Randomization of classical inference patterns and its application

By means of randomization, the concept of D-randomized truth degree of formulas in two-valued propositional logic is introduced, and it is proved that the set of values of D-randomized truth degree of formulas has no isolated point in [0,1]. The concepts of D-logic pseudo-metric and D-logic metric space are also introduced and it is proved that there is no isolated point in the space. The new built D-randomized concepts are extensions of the corresponding concepts in quantified logic. Moreover, it is proved that the basic logic connectives are continuous operators in D-logic metric space. Lastly, three different types of approximate reasoning patterns are proposed.     

Application of optical proximity correction technology

As process technology scales down to very deep sub-micron （VDSM） in semiconductor manufacturing technology, intrinsic size becomes close to or even shorter than the wavelength used for optical lithography. Thus, some distortions and deformations are introduced by optical proximity effects （OPE） mainly caused by the diffraction and interference of exposure light when layout patterns on a mask are transcribed to a wafer, which influence on the yield and performance of IC circuit. In order to compensate for the deformations, optical proximity correction （OPC） is the most commonly used methodology. Presently, the OPC method is to use a unitary toleration on the whole chip layer, which makes the run time of OPC algorithm longer, causes the size of GDSII files to follow exponential growth, and results in the cost of making mask grow immensely. Firstly, this paper proposes a selfadaptation OPC method with preprocessing function of patterns classification. According to the need of the correction precision, the OPC system divides patterns corrected into two groups with different toleration： critical patterns and general patterns, which enhance the efficiency of the OPC approach. Secondly, a model-based OPC method is presented based on pattern subsection and classifi- cation, which keeps the precision of the correction as well as enhances the efficiency. We also propose a rule-based OPC method with general, concise and complete correction rules, and achieve automatic-built rules-based and its looking-up. Thirdly, we also implement an OPC system, called MR-OPC; the MR-OPC system integrates both rule-based OPC and model-based OPC into a whole, so it can solve the confliction between the efficiency and precision. Experimental results show that the MR-OPC system we suggested has advantages of the efficiency and expansibility.     

Electrocardiogram (ECG) pattern modeling and recognition via deterministic learning

A method for electrocardiogram （ECG） pattern modeling and recognition via deterministic learning theory is presented in this paper. Instead of recognizing ECG signals beat-to-beat, each ECG signal which contains a number of heartbeats is recognized. The method is based entirely on the temporal features （i.e., the dynamics） of ECG patterns, which contains complete information of ECG patterns. A dynamical model is employed to demonstrate the method, which is capable of generating synthetic ECG signals. Based on the dynamical model, the method is shown in the following two phases： the identification （training） phase and the recognition （test） phase. In the identification phase, the dynamics of ECG patterns is accurately modeled and expressed as constant RBF neural weights through the deterministic learning. In the recognition phase, the modeling results are used for ECG pattern recognition. The main feature of the proposed method is that the dynamics of ECG patterns is accurately modeled and is used for ECG pattern recognition. Experimental studies using the Physikalisch-Technische Bundesanstalt （PTB） database are included to demonstrate the effectiveness of the approach.     

Structure and Application pf WAV File

As regards audio digitization, the researcher introduced several computer process means of audio information, and then, presented application patterns based on WAV file after analyzing thoroughly the structure of the widely used WAV File in computer application field.     

Efficient Mining of Frequent Closed XML Query Pattern

Previous research works have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent but only the closed ones because the latter leads to not only more compact yet complete result set but also better efficiency. Upon discovery of frequent closed XML query patterns, indexing and caching can be effectively adopted for query performance enhancement. Most of the previous algorithms for finding frequent patterns basically introduced a straightforward generate-and-test strategy. In this paper, we present SOLARIA＊, an efficient algorithm for mining frequent closed XML query patterns without candidate maintenance and costly tree-containment checking. Efficient algorithm of sequence mining is involved in discovering frequent tree-structured patterns, which aims at replacing expensive containment testing with cheap parent-child checking in sequences. SOLARIA＊ deeply prunes unrelated search space for frequent pattern enumeration by parent-child relationship constraint. By a thorough experimental study on various real-life data, we demonstrate the efficiency and scalability of SOLARIA＊ over the previous known alternative. SOLARIA＊ is also linearly scalable in terms of XML queries＇ size.     

Implementation of Interference Checking Based on Construction Space Concept

Methods of interference checking in NC programming are briefly discussed. A new approach for interference detection in 3-axis NC machining of sculpture surface based on the concept of construction space is introduced. The space is firstly divided into millable space and gouge one and then the toolpath segments in the gouge space are checked and eliminated. The algorithm described in this paper is stable and reliable, and is suitable for ball-end，round-end and flat-end cutters.     

Experimental Studies of Artificial Conscious Systems

Human consciousness is the most interesting and mysterious phenomenon in the world.In this paper,the results of the computational study and simulation of the conscious behaviour,such as the learning of language and image patterns,traditional conditioning,association,imagination and dream,have been presented.Based on these results,an experimental conscious systekm-CONSCITRON,has been developed.Further discussion on development of artificial conscious systems is also provided.     

Analyzing Sequential Patterns in Retail Databases

Finding correlated sequential patterns in large sequence databases is one of the essential tasks in data mining since a huge number of sequential patterns are usually mined, but it is hard to find sequential patterns with the correlation. According to the requirement of real applications, the needed data analysis should be different. In previous mining approaches, after mining the sequential patterns, sequential patterns with the weak affinity are found even with a high minimum support. In this paper, a new framework is suggested for mining weighted support affinity patterns in which an objective measure, sequential ws-confidence is developed to detect correlated sequential patterns with weighted support affinity patterns. To efficiently prune the weak affinity patterns, it is proved that ws-confidence measure satisfies the anti-monotone and cross weighted support properties which can be applied to eliminate sequential patterns with dissimilar weighted support levels. Based on the framework, a weighted support affinity pattern mining algorithm （WSMiner） is suggested. The performance study shows that WSMiner is efficient and scalable for mining weighted support affinity patterns.     

Synchro-control of twin-rudder with cloud model

In ships having two rudders, an angle error exists if there is a difference in structural and electrical parameters in two steering gear systems. Such an error also results in reduced efficiency of ship maneuverability during navigation. For the sake of reducing the angle error, a synchro-ballistic control approach based on cloud model is proposed in this paper. First, the mechanism model of steering gear system is introduced. Second, the structure of synchro-control system of twin-rudder is proposed based on the master-slave control strategy. Third, synchro-ballistic controller based on cloud model is designed to solve the nonlinearity and uncertainty of system. Finally, the designed controller is tested via simulation under two different situations. The simulated results demonstrate that this method is simple and has stronger robustness against the variation of states and parameters of plants. Hence, the validity and reliability of the method is proved for synchro-control of two rudders, which is a significant engineering application.     

An Attack-Finding Algorithm for Security Protocols

This paper proposes an automatic attack construction algorithm in order to find potential attacks on ecurity protocols.It is based on a dynamic strand space model,which enhances the original strand space model by introducing active nodes on strands so as to characterize the dynamic procedure of protocol execution.With exact causal dependency relations between messages considered in the model,this algorithm can avoid state space explo-sion caused by asynchronous composition.In order to get a finite state space,a new method called strand-added on demand is exploited,which extends a bundle in an incremental manner without requiring explicit configuration of protocol execution parameters.A finer granularity model of term structure is also introduced, in which subterms are divided into check subterms and data subterms .Moreover,data subterms can be further classified based on the compatible data subterm relation to obtain automatically the finite set of valid acceptable terms for an honest principal.In this algorithm,terms core is designed to represent the intruder‘s knowledge compactly,and forward search technology is used to simulate attack patterns easily.Using this algorithm,a new attack on the Dolve-Yao protocol can be found,which is even more harmful beeause the secret is revealed before the session terminates.     

Mining hybrid sequential patterns and sequential rules

The problem addressed in this paper is to discover the frequently occurred sequential patterns from databases. Basically, the existing studies on finding sequential patterns can be roughly classified into two main categories. In the first category, the discovered patterns are continuous patterns, where all the elements in the pattern appear in consecutive positions in transactions. The second category is to mine discontinuous patterns, where the adjacent elements in the pattern need not appear consecutively in transactions. Although there are many researches on finding either kind of patterns, no previous researches can find both of them. Neither can they find the discontinuous patterns formed of several continuous sub-patterns. Therefore, we define a new kind of patterns, called hybrid pattern, which is the combination of continuous patterns and discontinuous patterns. In this paper, two algorithms are developed to mine hybrid patterns, where the first algorithm is easy but slow while the second complicated but much faster than the first one. Finally, the simulation result shows that our second algorithm is as fast as the currently best algorithm for mining sequential patterns.     

基于二进制表示的事务属性挖掘方法

在关联规则数据挖掘中采用二进制系统易于产生冗余模式。该文提出一种基于二进制事务属性层次划分的两级数据挖掘方法,即MLADM算法。该算法通过高层次模式获取最大可能频繁模式集,在低层次模式中对其进行验证,优先获得长频繁模式。实验结果表明,该算法可以在密集数据集中有效挖掘长模式并避免冗余模式。     

基于单元故障模型的树型加法器的测试

首先分析了树型加法器的原理，总结了其运算特性．其次在介绍单元故障模型的基础上分析了树型加法器的测试向量生成．分析结果表明，5n-1个测试向量可以实现树型加法器中所有单元故障的检测．这些测试向量具有很好的规则性，能够利用片上测试向量生成器实现，适合于应用内建自测试技术测试．基于此，作者提出了一种内建自测试的测试结构，测试时只需存储7个籽测试向量，其它测试向量可以在这7个籽测试向量的基础上通过循环移位实现．最后给出了实验分析结果．     

设计模式在Web应用程序中的应用

主要讨论MVC模式及其两种扩展模式在构建Web应用程序中的应用。通过实例说明正确运用设计模式对于构建复杂web应用程序的意义;同时,针对当前最为成功的两种Web应用程序开发平台：ASP．Net和Struts,分析了它们对设计模式的支持和实现。     

新疆民间艺术图案数字化技术

目的:解决如何进行数字化具有民族风格的图案纹样是一个富有挑战的问题.方法:以新疆民族民间织物图案的数字化设计为实例,提出一套研究织物图案的计算机辅助设计方案.首先,分割织物图案,抽取图案基本元素,构成多级图案基元库;然后采用路径、图层、画笔预设、区域选择及多方案组合的设计技术,实现基于PhotoShop的织物图案设计方...     

频繁模式溯源

数据起源是关于数据来源、转换和更新过程的研究。基于频繁模式挖掘的性质和特点,提出了FP+树来记录频繁模式来源。给出了频繁模式溯源的相关理论和证明,根据不同追溯机制提出了三种频繁模式溯源方法,并对方法的正确性和执行代价给出了理论证明和推导。在进行频繁模式挖掘时,在不增加额外负担的情况下实现了频繁模式溯源。针对条件FP+树结构特点和频繁模式性质,提出了采用α-剪枝求解条件FP+树的投影操作,加快了频繁模式挖掘和数据溯源的执行效率。实验结果显示,采用基于FP+树的频繁模式溯源方法,可以高效地实现频繁模式溯源,并且条件FP+树的α-剪枝策略的有效性得到验证。     

模糊语义模式及其在汉英机译系统英文生成选词中的应用

研究生成选词问题对改善机翻系统的翻译质量有重要意义, 基于语义模式的选词方法是常用的选词方法, 在混合选词模型也扮演了重要角色。本文针对该方法的不足, 提出了语义模式自动获取的思路和模糊语义模式的概念, 对其进行了改进。采用语义模式自动获取的思路可以克服传统手工方法需要巨大工作量的问题, 而模糊语义模式概念的提出则使语义模式能表示语言现象的量化差别。文中首先讨论该研究的重要性, 然后介绍了模糊语义模式的概念, 接着给出了构建模糊语义模式库时使用的一个训练算法, 最后给出了应用模糊语义模式进行选词的具体算法并将它与传统算法进行了比较。     

Concept formation in design

This paper presents a computationally tractable view on where simple design concepts come from by proposing a paradigm for the formation of design concepts based on the emergence of patterns in the representation of designs. It is suggested that these design patterns form the basis of concepts. These design patterns once learned are then added to the repertoire of known patterns so that they do not need to be learned again. This approach uses the notion called the `loosely-wired brain'. This paper elaborates on this idea primarily through implemented examples drawn from the genetic engineering of evolutionary systems, and the qualitative representation of shapes and their multiple representations.     

基于显露模式的对比挖掘研究及应用进展

对比挖掘是近年来数据挖掘领域的新热点之一。对比挖掘关注并描述不同类别和条件下,或随时间变化的知识,旨在设计能够发现刻画数据集中不同类别或条件的样本间差异的模式或模型的方法。由于对比挖掘技术能化繁为简、准确分类,在实践中得到广泛应用。显露模式的挖掘和应用是对比挖掘的重要分支。综述了显露模式的背景、基本概念和原理,分析了显露模式的挖掘方法,讨论了显露模式的扩展定义和挖掘,介绍了基于显露模式的分类器构造方法,展示了显露模式的若干实际应用,展望了基于显露模式的对比挖掘的未来研究。     

Deterministic Learning and Rapid Dynamical Pattern Recognition

Recognition of temporal/dynamical patterns is among the most difficult pattern recognition tasks. In this paper, based on a recent result on deterministic learning theory, a deterministic framework is proposed for rapid recognition of dynamical patterns. First, it is shown that a time-varying dynamical pattern can be effectively represented in a time-invariant and spatially distributed manner through deterministic learning. Second, a definition for characterizing similarity of dynamical patterns is given based on system dynamics inherently within dynamical patterns. Third, a mechanism for rapid recognition of dynamical patterns is presented, by which a test dynamical pattern is recognized as similar to a training dynamical pattern if state synchronization is achieved according to a kind of internal and dynamical matching on system dynamics. The synchronization errors can be taken as the measure of similarity between the test and training patterns. The significance of the paper is that a completely dynamical approach is proposed, in which the problem of dynamical pattern recognition is turned into the stability and convergence of a recognition error system. Simulation studies are included to demonstrate the effectiveness of the proposed approach