Characterising effective eLearning resources

The widespread availability of digital learning resources in a variety of media formats offers the possibility to make a profound difference in education. This potential has not been fully realised for range of interrelated reasons. In this paper we study the key characteristics of learning resources that have proved effective in changing learning and teaching, and relate them to existing frameworks for understanding resources. We outline the relationships between resources, their users, and the way they are used, and explore issues that influence practitioners in choosing a particular resource. Our study is based on a review of resources for e-learning and chemistry in post-compulsory education, undertaken for the UK Joint Information Systems Committees (JISC), as part of a wider study examining ‘The Effectiveness of Resources, Tools and Support Services used by Tutors in Designing and Delivering E-Learning Activities’.     

A Numerical Study of Diagonally Split Runge–Kutta Methods for PDEs with Discontinuities

Diagonally split Runge–Kutta (DSRK) time discretization methods are a class of implicit time-stepping schemes which offer both high-order convergence and a form of nonlinear stability known as unconditional contractivity. This combination is not possible within the classes of Runge–Kutta or linear multistep methods and therefore appears promising for the strong stability preserving (SSP) time-stepping community which is generally concerned with computing oscillation-free numerical solutions of PDEs. Using a variety of numerical test problems, we show that although second- and third-order unconditionally contractive DSRK methods do preserve the strong stability property for all time step-sizes, they suffer from order reduction at large step-sizes. Indeed, for time-steps larger than those typically chosen for explicit methods, these DSRK methods behave like first-order implicit methods. This is unfortunate, because it is precisely to allow a large time-step that we choose to use implicit methods. These results suggest that unconditionally contractive DSRK methods are limited in usefulness as they are unable to compete with either the first-order backward Euler method for large step-sizes or with Crank–Nicolson or high-order explicit SSP Runge–Kutta methods for smaller step-sizes. We also present stage order conditions for DSRK methods and show that the observed order reduction is associated with the necessarily low stage order of the unconditionally contractive DSRK methods. The work of C.B. Macdonald was partially supported by an NSERC Canada PGS-D scholarship, a grant from NSERC Canada, and a scholarship from the Pacific Institute for the Mathematical Sciences (PIMS). The work of S. Gottlieb was supported by AFOSR grant number FA9550-06-1-0255. The work of S.J. Ruuth was partially supported by a grant from NSERC Canada.     

Stability of linear multistep methods for delay integro-differential equations

This paper is concerned with the numerical solution of delay integro-differential equations. The adaptation of linear multistep methods is considered. The emphasis is on the linear stability of numerical methods. It is shown that every A-stable, strongly 0-stable linear multistep method of Pouzet type can preserve the delay-independent stability of the underlying linear systems. In addition, some delay-dependent stability conditions for the stability of numerical methods are also given.     

Over-Parameterized Variational Optical Flow

A novel optical flow estimation process based on a spatio-temporal model with varying coefficients multiplying a set of basis functions at each pixel is introduced. Previous optical flow estimation methodologies did not use such an over parameterized representation of the flow field as the problem is ill-posed even without introducing any additional parameters: Neighborhood based methods of the Lucas–Kanade type determine the flow at each pixel by constraining the flow to be described by a few parameters in small neighborhoods. Modern variational methods represent the optic flow directly via the flow field components at each pixel. The benefit of over-parametrization becomes evident in the smoothness term, which instead of directly penalizing for changes in the optic flow, accumulates a cost of deviating from the assumed optic flow model. Our proposed method is very general and the classical variational optical flow techniques are special cases of it, when used in conjunction with constant basis functions. Experimental results with the novel flow estimation process yield significant improvements with respect to the best results published so far.     

Nonparametric Bayesian Image Segmentation

Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model for histogram clustering which automatically determines the number of segments when spatial smoothness constraints on the class assignments are enforced by a Markov Random Field. A Dirichlet process prior controls the level of resolution which corresponds to the number of clusters in data with a unique cluster structure. The resulting posterior is efficiently sampled by a variant of a conjugate-case sampling algorithm for Dirichlet process mixture models. Experimental results are provided for real-world gray value images, synthetic aperture radar images and magnetic resonance imaging data.     

Motion Planning for Haptic Guidance

Haptic devices allow a user to feel either reaction forces from virtual interactions or reaction forces reflected from a remote site during a bilateral teleoperation task. Also, guiding forces can be exerted to train the user in the performance of a virtual task or to assist him/her to safely teleoperate a robot. The generation of guiding forces relies on the existence of a motion plan that provides the direction to be followed to reach the goal from any free configuration of the configuration space (-space). This paper proposes a method to obtain such a plan that interleaves a sampling-based exploration of -space with an efficient computation of harmonic functions. A deterministic sampling sequence (with a bias based on harmonic function values) is used to obtain a hierarchical cell decomposition model of -space. A harmonic function is iteratively computed over the partially known model using a novel approach. The harmonic function is the navigation function used as motion plan. The approach has been implemented in a planner (called the Kautham planner) that, given an initial and a goal configuration, provides: (a) a channel of cells connecting the cell that contains the initial configuration with the cell that contains the goal configuration; (b) two harmonic functions over the whole -space, one that guides motions towards the channel and another that guides motions within the channel towards the goal; and (c) a path computed over a roadmap built with the free samples of the channel. The harmonic functions and the solution path are then used to generate the guiding forces for the haptic device. The planning approach is illustrated with examples on 2D and 3D workspaces. This work was partially supported by the CICYT projects DPI2005-00112 and DPI2007-63665.     

浅谈硬盘保护机房中几种电子作业存储方法

目前学校公共机房的计算机,为了防止学生对系统的有意或无意的破坏,减少病毒对电脑的破坏,通常采用软件或硬件对硬盘数据进行保护,这是很有必要的,随之就带来了一个问题:一些连续性比较强的项目学习,以及平时的随堂练习中,学生需要保存一些文件,如何解决。笔者在日常机房管理中尝试了多种方法,该文将谈谈各种方法,以供大家参考。     

Photoshop创建选区的方法与技巧

创建选区是Photoshop中最基本,也是最重要的技法之一。该文归纳了Photoshop中选区的多种方法和思路,阐明了各种方法的优势和特点,探讨如何综合运用各种工具和命令,充分发挥各工具特点,从而快速精确的建立选区。     

从软件角度看学校机房的管理与维护

学校机房管理软件与维护软件是学校机房教师上课与学生实训的有力保障,其中包括多媒体电子教室软件、硬盘保护与网络克隆管理软件、学校机房综合管理软件和学生管理软件。     

电子阅览室的维护与管理

根据我校图书馆电子阅览室运行的实际情况及经验,阐述了电子阅览室的维护和管理方法。