具有全序时态类型集时态函数依赖集的研究

好的数据库逻辑设计目标是消除数据冗余以及插入、删除和更新异常.对于时态数据库,可以通过具有多时间粒度的时态函数依赖(TFDs)约束对时态数模式进行规范化.但是由于时间维的引入和多时间粒度的使用而给数据库设计带来巨大的复杂性.一般来说,系统所能处理的和相当多的应用所涉及到的时态类型集满足全序关系,并且具有全序时态类型集的TFD集的推导规则与传统函数依赖(FDs)的Armstrong公理有着紧密的联系.通过分析TFDs与FDs之间存在的联系,利用传统FD集的相应算法,提出了成员籍、有限属性闭包等TFD集的一些重要算法.这些算法是时态数据库进一步规范化的基础.     

关于标准FD集的几个相关问题的讨论

本文为讨论ＦＤ集的简化和研究最优覆盖的多项式求法，对标准ＦＤ集进行了定义和讨论。同时，还定义了与它相关的几个概念，讨论了标准ＦＤ集Ｆ成为最小覆盖的充要条件及其它问题。     

一个具有多时间粒度时态函数依赖集的成员籍算法

对于具有函数依赖（FDs)约束的传统关系数据库规范化理论来说，判定一个FD是否被给定FD集所逻辑蕴涵（即成员籍问题）是非常重要的，这有助于设计有效的模式分解算法，而对于具有时态函数依赖（TFDs)约束的时态模式来说，由于多时间粒度的使用使成员籍问题的解决变得更加复杂，由此讨论了时态类型的一些特性，并提出了有限决定集的概念，基于求得属性的有限决定集，对每一个元素的左部属性集是单一属性的TFD集给出了一个有效的成员籍算法和相关的正确性证明。     

基于闭包的3NF模式综合算法

文中基于属性集关于函数依赖集的闭包，并采用模式矩阵，给出了一个从函数依赖集综合出３ＮＦ模式的算法。该算法不用Ａｒｍｓｔｒｏｎｇ公理进行烦琐的推导，与Ｂｅｒｎｓｔｅｉｎ算法相比，较为简单且易于实现。     

基于最大相关块的关系模式全部主属性的一种解法

本文是把关系模式中的函依赖集进行划分，对应的属性集合构成一个相关块，再对每个相关块求其主属性，最终给出求全部主属性的多项式时间的一种算法。     

Design by example for SQL table definitions with functional dependencies

A database is C-Armstrong for a given set of constraints in a class C if it satisfies every constraint of the set and violates every constraint in C not implied by the set. Therefore, Armstrong databases are test data that perfectly illustrate the current perceptions about the semantics of a schema. We extend the existing theory of Armstrong relations to a toolbox of Armstrong tables. That is, we investigate structural and computational properties of Armstrong tables for the class of functional dependencies (FDs) over SQL tables. Relations are special instances of SQL tables with no duplicate rows and no null value occurrences. While FDs do not enjoy Armstrong tables, the combined class of standard FDs and NOT NULL constraints does enjoy Armstrong tables. The problem of finding an Armstrong table is shown to be precisely exponential for this combined class. However, we establish an algorithm that computes Armstrong tables with a size at most quadratic in that of a minimum-sized Armstrong table. Our resulting toolbox of Armstrong tables can be applied by data engineers to concisely visualize constraints on SQL data. Such support can lead to designs that guarantee efficient data management in practice.     

An improved algorithm based on subset closures for synthesizing arelational database scheme

An algorithm for synthesizing a better relational database scheme in elementary key normal form (EKNF) is developed. This algorithm eliminates not only extraneous attributes and other redundancies, but also superfluities from a given set of functional dependences (FDs), based primarily on subset closures, Hamiltonian cycles of FDs, and equivalent subsets of attributes. Following this algorithm, a better LR-minimum FD covering is obtained. A more practical and efficient method for designing a relational database scheme in EKNF is then provided. The time complexity of the algorithm is polynomial     

The additivity problem for functional dependencies in incomplete relations

Incomplete relations are relations which contain null values, whose meaning is “value is at present unknown”. A functional dependency (FD) is weakly satisfied in an incomplete relation if there exists a possible world of this relation in which the FD is satisfied in the standard way. Additivity is the property of equivalence of weak satisfaction of a set of FDs, say F, in an incomplete relation with the individual weak satisfaction of each member of F in the said relation. It is well known that satisfaction of FDs is not additive. The problem that arises is: under what conditions is weak satisfaction of FDs additive. We solve this problem by introducing a syntactic subclass of FDs, called monodependent FDs, which informally means that for each attribute, say A, there is a unique FD that functionally determines A, and in addition only trivial cycles involving A arise between any two FDs one of which functionally determines A. We show that weak satisfaction of FDs is additive if and only if the set F of FDs is monodependent and that monodependence can be checked in time polynomial in the size of F. Received: 8 December 1993 / 9 November 1995     

Mining functional dependencies from data

In this paper, we propose an efficient rule discovery algorithm, called FD_Mine, for mining functional dependencies from data. By exploiting Armstrong’s Axioms for functional dependencies, we identify equivalences among attributes, which can be used to reduce both the size of the dataset and the number of functional dependencies to be checked. We first describe four effective pruning rules that reduce the size of the search space. In particular, the number of functional dependencies to be checked is reduced by skipping the search for FDs that are logically implied by already discovered FDs. Then, we present the FD_Mine algorithm, which incorporates the four pruning rules into the mining process. We prove the correctness of FD_Mine, that is, we show that the pruning does not lead to the loss of useful information. We report the results of a series of experiments. These experiments show that the proposed algorithm is effective on 15 UCI datasets and synthetic data.     

A feasible intrusion detector for recognizing IIS attacks based on neural networks

Most activities on the Internet can be recorded as log files of websites and website administrators can inspect log files to locate problems after any network intrusion occurs. However, since log files usually contain a huge quantity of data, without effective methods, it is generally not feasible for administrators to determine the concealed meanings within log files. One method for dealing with this issue is to use neural networks; this is an effective means to distinguish and classify abnormal data in log files, thus alleviating the administrator's burden. This paper presents the results of a study on intrusion detection on IIS (Internet information services) utilizing a hybrid intrusion detection system (IDS). The feasibility of the hybrid IDS is validated based on the Internet scanner system (ISS). In the intrusion detection system proposed, we used four different training data sets: 200, 800, 1400, and 2000. The system is trained either by Taguchi's experimental design or full factorial experimental design under different training data sets; the former can save much more time than the latter. Under Taguchi's experimental design, the best results are obtained when the training data set is of size 1400; overall accuracy in this case is 97.5%. On the contrary, for the full factorial experimental design, the best results are reached when the training data set is of size 2000; overall accuracy is 97.6%. Our study indicates that when to retrain the detector and how much time to allow for this training fully depend on the downgrade percentage of the detection rate, which determines the size of the retraining data set. To reduce the void time for updating the detector, the downgrade percentage should be restricted.     

一个多时间粒度下时态函数依赖的有限属性闭包算法

为了有效地进行时态数据库设计,支持多时间粒度的时态函数依赖(TFDs)被用于时态模式的规范化．时态模式规范化所要解决的一个关键问题是求解时态函数依赖的有限属性闭包问题．由于多时间粒度的使用,使得有限属性闭包问题变得非常复杂．实际上,TFDs与传统的函数依赖(FDs)之间存在着密切的联系．通过分析这些联系和封闭时态类型集的特性,利用传统FDs的相关算法提出一个有效的求解有限属性闭包的算法．通过分析和与相关算法的实验比较,该算法更加有效．     

k-匿名方法中准标识符的求解算法

k-匿名是保证视图安全的一种主要手段,如何找出正确的准标识符对k-匿名方法的有效性具有重要意义.针对这一问题,分析了不存在函数依赖和存在函数依赖两种情况下准标识符的组成特征,即当不存在函数依赖时,准标识符由视图间的公共属性组成,当存在函数依赖时,准标识符由视图间的公共属性和秘密信息包含的函数依赖关系的前件属性组成,在此基础上,给出了准标识符的通用求解算法,并用实验证明了算法的有效性和正确性.     

Computing unique canonical covers for simple FDs via transitive reduction

Although there is a rich body of research on dependency theory, only few results concerning simple functional dependencies (FDs) have been published. In this paper, the following key results regarding simple FDs are shown. First, given an acyclic set F of simple FDs there exists exactly one canonical cover for F. Second, this uniquely determined canonical cover can be computed via transitive reduction. Third, it is shown how a uniquely determined canonical cover can be fixed in case of arbitrary simple FDs via transitive reduction.     

LR最小替换集求解算法研究

文中对Ｄ．Ｍａｉｅｒ提出的关于关系数据库中的ＬＲ最小集的结构进行了分析，提出了一个比“ＬＲ最小集”更为简化的ＦＤ集的覆盖－ＬＲ最小替换集。给出了一个求ＬＲ最小替换集的多项式时间算法。修正了Ｄ．Ｍａｉｅｒ在其文中给出的一个ＦＤ集为最优覆盖的必要条件。     

An improvement on the automatic tool for relational database design

This paper corrects some misconceptions regarding an automatic tool for relational database design. A modified algorithm (SYNTHESIZER+) from the synthesis algorithm SYNTHESIZER is presented. For a given set of FDs, it can produce a third normal form (3NF) relational database schema with a minimum number of relations.     

Maintenance of a Piercing Set for Intervals with Applications

We show how to maintain efficiently a minimum piercing set for a set S of intervals on the line, under insertions and deletions to/from S. A linear-size dynamic data structure is presented, which enables us to compute a new minimum piercing set following an insertion or deletion in time O(c( S) log |S|), where c (S) is the size of the new minimum piercing set. We also show how to maintain a piercing set for S of size at most (1+?)c (S), for 0 < ? ≤ 1 , in $\bar O$ ((log |S|)/?) amortized time per update. We then apply these results to obtain efficient solutions to the following three problems: (i) the shooter location problem, (ii) computing a minimum piercing set for arcs on a circle, and (iii) dynamically maintaining a box cover for a d -dimensional point set.     

Clique-perfectness and balancedness of some graph classes

A graph is clique-perfect if the maximum size of a clique-independent set (a set of pairwise disjoint maximal cliques) and the minimum size of a clique-transversal set (a set of vertices meeting every maximal clique) coincide for each induced subgraph. A graph is balanced if its clique-matrix contains no square submatrix of odd size with exactly two ones per row and column. In this work, we give linear-time recognition algorithms and minimal forbidden induced subgraph characterizations of clique-perfectness and balancedness of P₄-tidy graphs and a linear-time algorithm for computing a maximum clique-independent set and a minimum clique-transversal set for any P₄-tidy graph. We also give a minimal forbidden induced subgraph characterization and a linear-time recognition algorithm for balancedness of paw-free graphs. Finally, we show that clique-perfectness of diamond-free graphs can be decided in polynomial time by showing that a diamond-free graph is clique-perfect if and only if it is balanced.     

Deciding implication for functional dependencies in complex-value databases

Modern applications increasingly require the storage of data beyond relational structure. The challenge of providing well-founded data models that can handle complex objects such as lists, sets, multisets, unions and references has not been met yet in a completely satisfactory way. The success of such data models will greatly depend on the existence of automated database design techniques that generalise achievements from relational databases. In this paper, we study the implication problem of functional dependencies (FDs) in the presence of records, sets, multisets and lists. Database schemata are defined as nested attributes, database instances as nested relations and FDs are defined in terms of subattributes of the database schema. The expressiveness of FDs deviates fundamentally from previous approaches in different data models including the nested relational data model and XML.     

粗集理论在空中目标威胁等级判断中的应用

针对目标进行威胁等级判断时,由于获得的空中目标属性信息的不完全性和不确定性带来的决策困难问题,采用把粗糙集理论引入到空战决策系统中,根据空战冗余信息是可以约简的结论,提出了一种利用粗糙集理论约简求取规则的决策算法。应用SOM网络离散化决策系统输入数据的连续属性值,利用粗集数据分析方法,从数据中提取出规则将输入映射到输出的子空间。通过粗集数据挖掘后提取的规则,不仅规则数目减少,且规则是不完全规则,因此特别适合对空战信息的融合。     

High-capacity PVO-based reversible data hiding scheme using changeable step size

Reversible data hiding (RDH) algorithm based on pixel-value-ordering (PVO) has received widespread attention because of its excellent performance. PVO algorithm divides the host image into non-overlapped equal-sized blocks, then achieves data embedding by modifying the maximum and minimum values of each block. Every pixel block can be a host of watermark data, so the smaller number of pixel blocks limit the embedding capacity (EC). In our work, a novel PVO with changeable step size (CPVO) is presented which can choose suitable step size based on the number of watermark data bits, even that allow one block to overlap other ones. Take the block size 2 × 2 as an example, we can set step size 2 × 1 or another one in CPVO. Consequently, with a block selection skill based on the noise level (NL) of a pixel block, CPVO can embed more hidden data bits into a host image. Compared to the original PVO-based schemes, experimental results show that our proposed scheme increases the EC by 2 ～ 3 times, and the marked image quality keeps much higher, even outperforms some other state-of-the-art works in some test images.