基于BPNN局部位移场拟合的心脏形变计算模型

加标记的心脏核磁共振图像（tagged MRI）提供了一种非介入性的方法来跟踪心肌组织的运动,通过对MRI中tag线的分割可以获得在心动周期不同时刻的多帧稀疏的tag线位移信息．如何借助这些信息近似恢复整个心脏的运动是一个具有挑战性的课题．提出了一种新颖的心脏形变计算模型：由tag线交点信息通过BE神经网建立描述连续位移场的局部拟合函数;再通过对位移场函数的迭代求解心肌质点的运动,实现心脏形变计算．实验表明模型具有物理意义明确、算法简单和计算精度高的特点．     

基于VLAN技术在高校校园网建设中的应用

随着校园网规模的不断扩大,网络信息需求的不断增加,VLAN技术被运用到校园网的建设中。VLAN是在物理网络的基础上通过技术手段按照管理功能建立的逻辑网络;VLAN技术的应用有效避免了广播风暴;增强了局域网的安全性。本文描述了VLAN的基本概念和原理,VLAN的种类划分及其特点,并结合实际分析了VLAN技术在校园网建设中的应用。     

使用VLAN技术实现网络扩容

虚拟局域网(VLAN)不仅有利于网络安全和防止网络风暴,而且可以提高网络运行的效率,解决许多其他问题。第三层交换机的普及为VLAN的应用创造了条件。笔者在实现网络升级改造的过程中,也采用VLAN技术解决了网络扩容的问题。     

采用VLAN增加企业内部网安全性

本文介绍了VLAN技术,并通过VLAN在企业中的应用实例,探讨了采用VLAN增强企业内部网络的安全性的方法和VLAN配置过程.     

采用VLAN增加企业内部网安全性

本文介绍了VLAN技术,并通过VLAN在企业中的应用实例,探讨了采用VLAN增强企业内部网络的安全性的方法和VLAN配置过程。     

虚拟局域网技术浅谈

当今世界是一个高度信息化的社会,网络时时刻刻地在影响着我们的生活和工作。给我们的工作生活带来了极大的变革,各种组网技术和手段层出不穷。VLAN作为新兴的技术,在组网过程中得到了广泛的应用。本文从虚拟局域网（VLAN）的基本概念和主要功能,VLAN的划分方式,建立VLAN的交换技术,VLAN的配置方式,VLAN成员信息的传递方式,VLAN之间路由与通信方式等方面,分析与概述了虚拟局域网技术。深入浅出地阐述了虚拟局域网技术的基本原理和工作过程,以及在实践中的指导作用。     

VLAN间路由的研究与仿真

在配置有多个VLAN的交换式局域网中,VLAN间路由的实现保证了整个网络的畅通运行。分析了VLAN间路由不同实现方法的特点。针对不同的实现方法,分别设计了实验网络模型,并在Packet Tracer软件中进行了仿真,详细阐述了配置过程。仿真结果验证了不同实现方法的可行性。     

VLAN间路由的研究与仿真

在配置有多个VLAN的交换式局域网中,VLAN间路由的实现保证了整个网络的畅通运行。分析了VLAN间路由不同实现方法的特点。针对不同的实现方法,分别设计了实验网络模型,并在Packet Tracer软件中进行了仿真,详细阐述了配置过程。仿真结果验证了不同实现方法的可行性。     

基于MAC地址的动态VLAN原理及组网应用

给出了VLAN的定义和分类,分析了静态VLAN和动态VLAN的优缺点并对动态VLAN进行了分类.重点介绍了基于MAC地址的动态VLAN的工作原理和配置过程,最后结合实际介绍其在校园网络中的应用.     

VLAN技术在企业网络中的设计及应用

合理的设计和应用虚拟局域网技术(VLAN)能很好解决企业网络在逐渐庞大的过程中产生网络使用效率降低、网络管理复杂等问题,本文通过对VLAN技术的详细介绍,并结合实际对VLAN进行合理的设计和配置。     

Geotag propagation in social networks based on user trust model

In the past few years sharing photos within social networks has become very popular. In order to make these huge collections easier to explore, images are usually tagged with representative keywords such as persons, events, objects, and locations. In order to speed up the time consuming tag annotation process, tags can be propagated based on the similarity between image content and context. In this paper, we present a system for efficient geotag propagation based on a combination of object duplicate detection and user trust modeling. The geotags are propagated by training a graph based object model for each of the landmarks on a small tagged image set and finding its duplicates within a large untagged image set. Based on the established correspondences between these two image sets and the reliability of the user, tags are propagated from the tagged to the untagged images. The user trust modeling reduces the risk of propagating wrong tags caused by spamming or faulty annotation. The effectiveness of the proposed method is demonstrated through a set of experiments on an image database containing various landmarks.     

QinQ VLAN模式下校园网IPv6升级方案

绝大多数校园网的VLAN规划都采用给用户数据包打单层vlan标签的模式。而上海财经大学校园网采用QinQ的VLAN模式,对用户数据包打两层vlan标签,大大增加可用vlan数目,可以给每个用户划分一个vlan。该模式可以有效防范ARP病毒,但是在增强网络安全性的同时造成用户vlan过多,IPv6升级改造的难度相应加大。介绍在QinQ VLAN模式下校园网由IPv4网络升级到IPv6网络的方案,对升级过程中遇到的问题进行分析,给出了校园网升级后的网络拓扑、交换机上的关键配置、IPv6路由设计、IPv6 SAVI的部署以及升级完成后IPv6网络使用情况。     

基于密度分布的半监督回归算法研究

提出了推导密度函数的基本假设,对密度函数进行了推导,通过密度函数实现了密度区域的划分;对同一密度范围内的未标签值标记的估计给出了具体的处理方法;最后介绍了基于密度分布的半监督回归算法的具体实现步骤。该算法实现了对未标签点的标记,能够减小对未标签点标签值的估计误差,提高估计的准确度。     

A Review of Ontology‐Based Tag Recommendation Approaches

Tag recommender schemes suggest related tags for an untagged resource and better tag suggestions to tagged resources. Tagging is very important if the user identifies the tag that is more precise to use in searching interesting blogs. There is no clear information regarding the meaning of each tag in a tagging process. An user can use various tags for the same content, and he can also use new tags for an item in a blog. When the user selects tags, the resultant metadata may comprise homonyms and synonyms. This may cause an improper relationship among items and ineffective searches for topic information. The collaborative tag recommendation allows a set of freely selected text keywords as tags assigned by users. These tags are imprecise, irrelevant, and misleading because there is no control over the tag assignment. It does not follow any formal guidelines to assist tag generation, and tags are assigned to resources based on the knowledge of the users. This causes misspelled tags, multiple tags with the same meaning, bad word encoding, and personalized words without common meaning. This problem leads to miscategorization of items, irrelevant search results, wrong prediction, and their recommendations. Tag relevancy can be judged only by a specific user. These aspects could provide new challenges and opportunities to its tag recommendation problem. This paper reviews the challenges to meet the tag recommendation problem. A brief comparison between existing works is presented, which we can identify and point out the novel research directions. The overall performance of our ontology‐based recommender systems is favorably compared to other systems in the literature.     

A collaborative desktop tagging system for group knowledge management based on concept space

The advent of internet has led to a significant growth in the amount of information available, resulting in information overload, i.e. individuals have too much information to make a decision. To resolve this problem, collaborative tagging systems form a categorization called folksonomy in order to organize web resources. A folksonomy aggregates the results of personal free tagging of information and objects to form a categorization structure that applies utilizes the collective intelligence of crowds. Folksonomy is more appropriate for organizing huge amounts of information on the Web than traditional taxonomies established by expert cataloguers. However, the attributes of collaborative tagging systems and their folksonomy make them impractical for organizing resources in personal environments.This work designs a desktop collaborative tagging (DCT) system that enables collaborative workers to tag their documents. This work proposes an application in patent analysis based on the DCT system. Folksonomy in DCT is built by aggregating personal tagging results, and is represented by a concept space. Concept spaces provide synonym control, tag recommendation and relevant search. Additionally, to protect privacy of authors and to decrease the transmission cost, relations between tagged and untagged documents are constructed by extracting document’s features rather than adopting the full text.Experimental results reveal that the adoption rate of recommended tags for new documents increases by 10% after users have tagged five or six documents. Furthermore, DCT can recommend tags with higher adoption rates when given new documents with similar topics to previously tagged ones. The relevant search in DCT is observed to be superior to keyword search when adopting frequently used tags as queries. The average precision, recall, and F-measure of DCT are 12.12%, 23.08%, and 26.92% higher than those of keyword searching.DCT allows a multi-faceted categorization of resources for collaborative workers and recommends tags for categorizing resources to simplify categorization easier. Additionally, DCT system provides relevance searching, which is more effective than traditional keyword searching for searching personal resources.     

基于VLAN的攻击与安全防范

在交换技术的网络中VLAN为网络的管理与有效抑制广播风暴提供了技术支持,同时在Trunk端口配置、802.1Q协议封装以及VTP配置等实施中也为黑客的攻击留下隐患。常见的攻击形式有MAC洪泛攻击、802.1Q和ISL标记攻击、双封装802.1Q/嵌套式VLAN攻击、VLAN跳跃攻击、VTP攻击等。针对以上攻击文中提出了端口安全配置、Trunk端口配置以及VTP协议的安全配置等措施,有效地防范黑客对网络的攻击。     

加标记的左心室核磁共振图像位移场的运动重建

利用改进的左心室数字模拟器提供的加标记的核磁共振图像(MRI),文章研究左心室位移场的运动重建方法。先以双三次B样条曲面技术拟合短轴和长轴影像层三个方向的标记面,然后采用最小二乘原理确定短轴和长轴影像层标记点1D逆向位移场的最优控制顶点,在此基础上拟合的短轴影像层上标记点的3D逆向位移场达到亚像素精度。这对于跟踪心肌点几何位置,分析左心室的运动变形具有重要意义。     

一种基于子空间学习的图像标签推荐方法

Represented by Flickr and Picasa, online photo albums allow users to tag images, hoping to make it more convenient as well as efficient to organize and retrieve image resources. Recently, automatic tag recommendation system has become a hot research field considering the increasing request that high-quality tags be provided. In this thesis, a new method for tag recommendation system is proposed. Unlike the traditional one which only depends on frequency information or visual feature similarity while neglecting the relation between visual content and the semantic meaning contained in tags thus leading to unsatisfactory recommendations, the new method can find out a latent subspace shared by visual features and tag contents using matrix factorization. As for an untagged image, recommendations can be made when its visual features are projected into the latent subspace and the relevance level it has with others tags is figured out. This new method has been proved efficient after being tested on NUS-WIDE data set with more satisfactory results.     

半监督学习的老挝语词性标注方法研究

针对老挝语语料资源极少而无法直接利用有监督学习的方法实现老挝语词法分析的问题,提出了基于半监督学习的老挝语词性标注方法。首先利用仅有的少量标注词典和未标注语料资源,采用简单概率模型建模,获取较为完整的标注词典;其次利用整数规划获取大量自动标注的语料;最后在训练语 料充足的情况下,利用二阶隐马尔科夫模型建模,实现高质量的老挝语词性标注。提出的方法在老挝语词性标注方面取得了较好的效果,其准确率达到89.8%。     

i-TagRanker: an efficient tag ranking system for image sharing and retrieval using the semantic relationships between tags

Folksonomy, considered a core component for Web 2.0 user-participation architecture, is a classification system made by user’s tags on the web resources. Recently, various approaches for image retrieval exploiting folksonomy have been proposed to improve the result of image search. However, the characteristics of the tags such as semantic ambiguity and non-controlledness limit the effectiveness of tags on image retrieval. Especially, tags associated with images in a random order do not provide any information about the relevance between a tag and an image. In this paper, we propose a novel image tag ranking system called i-TagRanker which exploits the semantic relationships between tags for re-ordering the tags according to the relevance with an image. The proposed system consists of two phases: 1) tag propagation phase, 2) tag ranking phase. In tag propagation phase, we first collect the most relevant tags from similar images, and then propagate them to an untagged image. In tag ranking phase, tags are ranked according to their semantic relevance to the image. From the experimental results on a Flickr photo collection about over 30,000 images, we show the effectiveness of the proposed system.