Quality evaluation methods – a review

Quality is understood as a set of features that determine how a product fits to satisfy certain needs. Therefore, a set of measurements X1, X2,…, Xn characterizes each product, and also serves as information in evaluation of product\u27s quality. Individual measurements Xi are quantitative (numerical) or qualitative (non-numerical) variables expressing the value of the ith index of quality. Evaluation of the overall level of quality, comparison of similar products, measuring and reporting quality improvement and other related problems need construction of some integral quality index Q in which all individual measurements are taken into account. Several proposals for integral quality indices, such as differential approach, weighted means, mixed method, generalized index, algorithmic methods as KORTER, and PATTERN, and a multiplicative integral index are considered. A brief discussion of the properties of each approach is provided, Advantages and disadvantages are pointed out. Examples of how to find the product that exhibits the best fit to its multivariate quality index, and how to rate products according to their quality in a set of similar products are briefly shown

Semantic Notation and Retrieval in Art and Architecture Image Collections

In this paper we analyze various methods used for semantic annotation and search in a collection of art and architecture images. We discuss the Art and Architecture Thesaurus, WordNet, ULAN and Iconclass ontology. Systems for searching and retrieval art and architecture image collections are presented. We explore if the MPEG 7 descriptors are useful for art and architecture image annotations. For illustrations we use images from Antoni Gaudi architecture and Claude Monet paintings

The BALM copula

The class of probability distributions possessing the almost-lack-of-memory property appeared about 20 years ago. It reasonably took place in research and modeling, due to its suitability to represent uncertainty in periodic random environment. Multivariate version of the almost-lack-of-memory property is less known, but it is not less interesting. In this paper we give the copula of the bivariate almost-lack-of-memory (BALM) distributions and discuss some of its properties and applications. An example shows how the Marshal-Olkin distribution can be turned into BALM and what is its copula

Local Dependence Structure of the Bivariate Normal Distribution

In several previous publications we developed an idea how probability tools can be used to measure strength of dependence between random events. In this talk we use it for measuring magnitude of local dependence inside the normally distributed random variables, using the regression coefficients in case of random events. Short illustrations (graphics and tables) are showing the use of these measures in already known popular Bivariate Normal distribution with different correlation values

On Revelation Transforms that Characterize Probability Distributions

A characterization of exponential, geometric and of distributions with almost-lack-of-memory property, based on the revelation transform of probability distributions and relevation of random variables is discussed. Known characterizations of the exponential distribution on the base of relevation transforms given by Grosswald et al. [4], and Lau and Rao [7] are obtained under weakened conditions and the proofs are simplified. A characterization the class of almost-lack-of-memory distributions through the relevation is specified

Transfer of Global Measures of Dependence into Cumulative Local

We explore an idea of transferring some classic measures of global dependence between random variables X1,X2,…,Xn into cumulative measures of dependence relative at any point (X1,X2,…,Xn) in the sample space. It allows studying the behavior of these measures throughout the sample space, and better understanding and use of dependence. Some examples on popular copula distributions are also provided

Some Issues in the Art Image Database Systems

In this paper we illustrate several aspects of art databases, such as: the spread of the multimedia art images; the main characteristics of art images; main art images search models; unique characteristics for art image retrieval; the importance of the sensory and semantic gaps. In addition, we present several interesting features of an art image database, such as: image indexing; feature extraction; analysis on various levels of precision; style classification. We stress color features and their base, painting analysis and painting styles. We study also which MPEG-7 descriptors are best for fine painting images retrieval. An experimental system is developed to see how these descriptors work on 900 art images from several remarkable art periods. On the base of our experiments some suggestions for improving the process of searching and analysis of fine art images are given