68 compounds were identified in the active fraction of XXMD.including 14 templated compounds（reference compounds）,50 related compounds fished by MTSF technique,and 4 unrelated compounds identified by manual method.This study successfully applied MTSF technology for the first time to discover and identify the components of Chinese prescription.The results demonstrated that MTSF technique should be useful to the discovery and identification of compounds in Chinese prescription.This study also proved that MTSF can be applied to the targeted phytochemical separation.

LPC parameters substitution for speech information hiding

Information hiding techniques adopted in secret communication should meet the requirements of high hiding capacity,real-time and high robustness.For the purpose of real-time speech secure communication,an information hiding algorithm based on the analysis-by-synthesis（ABS） speech coding scheme is presented in this article.This algorithm substitutes secret speech data bits for linear predictive coefficients（LPCs） in linear predictive coding（LPC）.Statistics show that the change of voiced signal track is slow and the codebook for LPCs vector is large in ABS coding scheme.Therefore,a new concept,filter similarity,is proposed to determine the LPC parameters for substituting with secret speech information,and to generate multi-codebook for saving storage space to store secret speech information.To achieve the best effects of information hiding,a dynamic threshold is built to make an optimal trade-off among hiding-capacity,security,robustness,transparence and real time.Experiments show that the proposed approach meets the requirements of information hiding and secret communication speech quality.The test results indicate that this approach reaches high hiding capacity with an excellent speech quality and complicating speakers＇ recognition.