基于图像特征提取的飞行器故障诊断系统设计

为提高飞行器测试数据的利用率,解决飞行器故障诊断中资源浪费的问题。提出并实现了一种基于数据图像特征提取的飞行器故障自动诊断系统。系统通过建立一个历史测试数据库,对各种测试项目的历史图像提取特征值,将其存储在数据库中,且将该次测试对应的诊断信息存储在内。利用小波变换法作为特征提取的方法,小波能谱熵作为特征值表征。将当前测试故障的数据图像进行特征提取,并与数据库中图像进行比对,找出相似度最高的历史数据图像。从而帮助测试人员进行故障定位诊断工作。     

Designing secure databases

Security is an important issue that must be considered as a fundamental requirement in information systems development, and particularly in database design. Therefore security, as a further quality property of software, must be tackled at all stages of the development. The most extended secure database model is the multilevel model, which permits the classification of information according to its confidentiality, and considers mandatory access control. Nevertheless, the problem is that no database design methodologies that consider security (and therefore secure database models) across the entire life cycle, particularly at the earliest stages currently exist. Therefore it is not possible to design secure databases appropriately. Our aim is to solve this problem by proposing a methodology for the design of secure databases. In addition to this methodology, we have defined some models that allow us to include security information in the database model, and a constraint language to define security constraints. As a result, we can specify a fine-grained classification of the information, defining with a high degree of accuracy which properties each user has to own in order to be able to access each piece of information. The methodology consists of four stages: requirements gathering; database analysis; multilevel relational logical design; and specific logical design. The first three stages define activities to analyze and design a secure database, thus producing a general secure database model. The last stage is made up of activities that adapt the general secure data model to one of the most popular secure database management systems: Oracle9i Label Security. This methodology has been used in a genuine case by the Data Processing Center of Provincial Government. In order to support the methodology, we have implemented an extension of Rational Rose, including and managing security information and constraints in the first stages of the methodology.     

基于Domino技术的企业数据交换策略研究

随着网络技术的发展 ,企业加大了在信息基础设施方面的投入。由于历史的原因 ,企业数据一般由文件、关系型数据库、文档型数据库等构成。这些数据的共享与重用性差 ,数据之间的交换困难 ,不利于员工的使用和管理层的决策。提出了一种基于Domino技术的数据交换策略的体系结构 ,用来解决这类问题。这种结构的核心是数据接口和中间件 ,即中间件技术的应用。详细地描述了中间件技术结构设计的四个主要组成部分 :请求管理模块、连接管理模块、操作管理及评价模块、结果缓冲集 ,并提出了在实际应用中系统设计的一种可行的开发工具。     

Labeling design documents based on operators’ consensus—A case study of robotic design

Designers usually begin with a database to look for historical design solution, available experience and techniques through design documents, when initiating a new design. This database is a collection of labeled design documents under a few of predefined categories. However, little work has been done on labeling a relatively small number of design documents for information organization, so that most of design documents in this database can be automatically categorized.This paper initiates a study on this topic and proposes a methodology in four steps: design document collection, documents labeling, finalization of documents labeling and categorization of design database. Our discussion in this paper focuses on the first three steps. The key of this method is to collect relatively small number of design documents for manual labeling operation, and unify the effective labeling results as the final labels in terms of labeling agreement analysis and text classification experiment. Then these labeled documents are utilized as training samples to construct classifiers, which can automatically give appropriate labels to each design document.With this method, design documents are labeled in terms of the consensus of operators’ understanding, and design information can be organized in a comprehensive and universally accessible way. A case study of labeling robotic design documents is used to demonstrate the proposed methodology. Experimental results show that this method can significantly benefit efficient design information search.     

Fault diagnosis with multivariate statistical models part I: using steady state fault signatures

Multivariate statistical approaches to fault detection based on historical operating data have been found to be useful with processes having a large number of measured variables and when causal models are unavailable. For fault isolation or diagnosis they have been less powerful because of the non-causal nature of the data on which they are based. To improve the fault isolation with these methods, additional data on past faults have been used to supplement the models. A critical review of this fault isolation literature is given, and an improved approach capable of handling both simple and complex faults is presented. This approach extracts fault signatures that are vectors of movement of the fault in both the model space and the residual space. The directions of these vectors are then compared to the corresponding vector directions of known faults in the fault library. Isolation is then based on a joint plot of the angles between the vectors of the current fault and those of the known faults. Although the fault signatures are based on steady-state information, the methodology assumes that time varying disturbances due to common-cause sources are always present, and it is applied to dynamic data as soon as a fault is detected. The method is demonstrated using a simulated CSTR system with feedback control, and is shown to be effective in isolating both simple and complex faults.     

Algebraic approaches for fault identification in discrete-event systems

In this note, we develop algebraic approaches for fault identification in discrete-event systems that are described by Petri nets. We consider faults in both Petri net transitions and places, and assume that system events are not directly observable but that the system state is periodically observable. The particular methodology we explore incorporates redundancy into a given Petri net in a way that enables fault detection and identification to be performed efficiently using algebraic decoding techniques. The guiding principle in adding redundancy is to keep the number of additional Petri net places small while retaining enough information to be able to systematically detect and identify faults when the system state becomes available. The end result is a redundant Petri net embedding that uses 2k additional places and enables the simultaneous identification of 2k-1 transition faults and k place faults (that may occur at various instants during the operation of the Petri net). The proposed identification scheme has worst-case complexity of O(k(m+n)) operations where m and n are respectively the number of transitions and places in the given Petri net.     

Schema Vacuuming in Temporal Databases

Temporal databases facilitate the support of historical information by providing functions for indicating the intervals during which a tuple was applicable (along one or more temporal dimensions). Because data are never deleted, only superceded, temporal databases are inherently append-only resulting, over time, in a large historical sequence of database states. Data vacuuming in temporal databases allows for this sequence to be shortened by strategically, and irrevocably, deleting obsolete data. Schema versioning allows users to maintain a history of database schemata without compromising the semantics of the data or the ability to view data through historical schemata. While the techniques required for data vacuuming in temporal databases have been relatively well covered, the associated area of vacuuming schemata has received less attention. This paper discusses this issue and proposes a mechanism that fits well with existing methods for data vacuuming and schema versioning.     

Information system analysis and conceptual database design in production environments with M1

A methodology, called M¹, for information system analysis and database design of production environments is presented in detail. The originality of M¹ is to recognize the importance of integrating factory analysis methods for data and user requirements definition with logical database design methods for database specification. M¹ is a pragmatic, complete, manual methodology involving three major phases: Enterprise Modelling and Analysis which is the phase devoted to accurate analysis of the structure of the enterprise and precise definition of the scope of the future database application; Conceptual Design which is the phase concerned with data modelling of both static and dynamic properties of the enterprise; and Implementation Design which is the phase dealing with adaptation of the conceptual schema to the data model specifications of the physical database system used for application development and tuning performances of the physical system. The methodology is explained and illustrated by means of an example related to a Flexible Manufacturing System for mechanical parts.     

Improving the coverage criteria of UML state machines using data flow analysis

A number of coverage criteria have been proposed for testing classes and class clusters modeled with state machines. Previous research has revealed their limitations in terms of their capability to detect faults. As these criteria can be considered to execute the control flow structure of the state machine, we are investigating how data flow information can be used to improve them in the context of UML state machines. More specifically, we investigate how such data flow analysis can be used to further refine the selection of a cost‐effective test suite among alternative, adequate test suites for a given state machine criterion. This paper presents a comprehensive methodology to perform data flow analysis of UML state machines—with a specific focus on identifying the data flow from OCL guard conditions and operation contracts—and applies it to a widely referenced coverage criterion, the round‐trip path (transition tree) criterion. It reports on two case studies whose results show that data flow information can be used to select the best transition tree, in terms of cost effectiveness, when more than one satisfies the transition tree criterion. The results also suggest that different trees are complementary in terms of the data flow that they exercise, thus, leading to the detection of intersecting but distinct subsets of faults. Copyright © 2009 John Wiley & Sons, Ltd.     

历史航空影像数字化与建库技术初探

历史航空影像客观有效地记录了自然景观与人文景观的演化变迁过程，是人类进行资源环境问题研究和改造客观现实世界的基础信息资源，从而为社会进步和可持续发展提供科学的决策支持。针对历史航空影像数字化与数据库建设工作的技术要求，通过对历史航空影像资料数字化作业规程的分析与探讨，给出了实用有效的历史航空影像数字化作业流程和技术指标，进而提出了切实可行的数字化历史航空影像建库技术路线和解决方案，并以历史航空影像数字化与建库试验研究验证了技术方案的合理性和可操作性，为历史航空影像数据库的建设提供前期的试验指导。     

SICTQUAL: A fuzzy linguistic multi-criteria model to assess the quality of service in the ICT sector from the user perspective

The Information and Communication Technologies (ICTs) play an important role in the economic development, making it necessary to assess the quality of service perceived by consumers in this sector. The most effective quality assessment from the consumer perspective is still to be researched, yet the most common approach is oriented towards quantitative indicators. This study proposes to use a two-dimensional model that combines the widely accepted segmentation of ICTs with elements from the SERVQUAL quality model. This model, useful in multi-criteria decision-making situations, has been developed using the 2-tuple linguistic representation and fuzzy logic principles. This methodology prevents data loss during processing and provides relevant information through 16 indicators related to the quality of service. Besides, an expert-based mechanism is defined for the use of historical information extracted from completed surveys. As a practical case, this mechanism is applied to the historical information of a telecommunications company for assessing the quality of the service provided to its customers.     

A bayesian belief network based model for predicting software faults in early phase of software development process

It is always better to have an idea about the future situation of a present work. Prediction of software faults in the early phase of software development life cycle can facilitate to the software personnel to achieve their desired software product. Early prediction is of great importance for optimizing the development cost of a software project. The present study proposes a methodology based on Bayesian belief network, developed to predict total number of faults and to reach a target value of total number of faults during early development phase of software lifecycle. The model has been carried out using the information from similar or earlier version software projects, domain expert’s opinion and the software metrics. Interval type-2 fuzzy logic has been applied for obtaining the conditional probability values in the node probability tables of the belief network. The output pattern corresponding to the total number of faults has been identified by artificial neural network using the input pattern from similar or earlier project data. The proposed Bayesian framework facilitates software personnel to gain the required information about software metrics at early phase for achieving targeted number of software faults. The proposed model has been applied on twenty six software project data. Results have been validated by different statistical comparison criterion. The performance of the proposed approach has been compared with some existing early fault prediction models.     

The evaluation of computer hardware/software plans for municipalities

This paper presents a methodology employing systems analysis techniques which may be used to evaluate alternative data processing plans for municipalities. The basic information which must be formulated for the analysis includes the following three areas: general hardware specifications, implementation schedules for database applications, and cost profiles which include capital and operating expense estimates. Specific factors are developed which may be used to assign numeric ratings to the relative advantages of each plan, and as a basis for making recommendations in the areas of hardware, software, staffing and costs. The methodology is illustrated by the analysis and evaluation of five plans developed to meet the data processing needs of a large metropolitan area.     

Towards a new approach to secure database design

The problem of designing and managing a secure database system is considered in this paper. The approach which is proposed is primarily concerned with the security information definition and management in a database environment. A multiphase design methodology is presented reflecting current proposals of database design methodology. In particular four design phases are proposed: requirements analysis of the security system, conceptual, logical and physical design of security information. The content and the solution techniques of each phase are examined. A database management system architecture is also presented which is suitable to control access rights to the database.     

PI-ACE在重钢新区铁区信息系统的应用

PI是应用广泛的实时/历史数据库系统,在高效数据访问、海量数据存储等方面表现出关系数据无法比拟的优势。PI提供了比较完善的PI数据库访问工具,但没有提供数据分析和挖掘工具,实现数据分析和挖掘,需要利用第三方开发工具。研究了PI数据库访问的原理以及VB.NET利用PI-ACE访问PI数据库的方法,并将该方法应用到重钢新区铁区信息系统中,实现了PI中铁区工艺数据的访问和整合。实际应用说明该方法是稳定有效的。     

基于甲骨文数据库管理系统的化学结构检索数据库的设计与实现

设计了一种基于大型数据库管理系统Oracle的化学结构数据存储模式,并实现了相应于此模式的高效化学结构检索方法。结构检索方法建立在图子图匹配算法VF2的基础上,对其进行了必要的改造和扩展,使之适合于化学结构检索。在此基础上,针对美国NCl(National Cancer Institute)25万个化合物的2D结构建立了数据库,成功进行了结构检索试验。结果表明,这种实现方法不仅能高效存储并准确检索化合物的结构信息,而且也容易实现与药物研发过程中所产生的大量其它数据(如生物筛选数据和DNA芯片基因表达数据等)进行高效整合。这个设计的改进版已经集成于微芯公司的药物研发生化信息学软件系统——TASS(Target Activity Structure System)中。     

A methodology for learning across application domains for databasedesign systems

Although database design tools have been developed that attempt to automate (or semiautomate) the design process, these tools do not have the capability to capture common sense knowledge about business applications and store it in a context-specific manner. As a result, they rely on the user to provide a great deal of "trivial" details and do not function as well as a human designer who usually has some general knowledge of how an application might work based on his or her common sense knowledge of the real world. Common sense knowledge could be used by a database design system to validate and improve the quality of an existing design or even generate new designs. This requires that context-specific information about different database design applications be stored and generalized into information about specific application domains (e.g., pharmacy, daycare, hospital, university, manufacturing). Such information should be stored at the appropriate level of generality in a hierarchically structured knowledge base so that it can be inherited by the subdomains below. For this to occur, two types of learning must take place. First, knowledge about a particular application domain that is acquired from specific applications within that domain are generalized into a domain node (e.g., entities, relationships, and attributes from various hospital applications are generalized to a hospital node). This is referred to as within domain learning. Second, the information common to two (or more) related application domain nodes is generalized to a higher-level node; for example, knowledge from the car rental and video rental domains may be generalized to a rental node. This is called across domain learning. This paper presents a methodology for learning across different application domains based on a distance measure. The parameters used in this methodology were refined by testing on a set of representative cases; empirical testing provided further validation     

论计算机网络数据库安全技术

随着科学技术的发展,计算机技术也在随之快速的发展,但是相应的问题也随之而来。其中,由于计算机网络数据库中储存中许多重要的信息资料,计算机网络数据库的安全问题尤为重要。而国家在发展期间,国家与国家之间的竞争也随着转移到了计算机网络数据库安全上面。因此,为了国家的发展、经济的发展,保障计算机网络数据库的安全是目前社会面临的重要问题。     

Evaluation criteria for logical database design methodologies

The increasing acceptance of database systems has shown the need for logical database design methodologies and evaluation criteria to select the one most appropriate for a particular task. Application of currently existing methodologies to a portion of the data handled during chemical process plant design has highlighted strengths and shortcomings of the methodologies analysed. Using these results, evaluation criteria are established and synthesis of a methodology which is responsive to the identified criteria is proposed.