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.     

A synergistic strategy for combining thesaurus-based and corpus-based approaches in building ontology for multilingual search engines

In this article we illustrate a methodology for building cross-language search engine. A synergistic approach between thesaurus-based approach and corpus-based approach is proposed. First, a bilingual ontology thesaurus is designed with respect to two languages: English and Spanish, where a simple bilingual listing of terms, phrases, concepts, and subconcepts is built. Second, term vector translation is used – a statistical multilingual text retrieval techniques that maps statistical information about term use between languages (Ontology co-learning). These techniques map sets of t f id f term weights from one language to another. We also applied a query translation method to retrieve multilingual documents with an expansion technique for phrasal translation. Finally, we present our findings.     

复合材料空心飞轮多环套装整体变形及应力简化精细分析

采用多环过盈装配是解决复合材料飞轮径向强度过低的有效途径之一。本文作者采用平面应力简化模型,提出了计及过盈配合后变形导致实际过盈量增大计算飞轮套装后的初终应力分布的方法;提出了基于叠加原理计算多环过盈装配旋转飞轮应力的方法;提出了保证飞轮旋转时配合界面不脱离的相关临界转速的概念和计算方法。算例分析表明:过盈配合后的变形对初终应力的影响不能忽略;过盈量和套装环数与飞轮的初终应力和相关临界转速有密切的关系。     

Moving Least-Squares Differential Quadrature Method for Free Vibration of Antisymmetric Laminates

In this paper, the moving least-squares differential quadrature (MLSDQ) method is employed for free vibration of thick antisymmetric laminates based on the first-order shear deformation theory. The generalized displacements of the laminates are independently approximated with the centered moving least-squares (MLS) technique within each domain of influence. The MLS nodal shape functions and their partial derivatives are computed quickly through back-substitutions after only one LU decomposition. Subsequently, the weighting coefficients in the MLSDQ discretization are determined with the nodal partial derivatives of the MLS shape functions. The MLSDQ method combines the merits of both the differential quadrature and meshless methods which can be conveniently applied to complex domains and irregular discretizations without loss of implementation efficiency and numerical accuracy. The natural frequencies of the laminates with various edge conditions, ply angles, and shapes are calculated and compared with the existing solutions to study the numerical accuracy and stability of the MLSDQ method. Effects of support size, order of completeness of basis functions, and node irregularity on the numerical accuracy are investigated in detail.     

A Neural Network Approach for Signal Detection in Digital Communications

In this paper, we propose a new approach for signal detection in wireless digital communications based on the neural network with transient chaos and time-varying gain (NNTCTG), and give a concrete model of the signal detector after appropriate transformations and mappings. It is well known that the problem of the maximum likelihood signal detection can be described as a complex optimization problem that has so many local optima that conventional Hopfield-type neural networks fail to solve. By refraining from the serious local optima problem of Hopfield-type neural networks, the NNTCTG makes use of the time-varying parameters of the recurrent neural network to control the evolving behavior of the network so that the network undergoes the transition from chaotic behavior to gradient convergence. It has richer and more flexible dynamics rather than conventional neural networks only with point attractors, so that it can be expected to have much ability to search for globally optimal or near-optimal solutions. After going through a transiently inverse-bifurcation process, the NNTCTG can approach the global optimum or the neighborhood of global optimum of our problem. Simulation experiments have been performed to show the effectiveness and validation of the proposed neural network based method for the signal detection in digital communications.     

Set－up of a Pure Electron Plasma Device

An electron Penning-Malmberg trap,which can confine an electron column and provide a good platform to investigate the cross-filed transportation of strongly magnetized electron plasma ,has been set up.With the device,an electron plasma with a density of 10^7 cm^-3 can be confined for a relatively long time.The structure of the trap,electron source,as well as the way how th measure electron plasma density profile and velocity distrbustion are introduced in detail.     

A new colloidal precursor cooperative conversion route to nanocrystalline quaternary copper sulfide

A novel milk-like Cu-thiourea colloid has been synthesized. Nanocrystalline quaternary copper sulfide Cu₂FeSnS₄ was obtained through the Cu-thiourea colloidal precursor cooperative conversion route at low temperature. The samples were characterized by means of X-ray powder diffraction, transmission electron microscopy, scanning electron microscopy, inductively coupled plasma atomic emission spectroscopy, and X-ray energy dispersive spectroscopy techniques. The reaction details and features were described and discussed.     

Analysis of dispersion characteristics for a circular dielectric waveguide with periodic metallic strips by using the method of lines

The dispersion characteristics of circular dielectric waveguide with periodic metallic strips are analyzed by the method of lines. The filter property of the metallic strip loaded structure is carefully investigated for both TE and TM modes. The brillioum diagrams for both TE₀₁ and TM₀₁ modes are given. A comparison is made between the results obtained by Galerkin's method and those calculated with the method of lines, and very good agreement has been found; the accuracy of the present method is thus justified. On the basis of the analysis, some useful guidelines for the design of the bandreject filters are suggested.     

Formation of mushroom-like ZnO microcrystals through a solution calcination process

Mushroom-like ZnO microcrystals have been prepared via a solution calcination route, using Zn(NO₃)₂ as Zn source in the absence of any surfactants, templates or catalysts. This is the first example to prepare mushroom-like crystals as semiconductors, which are expected to show particular physical properties. The ZnO products were investigated by X-ray powder diffraction (XRD), scanning electron microscopy (SEM), Raman spectroscopy and photoluminescence (PL) spectrum measurements. A suitable concentration of Zn(NO₃)₂ solution was important for the growth of the mushroom-like products. The reported synthetic procedure is straightforward and inexpensive, and thus can be readily adopted to produce large quantities of mushroom-like ZnO microcrystals.