高校教师在多媒体教学中的角色思考

多媒体教学已经成为高校重要的教学组织形式。目前多媒体教学中存在的诸多问题源于多媒体教学中的认识误区。解决这些问题的关键在于明确教师在多媒体教学中的主导地位。教师在高校多媒体教学中应发挥课程开发和设计者、教学资源和教学信息整合者、教学活动组织者、学生学习合作者、教学研究实践者等五个方面的作用。     

软件过程改进方法研究与实施

信息化作为军事变革的本质和核心,是高新武器装备发展的方向,而软件又是信息化武器装备的中枢神经。文章介绍了军用软件改进方法的研究与实施,从软件的实施规划、过程定义、试点实施、全面推广入手,从而提高了军用软件的质量。     

Communicating Is Crowdsourcing: Wi-Fi Indoor Localization with CSI-Based Speed Estimation

Numerous indoor localization techniques have been proposed recently to meet the intensive demand for location-based service (LBS). Among them, the most popular solutions are the Wi-Fi fingerprint-based approaches. The core challenge is to lower the cost of fingerprint site-survey. One of the trends is to collect the piecewise data from clients and establish the radio map in crowdsourcing manner. However the low participation rate blocks the practical use. In this work, we propose a passive crowdsourcing channel state information (CSI) based indoor localization scheme, C²IL. Despite a crowdsourcing based approach, our scheme is totally transparent to the client and the only requirement is to connect to our 802.11n access points (APs). C²IL is built upon an innovative method to accurately estimate the moving speed solely based on 802.11n CSI. Knowing the walking speed of a client and its surrounding APs, a graph matching algorithm is employed to extract the received signal strength (RSS) fingerprints and establish the fingerprint map. For localization phase, we design a trajectory clustering based localization algorithm to provide precise real-time indoor localization and tracking. We develop and deploy a practical working system of C²IL in a large office environment. Extensive evaluations indicate that the error of speed estimation is within 3%, and the localization error is within 2 m at 80% time in a very complex indoor environment.     

Ajax技术在教学论坛制作中的应用

当用户访问传统的ASP技术制作的论坛,并进行多种操作时,会多次重载页面或在不同页面间跳转。造成用户视觉上的不舒服以及花费较多的等待时间。采用Ajax技术可以很好的解决这样的问题,本文给出了用Ajax技术实现教学论坛部分功能的设计方法,使访问者获得更好的Web体验。     

实现兼类样本增量学习的一种算法

针对兼类样本,提出一种增量学习算法.利用超球支持向量机,在特征空间对属于同一类别的样本求得一个能包围该类尽可能多样本的最小超球,使各类样本之间通过超球隔开.增量学习过程中,只对新增样本以及与新增样本具有相同兼类的旧样本集中的支持向量进行训练,且每次训练只针对一类样本,使得算法在很小的样本集、很小的空间代价下实现兼类样本增量学习,同时保留了与新增样本类别无关的历史训练结果.分类过程中,通过计算待分类样本到各超球球心的距离判定其所属类别,分类准确快捷.实验结果证明了该算法的有效性.     

一种带有路由反射的BGP路由预测算法

由于路由反射器的影响,路由器可能只知道非常有限的到达外部目的地的路由的子集,BGP路径选择过程并不会形成一个确定的路径等级顺序,使得路径预测变得非常困难.给出了一种算法,该算法不需要对路由协议动态进行复杂的模拟,只需要静态的路由数据就可以计算出带有路由反射的路由选择结果,并在一个模拟的大型ISP上验证了预测算法的正确性.结果显示配置的改变可以引起路由表的变化.     

A short note on some properties of rough groups

It is a useful method in research of group theory to construct a new group by using known groups. Lower and upper approximation operators of rough sets are applied into group theory and so the notion of a rough group has been introduced. In this paper, we first point out that there are still some incomplete propositions in [N. Kuroki, P.P. Wang, The lower and upper approximations in a fuzzy group, Inform. Sci. 90 (1996) 203–220] although some authors have showed several incorrect statements in the literature. We then present improved versions of the incomplete propositions and continue to study the image and inverse image of rough approximations of a subgroup with respect to a homomorphism between two groups.     

A rough set approach to feature selection based on power set tree

Feature selection is viewed as an important preprocessing step for pattern recognition, machine learning and data mining. Traditional hill-climbing search approaches to feature selection have difficulties to find optimal reducts. And the current stochastic search strategies, such as GA, ACO and PSO, provide a more robust solution but at the expense of increased computational effort. It is necessary to investigate fast and effective search algorithms. Rough set theory provides a mathematical tool to discover data dependencies and reduce the number of features contained in a dataset by purely structural methods. In this paper, we define a structure called power set tree (PS-tree), which is an order tree representing the power set, and each possible reduct is mapped to a node of the tree. Then, we present a rough set approach to feature selection based on PS-tree. Two kinds of pruning rules for PS-tree are given. And two novel feature selection algorithms based on PS-tree are also given. Experiment results demonstrate that our algorithms are effective and efficient.