Sistema especialista fuzzy para dimensionamento de bombeio mecânico

Despite the emergence of other forms of artificial lift, sucker rod pumping systems remains hegemonic because of its flexibility of operation and lower investment cost compared to other lifting techniques developed. A successful rod pumping sizing necessarily passes through the supply of estimated flow and the controlled wear of pumping equipment used in the mounted configuration. However, the mediation of these elements is particularly challenging, especially for most designers dealing with this work, which still lack the experience needed to get good projects pumping in time. Even with the existence of various computer applications on the market in order to facilitate this task, they must face a grueling process of trial and error until you get the most appropriate combination of equipment for installation in the well. This thesis proposes the creation of an expert system in the design of sucker rod pumping systems. Its mission is to guide a petroleum engineer in the task of selecting a range of equipment appropriate to the context provided by the characteristics of the oil that will be raised to the surface. Features such as the level of gas separation, presence of corrosive elements, possibility of production of sand and waxing are taken into account in selecting the pumping unit, sucker-rod strings and subsurface pump and their operation mode. It is able to approximate the inferente process in the way of human reasoning, which leads to results closer to those obtained by a specialist. For this, their production rules were based on the theory of fuzzy sets, able to model vague concepts typically present in human reasoning. The calculations of operating parameters of the pumping system are made by the API RP 11L method. Based on information input, the system is able to return to the user a set of pumping configurations that meet a given design flow, but without subjecting the selected equipment to an effort beyond that which can bear

Automatic identification by C-13 NMR of substituent groups bonded in natural product skeletons

The aim of this paper is to present a procedure that utilizes C-13 NMR for identification of substituent groups which are bonded to carbon skeletons of natural products. For so much was developed a new version of the program (MACRONO), that presents a database with 161 substituent types found in the most varied terpenoids. This new version was widely tested in the identification of the substituents of 60 compounds that, after removal of the signals that did not belong to the carbon skeleton, served to test the prediction of skeletons by using other programs of the expert system (SISTEMAT). (C) 2002 Elsevier B.V. Ltd. All rights reserved.

A constraints generator in structural determination by microcomputer

We present a new expert system: a constraints generator for structure determination of natural products. The constraints that the system furnishes are: skeleton (reliability: 95%), large substructures (reliability: 98%) and their associated assignments (reliability: 90%) This system is intended for structure determination of carbon-rich compounds (sesqui-, di- and triterpenes, sterols etc.) for which most structures generators are not very effective. We also present a new algorithm that can avoid the combinatorial explosion during subspectrum/substructure analysis.

A computer-assisted approach for chemotaxonomic studies - Diterpenes in Lamiaceae

This paper describes a new computer approach for chemotaxonomic studies. The methodology employed enables the search for chemical substructures as taxonomic descriptors using all expert system built with plant natural products. The operation of the system was tested with diterpenes as taxonomic markers in Lamiaceae. © 2001 Elsevier Science Ltd.

A program for terpenoid skeleton prediction based on botanical information

This paper describes a new program developed to the SISTEMAT expert system, the SISOCBOT program. This program employs the botanical data analysis and predicts, at the end of analysis, the probable skeleton of a compound based on the input of family or genus names. The SISOCBOT program was tested with 78 samples involving 302 substances, pertaining to 38 carbon skeletons, and showed a high hit index on skeleton prediction, thus emphasizing the potential importance of these data for structural determination of natural products. © 2002 Elsevier Science Ltd. All rights reserved.

SISTAX - An intelligent tool for recovering information on natural products chemistry

This work describes the development of a new program, named SISTAX, for the expert system SISTEMAT. This program allows anyone interested in chemotaxonomy to carry out an intelligent search for organic compounds in databases through chemical structures. When coupled with can efficient encoding system, the program recognizes skeletal types and can find any substructural constraints demanded by the user. An example of an application of the program to the diterpene class found in plants is described.

Sistema especialista para a monitoração do processo de degradação de medidores tipo indução de energia elétrica ativa

This paper presents a methodology and software for hazard rate analysis of induction type watt-hour meters, considering the main variables related with the degradation process of these meters, for the Elektro Electricity and Services SA. The modeling developed to calculate the watt-hour meters hazard rate was implemented in a tool through a user friendly platform, in Delphi language, enabling not only hazard rate analysis, but also a classification by risk range, localization of installation for the analyzed meters, and, allowing, through an expert system, the sampling of induction type watt-hour meters, based on the model risk developed with artificial intelligence, with the mainly goal of follow and manage the process of degradation, maintenance and replacement of these meters. © 2010 IEEE.

Specialist tool for monitoring the measurement degradation process of induction active energy meters

This paper presents a methodology and a specialist tool for failure probability analysis of induction type watt-hour meters, considering the main variables related to their measurement degradation processes. The database of the metering park of a distribution company, named Elektro Electricity and Services Co., was used for determining the most relevant variables and to feed the data in the software. The modeling developed to calculate the watt-hour meters probability of failure was implemented in a tool through a user friendly platform, written in Delphi language. Among the main features of this tool are: analysis of probability of failure by risk range; geographical localization of the meters in the metering park, and automatic sampling of induction type watt-hour meters, based on a risk classification expert system, in order to obtain information to aid the management of these meters. The main goals of the specialist tool are following and managing the measurement degradation, maintenance and replacement processes for induction watt-hour meters. © 2011 IEEE.

ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

Metodologia para diagnosticar a qualidade de energia elétrica referente à distorção harmônica em sistema trifásico de baixa tensão utilizando lógica fuzzy

Este trabalho ressalta a importância de monitorar e diagnosticar a qualidade de energia elétrica sob a ótica das distorções harmônicas presente nas instalações elétricas em sistema trifásico de baixa tensão através de uma proposta metodológica para analisar e diagnosticar o nível dos distúrbios harmônico avaliando o indicador total de distorção harmônica (THD), apoiado por um sistema especialista baseado em um sistema de inferência Fuzzy.

Reflexões sobre o desencaixe na educação brasileira e o eventual impasse entre o docentrismo e o discentrismo

Undocked institutions widely dilate the scope of time-space distancing, since the separation between these elements is crucial for the extreme dynamism of modernity. This separation is the prime condition of the process of disembedding, in which the displacement of social relations of local contexts of interaction and its redesign through indefinite extensions of time and space are favored. Therefore, there are two types of dislocated mechanisms intrinsically involved in the development of social modern institutions: symbolic tokens and expert systems. These mechanisms depend on reliability. Within this context, this present paper sees the professional life cycle of the teacher in the perspective of the expert system. It also sees the work stability of public servants in the symbolic token perspective, more specifically public teachers in Brazil. This paper also attempts to propose some reflections on what a disembedding in Brazilian education would mean and on how an eventual impasse between teachercentrism and studentcentrism would affect this process if necessary or desired, from one would understand by modernity.

Preventive diagnosis of dairy cow lameness

This research aimed to develop a Fuzzy inference based on expert system to help preventing lameness in dairy cattle. Hoof length, nutritional parameters and floor material properties (roughness) were used to build the Fuzzy inference system. The expert system architecture was defined using Unified Modelling Language (UML). Data were collected in a commercial dairy herd using two different subgroups (H-1 and H-2), in order to validate the Fuzzy inference functions. The numbers of True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN) responses were used to build the classifier system up, after an established gold standard comparison. A Lesion Incidence Possibility (LIP) developed function indicates the chances of a cow becoming lame. The obtained lameness percentage in H-1 and H-2 was 8.40% and 1.77%, respectively. The system estimated a Lesion Incidence Possibility (LIP) of 5.00% and 2.00% in H-1 and H-2, respectively. The system simulation presented 3.40% difference from real cattle lameness data for H-1, while for H-2, it was 0.23%; indicating the system efficiency in decision-making.

Ditregra - An auxiliary program for structural determination of diterpenes

This work describes the creation of heuristics rules based on 13C-NMR spectroscopy that characterize several skeletal types of diterpenes. Using a collection of 2745 spectra we built a database linked to the expert system SISTEMAT. Several programs were applied to the database in order to discover characteristic signals that identify with a good performance, a large diversity of skeletal types. The heuristic approach used was able to differentiate groups of skeletons based firstly on the number of primary, secondary, tertiary and quaternary carbons, and secondly the program searches, for each group, if there are ranges of chemical shifts that identifies specific skeletal type. The program was checked with 100 new structures recently published and was able to identify the correct skeleton in 65 of the studied cases. When the skeleton has several hundreds of compounds, for example, the labdanes, the program employs the concept of subskeletal, and does not classify in the same group labdanes with double bounds at different positions. The chemical shift ranges for each subskeletal types and the structures of all skeletal types are given. The consultation program can be obtained from the authors. © 1997 - IOS Press. All rights reserved.

Portal de Busca Integrada

O SIBiUSP lançou em março de 2012 uma nova ferramenta de busca de conteúdos acadêmicos/científicos, o nome dado foi Portal de Busca Integrada. Esta ferramenta pertence à uma categoria de softwares intitulada de “Web Scale Discovery”, que permitem a integração de diversas e dispersas fontes de dados em uma única interface de busca e entrega de resultados. Dessa forma, apresentam-se aqui os processos de seleção e implantação desta solução.

Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.