Continuously Performing the Consultation and Social Service Roles of Human Rights Bases

The Ministry of Education and the State Council Information Office have named Renmin University of China as one of the human rights national education and training bases. This shows the full affirmation and trust in the university＇s education, research and training work and also represents encouragement for its future work.

Development of slope mass rating system using K-means and fuzzy c-means clustering algorithms

Classification systems such as Slope Mass Rating(SMR) are currently being used to undertake slope stability analysis. In SMR classification system, data is allocated to certain classes based on linguistic and experience-based criteria. In order to eliminate linguistic criteria resulted from experience-based judgments and account for uncertainties in determining class boundaries developed by SMR system,the system classification results were corrected using two clustering algorithms, namely K-means and fuzzy c-means(FCM), for the ratings obtained via continuous and discrete functions. By applying clustering algorithms in SMR classification system, no in-advance experience-based judgment was made on the number of extracted classes in this system, and it was only after all steps of the clustering algorithms were accomplished that new classification scheme was proposed for SMR system under different failure modes based on the ratings obtained via continuous and discrete functions. The results of this study showed that, engineers can achieve more reliable and objective evaluations over slope stability by using SMR system based on the ratings calculated via continuous and discrete functions.

An efficient sensitivity analysis for energy performance of building envelope: A continuous derivative based approach

Within the framework of building energy assessment,this article proposes to use a derivative based sensitivity analysis of heat transfer models in a building envelope.Two,global and local,estimators are obtained at low computational cost,to evaluate the influence of the parameters on the model outputs.Ranking of these estimators values allows to reduce the number of model unknown parameters by excluding non-significant parameters.A comparison with variance and regression-based methods is carried out and the results highlight the satisfactory accuracy of the continuous-based approach.Moreover,for the carried investigations the approach is 100 times faster compared to the variance-based methods.A case study applies the method to a real-world building wall.The sensitivity of the thermal loads to local or global variations of the wall thermal properties is investigated.Additionally,a case study of wall with window is analyzed.

A study on continuous Chinese speech recognition based on stochastic trajectory models

After pointed the unreasonableness of the three basic assumptions contained in HMM, we introduce the theory and the advantage of Stochastic najectory Models (STMs) that possibly resolve these problems caused by HMM assumptions. In STM, the acoustic observations of an acoustic unit are represented as clusters of trajectories in a parameter space.The trajectories are modelled by mixture of probability density functions of random sequence of states. After analyzing the characteristics of Chinese speech, the acoustic units for continuous Chinese speech recognition based on STM are discussed and phone-like units are suggested. The performance of continuous Chinese speech recognition based on STM is studied on VINICS system. The experimental results prove the efficiency of STM and the consistency of phone-like units.

NOT A MILITARY ALLIANCE——The SCO should continue to implement its founding principles,based on security and economic cooperation,rather than expanding its membership

In reinventing itself, the Shanghai Cooperation Organization should stick to being a regional cooperative organization guided by a new concept and prioritizing security and economic cooperation. Meanwhile, brash expansion of the organization will cause a lot of problems.