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’.     

基于J2EE的O/R(Object-Relation)映射方案研究

对象模型和关系模型是两种完全不同的模式,在开发中如何实现对象到关系的映射是一个关键的问题,分析了对象关系映射不匹配的各个方面,以及当前的各种持久化解决方案,并重点分析了透明对象关系映射的特点,最后对如何实现对象关系映射的关键技术进行了研究.     

一种空间自适应正则化MAP超分辨率重建算法

提出一种简单、通用的基于正则化技术的自适应MAP超分辨率重建算法。与以往算法不同,该方法引入了局部空间自适应正则化参数,弥补了传统算法对图像自身的局部特性缺乏考虑的不足。算法通过迭代的方式,利用中间重建结果不断对正则化参数进行更新,并最终得到重建图像。实验结果表明,该方法可以根据不同图像序列的特点以及图像的局部灰度特性,自适应地确定相应的正则化参数,并找到最优解,有效地保护了高分辨率图像的细节信息。     

基于DSP平台的激光二极管控制系统

介绍了以DSP芯片TMS320F2812为核心设计的控制平台、利用半导体制冷器和光功率传感器调节激光二极管工作温度和发射功率的控制系统;设计了具有良好性能的模拟通道,提出了针对特定调节对象的PID算法.结合优化设计的执行单元实现了很好的控制效果,有效地提高了激光二极管系统的稳定性和可靠性;设计的控制系统在环境温度-10℃～50℃时能够达到±0.03℃的控制精度.     

语义驱动的集成化产品建模

针对复杂产品研发过程中多领域协同对产品知识共享和重用的需求,提出一种语义驱动的集成化产品建模方法.结合多本体技术,给出了集成化产品建模框架,该框架由概念层和模型层构成,概念层包括高层核心产品本体和领域本体,模型层由主模型和领域模型等一族模型构成;同时还给出了集成化产品模型的形式化语义描述,在构建高层核心产品本体的基础上建立主模型;基于多领域本体,进行由概念层语义驱动的领域模型快速重构,在语义理解基础上实现跨领域的产品知识重用.     

Artificial convolution neural network techniques and applications for lung nodule detection

We have developed a double-matching method and an artificial visual neural network technique for lung nodule detection. This neural network technique is generally applicable to the recognition of medical image pattern in gray scale imaging. The structure of the artificial neural net is a simplified network structure of human vision. The fundamental operation of the artificial neural network is local two-dimensional convolution rather than full connection with weighted multiplication. Weighting coefficients of the convolution kernels are formed by the neural network through backpropagated training. In addition, we modeled radiologists' reading procedures in order to instruct the artificial neural network to recognize the image patterns predefined and those of interest to experts in radiology. We have tested this method for lung nodule detection. The performance studies have shown the potential use of this technique in a clinical setting. This program first performed an initial nodule search with high sensitivity in detecting round objects using a sphere template double-matching technique. The artificial convolution neural network acted as a final classifier to determine whether the suspected image block contains a lung nodule. The total processing time for the automatic detection of lung nodules using both prescan and convolution neural network evaluation was about 15 seconds in a DEC Alpha workstation.     

The design of the TEI encoding scheme

This paper discusses the basic design of the encoding scheme described by the Text Encoding Initiative'sGuidelines for Electronic Text Encoding and Interchange (TEI document number TEI P3, hereafter simplyP3 orthe Guidelines). It first reviews the basic design goals of the TEI project and their development during the course of the project. Next, it outlines some basic notions relevant for the design of any markup language and uses those notions to describe the basic structure of the TEI encoding scheme. It also describes briefly the core tag set defined in chapter 6 of P3, and the default text structure defined in chapter 7 of that work. The final section of the paper attempts an evaluation of P3 in the light of its original design goals, and outlines areas in which further work is still needed.C. M. Sperberg-McQueen is a Senior Research Programmer at the academic computer center of the University of Illinois at Chicago; his interests include medieval Germanic languages and literatures and the theory of electronic text markup. Since 1988 he has been editor in chief of the ACH/ACL/ALLC Text Encoding Initiative. Lou Burnard is Director of the Oxford Text Archive at Oxford University Computing Services, with interests in electronic text and database technology. He is European Editor of the Text Encoding Initiative's Guidelines.     

基于CSAPSO-BP神经网络的光纤陀螺温度补偿研究

光纤陀螺是惯导系统的重要组成器件,环境温度变化会造成光纤陀螺的零偏发生漂移,从而降低测量精度。运用传统的BP神经网络进行预测易陷入局部极小值,导致补偿失败。该文采用混沌模拟退火粒子群BP神经网络的光纤陀螺零偏温度补偿模型,优化了网络参数。通过在-40～60℃的升降温实验对模型进行验证,实验结果表明,该温度补偿模型的零偏稳定性比补偿前约有70%的精度提升,与以往BP模型相比,其预测性能和补偿效果更好。     

Functional 2D Phases in Mixed Dimensional Perovskite Photovoltaics

Organic-inorganic hybrid perovskite solar cells (PSCs) with unique properties exhibit their powerful competitiveness in the photovoltaic field over the past few years. However, the challenges of stability for perovskite devices limit the commercialization and further development. The 2D/3D hybrid structures combine the superior efficiency of bulk perovskites and the superior stability of layered perovskites and gradually get hotspots of the photovoltaic field. In addition, there remains a lack of comprehensive understanding and systematic summary of the function of 2D perovskite attributed to the complex nature of 2D/3D structures. Here, the latest progress of 2D/3D hybrid structures and focus on the functionality of 2D phases in mixed structures and the underlying mechanism from the perspective of their different distributions in the perovskite layer is summarized. Then, the insight and vital factors for overall improvements in the stability of 2D/3D structures are thoroughly discussed. Finally, it is expected that this review will contribute to the present challenges and future research prospects in the photovoltaic industry.