活性肽搜寻与蛋白模拟水解数据库的建立

利用Microsoft Office XP中的Access XP数据库软件建立3个数据库系统,蛋白质数据库包含小麦面筋、大米、玉米等常见食物蛋白质序列23739条,活性肽数据库包含ACE抑制肽、免疫肽、阿片肽等生物活性肽序列1396条,以及常见的蛋白质水解酶信息。数据库与编制的“生物活性肽搜寻与酶解模拟系统”程序配合,实现单条、多条活性肽序列在蛋白质中批量搜寻,并找出活性肽含量的链长百分比,活性肽在蛋白质中的位置和前后氨基酸的种类,实现肽的活性不完全归纳预测活性,实现蛋白质用单酶或者复酶的模拟水解并标出水解产物中活性肽及其功能。     

基于网格的生物序列比对与分析系统

提出了一个基于网格的生物基因序列比对与分析平台BioSA,详细描述了BioSA系统的各个组成模块,通过各个模块的分工与合作,BioSA系统可以给计算密集型基因序列比对提供一个统一与可扩展的计算环境.使用网格平台中的Web Services技术、消息通知机制,序列比较分析与查询匹配也可以实现.BioSA不仅支持系统定义的序列比对和分析,而且支持用户定义的、远程的序列分析.通过对实际序列比对的案例实现,验证了BioSA系统的正确性与高效性.     

基于蛋白质CGR的线粒体蛋白质序列比对

利用蛋白质混沌游走表示法（PCGR）提出一种新的蛋白质序列比对方法。通过计算两序列之间的PCGR点距离,就可以找到所有的局部相似片断。根据氨基酸的化学物理性质把氨基酸分成4和7类,针对分类与无分类的各种情况进行蛋白质序列比对。为了更直观地描述比对结果,采用点阵图来表示比对数据,不仅能显示两序列间所有相同片断,还可以体现出序列的相似性。     

演绎数据库及其实现方法的分析

演绎数据库是人工智能技术与数据库技术相结合的产物,是数据库研究领域中引人瞩目的一个新的研究方向。我国对演绎数据库的研究始于八十年代初,至今在理论上与实现上都取得了不少成果。本文首先讨论一下演绎数据库的理论,然后,对各种实现方法进行分类分析,并作相应的评价。     

Oracle数据库系统分析的容灾性应用研究

针对Oracle数据库应用系统的容灾性,分析存储层次容灾方式、应用层次容灾方式、操作系统层次容灾方式、数据库层次容灾方式4种容灾方式,在此基础上,设计了基于ORACLE数据库应用的容灾系统,对Oracle数据库容灾技术的应用进行了更深一步的研究,并给出Oracle数据库容灾技术应用的实际效果比对分析结果。     

两序列比对算法与软件研究进展

两序列比对是一种基本序列分析方法,广泛用于序列之间的相似性分析和数据库同源性搜索。现今,用于两序列的软件有上百种,它们应用不同的算法或针对不同的序列类型,在比对速度和比对质量等方面也有很大的差异。根据要比对的序列情况以及要达到的目的选择合适的比对软件是非常有必要的。对现有两序列比对的算法和常用软件进行归类和比较,为研究人员了解现今序列比对情况,筛选合适的比对算法和软件提供参考。     

一种调和序列生成及其在故障定位中的应用

为了提高软件的可靠性,在软件运行发生故障时,快速、准确地定位故障点成为非常有意义的研究课题。与以往方法不同,在将故障运行序列和最部近运行序列进行差异对比前,为了避免选取第一条最近成功路径时引起的“盲区”使得后期搜索空间加大,引入了生物学基因序列比对原理,对最部近运行序列不是通过编辑距离比较进行选取,而是通过一条调和序列进行处理。实验表明,方法的故障定位效果较好。     

广义差错长序列的数据库搜索及其快速算法

所谓广义差错是指同时可能具有符号改变、插入与删除的差错,在数据库搜索中如何对具有广义差错的语句进行搜索是近期计算科学发展的重要问题,尤其是对长序列的搜索问题的研究还很少开展。论文对此问题进行讨论,并给出它的快速算法。     

生物信息学中的序列比对算法

生物信息学是以计算机为工具对生物信息进行储存、检索和分析的科学。序列比对是生物信息学中的一个基本问题,设计快速而有效的序列比对算法是生物信息学研究的一个重要内容,通过序列比较可以发现生物序列中的功能、结构和进化的信息,序列比较的基本操作是比对。本文介绍了序列比对算法的发展现状,描述了常用的各类序列比对算法,并分析了它们的优劣。     

土地利用扫描图件的注记自动识别与入库研究

土地利用基础图件建库是国土资源信息化和“数字国土”的重要组成部分.在传统建库过程中,图件上的大量注记主要是人工识别、手工录入到数据库中,影响了数据库建库的进度,并使数据库质量难以保障.为此提出了扫描图件数字注记自动识别与属性自动入库技术流程和方法,设计开发了较为实用的软件.在包头市土地利用详查数据库建库中的应用表明,上述技术方法合理,注记自动识别精度在87%以上,属性的自动入库准确率超过90%,具有较高的实用价值.     

主动数据库及在DSS中的应用研究

主动数据库是数据库技术中一个活跃的研究领域，它是在传统数据库的基础上，结合人工智能和面向对象技术提出的，其主动性功能正在各种应用中发挥越来越大的作用。主动数据库强调数据库反应能力上具有主动性、快速性和智能化的特性，而决策支持系统要求数据库具有很强的数据预处理和数据分析能力，将主动数据库应用于决策支持系统中，一定会使决策支持系统具有更强的优越性，从而更好地发挥决策支持系统辅助决策的作用，以满足各种层次、各种类型、不同决策者的决策过程对数据的要求。     

综合武器系统数据库的研究

介绍了综合武器系统数据库(JWSDB)的基本概念,论述了JWSDB的物理模型和体系结构,并提出了一种JWSDB集成的方案,最后论证了我国建立JWSDB的必要性和可行性。     

Semantic Extraction and Semantics-Based Annotation and Retrieval for Video Databases

Digital video databases have become more pervasive and finding video clips quickly in large databases becomes a major challenge. Due to the nature of video, accessing contents of video is difficult and time-consuming. With content-based video systems today, there exists a significant gap between the user's information and what the system can deliver. Therefore, enabling intelligent means of interpretation on visual content, semantics annotation and retrieval are important topics of research. In this paper, we consider semantic interpretation of the contents as annotation tags for video clips, giving a retrieval-driven and application-oriented semantics extraction, annotation and retrieval model for video database management system. This system design employs an algorithm on objects' relation and it can reveal the semantics defined with fast real-time computation.     

系统试验数据库及其在仿真系统中的应用

如何对试验数据统一管理并利用其进行数据驱动,是很多工程中都遇到的一个重要问题。该文详细描述了系统试验数据库中所包含的数据内容、各实体之间的相互关系,以及数据库的体系结构,并对系统试验数据库在仿真系统中的具体应用作了简要介绍。文章重点阐述了该数据库系统在实现过程中涉及到的数据库模型设计、多功能数据窗口及组合查询、数据文件与数据库表的关联及不确定结构的报文组织和转发等几项关键技术。该数据库系统已在某些仿真工程中得到验证和应用。     

An Integrated Framework for Semantic Annotation and Adaptation

Tools for the interpretation of significant events from video and video clip adaptation can effectively support automatic extraction and distribution of relevant content from video streams. In fact, adaptation can adjust meaningful content, previously detected and extracted, to the user/client capabilities and requirements. The integration of these two functions is increasingly important, due to the growing demand of multimedia data from remote clients with limited resources (PDAs, HCCs, Smart phones). In this paper we propose an unified framework for event-based and object-based semantic extraction from video and semantic on-line adaptation. Two cases of application, highlight detection and recognition from soccer videos and people behavior detection in domotic^* applications, are analyzed and discussed.Domotics is a neologism coming from the Latin word domus (home) and informatics.Marco Bertini has a research grant and carries out his research activity at the Department of Systems and Informatics at the University of Florence, Italy. He received a M.S. in electronic engineering from the University of Florence in 1999, and Ph.D. in 2004. His main research interest is content-based indexing and retrieval of videos. He is author of more than 25 papers in international conference proceedings and journals, and is a reviewer for international journals on multimedia and pattern recognition.Rita Cucchiara (Laurea Ingegneria Elettronica, 1989; Ph.D. in Computer Engineering, University of Bologna, Italy 1993). She is currently Full Professor in Computer Engineering at the University of Modena and Reggio Emilia (Italy). She was formerly Assistant Professor (‘93–‘98) at the University of Ferrara, Italy and Associate Professor (‘98–‘04) at the University of Modena and Reggio Emilia, Italy. She is currently in the Faculty staff of Computer Engenering where has in charges the courses of Computer Architectures and Computer Vision.Her current interests include pattern recognition, video analysis and computer vision for video surveillance, domotics, medical imaging, and computer architecture for managing image and multimedia data.Rita Cucchiara is author and co-author of more than 100 papers in international journals, and conference proceedings. She currently serves as reviewer for many international journals in computer vision and computer architecture (e.g. IEEE Trans. on PAMI, IEEE Trans. on Circuit and Systems, Trans. on SMC, Trans. on Vehicular Technology, Trans. on Medical Imaging, Image and Vision Computing, Journal of System architecture, IEEE Concurrency). She participated at scientific committees of the outstanding international conferences in computer vision and multimedia (CVPR, ICME, ICPR, ...) and symposia and organized special tracks in computer architecture for vision and image processing for traffic control. She is in the editorial board of Multimedia Tools and Applications journal. She is member of GIRPR (Italian chapter of Int. Assoc. of Pattern Recognition), AixIA (Ital. Assoc. Of Artificial Intelligence), ACM and IEEE Computer Society.Alberto Del Bimbo is Full Professor of Computer Engineering at the Università di Firenze, Italy. Since 1998 he is the Director of the Master in Multimedia of the Università di Firenze. At the present time, he is Deputy Rector of the Università di Firenze, in charge of Research and Innovation Transfer. His scientific interests are Pattern Recognition, Image Databases, Multimedia and Human Computer Interaction. Prof. Del Bimbo is the author of over 170 publications in the most distinguished international journals and conference proceedings. He is the author of the “Visual Information Retrieval” monography on content-based retrieval from image and video databases edited by Morgan Kaufman. He is Member of IEEE (Institute of Electrical and Electronic Engineers) and Fellow of IAPR (International Association for Pattern Recognition). He is presently Associate Editor of Pattern Recognition, Journal of Visual Languages and Computing, Multimedia Tools and Applications Journal, Pattern Analysis and Applications, IEEE Transactions on Multimedia, and IEEE Transactions on Pattern Analysis and Machine Intelligence. He was the Guest Editor of several special issues on Image databases in highly respected journals.Andrea Prati (Laurea in Computer Engineering, 1998; PhD in Computer Engineering, University of Modena and Reggio Emilia, 2002). He is currently an assistant professor at the University of Modena and Reggio Emilia (Italy), Faculty of Engineering, Dipartimento di Scienze e Metodi dell’Ingegneria, Reggio Emilia. During last year of his PhD studies, he has spent six months as visiting scholar at the Computer Vision and Robotics Research (CVRR) lab at University of California, San Diego (UCSD), USA, working on a research project for traffic monitoring and management through computer vision. His research interests are mainly on motion detection and analysis, shadow removal techniques, video transcoding and analysis, computer architecture for multimedia and high performance video servers, video-surveillance and domotics. He is author of more than 60 papers in international and national conference proceedings and leading journals and he serves as reviewer for many international journals in computer vision and computer architecture. He is a member of IEEE, ACM and IAPR.     

一个适用于IC－CAD系统的设计库管理系统及其改进

当前，开发以数据库为核心的集成化ＣＡＤ系统已迫在眉睫。本文简单回顾了工程数据库的发展背景，然后介绍一个适用于ＩＣ－ＣＡＤ系统的设计库管理系统ＩＣＤＭＳ，着重讨论了对该系统的一些改进。经测试，改进以后的ＩＣＤＭＳ的功能有明显的增强和改善。     

ORACLE远程数据库访问技术及实现

介绍了ORACLE数据库系统中的远程访问分布式数据库技术,通过对某银行为供电局代收电费系统的设计、开发,详细说明了远程访问技术的原理、特点。