Energy data base.

Mode of access: Internet.

Aeration of sewage lagoons, reservoirs, and streams : citations from the NTIS data base : search period covered, 1964 - March 1976.

Prepared by information specialists at NTIS; Edward J. Lehmann, editor.

Solar energy collectors and concentrators : citations from the NTIS data base.

Inserted bibliographic data sheet designates Audrey S. Hundemann as "editor."

Manual of acute toxicity : interpretation and data base for 410 chemicals and 66 species of freshwater animals /

Mode of access: Internet.

A data base management approach to Privacy Act compliance /

Includes bibliographical references (p. 17-19).

The National Geographic Names Data Base :

Mode of access: Internet.

Rules for mapping a conceptual model onto various data base management systems. Available in 2 volumes.

The design and implementation of data bases involve, firstly, the formulation of a conceptual data model by systematic analysis of the structure and information requirements of the organisation for which the system is being designed; secondly, the logical mapping of this conceptual model onto the data structure of the target data base management system (DBMS); and thirdly, the physical mapping of this structured model into storage structures of the target DBMS. The accuracy of both the logical and physical mapping determine the performance of the resulting systems. This thesis describes research which develops software tools to facilitate the implementation of data bases. A conceptual model describing the information structure of a hospital is derived using the Entity-Relationship (E-R) approach and this model forms the basis for mapping onto the logical model. Rules are derived for automatically mapping the conceptual model onto relational and CODASYL types of data structures. Further algorithms are developed for partly automating the implementation of these models onto INGRES, MIMER and VAX-11 DBMS.

Computer-aided tool for the teaching of relational algebra in data base courses

This article describes the design and implementation of computer-aided tool called Relational Algebra Translator (RAT) in data base courses, for the teaching of relational algebra. There was a problem when introducing the relational algebra topic in the course EIF 211 Design and Implementation of Databases, which belongs to the career of Engineering in Information Systems of the National University of Costa Rica, because students attending this course were lacking profound mathematical knowledge, which led to a learning problem, being this an important subject to understand what the data bases search and request do RAT comes along to enhance the teaching-learning process.It introduces the architectural and design principles required for its implementation, such as: the language symbol table, the gramatical rules and the basic algorithms that RAT uses to translate from relational algebra to SQL language. This tool has been used for one periods and has demonstrated to be effective in the learning-teaching process.  This urged investigators to publish it in the web site: www.slinfo.una.ac.cr in order for this tool to be used in other university courses.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Power systems reliability calculation based on fuzzy data mining

This paper presents a methodology supported on the data base knowledge discovery process (KDD), in order to find out the failure probability of electrical equipments’, which belong to a real electrical high voltage network. Data Mining (DM) techniques are used to discover a set of outcome failure probability and, therefore, to extract knowledge concerning to the unavailability of the electrical equipments such us power transformers and high-voltages power lines. The framework includes several steps, following the analysis of the real data base, the pre-processing data, the application of DM algorithms, and finally, the interpretation of the discovered knowledge. To validate the proposed methodology, a case study which includes real databases is used. This data have a heavy uncertainty due to climate conditions for this reason it was used fuzzy logic to determine the set of the electrical components failure probabilities in order to reestablish the service. The results reflect an interesting potential of this approach and encourage further research on the topic.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Exploração de dados de uma solução mobile wallet usando as técnicas de data mining

A descoberta de conhecimento em dados hoje em dia é um ponto forte para as empresas. Atualmente a CardMobili não dispõe de qualquer sistema de mineração de dados, sendo a existência deste uma mais-valia para as suas operações de marketing diárias, nomeadamente no lançamento de cupões a um grupo restrito de clientes com uma elevada probabilidade que os mesmos os utilizem. Para isso foi analisada a base de dados da aplicação tentando extrair o maior número de dados e aplicadas as transformações necessárias para posteriormente serem processados pelos algoritmos de mineração de dados. Durante a etapa de mineração de dados foram aplicadas as técnicas de associação e classificação, sendo que os melhores resultados foram obtidos com técnicas de associação. Desta maneira pretende-se que os resultados obtidos auxiliem o decisor na sua tomada de decisões.

Integração da área de negócio de retalho do grupo Riopele no Data Warehouse corporativo

Dissertação de mestrado integrado em Engenharia e Gestão de Sistemas de Informação

A reestruturação da fracção medieval da base de dados descritiva da Colecção Cronológica do Arquivo Distrital de Braga

Relatório de estágio de mestrado em História