Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 99-108. / by Marvin Stuart Keshner. / Sc.D.

A dieta é considerada um dos fatores que mais influencia o comportamento espacial dos primatas. Muitas pesquisas que abordam essa relação apresentam similaridades nos seus delineamentos, mas não existe uma metodologia padrão comum. Para compreender melhor a relação entre dieta e padrões espaciais dos primatas, é preciso investigar o efeito de alguns problemas metodológicos. No presente estudo, descrevemos quatro:o problema da descontinuidade do registro, que é o efeito da dependência temporal sobre registros distribuídos desigualmente ao longo do tempo; o problema de filtragem, que descreve a dificuldade para isolar o efeito da variável independente, dieta; o problema do fracionamento, que alerta sobre os perigos de transportar conclusões a grande escala com dados de pequena escala; e o problema da linearidade fechada, que discute a validade das medidas de superfície quando o tempo registrado é muito curto. Desenvolvemos uma metodologia para controlar esses problemas. A metodologia foi aplicada com registros da dieta e localizações de um grupo de Sapajus nigritus do Parque Estadual Carlos Botelho, São Paulo, coletados em dois períodos, 2007-2008 e 2009-2010. Também utilizamos um delineamento mais convencional e comparamos os resultados obtidos com ambas asmetodologias. Os resultados foram similares com ambos os delineamentos, mas em alguns aspectosa metodologia nova teve melhor desempenho. A dieta foi analisada utilizando as categorias alimentos agregados e dispersos. Essa classificação tem sido criticada pela amplitude das suas categorias, mas no presente estudo foi sensível a mudanças nos padrões espaciais de Sapajus. Os resultados não foram conclusivos com períodos grandes descontínuos, mas foram visíveis com períodos curtos e contínuos. Com o aumento de consumo de itens dispersos diminuiu a distância diária percorrida e o espaço foi utilizado de forma mais uniforme. As maiores áreas foram observadas com períodos de consumo misto. Os padrões espaciais desses primatas foram bem descritos com base na energia obtida e os custos do deslocamento / Diet is considered one of the most influential factors on primates spatial patterns. Many studies that have addressed this relationship present methodological similarities, but there is no common standard methodology. In order to better understand the relationship between diet and spatial patterns of primates we need to investigate the effect of some methodological problems. In thisstudy we describe four of these problems: the problem of the discontinuous data, that is, the effect of autocorrelation when observations are distributed unevenly over time; the filtering problem, that describes the difficulties to isolate the effect of the independent variable, in this case, the diet; the partialness problem, that calls our attention to the risk of making large scale conclusions based on small scale data; and the problem of fenced linearity, that discusses the validity of area estimations, when time sampling is too small. We developed a methodology to control these problems and tested it on the data collected for one group of Sapajus nigritus in Carlos Botelhos State Park, São Paulo (Brazil), during two periods, 2007-2008 and 2009-2010. We also used a more conventional methodology to compare results. Although the results obtained using both methodologies were similar, in some cases, the new one performed better. Diet was analyzed byusing the categories patchy and dispersed food items. This dichotomous classification has been criticized because of the broadness of its categories, but in the present study it was sensitive to changes in Sapajus spatial patterns. Results were inconclusive when analyzing data from large discontinuous periods, but some conclusions were obtained when considering data from short continuous periods: daily path length decreased and the use of space was more uniform with the increase of dispersed items on the diet. The largest ranging areas were observed when the diet was mixed. Spatial patterns of these primates can be explained in terms of energy obtained and travel costs

Made available in DSpace on 2017-05-12T14:46:51Z (GMT). No. of bitstreams: 1 Everton.pdf: 4714138 bytes, checksum: a59b9d4eb09d8201b1cddd3c78f52e24 (MD5) Previous issue date: 2012-12-01 / This paper aimed to present methods to be applied in the area of spatial statistics on soybean yield and agrometeorological factors in Western Paraná state. The data used, related to crop years from 2000/2001 to 2007/2008, are the following variables: soybean yield (t ha-1) and agrometeorological factors, such as rainfall (mm), average temperature (oC) and solar global radiation average (W m-2). In the first phase,it was used indices of spatial autocorrelation (Moran Global and Local) and presented multiple spatial regression models, with performance evaluations. The estimation of parameters occurred when using the Maximum Likelihood method and the performance evaluation of the models was based on the coefficient of determination (R2), the maximum value of the function of the logarithm of the maximum value of the likelihood function logarithm and the Bayesian information criterion of Schwarz. In a second step, cluster analysis was performed using spatial statistical multivariate associations, seeking to identify the same set of variables, but with a larger number of crop years. Finally, the data from one crop year were utilized in an approach based on fuzzy clustering, through the Fuzzy C-Means algorithm and the similarity measure by defining an index for this purpose. The first phase of the study showed the correlation between spatial autocorrelation and soybean yield and agrometeorological elements, through the analysis of spatial area, using techniques such as index Global Moran's I and Local univariate and bivariate and significance tests. It was possible to demonstrate, through the performance indicators used, that the SAR and CAR models offered better results than the classical multiple regression model. In the second phase, it was possible to present the formation of groups of cities using the similarities of the variables under analysis. Cluster analysis is a useful tool for better management of production activities in agriculture, since, with the grouping, it was possible to establish similarities parameters that provide better management of production processes that bring quantitative and qualitatively better, results sought by the farmer. In the final step, through the use of Fuzzy C-Means algorithm, it was possible to form groups of cities of similar soybean yield using the method of decision by the Higher Degree of Relevance (MDMGP) and Method of Decision Threshold by β (β CDM). Subsequently, identification of the adequate number of clusters was obtained using modified partition entropy. To measure the degree of similarity of each cluster, a Cluster Similarity Index (ISCl) was designed and used, which considers the degree of relevance of each city within the group to which it belongs. Within the perspective of this study, the method used was adequate, allowing to identify clusters of cities with degrees of similarities in the order of 60 to 78%. / Este trabalho apresenta métodos para serem aplicados na estatística espacial de área na produtividade da soja e fatores agrometeorológicos na região oeste do estado do Paraná. Os dados utilizados estão relacionados aos anos-safra de 2000/2001 a 2007/2008, sendo as variáveis: produtividade da soja (t ha-1) e agrometeorológicas, tais como precipitação pluvial (mm), temperatura média (oC) e radiação solar global média (W m-2). Em uma primeira fase foram utilizados índices de autocorrelação espacial (Moran Global e Local) e apresentados modelos de regressão espacial múltipla, com avaliações de desempenho. A estimativa dos parâmetros dos modelos ajustados se deu pelo uso do método de Máxima Verossimilhança e a avaliação do desempenho dos modelos foi realizada com base no coeficiente de determinação (R2), no máximo valor do logaritmo da função do máximo valor do logaritmo da função verossimilhança e no critério de informação bayesiano de Schwarz. Em uma segunda etapa foram realizadas análises de agrupamento espacial por meio da estatística multivariada, buscando identificar associações no mesmo conjunto de variáveis, porém com um número maior de anos-safra. Finalmente, os dados de um ano-safra foram aplicados em uma abordagem baseada em agrupamento difuso, por meio do algoritmo Fuzzy c-Means, tendo a similaridade medida pela definição de um índice com este objetivo. O estudo da primeira fase permitiu verificar a correlação e a autocorrelação espacial entre a produtividade da soja e os elementos agrometeorológicos, por meio da análise espacial de área, usando técnicas como o índice I de Moran Global e Local uni e bivariado e os testes de significância. Foi possível demonstrar que, por meio dos indicadores de desempenho utilizados, os modelos SAR e CAR ofereceram melhores resultados em relação ao modelo de regressão múltipla clássica. Na segunda fase, foi possível apresentar a formação de grupos de municípios utilizando as similaridades das variáveis em análise. A análise de agrupamento foi um instrumento útil para uma melhor gestão das atividades de produção da agricultura, em função de que, com o agrupamento, foi possível se estabelecer similaridades que proporcionem parâmetros para uma melhor gestão dos processos de produção que traga, quantitativa e qualitativamente, resultados almejados pelo agricultor. Na etapa final, por meio do algoritmo Fuzzy c-Means, foi possível a formação de grupos de municípios similares à produtividade de soja, utilizando o Método de Decisão pelo Maior Grau de Pertinência (MDMGP) e o Método de Decisão pelo Limiar β (MDL β). Posteriormente, a identificação do número adequado de agrupamentos foi obtida utilizando a Entropia de Partição Modificada. Para mensurar o nível de similaridade de cada agrupamento, foi criado e utilizado um Índice de Similaridade de Clusters (ISCl), que considera o grau de pertinência de cada município dentro do agrupamento a que pertence. Dentro das perspectivas deste estudo, o método empregado se mostrou adequado, permitindo identificar agrupamentos de municípios com graus de similaridades da ordem de 60 a 78%. espacial

My dissertation focuses on (i) the development of new analysis tools and methodologies for analyzing X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) data, and (ii) the comprehensive characterization of materials (nanodiamonds) using a multi-instrument approach. Chapter 1 contains (i) a discussion of the two techniques I focused on most in my work: XPS and ToF-SIMS, (ii) a discussion of the common chemometrics techniques used to analyze data from these methods, and (iii) the advantages/rationale behind the multi-instrument characterization of materials. Chapter 2 describes various good practices for obtaining reasonable peak fits in XPS, which can also be applied to peak fitting data from different techniques. To address the issue of user subjectivity/bias in XPS peak fitting, I introduce two less biased mathematical functions for characterizing XPS narrow scans, namely the equivalent width (EW) and the autocorrelation width (AW). These functions are discussed in Chapters 3 and 4. In Chapter 5, I then introduce uniqueness plots as simple and straightforward graphical tools for assessing the quality of XPS peak fits and for determining whether fit parameters are correlated. This tool is extensively used in spectroscopic ellipsometry, and the mathematics behind it is known in XPS. However, to the best of my knowledge, this graphical tool has never been applied to XPS. ToF-SIMS data analysis is somewhat challenging due to the enormous amounts of data that are collected, and also the matrix effect in SIMS. This amount of information is significantly increased when depth profiles are performed on samples. Chapter 6 discusses a new chemometrics tool that I introduce for analysis of complex data sets, with emphasis on XPS and ToF-SIMS depth profiling data. The new approach is called the Information Content (IC) or entropy, which is adapted from Claude Shannon's work on Information Theory. Chapter 7 then contains a presentation of the comprehensive characterization of five nanodiamond samples used to manufacture particles for liquid chromatography. The advantages of a multi-instrument approach for material characterization and the lack of comprehensive material characterization in the literature are emphasized. To the best of my knowledge this is the most comprehensive characterization of nanodiamonds that has been reported in the literature. Chapter 8 presents conclusions of my work and future work. This thesis also contains six appendices. Appendix 1 contains an article from a scientific magazine that I wrote to highlight the importance and applications of the EW and AW to characterize XPS narrow scans. Appendices 2-5 are application notes I wrote on separations I performed on a nanodiamond based HPLC column. Finally, Appendix 6 describes the ToF-SIMS analysis of the tungsten species in the nanodiamond samples characterized in Chapter 7.

A dusty plasma is a mixture of electrons, ions, neutral gas atoms, and small particles of solid matter (dust). In a dusty plasma produced in the laboratory, dust particles gain a large electric charge from the other charged species, so that their interparticle interactions can be very strong. Frequently, the average interparticle potential energy is higher than the thermal kinetic energy of the dust particles, and in this case, they constitute a strongly coupled plasma. As with all strongly coupled plasmas, the dust particles can behave like typical solids or liquids. In this thesis, I report the results of dusty plasma experiments that are focused on the behavior of liquids. I use a so-called two-dimensional (2D) dusty plasma that consists of only a single horizontal layer of dust particles. Tracking each particle with video microscopy and image analysis methods allows the calculation of important liquid properties, like the viscosity coefficient. In Chapter 2, I describe an improved laser heating method for producing liquid-like conditions in a 2D dusty plasma. Two laser beams are scanned across the dust layer in a new pattern to increase the kinetic energy of the particles and melt the ground state crystalline lattice. The new scanning pattern improves the randomness of the resulting particle motion so that it more closely resembles that of a liquid in a thermal equilibrium. In Chapter 3, I report a viscosity measurement in a dusty plasma that is unaffected by the complicating effects of temperature nonuniformities and shear thinning. This measurement is enabled by an addition to my experimental apparatus that I also detail here. I find the viscosity to be significantly higher than in previous measurements, which I attribute to the avoidance of shear thinning. In Chapter 4, I present measurements of viscosity using the Green-Kubo method, and compare the results to those of my previous measurement. I find that the two methods yield viscosity values that differ by about 60%, over the entire temperature range attained in the experiment. Possible sources of this difference are evaluated. Finally, in Chapter 5, I report the first experimental confirmation of a theoretical expression describing the decay of time autocorrelation functions. This theoretical expression fits experimentally calculated autocorrelation functions within error bars, especially at short times when a simple exponential decay fails. I also propose an intuitive description wherein an observed transition in the autocorrelation function is due to the onset of collisional scattering.

Several traffic characterization studies have been performed on wireless LANs with the main objective of realizing good and accurate models of the errors in the wireless channel. These models have been extended to model the effect of errors on higher layer protocols, mainly at the data link layer. However, no prior work has been done to study the application level characteristics of MPEG-4 video traffic over 802.11b wireless networks. In this thesis a traffic characterization study of MPEG-4 video traffic over IEEE 802.11b wireless LANs with the main goal of building a tool for software testing is performed. Using two freely available tools to send and receive real-time streams and collect and analyze traces, MPEG-4 encoded video frames are sent over a 11 Mbps, 802.11b wireless LAN to characterize the errors in the channel and the effect of those errors on the quality of the movie. The results of this traffic characterization were modeled using ARTA (Auto Regressive-To-Anything) software. These modeled characteristics were then used to build a tool that generates synthetic traffic emulating real wireless network scenario. The tool emulates the error length and error free length characteristics of the wireless network for the MPEG-4 video traffic using the corresponding modeled characteristics generated by ARTA. The tool can be used by software developers to test their MPEG-4 streaming media applications without the need of the real infrastructure. The tool can also be trained and extended to support testing of any streaming media applications.

Etude, dans un cadre probabiliste et statistique, de la fonction d'autocorrelation partielle d'un processus scalaire reel, a temps discret, stationnaire au second ordre et centre. Nous nous attachons, dans une premiere partie, a decrire de facon tres complete les differents aspects de cette fonction dans l'investigation, sur le plan probabiliste, de la structure du processus. Notre presentation est faite essentiellement dans le domaine temporel. Cependant le choix d'un langage geometrique, dans l'espace de hilbert engendre par les composantes du processus, facilite le lien avec le domaine spectral. Nous soulignons le role privilegie autoregressif. Nous considerons aussi le cas des processus vectoriels pour lesquels nous proposons la notion de fonction d'autocorrelation partielle canonique. La 2eme partie est consacree aux apports de la fonction d'autocorrelation partielle dans l'estimation de la structure temporelle du processus. La necessite de recourir a d'autres techniques que celle, usuelle, utilisant les autocorrelations empiriques se rencontre lorsque la serie observee est courte, meme en presence d'un echantillon, ou encore lorsqu'elle provient d'un modele proche de la singularite. Nous insistons sur la methode du maximum de vraisemblance, pour laquelle nous precisons les conditions d'utilisation (existence, unicite...) et nous proposons, dans le cas d'un echantillon de series courtes, une methode de relaxation pour sa mise en oeuvre. Nous analysons et comparons les differentes methodes d'estimation autoregressive dans le domaine temporel et constatons les bonnes performances de celle basee sur la version empirique des autocorrelaitons partielles que nous proposons.

<p>Since Dengue fever (DF) and its related forms, Dengue Hemorrhagic fever (DHF) and Dengue Shock Syndrome (DSS) have become important health concerns worldwide, it is also imperative to develop methods which will help in the analysis of the incidences. Dengue fever cases are growing in number as it also invades widely, affecting larger number of countries and crossing climatic boundaries. Considering that the disease as of now has neither an effective vaccine nor a cure, monitoring in order to prevent or control is the resorted alternative. GIS and its related technologies offer a wealth of interesting capabilities towards achieving this goal.</p><p><strong> </strong></p><p>The intention of this study was to develop methods to describe dengue fever outbreaks taking Rio de Janeiro, Brazil as a case study. Careful study of Census data with appropriate attributes was made to find out their potential influence on dengue fever incidence in the various regions or census districts. Dengue incidence data from year 2000 to year 2008 reported by the municipal secretariat of Rio was used to extract the necessary census districts. Base map files in MapInfo format were converted to shape files.  Using ArcGIS it was possible to merge the dengue fever incidence data with the available base map file of the City of Rio according to corresponding census districts. Choropleth maps were then created using different attributes from which patterns and trends could be used to describe the characteristic of the outbreak with respect to the socio-economic conditions. Incidence data were also plotted in Excel to see temporal variations. Cluster analysis were performed with the Moran I technique on critical periods and years of dengue outbreak. Using the square root of dengue incidence from January to April 2002 and 2008, inverse distance was selected as the conceptualised spatial relationship, Euclidean distance as the distance method. More detailed analyses were then done on the selected critical years of dengue outbreak, (years 2002 and 2008), to investigate the influence of socio-economic variables on dengue incidence per census district.</p><p> </p><p>Dengue incidence rate appeared to be higher during the rainy and warmer months between December and May. Outbreaks of dengue occurred in years 2002 and 2008 over the study period of year 2000 to 2008. Some factors included in the census data were influential in the dengue prevalence according to districts. Satisfactory results can be achieved by using this strategy as a quick method for assessing potential dengue attack, spread and possible enabling conditions. The method has the advantage where there is limited access to field work, less financial means for acquisition of data and other vital resources.</p><p>A number of difficulties were encountered during the study however and leaves areas where further work can be done for improvements. More variables would be required in order to make a complete and comprehensive description of influential conditions and factors.  There is still a gap in the analytical tools required for multi-dimensional investigations as the ones encountered in this study.  It is vital to integrate ‘GPS’ and ‘Remote Sensing’ in order to obtain a variety of up-to-date data with higher resolution.</p><p> </p>

Eine klassische Art, die Dynamik nichtlinearer Systeme zu beschreiben, besteht in der Analyse ihrer Fourierspektren. Für periodische und quasiperiodische Prozesse besteht das Fourierspektrum nur aus diskreten Deltafunktionen. Das Spektrum einer chaotischen Bewegung ist hingegen durch das Vorhandensein einer stetigen Komponente gekennzeichnet. In der Arbeit geht es um einen eigenartigen, weder regulären noch vollständig chaotischen Zustand mit sogenanntem singulärstetigen Leistungsspektrum. <br /> Unsere Analyse ergab verschiedene Fälle aus weit auseinanderliegenden Gebieten, in denen singulär stetige (fraktale) Spektren auftreten. Die Beispiele betreffen sowohl physikalische Prozesse, die auf iterierte diskrete Abbildungen oder gar symbolische Sequenzen reduzierbar sind, wie auch Prozesse, deren Beschreibung auf den gewöhnlichen oder partiellen Differentialgleichungen basiert. / One of the classical ways to describe the dynamics of nonlinear systems is to analyze theur Fourier spectra. For periodic and quasiperiodic processes the Fourier spectrum consists purely of discrete delta-functions. On the contrary, the spectrum of a chaotic motion is marked by the presence of the continuous component. In this work, we describe the peculiar, neither regular nor completely chaotic state with so called singular-continuous power spectrum. <br /> Our investigations concern various cases from most different fields, where one meets the singular continuous (fractal) spectra. The examples include both the physical processes which can be reduced to iterated discrete mappings or even symbolic sequences, and the processes whose description is based on the ordinary or partial differential equations.

This study posits that there may be a systematic bias in measuring the transit’s endogenous impact on land values in a built up area due to discrimination by location in the city. Studies of transit value-added effect report mixed results about the capitalization of station proximity. The question is not whether a transit station influences nearby land values, but how and where location determines the impacts. Examining 731 office rentals and land values in Seoul, this study finds that value premium over better accessibility to a station decays with increasing distance from the central business district (CBD) and significantly depends on the development density of the station area. Overall, station benefits seem to exist in Seoul, but they look more notable in centers with higher centrality. This makes a hierarchy of regression coefficients for station proximity by location, i.e. the beta in the CBD is the highest and those in the subcenters are next, while that in other areas is the lowest. Study findings imply that the potential of more compact and denser developments within station areas seems higher in a dense inner city, providing evidence for the concept of ‘compact city.’ Questions concerning model specification in the hedonic approach are raised: in research sampled heavily from the suburbs, the coefficient may be underestimated where this benefit actually exists. Also, due to the incongruence of station area with station value-added area, using a dummy variable seems intrinsically risky. This study shows that estimation with spatial models outperforms OLS estimation in the presence of spatial autocorrelation. Also, there is a strong spatial autocorrelation even in the SAR residuals where the omission of key variables still influences the estimation. Overall, spatial lag and error term variables greatly improve the fitness of regression equations; however, the latter seemed more useful than the former in this study. One thing to note is that the latter seems more sensitive to the choice of weight matrix than the lag variable. There may exist a unique weight scheme proper for the data structure which cannot be known in advance.