视频文字信息检查工具的设计与实现

针对某些特定视频中,画面文字信息经常包含较为敏感文字信息,导致信息泄露,设计实现了一种视频画面中的文字的检测识别系统,对视频画面中的文字标语、文字条幅,新闻画面中的文字导语等信息进行识别与比对。采用基于双阈值的视频镜头分割算法,根据颜色直方图信息提取关键帧,采用最大稳定极值区域算法提取图像中稳定区域,通过聚类和级联分类器实现文字区域提取,最后将文字区域分割后进行OCR识别,实验表明,设计的系统针对复杂背景中的文字能够达到较高的检测识别率。     

Chemical characterization of ancient potteries from Himera and Pestavecchia necropolis (Sicily, Italy) by Inductively Coupled Plasma–Optical Emission Spectrometry (ICP–OES)

Thirty-eight samples of pottery were analyzed for determining chemical composition in order to establish their provenance. The potteries tested in the present research come from Himera and Pestavecchia archaeological sites. After digestion in microwave oven, the samples have been analyzed for fourteen minor elements (Ba, Cd, Co, Cr, Cu, Ga, Li, Mn, Ni, Pb, Sr, Ti, Tl, and Zn) and six major elements (Al, Ca, Fe, K, Mg, and Na). Chemical analysis was carried out by Inductively Coupled Plasma–Optical Emission Spectroscopy (ICP–OES). The most abundant minor elements are Cr, Ba and Ni. Cr concentration ranged from 66 to 3635 mg kg^{− 1}, Ba concentration ranged from 388 to 2677 mg kg^{− 1} and Ni concentration ranged from 35 to 1758 mg kg^{− 1}. The relative standard deviation (RSD) of the replicates on the concentrations of analyzed metals ranged from 0.07% to 14%.The aim of this study is to assign the local or non-local provenance of the examined potteries, in particular validating and clarifying archaeological hypothesis based on the simple visual examination and stylistic characterization of ceramic objects. Principal component analysis performed on the dataset, together with the application of cluster technique and non statistical analysis, allowed the identification of three main groups of samples and a lonely one (R 97). In particular, sample R 97 shows high Cr concentration (3635 mg kg^{− 1}) and high Ni concentration (1758 mg kg^{− 1}), typical of Corinthian pottery. The results of chemical analysis show that the stylistic features are not always sufficient to correctly identify the origin of a ceramic object.     

Some robust objectives of FCM for data analyzing

There are many data clustering techniques available to extract meaningful information from real world data, but the obtained clustering results of the available techniques, running time for the performance of clustering techniques in clustering real world data are highly important. This work is strongly felt that fuzzy clustering technique is suitable one to find meaningful information and appropriate groups into real world datasets. In fuzzy clustering the objective function controls the groups or clusters and computation parts of clustering. Hence researchers in fuzzy clustering algorithm aim is to minimize the objective function that usually has number of computation parts, like calculation of cluster prototypes, degree of membership for objects, computation part for updating and stopping algorithms. This paper introduces some new effective fuzzy objective functions with effective fuzzy parameters that can help to minimize the running time and to obtain strong meaningful information or clusters into the real world datasets. Further this paper tries to introduce new way for predicting membership, centres by minimizing the proposed new fuzzy objective functions. And experimental results of proposed algorithms are given to illustrate the effectiveness of proposed methods.     

Algorithms for fair k-clustering with multiple protected attributes

We study fair center based clustering problems. In an influential paper, Chierichetti, Kumar, Lattanzi and Vassilvitskii (NIPS 2017) consider the problem of finding a good clustering, say of women and men, such that every cluster contains an equal number of women and men. They were able to obtain a constant factor approximation for this problem for most center based k-clustering objectives such as k-median, k-means, and k-center. Despite considerable interest in extending this problem for multiple protected attributes (e.g. women and men, with or without citizenship), so far constant factor approximations for these problems have remained elusive except in special cases. We settle this question in the affirmative by giving the first constant factor approximation for a wide range of center based k-clustering objectives.     

ANFIS训练参数设置研究

针对自适应神经模糊推理系统的特点,分析了其两种建模方式的优缺点,并最终选择了采用减法聚类算法进行建模.进一步地,针对ANFIS的减法聚类算法4个训练参数初始值的设置问题,采用一多峰函数对其进行了研究,分析了预测结果随该4个参数调节而变化的特点.     

普适的基于能量的分块局域激发态聚类算法

在普适的基于能量的分块(GEBF)方法的框架下,大体系的局域激发(LE)能可通过一系列活性子体系激发能的线性组合近似得到,从而有效降低了计算的时间标度.然而,在体系的局域激发具有多个激发态的情形下,如何有效识别所有活性子体系的激发特征并将其组合是一个挑战.提出了一种基于局域激发态聚类的算法.该方案基于空穴-电子分析和基于密度的聚类(DBSCAN)机器学习算法,可以自动地聚合不同子体系中最相似的激发态并组合得到相应的局域激发态能量或激发能.结合该算法改进的LE-GEBF方法在荧光分子衍生物、荧光染料-水团簇及绿色荧光蛋白模型体系的计算中均获得了令人满意的结果.该算法有望大大提升LE-GEBF方法在计算局域激发时的稳定性和准确性,并可以有效处理吸收光谱具有多重峰的大体系.     

入侵检测的CPN改进算法的研究

结合神经网络方法,对入侵检测技术的聚类分析方法进行了研究和分析,探讨了在传统的对偶传播神经网络（Counter Propagation Networks,CPN）的基础上,引入基因表达式编程（Gene Expression Programming,GEP）对聚类进行优化,提出一种应用于入侵检测的CPN改进算法,该方法融...     

Min-cut clustering

We describe a decomposition framework and a column generation scheme for solving a min-cut clustering problem. The subproblem to generate additional columns is itself an NP-hard mixed integer programming problem. We discuss strong valid inequalities for the subproblem and describe some efficient solution strategies. Computational results on compiler construction problems are reported.This paper is dedicated to Phil Wolfe on the occasion of his 65th birthday.This research was supported by NSF grants DMS-8719128 and DDM-9115768, and by an IBM grant to the Computational Optimization Center, Georgia Institute of Technology.     

The behaviour of water in poly(dimethylsiloxane)

Experimentally-determined permeation transients do not support the view that the behaviour of water in PDMS is significantly influenced by statistical-mechanical clustering; rather, they suggest that water behaves in a straightforward way. Simple calculations appear to confirm that the incidence of the statistical clustering of water in the polymer is negligible. A diffusion coefficient derived to include the influence of hydrophilic sites within the polymer is partially successful in mathematically reproducing measured quantities. An entropy calculation appears to suggest that the amount of mobile water in PDMS is solely thermally determined; hence the reduction of supposed hydrophilic impurities would probably not lead to a reduction in water permeation. The apparently large difference between the water solubility in PDMS, and that in siloxane liquids, a point of some interest in separation processes, remains unexplained in this paper.     

基于模糊聚类的属性匹配算法

提出了一种基于模糊聚类的属性匹配算法。该算法采用能综合反映属性名称相似性和语义相似性的模糊相似关系,提高了属性匹配的准确率;以等价闭包法对相似属性进行模糊聚类,得到多层次属性分类结果,更客观真实地反映了属性匹配的模糊性;同时,属性匹配过程中不需要设置匹配参数,避免了人为造成的误差。