Yes / Sex assessment is key when investigating human remains either from medicolegal contexts or archaeological sites. Sex is usually assessed by examination of the skull and pelvis, but this may not always be possible if skeletal material is fragmented or incomplete. The present study investigated the potential for using carpals to assess sex, utilizing one hundred individuals of known-sex from the Christ Church, Spitalfields Collection, curated at the Natural History Museum (London). A series of newly-defined measurements are applied to all eight carpals. Inter- and intra- observer error tests show that all measurements are satisfactorily reproduced by the first author and another observer. Paired t-tests to investigate side asymmetry of the carpals reveal that some, but not all, measurements are consistently larger on the right hand side than the left. Independent t-tests confirm that all carpals are sexually dimorphic. Univariate measurements produce accuracy levels that range from 64.6 to 84.7%. Stepwise discriminant function analysis, devised separately for left and right sides, provides reliable methods for assessing sex from single and multiple carpals, with an accuracy range of 71.7 to 88.6%. All functions derived are tested for accuracy on a sample of twenty additional individuals from the Christ Church, Spitalfields Collection.

Classification is a very common task in information processing and important problem in many sectors of science and industry. In the case of data measured as a function of a dependent variable such as time, the most used algorithms may not pattern each of the individual shapes properly, because they are interested only in the choiced measurements. For the reason, the presented paper focuses on the specific techniques that directly address the curve clustering problem and classifying new individuals. The main goal of this work is to develop alternative methodologies through the extension to various statistical approaches, consolidate already established algorithms, expose their modified forms fitted to demands of clustering issue and compare some efficient curve clustering methods thanks to reported extensive simulated data experiments. Last but not least is made, for the sake of executed experiments, comprehensive confrontation of effectual utility. Proposed clustering algorithms are based on two principles. Firstly, it is presumed that the set of trajectories may be probabilistic modelled as sequences of points generated from a finite mixture model consisting of regression components and hence the density-based clustering methods using the Maximum Likehood Estimation are investigated to recognize the most homogenous partitioning. Attention is paid to both the Maximum Likehood Approach, which assumes the cluster memberships to be some of the model parameters, and the probabilistic model with the iterative Expectation-Maximization algorithm, that assumes them to be random variables. To deal with the hidden data problem both Gaussian and less conventional gamma mixtures are comprehended with arranging for use in two dimensions. To cope with data with high variability within each subpopulation it is introduced two-level random effects regression mixture with the ability to let an individual vary from the template for its group. Secondly, it is taken advantage of well known K-Means algorithm applied to the estimated regression coefficients, though. The task of the optimal data fitting is devoted, because K-Means is not invariant to linear transformations. In order to overcome this problem it is suggested integrating clustering issue with the Markov Chain Monte Carlo approaches. What is more, this paper is concerned in functional discriminant analysis including linear and quadratic scores and their modified probabilistic forms by using random mixtures. Alike in K-Means it is shown how to apply Fisher's method of canonical scores to the regression coefficients. Experiments of simulated datasets are made that demonstrate the performance of all mentioned methods and enable to choose those with the most result and time efficiency. Considerable boon is the facture of new advisable application advances. Implementation is processed in Mathematica 4.0. Finally, the possibilities offered by the development of curve clustering algorithms in vast research areas of modern science are examined, like neurology, genome studies, speech and image recognition systems, and future investigation with incorporation with ubiquitous computing is not forbidden. Utility in economy is illustrated with executed application in claims analysis of some life insurance products. The goals of the thesis have been achieved.

This thesis develops a strategy for polymerized volume data set construction. Given a volume data set defined over a regular three-dimensional grid, a polymerized volume data set (PVDS) can be defined as follows: edges between adjacent vertices of the grid are labeled 1 (active) or 0 (inactive) to indicate the likelihood that an edge is contained in (or spans the boundary of) a common underlying object, adding information not in the original volume data set. This edge labeling “polymerizes” adjacent voxels (those sharing a common active edge) into connected components, facilitating segmentation of embedded objects in the volume data set. Polymerization of the volume data set also aids real-time data compression, geometric modeling of the embedded objects, and their visualization. To construct a polymerized volume data set, an adjacency class within the grid system is selected. Edges belonging to this adjacency class are labeled as interior, exterior, or boundary edges using discriminant functions whose functional forms are derived for three local adjacency classes. The discriminant function parameter values are determined by supervised learning. Training sets are derived from an initial segmentation on a homogeneous sample of the volume data set, using an existing segmentation method. The strategy of constructing polymerized volume data sets is initially tested on synthetic data sets which resemble neuronal volume data obtained by three-dimensional microscopy. The strategy is then illustrated on volume data sets of mouse brain microstructure at a neuronal level of detail. Visualization and validation of the resulting PVDS is shown in both cases. Finally the procedures of polymerized volume data set construction are generalized to apply to any Bravais lattice over the regular 3D orthogonal grid. Further development of this latter topic is left to future work.

Determination sex is one of the most important tasks in the identification of skeletal remains. Previous studies have shown that population differences in size and shape of femora can affect correct sex allocation. This thesis tested the discriminat functions generated from different populations and confirmed population specificity of the femur discriminant functions. Two samples of the identified adult femora for this project was used. First sample originates from the Czech population living in the 1st 20th century (78 males and 81 females) and second sample originates from the Czech population living in the 2nd 20th century (67 males and 35 females). Both samples also help us estimate the influence of secular trend of the femur'variables to the correct sex classification by discriminat functions calculated in the Czech population. The results showed the existence of the secular trend in femora size dimensions. Only the dimensions of the femoral head (vertical head diameter-F18, transverse head diameter-F19 and maximum diameter of the femoral head-MPH) and sagittal subtrochanteric diameter (F10) not chandged significantly during the 20th century. The secular trend has negatively influenced the correct sex classification, always for one subpopulation. Only the dimensions in which the secular trend...

Differences in height among human populations or changes in height over time may be associated with different degrees of sexual dimorphism in this feature. This thesis compared the height and sexual size dimorphism (SSD) between two groups of the population of Medieval Bohemia - rural residents and inhabitants of Prague. A sample of 179 adult skeletons from five Prague sites and 175 individuals from four rural sites, dating from the 11th to 14th century, was used. Sex was determined following the principle of primary and secondary sex diagnosis, which enabled the derivation of population-specific discriminant functions using the dimensions of the humerus, femur, tibia and talus. A subsequent analysis of body height did not show statistically significant differences either in height or in SSD between the Prague and the rural part of the population of Medieval Bohemia, despite the major changes which Czech Medieval society went through in the 13th century. Comparing our results with previously published data on the height of the Czech population during the early modern period indicates a statistically significant reduction in the magnitude of sexual size dimorphism in the population of the17th century, particularly associated with a decrease in the height of men. A significantly higher stature of...

Submitted by Jorge Silva (jorgelmsilva@ufrrj.br) on 2017-08-22T18:59:33Z No. of bitstreams: 1 2013 - Andr? Luis Oliveira Villela.pdf: 14328753 bytes, checksum: ce4f856fddd576111ae58d83bad8de61 (MD5) / Made available in DSpace on 2017-08-22T18:59:34Z (GMT). No. of bitstreams: 1 2013 - Andr? Luis Oliveira Villela.pdf: 14328753 bytes, checksum: ce4f856fddd576111ae58d83bad8de61 (MD5) Previous issue date: 2013-08-29 / CAPES / PETROBRAS / The Brazilian territory region covered by the Amazon rainforest, due to its continental dimensions and difficulty of access and various interests in extractive activities, has great demand for information to provide support for the occupation, exploitation, and systematic recuperation thus keeping environmental safeguards. The regional soil information available is scarce and in scales inconsistent with the current demands, and the investments in new areas of research in the region is still insufficient. With technological developments, especially in the area of informatics that enables the storage and analysis of large banks of pedological data, the soil mapping techniques improved considerably. Pedometric techniques have been used to store and to explore large databases, thus enabling the improvement of existing soil databases and allowing manufacture of new products in larger scale and mapped areas, with low investment required. The hypothesis of this study is that the technique of reference area may allow the systematic digital mapping of soils from the Solim?es Formation, in the Amazon State. The general objective was to develop and compare methods for mapping soils in the Oil Province Uruc? (AM), using relief covariates. A conventional pedological survey of an area of 8.000 hectares, at the detail level, was executed to be used as a reference area (RA), in the augmentation of the map using digital soil mapping (MDS) techniques for an area of 73.000 hectares after downscaling and grouping of the legend. The numerical modeling of the terrain (MDT) was used (11 covariates derived from MDT) for further application of this soil formation factor as a predictor of the map units, in discriminant functions (DF), and in an expert system based on a tree model classification (AC). Four MDS models were developed, where two were trained using the studied region conceptual model of the pedologist, and the other two were trained with models based on a statistical analysis of the reference area information. The techniques were effective for predicting the mapping units (MU) in the study region, with overall accuracy (EG) ranging from 74.62 % to 88.81 %, and the kappa index was between 0.68 and 0.85. The MDS based in the expert system and AC showed significantly better results in terms of the kappa index, general EG, and the EG for 3 of the 4 mapping units in the area. Although the FD had not the highest accuracy levels, they showed a great potential for use in MDS, especially for preliminary mapping for the pedological survey of new regions, using knowledge of AR neighboring areas. The limitations were observed in the use of FD for mapping unities with small territorial expression, and it is recommended to increase the number of training observations in a way inversely proportional to the frequency of observation of these MUs. The major contribution of this work to scientific community was the establishment of bases and techniques of MDS, using AR and the soil relief relationship, for systematic mapping of new soils form Solim?es Formation. / A regi?o do territ?rio brasileiro coberta por floresta tropical amaz?nica, por suas dimens?es continentais e dificuldade de acesso e interesses diversos em atividades extrativistas, apresenta forte demanda por informa??es gerais que possam servir como subs?dio para a ocupa??o, explora??o e recupera??o ordenada e ambientalmente equilibrada. As informa??es pedol?gicas dispon?veis sobre a ?rea s?o escassas e em escalas incompat?veis com as demandas atuais, e os investimentos em novas frentes de pesquisa na regi?o ainda s?o insuficientes. Com a evolu??o tecnol?gica, sobretudo na ?rea da inform?tica que possibilita o armazenamento e an?lises de extensos bancos de dados pedol?gicos, as t?cnicas de mapeamento pedol?gico v?m se aperfei?oando consideravelmente. T?cnicas de pedometria t?m sido utilizadas para armazenar e explorar grandes bancos de dados e t?m possibilitado o aperfei?oamento das bases pedol?gicas existentes e permitido a confec??o de novos produtos em escala e ?reas mapeadas maiores, com menores investimentos exigidos. A hip?tese deste trabalho ? de que a t?cnica de ?rea de refer?ncia permite o mapeamento digital sistem?tico dos solos da regi?o da forma??o Solim?es, e o objetivo geral foi desenvolver e comparar m?todos de mapeamento de solos da Forma??o Solim?es, na Prov?ncia Petrol?fera de Urucu, AM, utilizando covari?veis do relevo. Foi executado um levantamento pedol?gico convencional de uma regi?o com 8.000 ha, em n?vel de detalhe para ser utilizado como ?rea de refer?ncia (AR) para a amplia??o do mapa, com t?cnicas de mapeamento digital de solos (MDS) para uma ?rea de 73.000 ha com redu??o de escala e agrupamento de legenda. Foi ent?o elaborada modelagem num?rica do terreno (MDT) (11 covari?veis derivadas do MDT) para posterior utiliza??o deste fator de forma??o do solo, como preditor das unidades de mapeamento, em fun??es discriminantes (FD) e um sistema especialista baseado em modelo de ?rvores de classifica??o (AC). Foram desenvolvidas 4 cartas MDS, sendo duas treinadas por modelos baseados no modelo conceitual do ped?logo sobre a regi?o em estudo, e duas treinadas por modelos baseados em an?lise estat?stica de informa??es sobre a ?rea de referencia. As t?cnicas mostraram-se eficientes para predi??o de unidades de mapeamento (UM) na regi?o de estudo, com exatid?o global (EG) variando entre 74,62% a 88,81% e ?ndice kappa entre 0,68 e 0,85. O MDS baseado em sistema especialista e AC apresentou resultados sensivelmente melhores em termos de ?ndice kappa, EG geral e EG para 3 das 4 UM da ?rea. Embora as FD n?o tenham apresentado os maiores ?ndices de acur?cia, estas tem grande potencial de uso em MDS, sobretudo para a confec??o de mapas preliminares para o levantamento pedol?gico de novas regi?es, utilizando-se do conhecimento de AR de ?reas vizinhas. Foram observadas limita??es no emprego de FD para o mapeamento de UM?s com pequena express?o territorial, sendo recomend?vel o aumento do n?mero de observa??es de treinamento inversamente proporcional ? frequ?ncia de observa??o destas UM?s. A maior contribui??o deste trabalho para a comunidade cient?fica foi o estabelecimento de bases e t?cnicas de MDS, utilizando AR e rela??o solo-relevo para o mapeamento sistem?tico de novas ?reas da forma??o Solim?es.