Aplicação de uma rede neural artificial para a avaliação da rugosidade e soprosidade vocal

A avaliação perceptivo-auditiva tem papel fundamental no estudo e na avaliação da voz, no entanto, por ser subjetiva está sujeita a imprecisões e variações. Por outro lado, a análise acústica permite a reprodutibilidade de resultados, porém precisa ser aprimorada, pois não analisa com precisão vozes com disfonias mais intensas e com ondas caóticas. Assim, elaborar medidas que proporcionem conhecimentos confiáveis em relação à função vocal resulta de uma necessidade antiga dentro desta linha de pesquisa e atuação clínica. Neste contexto, o uso da inteligência artificial, como as redes neurais artificiais, indica ser uma abordagem promissora. Objetivo: Validar um sistema automático utilizando redes neurais artificiais para a avaliação de vozes rugosas e soprosas. Materiais e métodos: Foram selecionadas 150 vozes, desde neutras até com presença em grau intenso de rugosidade e/ou soprosidade, do banco de dados da Clínica de Fonoaudiologia da Faculdade de Odontologia de Bauru (FOB/USP). Dessas vozes, 23 foram excluídas por não responderem aos critérios de inclusão na amostra, assim utilizaram-se 123 vozes. Procedimentos: avaliação perceptivo-auditiva pela escala visual analógica de 100 mm e pela escala numérica de quatro pontos; extração de características do sinal de voz por meio da Transformada Wavelet Packet e dos parâmetros acústicos: jitter, shimmer, amplitude da derivada e amplitude do pitch; e validação do classificador por meio da parametrização, treino, teste e avaliação das redes neurais artificiais. Resultados: Na avaliação perceptivo-auditiva encontrou-se, por meio do teste Coeficiente de Correlação Intraclasse (CCI), concordâncias inter e intrajuiz excelentes, com p = 0,85 na concordância interjuízes e p variando de 0,87 a 0,93 nas concordâncias intrajuiz. Em relação ao desempenho da rede neural artificial, na discriminação da soprosidade e da rugosidade e dos seus respectivos graus, encontrou-se o melhor desempenho para a soprosidade no subconjunto composto pelo jitter, amplitude do pitch e frequência fundamental, no qual obteve-se taxa de acerto de 74%, concordância excelente com a avaliação perceptivo-auditiva da escala visual analógica (0,80 no CCI) e erro médio de 9 mm. Para a rugosidade, o melhor subconjunto foi composto pela Transformada Wavelet Packet com 1 nível de decomposição, jitter, shimmer, amplitude do pitch e frequência fundamental, no qual obteve-se 73% de acerto, concordância excelente (0,84 no CCI), e erro médio de 10 mm. Conclusão: O uso da inteligência artificial baseado em redes neurais artificiais na identificação, e graduação da rugosidade e da soprosidade, apresentou confiabilidade excelente (CCI > 0,80), com resultados semelhantes a concordância interjuízes. Dessa forma, a rede neural artificial revela-se como uma metodologia promissora de avaliação vocal, tendo sua maior vantagem a objetividade na avaliação.

Tuta absoluta (Meyrick, 1917) (Lepidoptera: Gelechiidae): adequação de uma dieta artificial e avaliação do seu controle biológico com Trichogramma pretiosum Riley em tomateiro

Tuta absoluta (Meyrick, 1917) é uma das pragas-chave da cultura do tomate e outras solanáceas na América do Sul e atualmente também na Eurásia e África. Devido aos grandes prejuízos que causa à cultura, são principalmente usados inseticidas para o seu controle. Entretanto, na busca de estratégias mais sustentáveis, cada dia adquire maior importância o uso do controle biológico, como uma das estratégias do manejo integrado de pragas. Para o desenvolvimento destas estratégias é fundamental desenvolver um método de criação de T. absoluta em laboratório, em dieta artificial, sem necessitar do hospedeiro natural, muitas vezes difícil de ser obtido e mantido em laboratório, e, de grande importância para produzir parasitoides específicos para esta praga. Dentre os parasitoides mais usados para ovos de lepidópteros está Trichogramma pretiosum Riley 1879 que é usado no controle biológico aplicado desta praga. Tendo como foco principal T. absoluta, neste trabalho foram pesquisados 1) a seleção de uma dieta artificial para este lepidóptero baseando-se em características físicas e químicas, avaliando o seu desempenho por várias gerações em laboratório, e 2) avaliação de aspectos biológicos e reprodutivos de T. pretiosum parasitando ovos de T. absoluta e aspectos físicos da planta (tricomas) para compreender o controle biológico desta praga no tomateiro. Foi encontrado que uma dieta à base de germe-de-trigo, caseína e celulose é apropriada para a criação deste lepidóptero, já que o inseto mostrou adaptação à mesma no transcorrer das gerações com base em características biológicas e de tabela de vida; adicionalmente, os ovos provenientes de T. absoluta alimentada com dieta artificial são comparáveis aos da dieta natural, no parasitismo de T. pretiosum. Com relação ao controle biológico foi demonstrado que este parasitoide desenvolvido em ovos de T. absoluta, diminui seu tamanho e desempenho com o transcorrer das gerações, apresentando menor capacidade de voo do que os insetos produzidos em A. kuenhiella, sendo necessária a liberação de altas densidades de parasitoides por ovo da praga. Foi observado que, embora o parasitismo de T. pretiosum de ovos de T. absoluta seja melhor em variedades com poucos tricomas, uma alta densidade destas estruturas não impede o controle da praga alvo dependendo da disposição destas estruturas. O controle biológico de T. absoluta com T. pretiosum tem uma ação momentânea, sendo necessárias liberações frequentes devido ao fato de os parasitoides desenvolvidos na praga serem menos competitivos com aqueles provenientes do hospedeiro alternativo que apresenta ovos maiores do que T. absoluta.

Topological SLAM using a graph-matching based method on omnidirectional images

Comunicación presentada en el XI Workshop of Physical Agents, Valencia, 9-10 septiembre 2010.

A novel information theory method for filter feature selection

In this paper, we propose a novel filter for feature selection. Such filter relies on the estimation of the mutual information between features and classes. We bypass the estimation of the probability density function with the aid of the entropic-graphs approximation of Rényi entropy, and the subsequent approximation of the Shannon one. The complexity of such bypassing process does not depend on the number of dimensions but on the number of patterns/samples, and thus the curse of dimensionality is circumvented. We show that it is then possible to outperform a greedy algorithm based on the maximal relevance and minimal redundancy criterion. We successfully test our method both in the contexts of image classification and microarray data classification.

An hybrid parallel algorithm for solving tridiagonal linear systems versus the Wang’s method in a Cray T3D BSP computer

In this paper we describe an hybrid algorithm for an even number of processors based on an algorithm for two processors and the Overlapping Partition Method for tridiagonal systems. Moreover, we compare this hybrid method with the Partition Wang’s method in a BSP computer. Finally, we compare the theoretical computation cost of both methods for a Cray T3D computer, using the cost model that BSP model provides.

Evaluating approximations generated by the GNG3D method for mesh simplification

In this paper we present different error measurements with the aim to evaluate the quality of the approximations generated by the GNG3D method for mesh simplification. The first phase of this method consists on the execution of the GNG3D algorithm, described in the paper. The primary goal of this phase is to obtain a simplified set of vertices representing the best approximation of the original 3D object. In the reconstruction phase we use the information provided by the optimization algorithm to reconstruct the faces thus obtaining the optimized mesh. The implementation of three error functions, named Eavg, Emax, Esur, permitts us to control the error of the simplified model, as it is shown in the examples studied.

A study of a soft computing based method for 3D scenario reconstruction

Several recent works deal with 3D data in mobile robotic problems, e.g., mapping. Data comes from any kind of sensor (time of flight, Kinect or 3D lasers) that provide a huge amount of unorganized 3D data. In this paper we detail an efficient approach to build complete 3D models using a soft computing method, the Growing Neural Gas (GNG). As neural models deal easily with noise, imprecision, uncertainty or partial data, GNG provides better results than other approaches. The GNG obtained is then applied to a sequence. We present a comprehensive study on GNG parameters to ensure the best result at the lowest time cost. From this GNG structure, we propose to calculate planar patches and thus obtaining a fast method to compute the movement performed by a mobile robot by means of a 3D models registration algorithm. Final results of 3D mapping are also shown.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

A robust and fast method for 6DoF motion estimation from generalized 3D data

Nowadays, there is an increasing number of robotic applications that need to act in real three-dimensional (3D) scenarios. In this paper we present a new mobile robotics orientated 3D registration method that improves previous Iterative Closest Points based solutions both in speed and accuracy. As an initial step, we perform a low cost computational method to obtain descriptions for 3D scenes planar surfaces. Then, from these descriptions we apply a force system in order to compute accurately and efficiently a six degrees of freedom egomotion. We describe the basis of our approach and demonstrate its validity with several experiments using different kinds of 3D sensors and different 3D real environments.

An improvement of a SLAM RGB-D method with movement prediction derived from a study of visual features

This paper presents a method for the fast calculation of a robot’s egomotion using visual features. The method is part of a complete system for automatic map building and Simultaneous Location and Mapping (SLAM). The method uses optical flow to determine whether the robot has undergone a movement. If so, some visual features that do not satisfy several criteria are deleted, and then egomotion is calculated. Thus, the proposed method improves the efficiency of the whole process because not all the data is processed. We use a state-of-the-art algorithm (TORO) to rectify the map and solve the SLAM problem. Additionally, a study of different visual detectors and descriptors has been conducted to identify which of them are more suitable for the SLAM problem. Finally, a navigation method is described using the map obtained from the SLAM solution.

A new method of making foliage for miniature dioramas / Alfred Lee Rowell --.

no.8(1953)

Artificial fireworks improved to the modern practice from the minutest to the highest branches ... : with all their ingredients, compositions, preparations, machines, moulds and manner to make them : with about 100 of the principal figures beautifully engraved on copper plates /

M. Belidor's New Method of mining. To which is added, M. Vallier's Dissertation on countermines.

Unlocking pathology archives for molecular genetic studies: a reliable method to generate probes for chromogenic and fluorescent in situ hybridization

Chromogenic (CISH) and fluorescent ( FISH) in situ hybridization have emerged as reliable techniques to identify amplifications and chromosomal translocations. CISH provides a spatial distribution of gene copy number changes in tumour tissue and allows a direct correlation between copy number changes and the morphological features of neoplastic cells. However, the limited number of commercially available gene probes has hindered the use of this technique. We have devised a protocol to generate probes for CISH that can be applied to formalin-fixed, paraffin-embedded tissue sections (FFPETS). Bacterial artificial chromosomes ( BACs) containing fragments of human DNA which map to specific genomic regions of interest are amplified with phi 29 polymerase and random primer labelled with biotin. The genomic location of these can be readily confirmed by BAC end pair sequencing and FISH mapping on normal lymphocyte metaphase spreads. To demonstrate the reliability of the probes generated with this protocol, four strategies were employed: (i) probes mapping to cyclin D1 (CCND1) were generated and their performance was compared with that of a commercially available probe for the same gene in a series of 10 FFPETS of breast cancer samples of which five harboured CCND1 amplification; (ii) probes targeting cyclin-dependent kinase 4 were used to validate an amplification identified by microarray-based comparative genomic hybridization (aCGH) in a pleomorphic adenoma; (iii) probes targeting fibroblast growth factor receptor 1 and CCND1 were used to validate amplifications mapping to these regions, as defined by aCGH, in an invasive lobular breast carcinoma with FISH and CISH; and (iv) gene-specific probes for ETV6 and NTRK3 were used to demonstrate the presence of t(12; 15)(p12; q25) translocation in a case of breast secretory carcinoma with dual colour FISH. In summary, this protocol enables the generation of probes mapping to any gene of interest that can be applied to FFPETS, allowing correlation of morphological features with gene copy number.

Artificial pumping errors in the Kool-Parker scaling model of soil moisture hysteresis

Hysteresis models that eliminate the artificial pumping errors associated with the Kool-Parker (KP) soil moisture hysteresis model, such as the Parker-Lenhard (PL) method, can be computationally demanding in unsaturated transport models since they need to retain the wetting-drying history of the system. The pumping errors in these models need to be eliminated for correct simulation of cyclical systems (e.g. transport above a tidally forced watertable, infiltration and redistribution under periodic irrigation) if the soils exhibit significant hysteresis. A modification is made here to the PL method that allows it to be more readily applied to numerical models by eliminating the need to store a large number of soil moisture reversal points. The modified-PL method largely eliminates any artificial pumping error and so essentially retains the accuracy of the original PL approach. The modified-PL method is implemented in HYDRUS-1D (version 2.0), which is then used to simulate cyclic capillary fringe dynamics to show the influence of removing artificial pumping errors and to demonstrate the ease of implementation. Artificial pumping errors are shown to be significant for the soils and system characteristics used here in numerical experiments of transport above a fluctuating watertable. (c) 2005 Elsevier B.V. All rights reserved.

Network topology and the evolution of dynamics in an artificial genetic regulatory network model created by whole genome duplication and divergence

Topological measures of large-scale complex networks are applied to a specific artificial regulatory network model created through a whole genome duplication and divergence mechanism. This class of networks share topological features with natural transcriptional regulatory networks. Specifically, these networks display scale-free and small-world topology and possess subgraph distributions similar to those of natural networks. Thus, the topologies inherent in natural networks may be in part due to their method of creation rather than being exclusively shaped by subsequent evolution under selection. The evolvability of the dynamics of these networks is also examined by evolving networks in simulation to obtain three simple types of output dynamics. The networks obtained from this process show a wide variety of topologies and numbers of genes indicating that it is relatively easy to evolve these classes of dynamics in this model. (c) 2006 Elsevier Ireland Ltd. All rights reserved.