Data Mart para apoio ?? capacita????o em gest??o de pol??ticas p??blicas voltado para uma Escola de Administra????o P??blica

Este trabalho consiste num estudo de caso que se destina ao desenvolvimento de um Data Mart que possibilite a Escola Nacional de Administra????o P??blica ??? ENAP conhecer o perfil e o panorama geral da situa????o funcional dos servidores p??blicos federais que se capacitaram na Escola nos ??ltimos 7 anos. O aplicativo foi desenvolvido cruzando o banco de dados do sistema gerenciador dos cursos ministrados pela ENAP, onde est??o armazenadas informa????es sobre os alunos capacitados, os cursos realizados, os resultados alcan??ados, o perfil dos docentes e demais informa????es relativas ??s atividades da Escola, com os dados gerados pelo Sistema Integrado de Administra????o de Recursos Humanos ??? SIAPE, cuja extra????o de dados foi direcionada para os registros sobre a situa????o funcional, cargos, carreiras, fun????es, ??rg??os e alguns dados pessoais dos alunos, servidores p??blicos federais que se encontram registrados no SIAPE

Balanced scorecard (BSC): uma vis??o metodol??gica para o acompanhamento de sua implementa????o

A Embrapa, na inten????o de operacionalizar a gest??o dos seus planos estrat??gicos (Plano Diretor da Embrapa ??? PDE e Planos Diretores das Unidades ??? PDUs) desenvolveu a metodologia Mogest para a implementa????o do seu Modelo de Gest??o Estrat??gica (MGE), no ??mbito corporativo e de suas 40 unidades de neg??cio, com base na modifica????o do m??todo Balanced Scorecard ??? BSC, de Kaplan. Posteriormente, ap??s a implementa????o dos MGEs, no per??odo de 1999 at?? os dias atuais, inicia-se e desenvolve-se a fase de acompanhamento por meio da elabora????o do m??todo MGE/Acompanha. Este trabalho aborda, de forma modificada, o uso do diagrama elaborado por Norton, apud Coutinho (2002), para acompanhar/avaliar a implementa????o do BSC para uma organiza????o orientada ?? estrat??gia, inserido no m??todo MGE/Acompanha (2000), elaborado pela Equipe MGE e aplicado em uma das unidades de neg??cio da Embrapa. Os resultados mostraram a efici??ncia do m??todo e proporcionaram a internaliza????o do conceito ???painel de bordo???, desenvolvido no software Oracle BSC (OBSC).

The Brazilian Business World: the difficult adaptation to globalization

The article deals with the internationalization of Brazilian businesses in the current decade. In the 1990s, Brazil embraced economic neoliberalism and promoted a huge opening up of its economy. At that time, Brazilian companies had to adapt rapidly. Twenty years later, the country has reinforced its presence in Latin America and has ensured a better position in the global markets, especially by through agricultural exports.

Uso do software Estradas para determinação do espaçamento entre desaguadouros em estradas não pavimentadas do interior de Goiás

Estradas não pavimentadas correspondem a aproximadamente 90% da malha rodoviária brasileira. Estas, na maioria das vezes, são construídas sem a realização de estudos prévios, estando sujeitas a vários tipos de problemas. Um dos principais fatores de deterioração dessas vias é a ineficiência do sistema de drenagem. Neste trabalho simulou-se o espaçamento entre desaguadouros em estradas não pavimentadas, utilizando-se um software desenvolvido com base num modelo matemático de dimensionamento de sistemas de drenagem em estradas não pavimentadas. Utilizaram-se valores de erodibilidade, tensão crítica de cisalhamento e massa específica para diferentes solos de estradas, localizadas no Estado de Goiás. Simularam-se cenários considerando alterações na declividade (1, 5, 10 e 15%) e na seção transversal do canal com relações entre altura e largura de 1:1, 1:2, 1:5 e 1:10. O modelo respondeu sensivelmente às alterações na declividade, na seção transversal do canal e nas de resistência do solo. Os espaçamentos obtidos indicaram que, estradas com declividades inferiores a 5%, mesmo com elevados valores de erodibilidade permitiram espaçamentos viáveis em aspectos construtivos. No entanto, para as declividades de 10 e 15%, os espaçamentos, na maioria dos casos, apresentaram dimensões reduzidas, tornando-se impraticáveis, sendo necessário, nestes casos, proteção do canal ou alteração de suas características hidráulicas.

GUIsurfer: A Reverse Engineering Framework for User Interface Software

GUIsurfer: A Reverse Engineering Framework for User Interface Software

COORDINSPECTOR: a tool for extracting coordination data from legacy code

More and more current software systems rely on non trivial coordination logic for combining autonomous services typically running on different platforms and often owned by different organizations. Often, however, coordination data is deeply entangled in the code and, therefore, difficult to isolate and analyse separately. COORDINSPECTOR is a software tool which combines slicing and program analysis techniques to isolate all coordination elements from the source code of an existing application. Such a reverse engineering process provides a clear view of the actually invoked services as well as of the orchestration patterns which bind them together. The tool analyses Common Intermediate Language (CIL) code, the native language of Microsoft .Net Framework. Therefore, the scope of application of COORDINSPECTOR is quite large: potentially any piece of code developed in any of the programming languages which compiles to the .Net Framework. The tool generates graphical representations of the coordination layer together and identifies the underlying business process orchestrations, rendering them as Orc specifications

Domain-Specific Language for Coordination patterns

The integration and composition of software systems requires a good architectural design phase to speed up communications between (remote) components. However, during implementation phase, the code to coordinate such components often ends up mixed in the main business code. This leads to maintenance problems, raising the need for, on the one hand, separating the coordination code from the business code, and on the other hand, providing mechanisms for analysis and comprehension of the architectural decisions once made. In this context our aim is at developing a domain-specific language, CoordL, to describe typical coordination patterns. From our point of view, coordination patterns are abstractions, in a graph form, over the composition of coordination statements from the system code. These patterns would allow us to identify, by means of pattern-based graph search strategies, the code responsible for the coordination of the several components in a system. The recovering and separation of the architectural decisions for a better comprehension of the software is the main purpose of this pattern language

The role of coordination analysis in software integration projects

What sort of component coordination strategies emerge in a software integration process? How can such strategies be discovered and further analysed? How close are they to the coordination component of the envisaged architectural model which was supposed to guide the integration process? This paper introduces a framework in which such questions can be discussed and illustrates its use by describing part of a real case-study. The approach is based on a methodology which enables semi-automatic discovery of coordination patterns from source code, combining generalized slicing techniques and graph manipulation

The perceived potential of business social networking sites

Business social networking is a facilitator of several business activities, such as market studies, communication with clients, and identification of business partners. This paper traduces the results of a study undertaken with the purpose of getting to know how the potential of networking is perceived in the promotion of business by participants of the LinkedIn network, and presents two main contributions: (1) to disseminate within the business community which is the relevance given to social networking; and (2) which are the social networks best suitable to the promotion of business, to support the definition of strategies and approaches accordingly. The results confirm that LinkedIn is the most suitable network to answer the needs of those that look for professional contacts and for the promotion of business, while innovation is the most recognized factor in the promotion of business through social networking. This study contributes to a better understanding of the potential of different business social networking sites, to support organizations and professionals to align their strategies with the perceived potential of each network.

Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.