一种多元分层知识库在避碰决策支持系统中的应用

根据对避碰决策系统的特点及各类避碰知识的分析 ,建立起一种多元分层知识库体系结构 ,并对每一类知识分别采用了不同的知识表示方法和推理机制 ,从而促进知识表示的性能 ,提高知识推理的效率。     

机器视觉在线路检测中的运用

以机器视觉技术为背景,运用LabVIEW语言,开发了PCB板线路检测系统,主要针对印刷线路板,断路、短路、缺损和毛刺4类缺陷进行检测。实验结果证明,这一系统不仅识别结果准确,而且速度快,电路板在检测过程中不容易受损,是实现PCB检测的一种行之有效的方法。     

基于双目点云的三维物体检测准确性分析

双目相机虽然能通过算法生成密集的深度数据,但其在精度上与激光雷达生成的深度数据有着较大的差距,特别是在纹理不明显的区域。针对这种现象,尝试使用激光雷达的精确点云来排除由双目相机产生的pseudo-LiDAR数据中与之差别较大的部分点,然后将优化后的pseudo-LiDAR用以进行三维物体检测。实验结果显示,将pseudo-LiDAR数据中的不准确点(坏点)排除,有助于提高检测准确率,最多可提高21.02%。因此,如何不依赖激光雷达数据来排除pseudo-LiDAR点云中的坏点是进一步提高双目相机系统检测准确率的关键。     

目标定向理论在武术教学中影响研究

运用文献资料法、问卷调查法、数理统计法对浙江省部分在校的大一、大二共286名武术公选学生二个月任务定向和自我定向自然实验的测试.统计结果表明:大学生在体育运动中任务定向均值较高,自我定向均值较低.但不同专项上的学生在任务定向和自我定向中有着差异.在选择体育项目时,大多数学生都选择项目难度小、轻松、不风吹日晒的项目,这也是大一、大二学生的任务定向与自我定向均值中造成差异的主要原因之一.     

一种基于超时消息数的SCP过载控制算法

对多业务环境中SCP的过载控制进行了研究,提出了一种基于超时消息数的过载检测方法。根据这种方法本文设计了一种基于超时消息数的SCP过载控制算法。实验和分析结果表明该算法具有效率高、健壮性强、公平性好的优点。     

信息整流与知识增值服务

本文提出数字图书馆的主要功能目标是信息整流与知识增值服务 ;信息与知识转换是数字图书馆的关键理论和技术问题。图书馆受到Internet的巨大冲击、不再是文献信息服务的唯一提供者 ,数字图书馆如何才能挽回失去的老用户 ,吸引新用户 ?知识管理工程将使数字图书馆成为 2 1世纪学习的大平台、文化知识的大平台和知识资源中心。     

数字图书馆中基于内容的视频拷贝检测关键技术研究

随着数字图书馆中数字视频资源的增长,数字视频版权保护问题逐渐暴露出来。基于内容的视频拷贝检测技术作为一种有效的版权保护技术,近年来逐渐受到研究人员的关注。本文对基于内容的视频拷贝检测的关键技术视频指纹提取和指纹匹配的研究成果进行了分析,总结了指纹提取和指纹匹配的研究现状,指出了该领域存在的问题,最后分析了该领域的发展方向。     

Topic discovery based on text mining techniques

In this paper, we present a topic discovery system aimed to reveal the implicit knowledge present in news streams. This knowledge is expressed as a hierarchy of topic/subtopics, where each topic contains the set of documents that are related to it and a summary extracted from these documents. Summaries so built are useful to browse and select topics of interest from the generated hierarchies. Our proposal consists of a new incremental hierarchical clustering algorithm, which combines both partitional and agglomerative approaches, taking the main benefits from them. Finally, a new summarization method based on Testor Theory has been proposed to build the topic summaries. Experimental results in the TDT2 collection demonstrate its usefulness and effectiveness not only as a topic detection system, but also as a classification and summarization tool.     

新一代ICP-MS功能及其痕量元素检测新技术

综述了ICP-MS仪器的基本原理、结构、发展应用概况及其新产品的功能特点;阐述了新一代ICP-MS在有色金属材料痕量元素检测分析中质谱干扰和非质谱干扰问题及其克服新技术。     

Scientific community detection via bipartite scholar/journal graph co-clustering

This paper stems from the observation that researchers in different fields tend to publish in different journals. Such a relationship between researchers and journals is quantitatively exploited to identify scientific community clusters, by casting the community detection problem into a co-clustering problem on bipartite graphs. Such an approach has the potential of leading not only to the fine- grained detection of scholar communities based on the similarity of their research activity, but also to the clustering of scientific journals based on which are the most representative of each community. The proposed methodology is purely data-driven and completely unsupervised, and does not rely on any semantics (e.g. keywords or a-priori subjective categories). Moreover, unlike “flat” data structures (e.g. collaboration graphs or citation graphs) our bipartite graph approach blends in a joint structure both the researcher's attitude and interests (i.e., freedom to select the venue where to publish) as well as the community's recognition (i.e., acceptance of the publication on a target journal); as such may perhaps inspire further scientometric evaluation strategies. Our proposed approach is applied to the Italian research system, for two broad areas (ICT and Microbiology&Genetics), and reveals some questionable aspects and community overlaps in the current Italian scientific sectors classification.