abstract: Mobile ad hoc networks (MANETs) have attracted attention for mission critical applications. This dissertation investigates techniques of statistical monitoring and control for overhead reduction in a proactive MANET routing protocol. Proactive protocols transmit overhead periodically. Instead, we propose that the local conditions of a node should determine this transmission decision. While the goal is to minimize overhead, a balance in the amount of overhead transmitted and the performance achieved is required. Statistical monitoring consists of techniques to determine if a characteristic has shifted away from an in-control state. A basic tool for monitoring is a control chart, a time-oriented representation of the characteristic. When a sample deviates outside control limits, a significant change has occurred and corrective actions are required to return to the in-control state. We investigate the use of statistical monitoring of local conditions in the Optimized Link State Routing (OLSR) protocol. Three versions are developed. In A-OLSR, each node uses a Shewhart chart to monitor betweenness of its two-hop neighbourhood. Betweenness is a social network metric that measures a node's influence; betweenness is larger when a node has more influence. Changes in topology are associated with changes in betweenness. We incorporate additional local node conditions including speed, density, packet arrival rate, and number of flows it forwards in A+-OLSR. Response Surface Methodology (RSM) is used to optimize timer values. As well, the Shewhart chart is replaced by an Exponentially Weighted Moving Average (EWMA) chart, which is more sensitive to small changes in the characteristic. It is known that control charts do not work as well in the presence of correlation. Hence, in A*-OLSR the autocorrelation in the time series is removed and an Auto-Regressive Integrated Moving Average (ARIMA) model found; this removes the dependence on node speed. A*-OLSR also extends monitoring to two characteristics concurrently using multivariate cumulative sum (MCUSUM) charts. The protocols are evaluated in simulation, and compared to OLSR and its variants. The techniques for statistical monitoring and control are general and have great potential to be applied to the adaptive control of many network protocols. / Dissertation/Thesis / Ph.D. Computer Science 2012

Successfully implementing continuous improvement and quality methodologies have been challenging over the past century. Challenges occur in managing change in the organization, which can be effectively addressed through relationship building in concert with strong leadership. Even with solid leadership, change management, and relationship building, initiatives have challenges quantifying and identifying when to intervene in order to keep them on track for success. Creating a quantitative model using a 3-parameter logit s-curve, Blythe S-curve, to illustrate the growth and decay of the handoff of projects to the process owner will allow leadership the knowledge and direction to keep the initiative moving in a positive direction. Leveraging the Hotelling T2 multivariate charts on the residuals derived from the Blythe S-curve will give definitive statistical evidence on when to intervene on projects in the earliest possible time frame. Leaders in organizations implementing and actively using change management, relationship building, the Blythe S-curve model, and Hotelling T2 multivariate charts to drive quality and continuous improvement methodologies in their organization will improve the likelihood of success.

CNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico / A Lei nº 13.033/2014 estabelece a adição de 7 ± 0,5% (v/v) de biodiesel ao óleo diesel utilizado no sistema viário e proíbe a adição de óleos vegetais ou quaisquer solventes nesta mistura. No entanto, há casos de adição irregular de óleos vegetais e/ou residuais no diesel devido, principalmente, ao baixo custo destas matérias-primas em comparação com o produto final ou contaminado durante seu transporte e armazenamento. Assim, são necessárias análises que forneçam respostas imediatas e eficientes para garantir a qualidade dos combustíveis comercializados. Nesse sentido, o presente trabalho propõe o monitoramento da qualidade das misturas biodiesel/diesel (7% de biodiesel e 93% de diesel) usando a Espectrometria no Infravermelho Médio associada a Cartas de Controle Multivariadas baseadas no sinal analítico líquido (NAS). Os biodieseis foram produzidos a partir de óleos de macaúba e algodão usando metanol e etanol. Para cada modelo, foram desenvolvidas três cartas (gráficos): a Carta NAS, que corresponde ao analito de interesse (nesse caso o biodiesel), a carta interferente, relacionadas às contribuições de outros componentes na amostra (diesel), e a carta resíduo correspondendo à variação não sistemática nos espectros (ruído instrumental). Foram analisadas 1508 amostras utilizadas na calibração e validação de seis modelos (biodieseis etílicos e metílicos de algodão, biodieseis metílicos da amêndoa da macaúba, biodieseis metílicos e etílicos do mesocarpo da macaúba, e também de B7 comercial). Na etapa de calibração foram usadas 103 amostras dentro das especificações de qualidade, amostras estas usadas para estabelecerem os limites estatísticos para cada carta. A etapa de validação se deu com amostras dentro e fora das especificações de qualidade (1405 amostras). A validação com amostras fora dos padrões de qualidade foi feita de duas maneiras: em relação ao teor de biodiesel no diesel e à presença de adulterantes no biodiesel, no diesel e na mistura. A presença de adulterantes se deu por substituição parcial do biodiesel por óleos de soja, milho e residual, substituição parcial do diesel por óleo lubrificante, querosene e gasolina e por adição direta dos adulterantes citados na mistura biodiesel/diesel (B7) na faixa de 3,5 a 43,5% (v/v) correspondendo a uma faixa de adulteração de 0,2 a 30% (v/v) na mistura. Assim, foi possível separar as amostras conformes e não conformes tanto em relação ao teor de biodiesel no diesel quanto à presença de adulterantes, uma vez que as amostras dentro das especificações ficaram dentro dos limites estabelecidos e as amostras fora das especificações saíram do limite em pelo menos uma das cartas. Desta maneira, os resultados mostraram que o método descrito neste trabalho é uma alternativa viável, eficiente e rápida no controle de qualidade de biocombustível. / The Law No. 13.033/2014 establishes the addition of 7 ± 0.5% (v/v) of biodiesel to the diesel used in the road system and prohibits the addition of vegetable oils or any solvents to this mixture. However, there are cases of irregular addition of vegetable and/or waste oils in diesel, mainly due to the low cost of these raw materials when compared to the final or contaminated product during transportation and storage. Thus, analyzes are necessary to provide immediate and efficient responses in order to ensure the quality of the marketed fuels. In this sense, the present study proposed the quality monitoring of biodiesel/diesel blends (7% biodiesel and 93% diesel) through the use of the Medium Infrared Spectrometry associated with Multivariate Control Charts based on the liquid analytical signal (NAS). Biodiesel was produced from macaúba (acrocomia aculeate) and cotton oils using methanol and ethanol. For each model, three charts were developed: the NAS Chart, which corresponds to the analyte of interest (in this case biodiesel); the interfering chart, related to the contributions of other components in the sample (diesel); and the waste chart, corresponding to non-systematic variation in spectra (instrumental noise). A total of 1508 samples were used for the calibration and validation of the six models (ethyl and cotton biodiesel, macaúba almond (acrocomia aculeate) methyl biodiesel, macaúba mesocarp (acrocomia aculeate) methyl and biodiesel, and also commercial B7 biodiesel). At the calibration stage, 103 samples were used within the quality specifications, these samples were used to establish the statistical limits for each chart. The validation step was carried out with samples within and out of the quality specifications (1405 samples). The validation with non-standard quality samples was carried out in two ways: in relation to the biodiesel content in diesel and the presence of adulterants in biodiesel, diesel and blend. The presence of adulterants was due to the partial replacement of biodiesel by soybean, corn and residual oils; the partial replacement of diesel by lubricating oil, kerosene and gasoline; and by direct addition of the adulterants mentioned in the biodiesel/diesel blend (B7) in the range of 3.5 to 43.5% (v/v) corresponding to an adulteration range of 0.2 to 30% (v/v) in the blend. Thus, it was possible to separate the conforming and non-conforming samples, both regarding the biodiesel content in diesel and the presence of adulterants, since the samples within the specifications were within the established limits, and the samples out of the specifications have exceeded the limit in least one of the charts. Thus, the results have showed that the method described in this study is a viable, efficient and fast alternative to the biofuel quality control. / Tese (Doutorado)

It is often important to detect an increase in the frequency of some event. Particular attention is given to medical events such as mortality or the incidence of a given disease, infection or birth defect. Observations are regularly taken in which either an incidence occurs or one does not. This dissertation contains the result of an investigation of prospective monitoring techniques in two distinct surveillance situations. In the first situation, the observations are assumed to be the results of independent Bernoulli trials. Some have suggested adapting the scan statistic to monitor such rates and detect a rate increase as soon as possible after it occurs. Other methods could be used in prospective surveillance, such as the Bernoulli cumulative sum (CUSUM) technique. Issues involved in selecting parameters for the scan statistic and CUSUM methods are discussed, and a method for computing the expected number of observations needed for the scan statistic method to signal a rate increase is given. A comparison of these methods shows that the Bernoulli CUSUM method tends to be more effective in detecting increases in the rate. In the second situation, the incidence information is available at multiple locations. In this case the individual sites often report a count of incidences on a regularly scheduled basis. It is assumed that the counts are Poisson random variables which are independent over time, but the counts at any given time are possibly correlated between regions. Multivariate techniques have been suggested for this situation, but many of these approaches have shortcomings which have been demonstrated in the quality control literature. In an attempt to remedy some of these shortcomings, a new control chart is recommended based on a multivariate exponentially weighted moving average. The average run-length performance of this chart is compared with that of the existing methods. / Ph. D.

Submitted by Maike Costa (maiksebas@gmail.com) on 2016-05-16T13:15:08Z No. of bitstreams: 1 arquivo total.pdf: 6619153 bytes, checksum: ab30577da64fe07f90d28f172fea6661 (MD5) / Made available in DSpace on 2016-05-16T13:15:08Z (GMT). No. of bitstreams: 1 arquivo total.pdf: 6619153 bytes, checksum: ab30577da64fe07f90d28f172fea6661 (MD5) Previous issue date: 2015-04-06 / Statistical process control is becoming increasingly important in the pharmaceutical industry, since it can act on the product quality assurance and monitoring of production efficiency. Regulatory agencies worldwide already include multivariate statistical process control on their recommendations. In this work we perform three applications of multivariate control charts to detect small variations in monitoring pharmaceutical process. The studies were performed in the Laboratório Farmacêutico do Estado de Pernambuco Governador Miguel Arraes - LAFEPE using process data and addressing real problems of the industry routine. The first one consists in the elaboration of the Annual Product Review using multivariate control charts based on Principal Component Analysis, accompanied by a simple and unique methodology for identification of multivariate signal out of control, which was performed by decomposition of T2 statistics based on the loadings of VARIMAX rotation. The method developed has allowed the sector responsible for the Quality Assurance industry to verify the variables that most impact the process. The second application consists in monitoring of the degradation of captopril in tablets by High Performance Liquid Chromatograph measurements. For this aim multivariate control charts based on residuals of principal component analysis were built. The weighting of the retention time of the chromatogram in the region of captopril disulfide highlights the residual chart for revealing slight changes in the chromatographic standards. The third and last application consists in monitoring of the degradation of captopril in tablets by near infrared and middle infrared measurements. For this aim T2 control charts were built by using a variable selection method and a CUSUM-COT scheme. Both the techniques showed to be able for detection of expired samples and Middle infrared was able to identify slight changes during degradation process. Keywords: Monitoring of Process, Multivariate Control Charts, Annual Prod / O controle estatístico de processos vem ganhando importância na indústria farmacêutica, uma vez que pode atuar na garantia da qualidade do produto e no monitoramento da eficiência da produção. Agências regulatórias no mundo já incluem o controle estatístico de processos multivariado em suas recomendações. Neste trabalho realizamos três aplicações de cartas de controle multivariadas para detectar pequenas variações em processos na indústria farmacêutica. Os estudos foram realizados no Laboratório Farmacêutico do Estado de Pernambuco Governador Miguel Arraes - LAFEPE, empregando dados do processo e abordando problemas reais da rotina da indústria. A primeira aplicação consiste na elaboração da Revisão Periódica de Produtos empregando cartas de controle multivariadas baseadas em Análise de Componentes Principais, acompanhada de uma metodologia simples e original para identificação do sinal multivariado fora de controle por meio da decomposição da estatística T2 com base nos pesos da rotação VARIMAX. O procedimento desenvolvido permitiu monitorar e diagnosticar os desvios no processo produtivo, além de permitir ao setor responsável pela Garantia da Qualidade verificar as variáveis que mais impactaram o processo. A segunda aplicação é demonstrada em estudos de estabilidade de medicamentos empregando Cromatografia Líquida de Alta Eficiência. No estudo de estabilidade a carta de resíduos das componentes principais permitiu monitorar o processo de degradação de comprimidos de captopril. A ponderação do cromatograma na região do dissulfeto de captopril sensibiliza a carta de resíduos para revelar alterações sutis no padrão cromatográfico. A terceira aplicação envolve estudos de estabilidade empregando a espectroscopia no infravermelho próximo e médio. Nesta aplicação, conclui-se que ambas as técnicas são eficientes em detectar amostras vencidas. O Processo de degradação do captopril pode ser acompanhado pela carta de resíduos baseada nos espectros do infravermelho próximo. No infravermelho médio, a carta T2 construída com um método de seleção de variáveis e um esquema CUSUM-COT também foi eficiente em detectar as pequenas alterações durante o processo de degradação.

Orientador: Ronei Jesus Poppi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-22T08:18:21Z (GMT). No. of bitstreams: 1 Avila_ThiagoCarvalhode_M.pdf: 7831860 bytes, checksum: 010f2295e00f097a9ecfaf3f498a7069 (MD5) Previous issue date: 2013 / Resumo: Este trabalho visou o uso de Espectroscopia Raman e de Quimiometria para monitoramento e controle da fermentação de glicose por Saccharomyces cerevisiae. Na primeira etapa, foi utilizada calibração multivariada baseada no método dos Mínimos Quadrados Parciais (PLS) para quantificação de glicose, etanol, glicerol, ácido acético e células. Os modelos foram desenvolvidos baseados nos valores de concentração obtidos pelos métodos de referência, cromatografia líquida de alta eficiência ¿ HPLC e espectrofotometria UV/Vis. Tanto na etapa de calibração quanto na de validação, a otimização foi realizada com eliminação de amostras anômalas, baseada nos valores de leverage, resíduos e escores. Na segunda etapa, cartas de controle multivariadas foram usadas para identificação de falhas em bateladas durante o processo de fermentação. Foram construídos modelos MPCA (Análise de Componentes Principais Multimodo) a partir de bateladas NOC (Condições Normais de Operação). As cartas de controle multivariadas foram aplicadas em dois modos de desdobramento dos dados obtidos durante o monitoramento, um preservando a direção das bateladas e outro a direção do tempo. As falhas estudadas foram temperatura, mudança no substrato e contaminação do sistema. No modo de desdobramento por bateladas, a carta de controle Q foi eficiente para detecção das falhas estudas, fato comprovado pela classificação correta de três bateladas NOC como dentro de controle. No entanto, a carta de controle T2 não foi capaz de identificar as falhas estudadas corretamente como fora de controle. O modo de desdobramento pelo tempo também apresentou classificações corretas das falhas estudadas / Abstract: This work aims the use of Raman Spectroscopy and Chemometrics in the monitoring and control in the fermentation of the glucose by Saccharomyces cerevisiae. In the first step, it was applied the multivariate calibration based on Partial Least Squares (PLS) for the quantification of glucose, ethanol, glycerol, acetic acid and cells. The developed of calibration models was performed against the concentration values obtained by the reference methods, High Performance Liquid Chromatography and UV/Vis spectrophotometer. The optimization of the calibration and validation steps, the elimination of outliers was performed based on the values of leverage, residues and scores. In the second step, multivariate control charts were used for identification of batch-fault during the fermentation process. Multi-way Principal Component Analysis (MPCA) models were developed from batch NOC (Normal Operation Conditions). The multivariate control charts were based on two modes of unfolding the multi-way data, obtained during monitoring, one preserving the direction of the batch and another the direction of time. The fault studied were temperature, changes in the substrate and contamination of the system. In unfolding batch mode, the chart Q was effective for detection of the faults studied, proven by the correctly classification of 3 NOC batches as in control. However, the chart T2 failed to identify faults studied. The unfolding in time mode, also presented correct classifications of the faults studied / Mestrado / Quimica Analitica / Mestre em Química