Materialization of fragmented views in multidimensional databases

The most effective technique to enhance performances of multidimensional databases consists in materializing redundant aggregates called views. In the classical approach to materialization, each view includes all and only the measures of the cube it aggregates. In this paper we investigate the benefits of materializing views in vertical fragments, aimed at minimizing the workload response time. We formalize the fragmentation problem as a 0–1 integer linear programming problem, which is then solved by means of a standard integer programming solver to determine the optimal fragmentation for a given workload. Finally, we demonstrate the usefulness of fragmentation by presenting a large set of experimental results based on the TPC-H benchmark.     

A new student performance analysing system using knowledge discovery in higher educational databases

Knowledge discovery is a wide ranged process including data mining, which is used to find out meaningful and useful patterns in large amounts of data. In order to explore the factors having impact on the success of university students, knowledge discovery software, called MUSKUP, has been developed and tested on student data. In this system a decision tree classification is employed as a data mining technique. With this software system all the tasks involved in the knowledge discovery process are kept together. The advantage of this approach is to have access to all the functionalities of SQL server and Analysis Services through single software. The study was carried out on the data from university students. According to results of the study, the types of registration to the university and the income levels of the students’ family were found to be associated with student success.     

Dynamic adaptation of response-time models for QoS management in autonomic systems

In transactional systems, the objectives of quality of service regarding are often specified by Service Level Objectives (SLOs) that stipulate a response time to be achieved for a percentile of the transactions. Usually, there are different client classes with different SLOs. In this paper, we extend a technique that enforces the fulfilment of the SLOs using admission control. The admission control of new user sessions is based on a response-time model. The technique proposed in this paper dynamically adapts the model to changes in workload characteristics and system configuration, so that the system can work autonomically, without human intervention. The technique requires no knowledge about the internals of the system; thus, it is easy to use and can be applied to many systems. Its utility is demonstrated by a set of experiments on a system that implements the TPC-App benchmark. The experiments show that the model adaptation works correctly in very different situations that include large and small changes in response times, increasing and decreasing response times, and different patterns of workload injection. In all this scenarios, the technique updates the model progressively until it adjusts to the new situation and in intermediate situations the model never experiences abnormal behaviour that could lead to a failure in the admission control component.     

A semantical framework for supporting subjective and conditional probabilities in deductive databases

We present a theoretical basis for supporting subjective and conditional probabilities in deductive databases. We design a language that allows a user greater expressive power than classical logic programming. In particular, a user can express the fact thatA is possible (i.e.A has non-zero probability),B is possible, but (A B) as a whole is impossible. A user can also freely specify probability annotations that may contain variables. The focus of this paper is to study the semantics of programs written in such a language in relation to probability theory. Our model theory which is founded on the classical one captures the uncertainty described in a probabilistic program at the level of Herbrand interpretations. Furthermore, we develop a fixpoint theory and a proof procedure for such programs and present soundness and completeness results. Finally we characterize the relationships between probability theory and the fixpoint, model, and proof theory of our programs.     

Support for modeling relationships in object-oriented databases

Modeling real-world applications typically consists of two parts: the representations of entities of interest, and the representations of relationships among the entities. Object-oriented data models support the first task. This paper argues through examples that the second modeling task is not well supported in current object-oriented database systems. An extended object-oriented data model that facilitates both modeling tasks is developed. This extension provides support for both the representation of complex relationships among entities and their manipulations (queries, updates). A prototype implemented on the ONTOS database management system is briefly described.     

虚拟选煤厂三维模型系统的实时性优化

虚拟现实模型系统的优化对于提高运行系统的实时性,保证虚拟现实系统的沉浸、交互等特性具有重要作用.结合虚拟选煤厂三维模型系统的优化,分析和探讨了虚拟现实模型系统实时性优化的几项关键技术,包括优化三维模型结构,节省模型系统的多边形开销,使系统中总多边形数不超过硬件的处理能力;优化纹理数据,在保证必要的纹理细节的前提下,有效节约纹理内存;优化模型数据库和LOD层次结构,改善运行系统的数据筛选性能,提高绘制速度.模型系统优化后系统的剔除和绘制时间曲线表明,优化后系统运行的实时性得到了有效提高.     

An approximate algorithm for top-k closest pairs join query in large high dimensional data

In this paper we present a novel approximate algorithm to calculate the top-k closest pairs join query of two large and high dimensional data sets. The algorithm has worst case time complexity and space complexity and guarantees a solution within a factor of the exact one, where t  {1, 2, … , ∞} denotes the Minkowski metrics L_t of interest and d the dimensionality. It makes use of the concept of space filling curve to establish an order between the points of the space and performs at most d + 1 sorts and scans of the two data sets. During a scan, each point from one data set is compared with its closest points, according to the space filling curve order, in the other data set and points whose contribution to the solution has already been analyzed are detected and eliminated. Experimental results on real and synthetic data sets show that our algorithm behaves as an exact algorithm in low dimensional spaces; it is able to prune the entire (or a considerable fraction of the) data set even for high dimensions if certain separation conditions are satisfied; in any case it returns a solution within a small error to the exact one.     

Minimal model generation for refined answering of generalized queries in disjunctive deductive databases

Generalized queries are defined as sets of clauses in implication form. They cover several tasks of practical importance for database maintenance such as answering positive queries, computing database completions and integrity constraints checking. We address the issue of answering generalized queries under the minimal model semantics for the class of disjunctive deductive databases (DDDBs). The advanced approach is based on having the query induce an order on the models returned by a sound and complete minimal model generating procedure. We consider answers that are true in all and those that are true in some minimal models of the theory. We address the issue of answering positive queries through the construction of the minimal model state of the DDDB, using a minimal model generating procedure. The refinements allowed by the procedure include isolating a minimal component of a disjunctive answer, the specification of possible updates to the theory to enable the derivability of certain queries and deciding the monotonicity properties of answers to different classes of queries.     

Cost-driven vertical class partitioning for methods in object oriented databases

In object-oriented databases (OODBs), a method encapsulated in a class typically accesses a few, but not all the instance variables defined in the class. It may thus be preferable to vertically partition the class for reducing irrelevant data (instance variables) accessed by the methods. Our prior work has shown that vertical class partitioning can result in a substantial decrease in the total number of disk accesses incurred for executing a set of applications, but coming up with an optimal vertical class partitioning scheme is a hard problem. In this paper, we present two algorithms for deriving optimal and near-optimal vertical class partitioning schemes. The cost-driven algorithm provides the optimal vertical class partitioning schemes by enumerating, exhaustively, all the schemes and calculating the number of disk accesses required to execute a given set of applications. For this, a cost model for executing a set of methods in an OODB system is developed. Since exhaustive enumeration is costly and only works for classes with a small number of instance variables, a hill-climbing heuristic algorithm (HCHA) is developed, which takes the solution provided by the affinity-based algorithm and improves it, thereby further reducing the total number of disk accesses incurred. We show that the HCHA algorithm provides a reasonable near-optimal vertical class partitioning scheme for executing a given set of applications.Received: 29 March 1999, Accepted: 11 March 2002, Published online: 3 April 2003This research has been supported, in part, by Hong Kong UGC Research Grants Council under grant CityU 733/96E and CityU 1119/99E.     

模型管理系统中构模知识的组织和获取方法

提出了一种构模知识的组织和获取方法。构模知识分为模型知识、领域知识和数据知识3个层次,数据知识是最底层的知识,高层知识的应用通过调用底层知识完成。模型知识和领域知识可以通过交互的方式在专家的帮助下获取,数据知识可以由系统自动获取。应用这种方法,系统能够在专家构建模型时获取构模的知识,从而使模型资源得到有效利用,并解决了模型管理系统知识获取的瓶颈问题。     

Knowledge acquisition techniques for feature recognition in CAD models

Automatic Feature Recognition (AFR) techniques are an important tool for achieving a true integration of design and manufacturing stages during the product development. In particular, AFR systems offer capabilities for recognising high-level geometrical entities, features, in Computer-Aided Design (CAD) models. However, the recognition performances of most of the existing AFR systems are limited to the requirements of specific applications. This paper presents automatic knowledge acquisition techniques to support the development of AFR systems that could be deployed in different application domains. In particular, a method to generate automatically feature recognition rules is proposed. These rules are formed by applying an inductive learning algorithm on training data consisting of feature examples. In addition, a technique for defining automatically feature hints from such rule sets is described. The knowledge acquisition techniques presented in this study are implemented within a prototype feature recognition system and its capabilities are verified on two benchmarking parts.     

科技开发项目微机管理系统

论述了高校科技管理自动化的意义与必要性,着重介绍“科技开发项目微机管理系统”软件的结构设计、软件开发、功能模块及系统运行环境等。分析了学校科技开发发服务工作的优势和不足之处,进一步明确了今后科技管理工作的目标,发挥高校的优势,促进学校的科技开发服务工作的不断发展。     

An efficient iconic indexing strategy for image rotation and reflection in image databases

Spatial relationships are important issues for similarity-based retrieval in many image database applications. With the popularity of digital cameras and the related image processing software, a sequence of images are often rotated or flipped. That is, those images are transformed in the rotation orientation or the reflection direction. However, many iconic indexing strategies based on symbolic projection are sensitive to rotation or reflection. Therefore, these strategies may miss the qualified images, when the query is issued in the orientation different from the orientation of the database images. To solve this problem, some researchers proposed a function to map the spatial relationship to its transformed one. However, this mapping consists of several conditional statements, which is time-consuming. Thus, in this paper, we propose an efficient iconic indexing strategy, in which we carefully assign a unique bit pattern to each spatial relationship and record the spatial information based on the bit patterns in a matrix. Without generating the rotated or flipped image, we can directly derive the index of the rotated or flipped image from the index of the original one by bit operations and matrix manipulation. In our performance study, we analyze the time complexity of our proposed strategy and show the efficiency of our proposed strategy according to the simulation results. Moreover, we implement a prototype to validate our proposed strategy.     

An architecture of an intelligent system for routing user requests in a network of heterogeneous databases

We present a general purpose model for routing user requests, e.g. queries, in a network of autonomous heterogeneous databases. The database schemas and other information on the database nodes are used to construct a multi-level knowledge-base (MKB) that resides in various nodes. Access to the databases is not done by creating direct connections between the user and the nodes where the data are presumably located. Rather, the user approaches the network by contents via an intelligent system that utilizes the MKB in order to identify the nodes and databases where the most relevant information resides, and establishes access routes to those nodes.     

多语种文本自动生成系统中句子规划部分知识表示模型的构造

提出了一种多语种文本自动生成系统中句子规划阶段的知识表示模型,它以句子结构类、句法规则和语义词典确定文本的具体形式,并详细介绍了该知识表示模型的结构及其匹配准则。     

A Knowledge-based Customization System for Supply Chain Integration

Hostile environmental pressure on supply chain management increases emphasis on supply chain agility, integration, and visibility to respond rapidly, effectively and efficiently to changes in the marketplace. There is a need for new methods and tools to visualize the supply chain topologies which captures and recognizes the complexity of the supply chain network. This paper presents a Knowledge-based Customization System for Supply Chain Integration (KCSSI) which is developed based on three core technologies: visualization of topologies, network analysis, and knowledge-based system so as to obtain quantified actionable information and formulating strategies for supply chain configuration leading the long term success. The performance of the system is verified by a series of controlled simulation experiments conducted in a selected reference site. It is verified that the KCSSI improves supply chain visibility by recognizing the structure clustering and interconnection of the supply chain network, quantifying and exploiting holistic supply chain performance to provide measurable insights for the customization of the supply chain configuration leading to long term success.     

电动助力转向器性能试验系统设计与实现

在对电动助力转向性能试验进行具体分析的基础上,提出了汽车电动助力转向装置性能试验系统的硬件设计方案和软件实现方法。由于试验产品在控制策略上仍有改进空间,系统采用DMA方式实现高速数据采集后数据的传输,通过对采集数据进行分析,可以在该试验装置上对ECU进行在线调试和控制策略修改。     

水位远程连续报测系统设计与实现

针对水位远程采集点位置分散、难以实现实时监测的特点,设计了一种采用FWD-F系列磁致伸缩液位传感器与TMS320F2812单片机配合设计的水位远程连续报测系统.系统由数据采集模块、无线传输模块和信息处理模块组成.采集到的水位信息通过GPRS向控制中心发送,并自动生成报表,实现了水位实时在线测量.试验证明,系统读识方便、可靠性高,且传输速度快.     

一种高效的多路数据采集与处理系统模型

分析了现有数据采集与处理系统模型在高数据率、大数据量应用中存在的弊端,提出了一种新的高效的系统模型,基于该模型建立的多路视频数据采集系统取得了良好的运行效果,充分证明了这种模型的实时性和高效性。