谈医院计算机网络信息资源的应用与管理

医院计算机网络信息资源在社会发展中正日益占据主导地位,只有对医院计算机网络信息资源进行有效的管理,才能将网络信息环境变为有序的信息空间,实现信息资源效用最大化,发挥它的最大潜能.     

论多媒体教学的特点及其在教学实践中的应用

随着科技的进步,计算机网络技术也在不断发展.伴随着教学改革的深入和办学条件的优化,多媒体教学作为一种新的教学手段被广泛应用于各个学校的教学活动中.多媒体教学技术是一种建立在计算机网络技术上的现代化教学手段,已经取代了传统的黑板粉笔式的手工教学,这对增强学生的学习兴趣,以及提高教师教学效率方面有着积极的推动作用.     

基于ZigBee协议的无线传感网路及应用

无线传感网络因其巨大的应用前景,已经引起了学术界的高度关注,成为科学界研究的热点问题之一。本文先对无线传感网路进行基本概述,接着介绍了ZigBee协议,最后以家用自动化的实例描述了基于ZigBee协议的无线传感网路及应用。     

计算机信息采集和编辑之图形图像初探

计算机的应用越来越被广泛的使用,有关计算机领域中各种作图软件也发展的十分快速,关于图形图像技术有着全面的知识理论,本文介绍了图形图像的有关初级内容和使用技巧.     

基于EDA的单片机实验教学改革的研究与应用

本文根据单片机原理与接口理论和实验教学的经验与研究,分析了目前这门课程实验教学的特点和存在的问题,提出将EDA仿真技术应用于实验教学的先进教学方法,可以大大提高学习积极性和总体能力。     

电力负荷特性在线记录系统软件设计

提出了一种基于电铁牵引变电站电力负荷特性在线记录系统的软件设计方案,以提供电力系统负荷建模所需的数据。系统以PC机进行后台数据处理并上传数据记录,可以对电铁牵引变电站双变压器并列运行实现全时间点状态监测和负荷特性记录,具有存储容量大、功能齐全、调试简便、开发周期短、测量精度高等优点。通过仿真和实际测试证明,开发工作是成功的,该系统能够满足电力系统负荷特性数据采集的要求。     

New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

Optimal models for single-period supply chain problems with fuzzy demand

The aim of this paper is to develop an optimal technique for dealing with the fuzziness aspect of demand uncertainties. Triangular fuzzy numbers are used to model external demand, and decision models in both non-coordination and coordination situations are constructed. It is shown that in the decision models there exists a unique solution that can be expressed analytically. Based on the closed form solutions for both models, the behaviors and relationships of both the manufacturer and the retailer are quantitatively analyzed, and a cooperative policy for the optimization of the whole supply chain is put forward.     

Using local transition probability models in Markov random fields for forest change detection

Change detection based on the comparison of independently classified images (i.e. post-classification comparison) is well-known to be negatively affected by classification errors of individual maps. Incorporating spatial-temporal contextual information in the classification helps to reduce the classification errors, thus improving change detection results. In this paper, spatial-temporal Markov Random Fields (MRF) models were used to integrate spatial-temporal information with spectral information for multi-temporal classification in an attempt to mitigate the impacts of classification errors on change detection. One important component in spatial-temporal MRF models is the specification of transition probabilities. Traditionally, a global transition probability model is used that assumes spatial stationarity of transition probabilities across an image scene, which may be invalid if areas have varying transition probabilities. By relaxing the stationarity assumption, we developed two local transition probability models to make the transition model locally adaptive to spatially varying transition probabilities. The first model called locally adjusted global transition model adapts to the local variation by multiplying a pixel-wise probability of change with the global transition model. The second model called pixel-wise transition model was developed as a fully local model based on the estimation of the pixel-wise joint probabilities. When applied to the forest change detection in Paraguay, the two local models showed significant improvements in the accuracy of identifying the change from forest to non-forest compared with traditional models. This indicates that the local transition probability models can present temporal information more accurately in change detection algorithms based on spatial-temporal classification of multi-temporal images. The comparison between the two local transition models showed that the fully local model better captured the spatial heterogeneity of the transition probabilities and achieved more stable and consistent results over different regions of a large image scene.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.