Submitted by Nadir Basilio (nadirsb@uninove.br) on 2017-02-22T21:06:29Z No. of bitstreams: 1 Henrricco Nieves Pujol Tucci.pdf: 3397813 bytes, checksum: c699bbae1cc911a864bb774413e18dec (MD5) / Made available in DSpace on 2017-02-22T21:06:29Z (GMT). No. of bitstreams: 1 Henrricco Nieves Pujol Tucci.pdf: 3397813 bytes, checksum: c699bbae1cc911a864bb774413e18dec (MD5) Previous issue date: 2016-11-21 / The aircraft supply is a major cause of flight delays since this process is slow and, if it does not start as soon as the aircraft is available for the maintenance team, the risk of being terminated after the last passenger has already boarded increases. The procedure usually only starts after the information of how much must be supplied get through the flight dispatcher and this information typically take some time to get to the maintenance team. However, it is intended to test a new scenario: start to supply with the minimum quantity of fuel and, if necessary, complete with the amount belatedly informed by dispatcher. Therefore, this paper aims to analyze the application of Six Sigma in this process through the Student's t-test and the Statistical Process Control (SPC). Sigma in this process through the Student t test and Statistical Process Control (SPC). The method adopted was multi cases study by interviews and organizational practices observations. The results showed that the new process is favorable in relation to the former, the Case 1 average time of flight delays has been reduced from 14 to 6 minutes (57%), Case 2 average time has been reduced from 10 to 6 minutes (53%), about flight delays quantity upper than 15 minutes, has reduced to 43% and 39% respectively. It concludes that the application of Six Sigma in aircraft refueling process is innovative to the scientific literature and was favorable for both companies, also helped to mitigate the risk of fines and penalties and, consequently, improved the level of quality of service offered by the airline company. / O abastecimento de aeronaves é uma das principais causas de atrasos de voo uma vez que este processo é lento e, caso este não seja iniciado assim que a aeronave esteja disponível para a equipe de manutenção, o risco de ser finalizado depois do último passageiro já ter embarcado aumenta. O processo de abastecimento usualmente só é iniciado após a informação de quanto se deve abastecer, esta informação costuma demorar a chegar para a equipe de manutenção. A melhoria no processo considera iniciar o abastecimento com a quantidade mínima de combustível e, se necessário, completar com a quantidade tardiamente informada. O objetivo desse trabalho é analisar a aplicação do Seis Sigma utilizando o teste t de Student e o Controle Estatístico do Processo (CEP) nas duas maiores companhias aéreas brasileiras. O método adotado foi estudo de múltiplos casos por meio de entrevista e observação na prática organizacional. O resultado demonstra que o tempo médio de atrasos de voo para o Caso 1 foi reduzido após a aplicação do Seis Sigma, de 14 para 6 minutos (57%). Além disso, a quantidade de atrasos acima de quinze minutos foi reduzida em 53%. Já no Caso 2, o tempo médio foi reduzido de 10 para 6 minutos, uma melhora de 43%, quanto a quantidade de atrasos acima de quinze minutos, houve uma redução de 39%. Conclui-se que a aplicação do Seis Sigma no processo de abastecimento de aeronaves é inovadora para a literatura científica e foi favorável para as duas empresas, também colaborou para mitigar os riscos de multas e penalidades e, consequentemente, melhorou o nível de qualidade do serviço oferecido pelas companhias aéreas.

This study investigates how outliers of different magnitude impact the robustness of the twosample t-test. A simulation study approach is used to analyze the behavior of type I error rates when outliers are added to generated data. Outliers may distort parameter estimates such as the mean and variance and cause misleading test results. Previous research has shown that Welch’s ttest performs better than the traditional Student’s t-test when group variances are unequal. Therefore these two alternative statistics are compared in terms of type I error rates when outliers are added to the samples. The results show that control of type I error rates can be maintained in the presence of a single outlier. Depending on the magnitude of the outlier and the sample size, there are scenarios where the t-test is robust. However, the sensitivity of the t-test is illustrated by deteriorating type I error rates when more than one outlier are included. The comparison between Welch’s t-test and Student’s t-test shows that the former is marginally more robust against outlier influence.

This essay investigates how realized variance affects the GARCH-models (GARCH, EGARCH, GJRGARCH) when added as an external regressor. The GARCH models are estimated with three different distributions; Normal-, Student’s t- and Normal inverse gaussian distribution. The results are ambiguous - the models with realized variance improves the model fit, but when applied to forecasting, the models with realized variance are performing similar Value at Risk predictions compared to the models without realized variance.

Submitted by Livia Mello (liviacmello@yahoo.com.br) on 2016-09-22T11:50:45Z No. of bitstreams: 1 DissPGLF.pdf: 2510277 bytes, checksum: ac0bc495fe911118e100ddeeaea3b4d9 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T14:47:09Z (GMT) No. of bitstreams: 1 DissPGLF.pdf: 2510277 bytes, checksum: ac0bc495fe911118e100ddeeaea3b4d9 (MD5) / Approved for entry into archive by Marina Freitas (marinapf@ufscar.br) on 2016-10-10T14:47:16Z (GMT) No. of bitstreams: 1 DissPGLF.pdf: 2510277 bytes, checksum: ac0bc495fe911118e100ddeeaea3b4d9 (MD5) / Made available in DSpace on 2016-10-10T14:47:24Z (GMT). No. of bitstreams: 1 DissPGLF.pdf: 2510277 bytes, checksum: ac0bc495fe911118e100ddeeaea3b4d9 (MD5) Previous issue date: 2016-02-15 / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Multiple Sclerosis (MS) is an inflammatory demyelinating (that is, with myelin loss) disease of the Central Nervous System (CNS). It is considered an autoimmune disease in which the immune system wrongly recognizes the myelin sheath of the CNS as an external element and attacks it, resulting in inflammation and scarring (sclerosis) of multiple areas of CNS’s white matter. Multi-contrast magnetic resonance imaging (MRI) has been successfully used in diagnosing and monitoring MS due to its excellent properties such as high resolution and good differentiation between soft tissues. Nowadays, the preferred method to segment MS lesions is the manual segmentation, which is done by specialists with limited help of a computer. However, this approach is tiresome, expensive and prone to error due to inter- and intra-variability between observers caused by low contrast on lesion edges. The challenge in automatic detection and segmentation of MS lesions in MR images is related to the variability of size and location of lesions, low contrast due to partial volume effect and the high range of forms that lesions can take depending on the stage of the disease. Recently, many researchers have turned their efforts into developing techniques that aim to accurately measure volumes of brain tissues and MS lesions, and also to reduce the amount of time spent on image analysis. In this context, this project proposes the study and development of an automatic computational technique based on an outlier detection approach, Student’s t-distribution finite mixture models and probabilistic atlases to segment and measure MS lesions volumes in MR images. / Esclerose Múltipla (EM) é uma doença inflamatória e desmielinizante (isto é, com perda de mielina) do sistema nervoso central (SNC). É considerada uma doença autoimune a qual o sistema imunológico reconhece erroneamente a bainha de mielina do SNC como um elemento externo e então a ataca, resultando em inflamação e formação de cicatrizes gliais (escleroses) em múltiplas áreas da substância branca do SNC. O imageamento multi- contraste por ressonância magnética (RM) tem sido usado clinicamente com muito sucesso para o diagnóstico e monitoramento da EM devido às suas excelentes propriedades como alta resolução e boa diferenciação de tecidos moles. Atualmente, o método utilizado para a segmentação de lesões de EM é o delineamento manual em imagens 3D de RM, o qual é realizado por especialistas com ajuda limitada do computador. Entretanto, tal procedimento é custoso e propenso à variabilidade inter e intraobservadores devido ao baixo contraste das bordas das lesões. A grande dificuldade na detecção e segmentação automáticas das le- sões de EM em imagens de RM está associada às suas variações no tamanho e localização, baixo contraste decorrente do efeito de volume parcial e o amplo espectro de aparências (realçadas, não-realçadas, black-holes) que elas podem ter, dependendo do estado evolutivo da doença. Atualmente, vários pesquisadores têm voltado seus esforços para o desenvol- vimento de técnicas que visam diminuir o tempo gasto na análise das imagens e medir, de maneira mais precisa, o volume dos tecidos cerebrais e das lesões de EM. Nesse contexto, este projeto propõe o estudo e o desenvolvimento de uma técnica computacional automá- tica, baseada na abordagem de detecção de outliers e usando modelos de misturas finitas de distribuições t-Student e atlas probabilísticos para a segmentação e medição do volume de lesões de EM em imagens de RM. / FAPESP: 2014/00019-6

This thesis deals with speech analysis of people who suffer from Parkinson’s disease. Purpose of this thesis is to obtain statistical sample of speech parameters which helps to determine if examined person is suffering from Parkinson’s disease. Statistical sample is based on hypokinetic dysarthria detection. For speech signal pre-processing DC-offset removal and pre-emphasis are used. The next step is to divide signal into frames. Phonation parameters, MFCC and PLP coefficients are used for characterization of framed speech signal. After parametrization the speech signal can be analyzed by statistical methods. For statistical analysis in this thesis Spearman’s and Pearson’s correlation coefficients, mutual information, Mann-Whitney U test and Student’s t-test are used. The thesis results are the groups of speech parameters for individual long czech vowels which are the best indicator of the difference between healthy person and patient suffering from Parkinson’s disease. These result can be helpful in medical diagnosis of a patient.