Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

Benchmark Evaluation of HOG Descriptors as Features for Classification of Traffic Signs

The purpose of this paper is to analyze the performance of the Histograms of Oriented Gradients (HOG) as descriptors for traffic signs recognition. The test dataset consists of speed limit traffic signs because of their high inter-class similarities.   HOG features of speed limit signs, which were extracted from different traffic scenes, were computed and a Gentle AdaBoost classifier was invoked to evaluate the different features. The performance of HOG was tested with a dataset consisting of 1727 Swedish speed signs images. Different numbers of HOG features per descriptor, ranging from 36 features up 396 features, were computed for each traffic sign in the benchmark testing. The results show that HOG features perform high classification rate as the Gentle AdaBoost classification rate was 99.42%, and they are suitable to real time traffic sign recognition. However, it is found that changing the number of orientation bins has insignificant effect on the classification rate. In addition to this, HOG descriptors are not robust with respect to sign orientation.

Corporate social responsibility and environmental sustainability: classification of the initiatives of the FMCG companies operating in Brazil

Este trabalho tem como objetivo fornecer uma análise detalhada do cenário da sustentabilidade ambiental e iniciativas de responsabilidade social corporativa nas empresas que operam no mercado de bens de consumo brasileiro. Para alcançar este objetivo as dez maiores empresas do mercado-alvo presente no Brasil foram analisadas por meio da classificação das suas iniciativas em três perspectivas amplas. Com esta classificação o cenário do mercado pode ser visto. As perspectivas utilizadas para a elaboração do trabalho são: (1) iniciativa ambiental ou social; (2) o foco interno ou externo e (3) a marca ou o custo como motivador. Depois de classificar todas as iniciativas, foi possível ver que as empresas similares, que operam em mercados semelhantes, têm estratégias que são muito parecidos entre si. Além disso, ficou claro que a estratégia de negócios da empresa influencia as suas políticas ambientais e sociais, em particular os objetivos que estas políticas procuram obter.Embora este trabalho apresente um panorama abrangente do setor de bens de consumo em relação a políticas de comportamento responsável das empresas, ele tem algumas limitações. A limitação mais significativa diz respeito a metodologia. As iniciativas foram avaliadas pela quantidade e a abrangência dos benefícios do impacto positivo não foram avaliados, impossibilitando assim a comparação do tamanho do impacto de cada empresa. Uma vez que pode haver um projeto de uma empresa que tem maior impacto do que vários outros feitos por alguma outra empresa. A metodologia foi baseada em clusters de categorias, no entanto, as iniciativas não são completamente uma coisa ou outra, ou seja, uma iniciativa pode ter diferentes impactos, drivers ou foco, nesses casos, os aspectos mais relevantes foram a escolhidos para classificá-los.

Classification of Boal, Malvazia, Sercial and Verdelho wines based on terpenoid patterns

Thirty-six Madeira wine samples from Boal, Malvazia, Sercial and Verdelho white grape varieties were analyzed in order to estimate the free fraction of monoterpenols and C13 norisoprenoids (terpenoid compounds) using dynamic headspace solid phase micro-extraction (HS-SPME) technique coupled with gas chromatography–mass spectrometry (GC–MS). The average values from three vintages (1998–2000) show that these wines have characteristic profiles of terpenoid compounds. Malvazia wines exhibits the highest values of total free monoterpenols, contrary to Verdelho wines which had the lowest levels of terpenoids but produced the highest concentration of farnesol. The use of multivariate analysis techniques allows establishing relations between the compounds and the varieties under investigation. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to the obtained matrix data. A good separation and classification power between the four groups as a function of their varietal origin was observed.

Environmental Fate of Neonicotinoids and Classification of Their Potential Risks to Hypogean, Epygean, and Surface Water Ecosystems in Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A classification of Pepper yellow mosaic virus isolates into pathotypes

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

Self-Organizing Maps as a New Tool for Classification of Plants at Lower Hierarchical Levels

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

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

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

Critical analysis of the international classification of headache disorders diagnostic criteria (ICHD I-1988) and (ICHD II-2004), for migraine in children and adolescents

The present study analyzed the (ICHD I-1988) and ( ICHD II-2004) diagnostic criteria in children and adolescents. Our population consisted of 496 patients of the Headache Outpatient Ward for Children and Adolescents retrospectively studied from 1992 to 2002. Individuals were classified according to three diagnostic groups: Intuitive Clinical Diagnosis ( Gold Standard), ICHD I-1988 and ICHD II-2004. They were statistically compared using the variables: Sensitivity ( S), Specificity (Sp), Positive Predictive Value (PPV), Negative Predictive Value (NPV). When ICHD I-1988 was used, the sensitivity of migraine without and with aura was 21% and 27%, respectively, whereas in ICHD II-2004 it changed to 53% and 71% without affecting specificity. As a conclusion, the current classification criteria ( ICHD II-2004) showed greater sensitivity and high specificity for migraine than ICHD I-1988, although it improved migraine diagnosis in children and adolescents, the sensitivity remains poor.

A Brazilian registry of juvenile dermatomyositis: onset features and classification of 189 cases

ObjectiveTo describe onset features, classification and treatment of juvenile dermatomyositis (JDM) and juvenile polymyositis (JPM) from a multicentre registry.MethodsInclusion criteria were onset age lower than 18 years and a diagnosis of any idiopathic inflammatory myopathy (IIM) by attending physician. Bohan & Peter (1975) criteria categorisation was established by a scoring algorithm to define JDM and JPM based oil clinical protocol data.ResultsOf the 189 cases included, 178 were classified as JDM, 9 as JPM (19.8: 1) and 2 did not fit the criteria; 6.9% had features of chronic arthritis and connective tissue disease overlap. Diagnosis classification agreement occurred in 66.1%. Medial? onset age was 7 years, median follow-up duration was 3.6 years. Malignancy was described in 2 (1.1%) cases. Muscle weakness occurred in 95.8%; heliotrope rash 83.5%; Gottron plaques 83.1%; 92% had at least one abnormal muscle enzyme result. Muscle biopsy performed in 74.6% was abnormal in 91.5% and electromyogram performed in 39.2% resulted abnormal in 93.2%. Logistic regression analysis was done in 66 cases with all parameters assessed and only aldolase resulted significant, as independent variable for definite JDM (OR=5.4, 95%CI 1.2-24.4, p=0.03). Regarding treatment, 97.9% received steroids; 72% had in addition at least one: methotrexate (75.7%), hydroxychloroquine (64.7%), cyclosporine A (20.6%), IV immunoglobulin (20.6%), azathioprine (10.3%) or cyclophosphamide (9.6%). In this series 24.3% developed calcinosis and mortality rate was 4.2%.ConclusionEvaluation of predefined criteria set for a valid diagnosis indicated aldolase as the most important parameter associated with de, methotrexate combination, was the most indicated treatment.

Concordance between macroinvertebrate communities and the typological classification of white and clear-water streams in Western Brazilian Amazonia

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)