A low-voltage low-power analog memory cell with built-in 4-quadrant multiplication

An accurate switched-current (SI) memory cell and suitable for low-voltage low-power (LVLP) applications is proposed. Information is memorized as the gate-voltage of the input transistor, in a tunable gain-boosting triode-transconductor. Additionally, four-quadrant multiplication between the input voltage to the transconductor regulation-amplifier (X-operand) and the stored voltage (Y-operand) is provided. A simplified 2 x 2-memory array was prototyped according to a standard 0.8 mum n-well CMOS process and 1.8-V supply. Measured current-reproduction error is less than 0.26% for 0.25 muA less than or equal to I-SAMPLE less than or equal to 0.75 muA. Standby consumption is 6.75 muW per cell @I-SAMPLE = 0.75 muA. At room temperature, leakage-rate is 1.56 nA/ms. Four-quadrant multiplier (4QM) full-scale operands are 2x(max) = 320 mV(pp) and 2y(max). = 448 mV(pp), yielding a maximum output swing of 0.9 muA(pp). 4QM worst-case nonlinearity is 7.9%.

Error function approximations of interest in electrochemistry.

The error function is present in several equations describing eletrode processes. But, only approximations of this function are used. In this work, these and other approximations are studied and evaluated according to precision.

Step by step analyses of Clarke's matrix correction procedure for untransposed three-phase transmission line cases

The correction procedure for Clarke's matrix, considering three-phase transmission line analyzes, is analyzed step by step in this paper, searching to improve the application of this procedure. Changing the eigenvectors as modal transformation matrices, Clarke's matrix has been applied to analyses for transposed and untransposed three-phase transmission line cases. It is based on the fact that Clarke's matrix is an eigenvector matrix for transposed three-phase transmission lines considering symmetrical and asymmetrical cases. Because of this, the application of this matrix has been analyzed considering untransposed three-phase transmission lines. In most of these cases, the errors related to the eigenvalues can be considered negligible. It is not true when it is analyzed the elements that are not in main diagonal of the quasi-mode matrix. This matrix is obtained from the application of Clarke's matrix. The quasi-mode matrix is correspondent to the eigenvalue matrix. Their off-diagonal elements represent couplings among the quasi-modes. So, the off-diagonal quasi-mode element relative values are not negligible when compared to the eigenvalues that correspond to the coupled quasi-modes. Minimizing these relative values, the correction procedure is analyzed in detail, checking some alternatives for the correction procedure application.

Correction procedure applied to a single real transformation matrix -Untransposed three-phase transmission line cases

Clarke's matrix has been used as an eigenvector matrix for transposed three-phase transmission lines and it can be applied as a phase-mode transformation matrix for transposed cases. Considering untransposed three-phase transmission lines, Clarke's matrix is not an exact eigenvector matrix. In this case, the errors related to the diagonal elements of the Z and Y matrices can be considered negligible, if these diagonal elements are compared to the exact elements in domain mode. The mentioned comparisons are performed based on the error and frequency scan analyses. From these analyses and considering untransposed asymmetrical three-phase transmission lines, a correction procedure is determined searching for better results from the Clarke's matrix use as a phase-mode transformation matrix. Using the Clarke's matrix, the relative errors of the eigenvalue matrix elements can be considered negligible and the relative values of the off-diagonal elements are significant. Applying the corrected transformation matrices, the relative values of the off-diagonal elements are decreased. The comparisons among the results of these analyses show that the homopolar mode is more sensitive to the frequency influence than the two other modes related to three-phase lines. © 2006 IEEE.

A study on human error in the interaction with the computer systems

The term human factor is used by professionals of various fields meant for understanding the behavior of human beings at work. The human being, while developing a cooperative activity with a computer system, is subject to cause an undesirable situation in his/her task. This paper starts from the principle that human errors may be considered as a cause or factor contributing to a series of accidents and incidents in many diversified fields in which human beings interact with automated systems. We propose a simulator of performance in error with potentiality to assist the Human Computer Interaction (HCI) project manager in the construction of the critical systems. © 2011 Springer-Verlag.

Evaluacion y correccion de datos demograficos. I. Conceptos basicos. II. El error en las estadisticas demograficas

Capítulos de este documento disponibles separadamente (3611.00, 4912.00 y 3336.00)

Mensajes de error del compilador WATFOR

El documento contiene una lista de errores detectados por el compilador WATFOR/360

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

Error estimates for a neumann problem in highly oscillating thin domains

In this work we analyze the convergence of solutions of the Poisson equation with Neumann boundary conditions in a two-dimensional thin domain with highly oscillatory behavior. We consider the case where the height of the domain, amplitude and period of the oscillations are all of the same order, and given by a small parameter e > 0. Using an appropriate corrector approach, we show strong convergence and give error estimates when we replace the original solutions by the first-order expansion through the Multiple-Scale Method.

Crenças e práticas de avaliação no processo interativo e na mediação de um par no tandem a distância: um estudo de caso

Pós-graduação em Estudos Linguísticos - IBILCE

Informação quântica e relatividade

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Controle de qualidade para 3D-vídeo streaming em redes em malha sem fio

Redes em Malha sem Fio ( do inglês Wireless Mesh Networks - WMNs) são previstas serem uma das mais importantes tecnologias sem fio no que se refere ao fornecimento do acesso de última milha em redes multimídia futuras. Elas vão permitir que milhares de usuários fixos e móveis acessem, produzam e compartilhem conteúdo multimídia de forma onipresente. Neste contexto, vídeo 3D está previsto atrair mais e mais o mercado multimídia com a perspectiva de reforçar as aplicações (vídeos de vigilância, controle demissões críticas, entretenimento, etc). No entanto, o desafio de lidar com a largura de banda optante, escassez de recursos e taxas de erros variantes com o tempo destas redes, ilustra a necessidade da transmissão de vídeos 3D mais resistentes a erros. Dessa forma, alternativas como abordagens de Correção Antecipada de Erros (FEC) se tornam necessárias para fornecer a distribuição de aplicações de vídeo para usuários sem fio com garantia de melhor qualidade de serviço (QoS) e Qualidade de Experiência (QoE). Esta dissertação apresenta um mecanismo baseado em FEC com Proteção Desigual de Erros (UEP) para melhorar a transmissão de vídeo 3D em WMNs, aumentando a satisfação do usuário e permitindo uma melhoria do uso dos recursos sem fio. Os benefícios e impactos do mecanismo proposto serão demonstrados usando simulação e a avaliação será realizada através de métricas de QoE objetivas e subjetivas.

Uso de modelos lineares mistos na avaliação genética de escores visuais: estudo de simulação

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

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.