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.     

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.     

公交车站牌报站屏的设计

介绍了新型太阳能公交车站牌报站显示系统。该系统利用太阳能、LED显示和微控制技术,采用W78E58单片机作为系统的中央控制单元,可实现同一站牌不同路数公交车站点的静态显示、动态显示和定时显示控制。利用VB软件编程可实现PC机通信,通过RS232接口可对整个系统升级,提高了系统的可操作性。整个系统采用太阳能供电,蓄电池作为后备电源,可有效节约电能。     

Interpersonal perception in bulletin board systems among Chinese Internet users

A study investigating the accuracy of interpersonal perception in Internet Bulletin Board Systems (BBS) and the variables that affect the accuracy were conducted in two phases: in the phase one, 58 participants were selected from the BBS which was built on the Internet in advance. During the phase two, participants were requested to complete the Myers–Briggs Type Indicator (MBTI) to assess their personalities, and to choose another member in the BBS as their “target”. The assessment packets were then administered to the participants in the following order: the demographic and Internet use survey, the MBTI used by the judge to assess their target’s personality, and the relationship survey between judge and target. The results showed that 76.7% participants made the correct judgment on two to three out of four dimensions of the personality type. The correlation analysis indicated that the variables affected the accuracy were from four aspects: judge, target, relationship and similarity. The binary logistic regression analysis showed that the target’s personality, the judge’s education level, the similarity between them, the stereotypes and projection played important roles on the accuracy. Possibilities for future research on this issue are also briefly discussed.     

An adaptive and trustworthy software testing framework on the grid

Grid computing, which is characterized by large-scale sharing and collaboration of dynamic distributed resources has quickly become a mainstream technology in distributed computing and is changing the traditional way of software development. In this article, we present a grid-based software testing framework for unit and integration test, which takes advantage of the large-scale and cost-efficient computational grid resources to establish a testbed for supporting automated software test in complex software applications. Within this software testing framework, a dynamic bag-of-tasks model using swarm intelligence is developed to adaptively schedule unit test cases. Various high-confidence computing mechanisms, such as redundancy, intermediate value checks, verification code injection, and consistency checks are employed to verify the correctness of each test case execution on the grid. Grid workflow is used to coordinate various test units for integration test. Overall, we expect that the grid-based software testing framework can provide efficient and trustworthy services to significantly accelerate the testing process with large-scale software testing.

形态结构特征约束下的树木参数化建模研究

树木建模是构建虚拟森林景观的主要环节,也是三维林业地理信息系统的基础。该文提出一种形态结构特征约束下的树木参数化建模方法,通过引进Bezier曲线控制树干以及树枝形状,并以荔枝树和马尾松为例对该方法进行设计与实现。实验结果表明,该方法能有效提高树木建模过程中的交互能力,较好地突出了树木的形态结构特征。     

P2P系统中基于副本链的一致性维护算法

提出一种无结构纯P2P的副本一致性维护算法。利用副本节点发起的第一次更新消息在P2P网络中的广播,由其他收到消息的副本节点给出响应,构建副本链。副本链建立后,更新消息在副本节点间进行传播,不再在网络中洪泛。副本链的维护通过记录首次发起更新的副本节点IP地址完成。仿真试验证明该算法是简单有效的。