65 resultados para Errors and omission
em Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho"
Analysis of diametrical wear of grinding wheel and roundness errors in the machining of steel VC 131
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Due to the high industrial competitiveness, the rigorous laws of environmental protection, the necessary reduction of costs, the mechanical industry sees itself forced to worry more and more with the refinement of your processes and products. In this context, can be mentioned the need to eliminate the roundness errors that appear after the grinding process. This work has the objective of verifying if optimized nozzles for the application of cutting fluid in the grinding process can minimize the formation of the roundness errors and the diametrical wear of grinding wheel in the machining of the steel VC 131 with 60 HRc, when compared to the conventional nozzles. These nozzles were analyzed using two types of grinding wheels and two different cutting fluids. Was verified that the nozzle of 3mm of diameter, integral oil and the CBN grinding wheel, were the best options to obtain smaller roundness errors and the lowest diametrical wears of grinding wheels.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.
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The ability of neural networks to realize some complex nonlinear function makes them attractive for system identification. This paper describes a novel method using artificial neural networks to solve robust parameter estimation problems for nonlinear models with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach.
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New formularizations, techniques and devices have become the dental whitening most safe and with better results. Although this, the verification of the levels whitening is being continued for visual comparison, that is an empirical, subjective method, subject to errors and dependent of the individual interpretation. Normally the result of the whitening is express for the amplitude of displacement between the initial and the final color, being take like reference the tonalities of a scale of color commanded of darkest for more clearly. Although to be the most used scale, the ordinance of the Vita Classical (R) - Vita, according to recommendations of the manufacturer, reveals inadequate for the evaluation of the whitening. From digital images and of algorithm OER (ordinance of the reference scale), especially developed for the ScanWhite (C), the ordinance of the tonalities of the scale Vita Classical (R) was made. For such, the values of the canals of color R, G, and B of medium part average of the crowns was adopted as reference for evaluation. The images had been taken with the camera Sony Cybershoot DSC F828. The results of the computational ordinance had been compared with the sequence proposal for the manufacturer and with the earned one for the visual evaluation, carried through by 10 volunteers, under standardized conditions of illumination. It statistics analyzes demonstrated significant differences between the ordinances.
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The non-native invasive anuran Lithobates catesbeianus is presently distributed in Brazil, especially in the Atlantic Rainforest biodiversity hotspot. Here, we use a maximum entropy ecological niche modeling algorithm (i) to model the North American native geographic distribution of this species and (ii) to project that model onto the whole of Brazil. After applying a threshold value that balances commission and omission errors, the projection results suggested high probabilities of occurrence mostly in southern and southeastern Brazil. We also present the first report on the species known distribution in Brazil, showing good agreement with model predictions. If the predictive map is interpreted as depicting invasiveness potential of L. catesbeianus, strategies to prevent further invasion in Brazil should be focused especially in the Atlantic Rainforest biodiversity hotspot.
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Alternant codes over arbitrary finite commutative local rings with identity are constructed in terms of parity-check matrices. The derivation is based on the factorization of x s - 1 over the unit group of an appropriate extension of the finite ring. An efficient decoding procedure which makes use of the modified Berlekamp-Massey algorithm to correct errors and erasures is presented. Furthermore, we address the construction of BCH codes over Zm under Lee metric.
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This paper by R. E. Catai, E. C. Bianchi, P. R de Águia and M. C. Alves reports on the results of an analysis made of roundness errors, residual stresses, and SEM micrographs of VC131 steel. The analysis involved workpieces ground with two types of cutting fluid: synthetic cutting fluid and emulsive oil. In this study, the cutting parameters were kept constant while the type of cutting fluid was varied. The amount of cutting fluid injected in the process was also varied, aiming to identify the ideal amount required to obtain good results without causing structural damage to the workpiece. The SEM analyses of roundness errors and residual stresses revealed that, of the two cutting fluids, emulsive oil provided better tensions due to its greater lubricating power.
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In the paper we discuss the potential of the new Galileo signals for pseudorange based surveying and mapping in open areas under optimal reception conditions (open sky scenarios) and suboptimal ones (multipath created by moderate to thick tree coverage). The paper reviews the main features of the Galileo E5 AltBOC and E1 CBOC signals; describes the simulation strategy, models and algorithms to generate realistic E5 and E1 pseudoranges with and without multipath sources; describes the ionosphere modeling strategy, models and algorithms and discusses and presents the expected positioning accuracy and precision results. According to the simulations performed, pseudoranges can be extracted from the Galileo E5 AltBOC signals with tracking errors (1-σ level) ranging from 0.02 m (open sky scenarios) to 0.08 m (tree covered scenarios) whereas for the Galileo E1 CBOC signals the tracking errors range between 0.25 m to 2.00 m respectively. With these tracking errors and with the explicit estimation of the ionosphere parameters, simulations indicate real-time open sky cm-level horizontal positioning precisions and dm-level vertical ones and dm-level accuracies for both the horizontal and vertical position components.
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Butyltin (BTs) quantification in environmental matrices can be affected by interfering species found primarily in complex matrices,such as sediment and biota tissues. This study investigated matrix effects in analytical procedures for butyltin (TBT,DBT and MBT) quantification and speciation in sediments and in two fish tissues (gill and liver) by gas chromatography with pulsed flame photometric detection (GC-PFPD) analysis. Unlike sediment samples,tissues exhibited a significant matrix effect,thus,the quantification should be made by curve over matrix to avoid quantification errors and loss of analytical accuracy. © 2013 Sociedade Brasileira de Química.
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To assist cattle producers transition from microsatellite (MS) to single nucleotide polymorphism (SNP) genotyping for parental verification we previously devised an effective and inexpensive method to impute MS alleles from SNP haplotypes. While the reported method was verified with only a limited data set (N = 479) from Brown Swiss, Guernsey, Holstein, and Jersey cattle, some of the MS-SNP haplotype associations were concordant across these phylogenetically diverse breeds. This implied that some haplotypes predate modern breed formation and remain in strong linkage disequilibrium. To expand the utility of MS allele imputation across breeds, MS and SNP data from more than 8000 animals representing 39 breeds (Bos taurus and B. indicus) were used to predict 9410 SNP haplotypes, incorporating an average of 73 SNPs per haplotype, for which alleles from 12 MS markers could be accurately be imputed. Approximately 25% of the MS-SNP haplotypes were present in multiple breeds (N = 2 to 36 breeds). These shared haplotypes allowed for MS imputation in breeds that were not represented in the reference population with only a small increase in Mendelian inheritance inconsistancies. Our reported reference haplotypes can be used for any cattle breed and the reported methods can be applied to any species to aid the transition from MS to SNP genetic markers. While ~91% of the animals with imputed alleles for 12 MS markers had ≤1 Mendelian inheritance conflicts with their parents' reported MS genotypes, this figure was 96% for our reference animals, indicating potential errors in the reported MS genotypes. The workflow we suggest autocorrects for genotyping errors and rare haplotypes, by MS genotyping animals whose imputed MS alleles fail parentage verification, and then incorporating those animals into the reference dataset.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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INTRODUCTION: Informatics and automation are important tools for the reduction of work, errors and costs in a hospital pharmacy. OBJECTIVES: To describe the structuring and function of an informatized system for the dispensing of medications and to assess its effect on nursing and pharmacy services during the period from 1997 to 2003. MATERIALS and METHODS: In this descriptive and retrospective study, we performed an analysis of documents addressing the structuring and implementation of the informatized medication dispensing system. In addition, we analyzed the perceptions of nurses, pharmacists and pharmacy assistants who participated in the structuring phase of the system when interviewed about the effect of informatization on administrative aspects (e.g., requisition of medications, presentation of the dispensed medication and system operationalization). RESULTS: The major advantages provided by the new system were 1) the elimination of manual transcripts for prescribed medications, 2) increased speed, 3) better identification of the doses prescribed by physicians, 4) medication labels containing all necessary identification and 5) practicality and safety of optical bar code-based verification of the requested and dispensed medications. CONCLUSIONS: The great majority of the interviewees considered the informatized medication supply system to be of good quality. Analysis of the data provided information that could contribute to the expansion and refinement of the system, provide support for studies regarding the utilization of medications and offer new perspectives for work and productivity.
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A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.
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This paper proposes the application of computational intelligence techniques to assist complex problems concerning lightning in transformers. In order to estimate the currents related to lightning in a transformer, a neural tool is presented. ATP has generated the training vectors. The input variables used in Artificial Neural Networks (ANN) were the wave front time, the wave tail time, the voltage variation rate and the output variable is the maximum current in the secondary of the transformer. These parameters can define the behavior and severity of lightning. Based on these concepts and from the results obtained, it can be verified that the overvoltages at the secondary of transformer are also affected by the discharge waveform in a similar way to the primary side. By using the tool developed, the high voltage process in the distribution transformers can be mapped and estimated with more precision aiding the transformer project process, minimizing empirics and evaluation errors, and contributing to minimize the failure rate of transformers. (C) 2011 Elsevier Ltd. All rights reserved.