The embodied embedded character of system 1 processing

In the last thirty years, a relatively large group of cognitive scientists have begun characterising the mind in terms of two distinct, relatively autonomous systems. To account for paradoxes in empirical results of studies mainly on reasoning, Dual Process Theories were developed. Such Dual Process Theories generally agree that System 1 is rapid, automatic, parallel, and heuristic-based and System 2 is slow, capacity-demanding, sequential, and related to consciousness. While System 2 can still be decently understood from a traditional cognitivist approach, I will argue that it is essential for System 1 processing to be comprehended in an Embodied Embedded approach to Cognition.© MSM 2013.

HTS and HTSn: New shape descriptors based on Hough transform statistics

With the widespread proliferation of computers, many human activities entail the use of automatic image analysis. The basic features used for image analysis include color, texture, and shape. In this paper, we propose a new shape description method, called Hough Transform Statistics (HTS), which uses statistics from the Hough space to characterize the shape of objects or regions in digital images. A modified version of this method, called Hough Transform Statistics neighborhood (HTSn), is also presented. Experiments carried out on three popular public image databases showed that the HTS and HTSn descriptors are robust, since they presented precision-recall results much better than several other well-known shape description methods. When compared to Beam Angle Statistics (BAS) method, a shape description method that inspired their development, both the HTS and the HTSn methods presented inferior results regarding the precision-recall criterion, but superior results in the processing time and multiscale separability criteria. The linear complexity of the HTS and the HTSn algorithms, in contrast to BAS, make them more appropriate for shape analysis in high-resolution image retrieval tasks when very large databases are used, which are very common nowadays. (C) 2014 Elsevier Inc. All rights reserved.

Up-converter nanophosphor Y2O2S:Er,Yb aminofunctionalized containing or not spherical silica conjugated with BSA

This work reports on the study of the nanophosphor. Y2O2S:Er(2%),Yb(1%) obtained from polymeric resin to be evaluated as fluorescent label with Suitable features to conjugate with bio-molecules for bioassay up-converting phosphor technology (UPT) application A conjugation protocol between bovine serum albumin (BSA) and the aminofunctionalized nanophosphor containing or not spherical silica was established UV-vis results indicated an effective conjugation between nanophosphor particles and the protein up-conversion measurements under 980 nm excitation performed for samples before and after aminofunctionalization showed that nanophosphor particles luminescence features keep unchanged in all cases All results suggest that the adapted protocol is feasible to provide a nanoparticle-protein effective conjugation preserving nanophosphor optical features The presence of spherical silica can be considered advantageous to increase conjugation efficiency Therefore. the developed procedure is applicable for future conjugations between the chosen nanophosphor and the streptavidin protein chat takes part in the well known self-recognition system avidin-biotin. (C) 2009 Elsevier B.V All rights reserved.

On-line redox speciation analysis of antimony using L-proline immobilized on controlled pore glass and hydride generation inductively coupled plasma optical emission spectrometry for detection

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

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Reconhecimento de voz para aplicações em automação implementado em FPGA

In many movies of scientific fiction, machines were capable of speaking with humans. However mankind is still far away of getting those types of machines, like the famous character C3PO of Star Wars. During the last six decades the automatic speech recognition systems have been the target of many studies. Throughout these years many technics were developed to be used in applications of both software and hardware. There are many types of automatic speech recognition system, among which the one used in this work were the isolated word and independent of the speaker system, using Hidden Markov Models as the recognition system. The goals of this work is to project and synthesize the first two steps of the speech recognition system, the steps are: the speech signal acquisition and the pre-processing of the signal. Both steps were developed in a reprogrammable component named FPGA, using the VHDL hardware description language, owing to the high performance of this component and the flexibility of the language. In this work it is presented all the theory of digital signal processing, as Fast Fourier Transforms and digital filters and also all the theory of speech recognition using Hidden Markov Models and LPC processor. It is also presented all the results obtained for each one of the blocks synthesized e verified in hardware

Detecção e quantificação de corantes de importância ambiental empregando sensores químicos baseados em fibras ópticas e polímeros molecularmente impressos

Pós-graduação em Química - IQ

Gota suspensa para avaliação de aldeído total no ar interno e externo do ambiente

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

Optimum-Path Forest Classifier for Large Scale Biometric Applications

This paper addresses biometric identification using large databases, in particular, iris databases. In such applications, it is critical to have low response time, while maintaining an acceptable recognition rate. Thus, the trade-off between speed and accuracy must be evaluated for processing and recognition parts of an identification system. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. The existing Gauss-Laguerre Wavelet based coding scheme is used for iris encoding. The performance of the OPF and two other - Hamming and Bayesian - classifiers, is compared using small, medium, and large-scale databases. Such a comparison shows that the OPF has faster response for large-scale databases, thus performing better than the more accurate, but slower, classifiers.

A Fast Large Scale Iris Database Classification with Optimum-Path Forest Technique: A Case Study

Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.

Estudo de métodos para classificação e localização precisa de padrões usando um sistema de luz estruturada

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Biomobile: sistema de identificação de usuários em dispositivos móveis na plataforma Android utilizando reconhecimento de faces a partir de vídeo

Pós-graduação em Ciência da Computação - IBILCE

Desenvolvimento e aperfeiçoamento de protocolos de conjugação de nanomarcadores luminescentes com sistemas biológicos para aplicação em imunoensaios

Pós-graduação em Química - IBILCE

Síntese e caracterização de híbridos orgânico-inorgânicos luminescentes para aplicação em ensaios biológicos

Pós-graduação em Química - IBILCE

Fusão de métodos baseados em minúcias e em cristas para reconhecimento de impressões digitais

Pós-graduação em Ciência da Computação - IBILCE