Data Flow Analysis and the Linear Programming Model

* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.be

An Approach to Variable Aggregation in Efficiency Analysis

In the nonparametric framework of Data Envelopment Analysis the statistical properties of its estimators have been investigated and only asymptotic results are available. For DEA estimators results of practical use have been proved only for the case of one input and one output. However, in the real world problems the production process is usually well described by many variables. In this paper a machine learning approach to variable aggregation based on Canonical Correlation Analysis is presented. This approach is applied for efficiency estimation of all the farms in Terceira Island of the Azorean archipelago.

Encyclopaedia Slavica Sanctorum: Activity, Users, Statistics

Encyclopaedia slavica sanctorum (eslavsanct.net) is designed as a complex heterogenous multimedia product. It is part of the project Encyclopaedia Slavica Sanctorum: Saints and Holy Places in Bulgaria (in electronic and Guthenberg versions). Until 2013, its web-based platform for online management and presentation of structured digital content has been prepared and numerous materials have been input. The platform is developed using the server technologies PHP, MySQL and HTML, JavaScript, CSS on the client side. The search in the e-ESS can be made by different parameters (12, or combinations of parameters), such as saints’ or feasts’ names, type of sainthood, types of texts dedicated to the saints, dates of saints’ commemorations, and several others. Both guests and registered users can search in the e-ESS but the latter have access to much more information including the publications of original sources. The e-platform allows for making statistics of what have been searched and read. The software used for content and access analysis is BI tool QlikView. As an analysis services provider, it is connected to the e-ESS objects repository and tracking services by a preliminary created data warehouse. The data warehouse is updated automatically, achieving real time analytics solution. The paper discusses some of the statistics results of the use of the e-ESS: the activities of the editors, users, and guests, the types of searches, the most often viewed object, such as the date of January 1 and the article on St. Basil the Great which is one of the richest encyclopaedia articles and includes both matadata and original sources published, both from medieval Slavonic manuscripts and popular culture records.

Analysis and Data Mining of Lead-Zinc Ore Data

This paper presents the results of our data mining study of Pb-Zn (lead-zinc) ore assay records from a mine enterprise in Bulgaria. We examined the dataset, cleaned outliers, visualized the data, and created dataset statistics. A Pb-Zn cluster data mining model was created for segmentation and prediction of Pb-Zn ore assay data. The Pb-Zn cluster data model consists of five clusters and DMX queries. We analyzed the Pb-Zn cluster content, size, structure, and characteristics. The set of the DMX queries allows for browsing and managing the clusters, as well as predicting ore assay records. A testing and validation of the Pb-Zn cluster data mining model was developed in order to show its reasonable accuracy before beingused in a production environment. The Pb-Zn cluster data mining model can be used for changes of the mine grinding and floatation processing parameters in almost real-time, which is important for the efficiency of the Pb-Zn ore beneficiation process. ACM Computing Classification System (1998): H.2.8, H.3.3.

Teaching Statistics to Engineers: Learning from Experiential Data

The purpose of the work is to claim that engineers can be motivated to study statistical concepts by using the applications in their experience connected with Statistical ideas. The main idea is to choose a data from the manufacturing factility (for example, output from CMM machine) and explain that even if the parts used do not meet exact specifications they are used in production. By graphing the data one can show that the error is random but follows a distribution, that is, there is regularily in the data in statistical sense. As the error distribution is continuous, we advocate that the concept of randomness be introducted starting with continuous random variables with probabilities connected with areas under the density. The discrete random variables are then introduced in terms of decision connected with size of the errors before generalizing to abstract concept of probability. Using software, they can then be motivated to study statistical analysis of the data they encounter and the use of this analysis to make engineering and management decisions.