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6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)最新文献

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Standard and Genetic k-means Clustering Techniques in Image Segmentation 图像分割中的标准和遗传k-均值聚类技术
D. Malyszko, S. Wierzchon
Clustering or data grouping is a key initial procedure in image processing. This paper deals with the application of standard and genetic k-means clustering algorithms in the area of image segmentation. In order to assess and compare both versions of k-means algorithm and its variants, appropriate procedures and software have been designed and implemented. Experimental results point that genetically optimized k-means algorithms proved their usefulness in the area of image analysis, yielding comparable and even better segmentation results.
聚类或数据分组是图像处理的关键初始步骤。本文讨论了标准k-均值聚类算法和遗传k-均值聚类算法在图像分割领域中的应用。为了评估和比较两个版本的k-means算法及其变体,已经设计和实现了适当的程序和软件。实验结果表明,遗传优化的k-means算法在图像分析领域证明了其有效性,产生了相当甚至更好的分割结果。
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引用次数: 47
A Study on the Importance of Biometric Technique Selection in the Protection of Company Resources 生物识别技术选择在企业资源保护中的重要性研究
A. Zajkowska, Wojciech Zimnoch, K. Saeed
In this paper some modern methods of physiological identification of people, the importance of biometrics in company management, and technical resources used in this field are presented. Authors describe the achievements of biometrics and its efficiency in ensuring the security of data and equipment resources from industrial management point of view. Also given the advantages of the solutions that are based on biometric methods, and evidence showing their increasing significance in company activity and its development.
本文介绍了人体生理识别的几种现代方法,生物识别技术在企业管理中的重要性,以及在该领域使用的技术资源。作者从工业管理的角度描述了生物识别技术的成就及其在确保数据和设备资源安全方面的效率。同时考虑到基于生物识别方法的解决方案的优势,以及证据表明它们在公司活动及其发展中日益重要。
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引用次数: 1
Finding a Needle in a Haystack: From Baldwin Effect to Quantum Computation 大海捞针:从鲍德温效应到量子计算
A. Imada
If we want to break someone else's PIN (personal identification number) of, say, an ATM (automated teller machine), how many trials would be necessary when we want to be efficient? This is a sort of what we call a-needle-in-a-hay-stack problem. In 1987, in their wonderful paper, Hinton & Nowlan proposed a genetic algorithm with a needle being a unique configuration of 20-bit binary string while all other configurations being a haystack. What they proposed was to exploit a lifetime learning of individuals in their genetic algorithm, calling it the Baldwin effect in a computer. Since then there has been a fair amount of exploration of this effect, claiming, "this is a-needle-in-a-hay-stack problem, and we've found a more efficient algorithm than a random search." Some of them, however, were found to be the results of an effect of like-to-hear-what-we-would-like-to- hear. In this talk, we will try a bird's eye view on a few examples we have had so far, and how they were explored, including the approach by means of quantum computation which claims, "The steps to find a needle are O(radicN) while those of exhaustive search by a traditional computer are O(N) where N is the number of search points."
如果我们想要破解别人的PIN(个人识别号码),比如说ATM(自动柜员机),要想提高效率,我们需要尝试多少次?这是一种我们称之为大海捞针的问题。1987年,Hinton和Nowlan在他们精彩的论文中提出了一种遗传算法,其中针是20位二进制字符串的唯一配置,而所有其他配置都是干草堆。他们的建议是在遗传算法中利用个体的终身学习,称之为计算机中的鲍德温效应。从那以后,人们对这种效应进行了大量的探索,声称“这是大海捞针的问题,我们已经找到了比随机搜索更有效的算法。”然而,其中一些被发现是“喜欢听我们想听的”效应的结果。在这次演讲中,我们将尝试鸟瞰我们目前为止的几个例子,以及它们是如何被探索的,包括通过量子计算的方法,它声称,“找到一根针的步骤是O(radicN),而传统计算机的穷举搜索是O(N),其中N是搜索点的数量。”
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引用次数: 1
Managing Information on Industrial Automation Projects 管理工业自动化项目信息
J. Jekielek
Today's perpetually improving industrial automation technology brings new equipment, systems, solutions and semantics. Project requirements become greater and the level of complexity, cost, documentation, and humbug tend to increase. Managing information becomes critical for project success. This paper offers solutions based on the use of 'nutshell' learning models that are simplified presentations of complex or vague concepts, designed to accelerate the learning process and extend retention of the acquired knowledge. A brief review of some aspects of automation technologies follows. Some traps and urban myths surrounding industrial projects and automation are unveiled. Needs for integration of technical and nontechnical content, as well as an investment in project's zz hi capital" are stressed. Pragmatic management si__k and practices are pointed out. Case study stories address data integration challenges and lead to a 'meta consulting' concept where technical and non-technical aspects are quickly assessed to form a basis for the powerful, rapid-engagement, priority-based solutions.
当今不断改进的工业自动化技术带来了新的设备、系统、解决方案和语义。项目需求变得更大,复杂性、成本、文档和欺诈的水平趋于增加。管理信息对于项目的成功至关重要。本文提供了基于“果壳”学习模型的解决方案,该模型是复杂或模糊概念的简化表示,旨在加速学习过程并延长所获得知识的保留。下面简要回顾一下自动化技术的一些方面。围绕工业项目和自动化的一些陷阱和城市神话被揭开。强调了技术和非技术内容的整合,以及项目“资本”的投入。指出了务实的管理理念和实践。案例研究故事解决了数据集成的挑战,并导致了“元咨询”的概念,在这个概念中,技术和非技术方面被快速评估,从而形成强大、快速参与、基于优先级的解决方案的基础。
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引用次数: 0
Iris Image Recognition 虹膜图像识别
R. Choras
The authentication of people using iris-based recognition is a widely developing technology. Iris recognition is feasible for use in differentiating between identical twins. Though the iris color and the overall statistical quality of the iris texture may be dependent on genetic factors, the textural details are independent and uncorrelated for genetically identical iris pairs. The feature extraction and classification are heavily based on the rich textural details of the iris.
基于虹膜的身份识别技术是一项正在广泛发展的技术。虹膜识别在区分同卵双胞胎方面是可行的。虽然虹膜颜色和虹膜纹理的总体统计质量可能依赖于遗传因素,但对于遗传相同的虹膜对,纹理细节是独立且不相关的。虹膜的特征提取和分类很大程度上依赖于虹膜丰富的纹理细节。
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引用次数: 3
On Frequency Synchronization of e-Learning Web System Users e-Learning Web系统用户频率同步研究
R. Mosdorf, B. Ignatowska
The aim of the paper was the identification of frequency synchronization phenomenon occurring between different groups of e-learning system users. The changes in time of daily logs of: administration workers, teachers and students have been analyzed. The following analyses: correlation, Fourier and wavelet have been used to identify the nature of data. Basing on the wavelet analysis it has been proposed the new criterion of evaluation of frequency synchronization of two chaotic systems. The modified wavelet power spectrum has been used to identify the frequency synchronization between chaotic behaviors of three groups of users of e-learning web system. Obtained results have shown that the proposed method is useful for analyzing the phenomena of frequency synchronization of user groups of e-learning system.
本文的目的是识别不同群体的电子学习系统用户之间发生的频率同步现象。分析了行政工作人员、教师和学生日常日志的时间变化情况。下面的分析:相关性,傅里叶和小波已被用于识别数据的性质。基于小波分析,提出了两混沌系统频率同步评价的新准则。利用改进的小波功率谱识别了网络学习系统中三组用户混沌行为之间的频率同步性。实验结果表明,该方法可用于分析电子学习系统中用户组频率同步现象。
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引用次数: 1
Finite Difference Runoff Modelling Using "Voronoi Buckets" 基于“Voronoi桶”的有限差分径流模型
M. Dakowicz, C. Gold
Finite difference flow modelling of runoff on a terrain surface has usually been done using a regular grid. This has various disadvantages, as the regular pattern does not conform well to observed features such as watersheds, the runoff pattern is biased to the grid axes, and original data points are lost. We propose a flow modelling method using TIN models. A random Voronoi pattern is added to the original data. This avoids the issues of grid based methods, as there is no axis bias, points may be added anywhere and original data points may be retained. Our flow model simply requires a set of "buckets " to hold the water (the Voronoi cells) and slope information to provide the local runoff rate (the Delaunay edges).
地表径流的有限差分流动模型通常使用规则网格来完成。这有各种缺点,因为规则模式不能很好地符合观测到的特征,如流域,径流模式偏向网格轴,原始数据点丢失。我们提出了一种使用TIN模型的流建模方法。在原始数据中加入一个随机的Voronoi模式。这避免了基于网格方法的问题,因为没有轴偏置,可以在任何地方添加点,并且可以保留原始数据点。我们的流量模型只需要一组“桶”来装水(Voronoi单元)和斜坡信息来提供当地的径流率(Delaunay边缘)。
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引用次数: 2
Mathematical Morphology Based ECG Feature Extraction for the Purpose of Heartbeat Classification 基于数学形态学的心电特征提取及其心跳分类
P. Tadejko, W. Rakowski
The paper presents the classification performance of an automatic classifier of the electrocardiogram (ECG) for the detection abnormal beats with new concept of feature extraction stage. Feature sets were based on ECG morphology and RR-intervals. Configuration adopted a Kohonen self-organizing maps (SOM) for analysis of signal features and clustering. In this study, a classifier was developed with SOM and learning vector quantization (LVQ) algorithms using the data from the records recommended by ANSI/AAMI EC57 standard. This paper compares two strategies for classification of annotated QRS complexes: based on original ECG morphology features and proposed new approach - based on preprocessed ECG morphology features. The mathematical morphology filtering is used for the preprocessing of ECG signal. The problem of choosing an appropriate structuring element of mathematical morphology filtering for ECG signal processing was studied. The performance of the algorithm is evaluated on the MIT-BIH Arrhythmia Database following the AAMI recommendations. Using this method the results of recognition beats either as normal or arrhythmias was improved.
本文介绍了一种基于特征提取阶段的心电图自动分类器在异常心跳检测中的分类性能。特征集基于心电形态和rr区间。配置采用Kohonen自组织映射(SOM)进行信号特征分析和聚类。在本研究中,使用ANSI/AAMI EC57标准推荐的记录数据,使用SOM和学习向量量化(LVQ)算法开发了一个分类器。本文比较了基于原始心电形态学特征和基于预处理心电形态学特征的标注QRS复合体分类策略。采用数学形态学滤波对心电信号进行预处理。研究了心电信号处理中数学形态学滤波结构元素的选择问题。根据AAMI的建议,在MIT-BIH心律失常数据库上对该算法的性能进行了评估。该方法可提高心律失常和正常心律的识别效果。
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引用次数: 80
Support of Decision Making by Business Intelligence Tools 通过商业智能工具支持决策制定
Milena Tvrdíková
Issues of business intelligence applications are discussed. Main parts of business intelligence tools are briefly described. The attention is paid to the data warehouses and to a new tool in this field, to the operational data stores. These technologies enable to get the data of first-rate quality. Some new features of operational data stores' applications are proposed. The role of users in the design of metadata is explained and its influence on the efficiency of information systems is emphasized. Business intelligence tools are the necessary conditions for applications of data mining, an efficient tool for getting new information from large datasets.
讨论了商业智能应用的问题。简要介绍了商业智能工具的主要组成部分。重点是数据仓库和该领域的一个新工具,即操作数据存储。这些技术使获得一流质量的数据成为可能。提出了操作性数据存储应用的一些新特性。解释了用户在元数据设计中的作用,并强调了其对信息系统效率的影响。数据挖掘是一种从大型数据集中获取新信息的有效工具,商业智能工具是数据挖掘应用的必要条件。
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引用次数: 44
Should Normal Distribution be Normal? The Student's T Alternative 正态分布应该是正态分布吗?学生的T选项
A. Bartkowiak
In the paper we try to answer, whether the Gaussian distribution - called widely the 'normal' distribution - is really basic, natural and normal. In particular, we investigate how the above statement conforms with the distribution of real data, namely daily returns of some stock indexes. It was the authors former experience that, when looking at the distributions of real data, it was very difficult to find there a 'normal', i.e. Gaussian distribution. The data, by their nature, are heterogeneous. If so, then the data should be modelled taking into account their possible heterogeneity. This can be done using mixture models - with mixtures composed from finite or infinite number of components. Students' T (univariate or multivariate) is one prominent example of distributions which may be obtained as a mixture of infinitesimal number of Gaussian distributions. The considerations are illustrated by an example of application to financial time series, namely daily returns of the indexes WIG20 and S&P500. We show, why the normality (i.e. 'Gaussianity') should be rejected and why the 't' distribution is plausible.
在本文中,我们试图回答,高斯分布-被广泛称为“正态”分布-是否真的是基本的,自然的和正态的。特别地,我们研究了上述陈述如何符合真实数据的分布,即一些股票指数的日收益。这是作者以前的经验,当观察真实数据的分布时,很难找到一个“正态”分布,即高斯分布。从本质上讲,这些数据是异构的。如果是这样,那么应该对数据进行建模,考虑到它们可能的异质性。这可以通过混合模型来实现,混合模型由有限或无限数量的成分组成。学生的T(单变量或多变量)是分布的一个突出例子,它可以作为无限小数量高斯分布的混合物来获得。通过一个应用于金融时间序列的例子,即WIG20指数和标准普尔500指数的日收益,说明了这些考虑。我们展示了为什么正常(即。“高斯性”)应该被拒绝,为什么“t”分布是可信的。
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引用次数: 12
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6th International Conference on Computer Information Systems and Industrial Management Applications (CISIM'07)
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