4 resultados para Geração de valor

em Universidade Federal do Rio Grande do Norte(UFRN)


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Technological innovation promotes the generation of economic value by creating a new product, process or organizational management model, being classified as dynamic and multidimensional. Government intervention has the role of acting through government grant programs to foster the integration of innovative processes in small companies, due to the high costs and risks of development, strengthening the country`s economy in this phase. The distribution of this grant is determined by criteria, based especially in subjective judgments, which are based on the beliefs and perceptions about the technological opportunities and market actors involved in the process, being very difficult to measure the probability of success of the project under evaluation. This study aims to identify the most relevant selection criteria that must be inserted in grants programs at Rio Grande do Norte executed by Fundação de Pesquisa do Rio Grande do Norte (FAPERN). Initially, there was a systematization of 18 countries, covering 41 programs in foreign countries and 29 in Brazil. Based on the data collected, we conducted one survey containing four programs of FAPERN (INOVA I, INOVA II , INOVA III and INOVA IV), covering 44 companies and analyzing their responses according to the Likert scale , obtaining the degree of importance given by the respondent to each of the criteria in the questionnaire . As a result, drew up a proposal for new criteria to be used in the next FAPERN´s grants, containing 13 new criteria. It is expected, therefore, to contribute to a better spending of public funds invested in companies subsidized in Brazil

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Artificial Intelligence techniques are applied to improve performance of a simulated oil distillation system. The chosen system was a debutanizer column. At this process, the feed, which comes to the column, is segmented by heating. The lightest components become steams, by forming the LPG (Liquefied Petroleum Gas). The others components, C5+, continue liquid. In the composition of the LPG, ideally, we have only propane and butanes, but, in practice, there are contaminants, for example, pentanes. The objective of this work is to control pentane amount in LPG, by means of intelligent set points (SP s) determination for PID controllers that are present in original instrumentation (regulatory control) of the column. A fuzzy system will be responsible for adjusting the SP's, driven by the comparison between the molar fraction of the pentane present in the output of the plant (LPG) and the desired amount. However, the molar fraction of pentane is difficult to measure on-line, due to constraints such as: long intervals of measurement, high reliability and low cost. Therefore, an inference system was used, based on a multilayer neural network, to infer the pentane molar fraction through secondary variables of the column. Finally, the results shown that the proposed control system were able to control the value of pentane molar fraction under different operational situations

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With the increasing complexity of software systems, there is also an increased concern about its faults. These faults can cause financial losses and even loss of life. Therefore, we propose in this paper the minimization of faults in software by using formally specified tests. The combination of testing and formal specifications is gaining strength in searches mainly through the MBT (Model-Based Testing). The development of software from formal specifications, when the whole process of refinement is done rigorously, ensures that what is specified in the application will be implemented. Thus, the implementation generated from these specifications would accurately depict what was specified. But not always the specification is refined to the level of implementation and code generation, and in these cases the tests generated from the specification tend to find fault. Additionally, the generation of so-called "invalid tests", ie tests that exercise the application scenarios that were not addressed in the specification, complements more significantly the formal development process. Therefore, this paper proposes a method for generating tests from B formal specifications. This method was structured in pseudo-code. The method is based on the systematization of the techniques of black box testing of boundary value analysis, equivalence partitioning, as well as the technique of orthogonal pairs. The method was applied to a B specification and B test machines that generate test cases independent of implementation language were generated. Aiming to validate the method, test cases were transformed manually in JUnit test cases and the application, created from the B specification and developed in Java, was tested. Faults were found with the execution of the JUnit test cases

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Formal methods and software testing are tools to obtain and control software quality. When used together, they provide mechanisms for software specification, verification and error detection. Even though formal methods allow software to be mathematically verified, they are not enough to assure that a system is free of faults, thus, software testing techniques are necessary to complement the process of verification and validation of a system. Model Based Testing techniques allow tests to be generated from other software artifacts such as specifications and abstract models. Using formal specifications as basis for test creation, we can generate better quality tests, because these specifications are usually precise and free of ambiguity. Fernanda Souza (2009) proposed a method to define test cases from B Method specifications. This method used information from the machine s invariant and the operation s precondition to define positive and negative test cases for an operation, using equivalent class partitioning and boundary value analysis based techniques. However, the method proposed in 2009 was not automated and had conceptual deficiencies like, for instance, it did not fit in a well defined coverage criteria classification. We started our work with a case study that applied the method in an example of B specification from the industry. Based in this case study we ve obtained subsidies to improve it. In our work we evolved the proposed method, rewriting it and adding characteristics to make it compatible with a test classification used by the community. We also improved the method to support specifications structured in different components, to use information from the operation s behavior on the test case generation process and to use new coverage criterias. Besides, we have implemented a tool to automate the method and we have submitted it to more complex case studies