A Proposal for System Performance Evaluation for an ERP Knowledge Extraction Model

Much has been researched and discussed in the importance played by knowledge in organizations. We are witnessing the establishment of the knowledge economy, but this "new economy" brings in itself a whole complex system of metrics and evaluations, and cannot be dissociated from it. Due to its importance, the initiatives of knowledge management must be continually assessed on their progress in order to verify whether they are moving towards achieving the goals of success. Thus, good measurement practices should include not only how the organization quantifies its knowledge capital, but also how resources are allocated to supply their growth. Thinking about the aspects listed above, this paper presents an approach to a model for Knowledge extraction using an ERP system, suggesting the establishment of a set of indicators for assessing organizational performance. The objective is to evaluate the implementation of projects of knowledge management and thus observe the general development of the organization.

A DOE based approach for the design of RBF artificial neural networks applied to prediction of surface roughness in AISI 52100 hardened Steel turning

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Quantitation of malondialdehyde in gingival crevicular fluid by a high-performance liquid chromatography-based method

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

In silico network topology-based prediction of gene essentiality

The identification of genes essential for survival is important for the understanding of the minimal requirements for cellular life and for drug design. As experimental studies with the purpose of building a catalog of essential genes for a given organism are time-consuming and laborious, a computational approach which could predict gene essentiality with high accuracy would be of great value. We present here a novel computational approach, called NTPGE (Network Topology-based Prediction of Gene Essentiality), that relies on the network topology features of a gene to estimate its essentiality. The first step of NTPGE is to construct the integrated molecular network for a given organism comprising protein physical, metabolic and transcriptional regulation interactions. The second step consists in training a decision-tree-based machine-learning algorithm on known essential and non-essential genes of the organism of interest, considering as learning attributes the network topology information for each of these genes. Finally, the decision-tree classifier generated is applied to the set of genes of this organism to estimate essentiality for each gene. We applied the NTPGE approach for discovering the essential genes in Escherichia coli and then assessed its performance. (C) 2007 Elsevier B.V. All rights reserved.

Utilização do intercepto-y na avaliação da aptidão anaeróbia e predição da performance de nadadores treinados

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Nanopore size growth and ultrafiltration performance of SnO2 ceramic membranes prepared by sol-gel route

Supported ceramic membranes have been produced by the sol-casting procedure from aqueous colloidal suspensions prepared by the sol-gel route. Coatings on a tubular alumina support have been successfully performed leading to crack free layers. Samples have been sintered at 400, 500 and 600 degreesC, and the effect of heating treatment on the nanostructure and on the ultrafiltration properties are analyzed. The characterization has been done by high resolution scanning electron microscopy, nitrogen adsorption-desorption isotherms, water permeation and cut-off determination using polyethylene glycol standard solutions. The micrographs have revealed that grains and pore size increase with the temperature, whereas their shape remains invariant. This results is in agreements with N-2 adsorption-desorption analyses, which have revealed that the mean pore size diameter increases from 4 to 10 nm as the sintering temperature increases from 400 to 600 degreesC, while the total porosity remains constant. Furthermore, the tortuosity, calculated from water permeability, is essentially invariant with the sintering temperatures. The membranes cut-off, determined with a retention rate equal to 95%, are 3500, 6500 and 9000 g . mol(-1) for 400, 500 and 600 degreesC, respectively, showing that the permeation properties of SnO2 ultrafiltration membranes can easily be controlled by sintering condition.

Variáveis fisiológicas e neuromusculares associadas com a performance aeróbia em corredores de endurance: efeitos da distância da prova

O objetivo deste estudo foi analisar a validade do consumo máximo de oxigênio (VO2max), velocidade associada ao VO2max (vVO2max), tempo de exaustão na vVO2max (Tlim), limiar anaeróbio (LAn), economia de corrida (EC) e força explosiva (FE) para predizer a performance aeróbia de corredores de endurance nas distâncias de 1.500m, 5.000m e 10.000m. Participaram deste estudo 11 corredores de endurance moderadamente treinados (28,36 ± 6,47 anos) que realizaram os seguintes testes: provas simuladas em uma pista de 400m em diferentes dias, nas distâncias de 10.000m, 5.000m e 1.500m; teste incremental máximo para determinar os índices VO2max, vVO2max, e LAn; um teste submáximo de carga constante para determinar a EC, seguido por um teste máximo também de carga constante a 100% da vVO2max para determinar o Tlim; e um teste de salto vertical para determinar a FE. de acordo com a análise de regressão múltipla, a vVO2max utilizada de forma isolada explicou 57% da variação de performance na prova de 1.500m. No entanto, quando o Tlim, a FE e a vVO2max foram analisados em conjunto, a explicação para a performance nessa prova foi de 88%. Nos 5.000m, o Tlim, a vVO2max e o LAn responderam por 88% da variação de performance (p < 0,05). Diferentemente, na prova de 10.000m, o LAn foi a única variável que apresentou capacidade de predição de performance. em conclusão, a predição da performance aeróbia de corredores moderadamente treinados por meio de variáveis fisiológicas e neuromusculares é dependente da distância da prova (1.500m, 5.000m e 10.000m)

USE OF PROGENY TESTING IN BEEF-CATTLE - PREDICTION OF GENETIC GAIN IN A NELORE CATTLE-BREEDING PROGRAM

Genetic gains predicted for selection, based on both individual performance and progeny testing, were compared to provide information to be used in implementation of progeny testing for a Nelore cattle breeding program. The prediction of genetic gain based on progeny testing was obtained from a formula, derived from methodology of Young and weller (J. Genetics 57: 329-338, 1960) for two-stage selection, which allows prediction of genetic gain per generation when the individuals under test have been pre-selected on the basis of their own performance. The application of this formula also allowed determination of the number of progeny per tested bull needed to maximize genetic gain, when the total number of tested progeny is limited.

Prediction and spatial variability of soil dynamic properties in sugar cane fields of São Paulo State Brazil

The objective of this work was to model and diagnose the spatial variability of soil load support capacity (SLSC) in sugar cane crop fields, as well as to evaluate the management impact on São Paulo State soil structure. The investigated variables were: pressure preconsolidation (sigma(p)), apparent cohesion () and internal friction angle (). The conclusions from the results were that the models and spatial dependence maps constitute important tools in the prediction and location of the mechanical internal strength of soils cultivated with sugar cane. They will help future soil management decisions so that soil structure sustainability will not be compromised.

Optimization of Radial Basis Function neural network employed for prediction of surface roughness in hard turning process using Taguchi's orthogonal arrays

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Use of progeny testing in beef cattle: Prediction of genetic gain in a Nelore Cattle Breeding Program

Genetic gains predicted for selection, based on both individual performance and progeny testing, were compared to provide information to be used in implementation of progeny testing for a Nelore cattle breeding program. The prediction of genetic gain based on progeny testing was obtained from a formula, derived from methodology of Young and Weiler (J. Genetics 57: 329-338, 1960) for two-stage selection, which allows prediction of genetic gain per generation when the individuals under test have been pre-selected on the basis of their own performance. The application of this formula also allowed determination of the number of progeny per tested bull needed to maximize genetic gain, when the total number of tested progeny is limited.

The influence of zero-value subtraction on the performance of two laser fluorescence devices for detecting occlusal caries in vitro

Background. The aim of this study was to evaluate the influence of zero-value subtraction on the performance of two laser fluorescence (LF) devices developed to detect occlusal caries. Methods. The authors selected 119 permanent molars. Two examiners assessed three areas (cuspal, middle and cervical) of both mesial and distal portions of the buccal surface and one occlusal site using an LF device and an LF pen. For each tooth, the authors subtracted the value measured in the cuspal, middle and cervical areas in the buccal surface from the value measured in the respective occlusal site. Results. The authors observed differences among the readings for both devices in the cuspal, middle and cervical areas in the buccal surface as well as differences for both devices with and without the zero-value subtraction in the occlusal surface. When the authors did not perform the zero-value subtraction, they found statistically significant differences for sensitivity and accuracy for the LF device. When this was done with the LF pen, specificity increased and sensitivity decreased significantly. Conclusions. For the LF device, the zero-value subtraction decreased the sensitivity. For this reason, the authors concluded that clinicians can obtain measures with the LF device effectively without using zero-value subtraction. For the LF pen, however, the absence of the zero-value subtraction changed both the sensitivity and specificity, and so the authors concluded that clinicians should not eliminate this step from the procedure. Clinical Implications. When using the LF device, clinicians might not need to perform the zero-value subtraction; however, for the LF pen, clinicians should do so.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Effects of spray nozzles and spray volume on spodoptera frugiperda management and narrow row corn performance

The high demand of pesticides in the production systems makes the application technology one of the main alternatives to optimize the products efficiency. In this context, the study aimed to evaluate the effects of spray nozzles and spray volumes on spraying deposits, armyworm control and crop corn performance in narrow row sowing system. The experiment was carried out at experimental area of Sao Paulo State University, Campus of Botucatu/SP, Brazil, during the 2009/2010 agricultural season, in randomized blocks with factorial scheme (2x2+1) and four replications. It was tested two flat fan spray nozzles (with and without air induction) combined with two spray volumes (100 and 200 L ha-1) plus a control treatment. There was no influence of spray nozzles (without air induction) in the spray deposits levels on plants. However, the flat fan nozzle with air induction was more effective on fall armyworm, with 100% of control against 47.84% from other at 15 days after spraying. The increase in the spray volume promoted high spray deposits (415.4 and 388.6 μL g-1 dry mass for flat fan nozzle with and without air induction, respectively at V10 growth stage) and consequently, the highest spray volume (200 L-1) was more efficient in the fall armyworm suppression, with 100% of control. All the technologies tested showed lower plant injury from fall armyworm. The insecticide sprayed with different technologies did not affect the parameters of plant height and leaf area index. The corn productivity was directly related with control efficiency of fall armyworm. © 2012 Academic Journals Inc.