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Methods of organization of SCORM-compliant teaching materials in electronic format  [cached]
Jacek Marciniak
EduAction : Electronic Education Magazine , 2012,
Abstract: This paper presents a method of organizing electronic teaching materials based on their role in the teaching process rather than their technical structure. Our method allows SCORM materials stored as e-learning courses ( electronic books”) to be subdivided and structured so that content can be used in multiple contexts. As a standard, SCORM defines rules for organizing content, but not how to divide and structure it. Our method uses UCTS nomenclature to divide content, define relationships between content entities, and aggregate those entities into courses. This allows content to be shared in different implementations of SCORM while guaranteeing that usability and consistency are maintained.
Realization of content packaging maker conforming SCORM

计算机系统应用 , 2007,
Abstract: SCORM规范是当前网络教育标准化规范中的一个重要标准,本文通过对SCORM规范中的内容包装规范和内容包装实践指南进行剖析,利用XML技术,开发了内容包制作工具,跟RELOAD EDITOR工具相比较,具有操作简单的特点.
stam – a Bioconductor compliant R package for structured analysis of microarray data
Claudio Lottaz, Rainer Spang
BMC Bioinformatics , 2005, DOI: 10.1186/1471-2105-6-211
Abstract: We present a computational tool for semi-supervised molecular disease entity detection. It automatically discovers molecular heterogeneities in phenotypically defined disease entities and suggests alternative molecular sub-entities of clinical phenotypes. This is done using both gene expression data and functional gene annotations.We provide stam, a Bioconductor compliant software package for the statistical programming environment R. We demonstrate that our tool detects gene expression patterns, which are characteristic for only a subset of patients from an established disease entity. We call such expression patterns molecular symptoms. Furthermore, stam finds novel sub-group stratifications of patients according to the absence or presence of molecular symptoms.Our software is easy to install and can be applied to a wide range of datasets. It provides the potential to reveal so far indistinguishable patient sub-groups of clinical relevance.Microarray analysis is among the most promising clinical applications of modern genomics. It opens perspectives for more reliable and efficient diagnosis of established tumor entities [1,2], risk group determination [3,4], and the prediction of response to treatment [5]. In the supervised setting, various software tools implementing algorithms from statistical learning theory are available and have been evaluated in the context of microarray data (e.g. [6-10]).All these methods aim for reproducing or predicting predefined clinical phenotypes. However, often clinical phenotypes will not be homogeneous from a molecular point of view. For example, when distinguishing between recurrent and non-recurrent disease, it is of course possible that recurrence has various molecular backgrounds. If this is the case, one will expect different molecular changes in different patients, and purely supervised analysis is unsatisfactory.In several studies, unsupervised clustering algorithms have been applied to patient profiles, with the aim to defi
Cross-species and cross-platform gene expression studies with the Bioconductor-compliant R package 'annotationTools'
Alexandre Kuhn, Ruth Luthi-Carter, Mauro Delorenzi
BMC Bioinformatics , 2008, DOI: 10.1186/1471-2105-9-26
Abstract: Cross-platform and cross-species analyses require matching probes on different microarray formats. This can be achieved using the information in microarray annotations and additional molecular biology databases, such as orthology databases. Although annotations and other biological information are stored using modern database models (e.g. relational), they are very often distributed and shared as tables in text files, i.e. flat file databases. This common flat database format thus provides a simple and robust solution to flexibly integrate various sources of information and a basis for the combined analysis of heterogeneous gene expression profiles.We provide annotationTools, a Bioconductor-compliant R package to annotate microarray experiments and integrate heterogeneous gene expression profiles using annotation and other molecular biology information available as flat file databases. First, annotationTools contains a specialized set of functions for mining this widely used database format in a systematic manner. It thus offers a straightforward solution for annotating microarray experiments. Second, building on these basic functions and relying on the combination of information from several databases, it provides tools to easily perform cross-species analyses of gene expression data.Here, we present two example applications of annotationTools that are of direct relevance for the analysis of heterogeneous gene expression profiles, namely a cross-platform mapping of probes and a cross-species mapping of orthologous probes using different orthology databases. We also show how to perform an explorative comparison of disease-related transcriptional changes in human patients and in a genetic mouse model.The R package annotationTools provides a simple solution to handle microarray annotation and orthology tables, as well as other flat molecular biology databases. Thereby, it allows easy integration and analysis of heterogeneous microarray experiments across different tec
SDLS: a Matlab package for solving conic least-squares problems  [PDF]
Didier Henrion,Jerome Malick
Mathematics , 2007,
Abstract: This document is an introduction to the Matlab package SDLS (Semi-Definite Least-Squares) for solving least-squares problems over convex symmetric cones. The package is shortly presented through the addressed problem, a sketch of the implemented algorithm, the syntax and calling sequences, a simple numerical example and some more advanced features. The implemented method consists in solving the dual problem with a quasi-Newton algorithm. We note that SDLS is not the most competitive implementation of this algorithm: efficient, robust, commercial implementations are available (contact the authors). Our main goal with this Matlab SDLS package is to provide a simple, user-friendly software for solving and experimenting with semidefinite least-squares problems. Up to our knowledge, no such freeware exists at this date.
Solving Differential Equations in R: Package deSolve  [PDF]
Karline Soetaert,Thomas Petzoldt,R. Woodrow Setzer
Journal of Statistical Software , 2010,
Abstract: In this paper we present the R package deSolve to solve initial value problems (IVP) written as ordinary differential equations (ODE), differential algebraic equations (DAE) of index 0 or 1 and partial differential equations (PDE), the latter solved using the method of lines approach. The differential equations can be represented in R code or as compiled code. In the latter case, R is used as a tool to trigger the integration and post-process the results, which facilitates model development and application, whilst the compiled code significantly increases simulation speed. The methods implemented are efficient, robust, and well documented public-domain Fortran routines. They include four integrators from the ODEPACK package (LSODE, LSODES, LSODA, LSODAR), DVODE and DASPK2.0. In addition, a suite of Runge-Kutta integrators and special-purpose solvers to efficiently integrate 1-, 2- and 3-dimensional partial differential equations are available. The routines solve both stiff and non-stiff systems, and include many options, e.g., to deal in an efficient way with the sparsity of the Jacobian matrix, or finding the root of equations. In this article, our objectives are threefold: (1) to demonstrate the potential of using R for dynamic modeling, (2) to highlight typical uses of the different methods implemented and (3) to compare the performance of models specified in R code and in compiled code for a number of test cases. These comparisons demonstrate that, if the use of loops is avoided, R code can efficiently integrate problems comprising several thousands of state variables. Nevertheless, the same problem may be solved from 2 to more than 50 times faster by using compiled code compared to an implementation using only R code. Still, amongst the benefits of R are a more flexible and interactive implementation, better readability of the code, and access to R’s high-level procedures. deSolve is the successor of package odesolve which will be deprecated in the future; it is free software and distributed under the GNU General Public License, as part of the R software project.
Mobility of the compliant joints and compliant mechanisms
Pavlovi? Nenad T.,Pavlovi? Nenad D.
Theoretical and Applied Mechanics , 2005, DOI: 10.2298/tam0504341p
Abstract: This paper deals with a mobility of the single compliant joints and entire compliant mechanisms. The compliance of the joints and the mobility of the compliant mechanism can be increased by variations of geometry as well as material type of the joints. Therefore the mobility of three kinds of compliant joints with different geometrical shapes (beam joints, film joints and notch joints) will be researched. The mobility of the compliant joints made of different material types (plastic joints, silicone joints) will be also researched. The mobility of compliant mechanisms will be analyzed by using of the Roberts-Tchebicheff mechanism which coupler point can be guided on an approximately rectilinear path.
BB: An R Package for Solving a Large System of Nonlinear Equations and for Optimizing a High-Dimensional Nonlinear Objective Function  [PDF]
Ravi Varadhan,Paul Gilbert
Journal of Statistical Software , 2009,
Abstract: We discuss R package BB, in particular, its capabilities for solving a nonlinear system of equations. The function BBsolve in BB can be used for this purpose. We demonstrate the utility of these functions for solving: (a) large systems of nonlinear equations, (b) smooth, nonlinear estimating equations in statistical modeling, and (c) non-smooth estimating equations arising in rank-based regression modeling of censored failure time data. The function BBoptim can be used to solve smooth, box-constrained optimization problems. A main strength of BB is that, due to its low memory and storage requirements, it is ideally suited for solving high-dimensional problems with thousands of variables.
基于scorm标准的学习门户研究  [PDF]
武汉理工大学学报 , 2007,
Abstract: ?从基于xml为基础的scorm(sharablecontentobjectreferencemodel)出发,着重研究了scorm1.2的内容聚合模型及运行环境的技术细节,以及学习门户系统对此的支持。在探讨ibmworkplacecollaborativelearning系统架构及内容发布模型的基础上,给出了应用实例,进一步说明课件标准对课件制作及学习平台本身的重要性。
T-SCORM: An Extension of the SCORM Standard to Support the Project of Educational Contents for t-Learning  [PDF]
Francisco Miguel da Silva, Francisco Milton Mendes Neto, Aquiles Medeiros Filgueira Burlamaqui, Diogo Henrique Duarte Bezerra
Creative Education (CE) , 2012, DOI: 10.4236/ce.2012.31017
Abstract: The Interactive Digital Television (iDTV) has facilitated and expanded the communication and interaction in activities of knowledge acquisitions, entertainment and recreation in Distance Learning field. This new way of teaching and learning has been called t-Learning. In this context, the Learning Objects (LOs) have an important role to assist in the electronic courses’ development. Due the fast progress of e-Learning, some efforts to standardization have appeared in order to enable the reusability of educational contents and interoperability among systems, and one of these standards is the Sharable Content Object Reference Model (SCORM). Therefore, the main goal of this work is to present an extension of SCORM aiming to adapt it in order to improve the search and navigation of LOs with educational content for t-Learning. That will be done through an authoring tool named T-SCORM ADAPTER, which will be able to apply this extension in a fast and efficient way.
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