Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs’ platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs’ platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.     

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

一种可替代漂珠的低密度材料

漂珠低密度水泥浆由于密度低、强度高、体系稳定而在油田低压易漏层及低压油气层长封固段固井作业中获得了广泛的应用。但近年来,由于漂珠的产量越来越少,油田低成本要求急需开发代替漂珠的新型减轻材料,以满足配制低密度水泥浆的需求。开发了BCL-10S低密度混合减轻材料,其物化性能与漂珠相当,用它作减轻剂配制的低密度水泥浆性能与用漂珠作减轻剂配制的低密度水泥浆性能相媲美,并已经在长庆油田获得了应用。     

湘中海相浅层湘冷1井酸压工艺研究及应用

湘冷1井具有气层埋藏浅（400m-500m）、纵向上裂隙发育的特点，属低孔、低渗的含泥质灰岩致密储层。大量室内实验和研究采用“前置液酸压＋闭合酸化”工艺技术，并优选了相应降阻酸和闭合酸配方。通过酸压实现了该井工业油气流的突破，取得了明显的增产效果，为新区海相浅层气的开发探索出了一套成熟的改造增产措施。     

Performance and Commercial Application of the Promoter LCC-A for Maximization of Propylene Yield

1 Introduction Propylene as an important feedstock for organic chemicals is mainly originated from steam cracking and catalytic cracking processes. During the FCC process the propylene content varies with the FCC catalyst and process technology adopted, resulting in significant difference in propylene concentration in the cracked product——LPG. The conventional FCC pro- cess generally gives a propylene yield of around 4%, while the FCC process with maximization of propylene yield can in…     

Sheldon Cohen: Award for Distinguished Scientific Contributions.

Provides the biography of Sheldon Cohen and announces that he has received the APA Award for Distinguished Scientific Contributions (2004) for his elegant research in psychoneuroimmunology. The award citation and a selected bibliography are also provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Cd-ZSM-5沸石催化剂的制备、表征和芳构化催化性能

采用离子交换、浸渍和混合三种方法制备镉改性ZSM-5沸石催化剂,考察了改性方法和镉含量对催化剂的表面酸性和Cd状态以及芳构化性能的影响。结果表明,加入镉降低了B酸性,Cd~(2+)与沸石结合形成了L_(1612)酸中心,其生成量取决于改性方法和Cd含量,并与芳构化活性提高有直接关系。     

相干源二维波达方向估计

本文分析了平面阵接收信号的协方差矩阵，发现它可分解为一个广义对称矩阵与一个非广义对称矩阵之和，利用信号协方差矩阵的这一结构特征，重点研究了相干源二维波达方向（DOA）估计．该方法通过构造一个差矩阵，求出其本特征值对应的任一特征向量，利用谱函数估计相干源二维DOA．简要分析了二维DOA估计的分维处理。     

A formal description of open distributed processing (ODP) trading based on guidelines for the definition of managed objects (GDMO)

New requirements of growing computer networks and information systems have an influence on extended client/server models with increased functionality. This forms the basis for service management in distributed systems which is realized by a service trading concept. This paper studies the requirements derived from the Open Distributed Processing (ODP) Reference Model in order to consider an open service market. Furthermore, it examines management possibilities for describing the service trading scenario. Because of similar architectures and properties ODP services, service offers, types, exporters and traders are mapped onto management components and modeled as managed objects. Therefore, the Guidelines for the Definition of Managed Objects (GDMO) are used. The final concept allows a precise and unambiguous study of the service trading scenario and provides means for exporting and importing of service offers in a distributed environment.