Sex estimation in bioarchaeological research is paramount for comparative analyses of skeletal remains and developing estimates of other demographic variables. Frequently, sex is estimated utilizing the morphology of pelvic and cranial bones in archaeological skeletal samples. Regrettably, these bones are often damaged, destroyed, or lost and cannot be employed for the estimation of sex. Fortunately, a variety of metric and visual sex estimation methods have been developed on modern skeletal samples with known demography. Disappointingly, due to the population specific nature of many of these metric methods, they cannot be accurately applied directly to alternate skeletal samples. However, these methods can be redeveloped and retested for archaeological skeletal samples if the proper protocol is utilized. This research utilizes the protocol for developing methods of sex estimation on samples with unknown sex developed by Murail et al. (1999). Utilizing select hand and foot bones from four prehistoric Native American skeletal samples from Alabama and Illinois, multiple discriminant functions were developed and tested on both Archaic and Mississippian Period skeletal samples. Furthermore, the four individual site samples were combined into two geographical and two temporal samples, as well as an all pooled sample in order to test the broader applicability of these methods. The results indicate that sex estimation methods can be developed on samples where sex is not known. Additionally, the discriminant functions developed produce high levels of classification for the sites, individually, as well as for the geographic, temporal, and all pooled samples. The latter suggests these functions have broader applicability for these regions and temporal periods. Moreover, the concordance rates for these functions are similar to the accuracy rates when these bones were applied to samples with known sex.

This project analyzes the sexual dimorphism of the femur and tibia using geometric morphometrics. The study sample includes 250 individuals of known sex and age at death with complete, non-damaged, non-pathological skeletal remains from the William M. Bass Donated Skeletal Collection at the University of Tennessee, Knoxville. Ages range from 19-96 for males (mean=56.92 years) and 29-97 for females (mean=59.48 years). A combination of landmarks and semi-landmarks were collected on the proximal and distal epiphyses of each bone using a Microscribe, which helps capture the overall size and shape variation present in the sample. Only individuals from one population, White, where analyzed in order to eliminate population variation bias. Classification rates for males and females for the proximal femur were 80.8% and 78.4% respectively, for the distal femur 92.6% and 89.6% respectively, for the proximal tibia 80.8% and 83.2% respectively, and the distal tibia 81.6% and 80.8% respectively, all with a p<0.0001. These rates created a classification model for which epiphysis gave the most accurate assessment of sex: the distal femur, followed by the proximal tibia, then the distal tibia, and lastly the proximal femur. This study indicates the knee joint is the most dimorphic, followed by the ankle and then the hip. The results fall in line with another study indicating the knee is more sexually dimorphic in a modern White population (Spradley and Jantz 2011), though in contrast to their results this study found the distal femur was more dimorphic than the proximal tibia. This method indicates that in comparison to standard measurements, geometric morphometrics may provide a more reliable method for sex estimation when used, specifically on the knee. Certain landmarks were then selected based on the standard taphonomic process of coffin wear and postmortem damage (Pokines and Baker 2014) for exclusion to determine the usability of the method on fragmented or damaged skeletal remains. When combinations of landmarks were removed, the distal femur still possessed the highest classification rates with over 80% accuracy.

This thesis covers misclassification probabilities via an Edgeworth-type expansion of the maximum likelihood based discriminant function. When deriving misclassification errors, first the expectation and variance in the population are assumed to be known where the variance is the same across populations and thereafter we consider the case where those parameters are unknown. Cumulants of the discriminant function for discriminating between two multivariate normal populations are derived. Approximate probabilities of the misclassification errors are established via an Edgeworth-type expansion using a standard normal distribution.

The distinct ecological requirements of Microtus xanthognathus (yellow-cheeked vole or taiga vole) and M. pennsylvanicus (meadow vole) warrant accurate discrimination of their remains in studies of paleoecology and past biogeographical shifts. An occlusal length of the lower 1st molars (ml) that is >3.2 mm for M. xanthognathus is the method most frequently used to separate these 2 taxa in archaeological and paleontological samples. However, these measurements alone are unreliable because some specimens of M. pennsylvanicus overlap smaller individuals of M. xanthognathus in size. Therefore, I created and tested a morphometric technique that discriminates Recent lower 1st molars (mis) of M. pennsylvanicus from those of M. xanthognathus, and is applicable to other taxa (both modern and fossil). Despite overlapping occlusal length, my discriminant function based on landmark data correctly classified 100% (n = 53) of Recent m1s from the 2 taxa and 97.7% (43 of 44) of (assumed) m1s of M. pennsylvanicus from an archaeological site from about AD 1200 in central Nebraska. This landmark scheme is applicable to fossil and modern Microtus worldwide. © 2006 American Society of Mammalogists.

The sexing of human skeletal remains is important for identification and demographic purposes. It is made more difficult when elements such as the skull and pelvis are not recovered or are in too poor of a condition to assess. Previous studies have used carpal (wrist) bones of contemporary populations to assess the viability of these skeletal elements exhibiting sexual dimorphism, as these bones are small, compact elements that are usually recovered in good condition. This study evaluates the use of carpal bones recovered from an ancient Maya population from Belize to determine the biological sex of individuals. The study sample is part of the Maya Archaeological Skeletal Collection (MASC), which contains individuals from the sites of Lamanai, San Pedro, Altun Ha, and Marco Gonzalez and dates from the Late Maya Pre-Classic (400 BC-AD 250) to the Spanish Colonial period (AD 1521-1821). Multiple measurements were taken on 36 capitate, 34 lunate, 34 scaphoid, 27 trapezium, 24 hamate, 22 triquetral, 22 trapezoid, and 16 pisiform bones from several individuals. Discriminant function analysis was used to determine if sexual dimorphism is measurable in this population using these elements. Previous studies used populations with known identities, assessing individuals from crypts, graveyards, or medical collections from the last few centuries. This study varies from previous studies as it utilizes archaeological remains, making this study one of the first to evaluate non-contemporary remains with unknown sex. Results of this study demonstrate that this population exhibits sexual dimorphism and discriminant function analysis can be used to distinguish between two groups. This demonstrates that carpals could be used to help determine biological sex of archaeological populations as well as a tool to help with identification in forensic cases.

Understanding cage aquaculture adoption decisions and factors affecting adoption is necessary to ensure that fish production from cage aquaculture in Ghana is both significant and sustainable. The goal of this study was to provide a framework for understanding cage aquaculture adoption decisions and to identify factors affecting adoption, to inform decision makers as they formulate policies aimed at promoting cage aquaculture adoption in Ghana. I surveyed 122 respondents comprising current cage fish farmers, farmers who have abandoned cage aquaculture, and potential adopters of cage aquaculture such as, fish traders, fishermen and land-based fish farmers. Respondents answered questions related to knowledge, interest, constraints in cage aquaculture, and demographics. I used non-metric multidimensional scaling and discriminant function analysis to identify unique groups within the respondents, classify respondents according to their position in the innovation-decision continuum, and identify factors affecting cage aquaculture adoption. Based on their differences in knowledge and interests, I placed respondents into one of three stages of the cage aquaculture innovation-decision process model I developed: (1) Unawareness, (2) Knowledge, Persuasion, and Decision (KPD), and (3) Implementation (Confirmation and Abandonment). Respondents in the KPD and Implementation stages had knowledge, were more interested in cage aquaculture, and were aware of constraints in cage aquaculture, whereas respondents in the Unawareness stage lacked knowledge and interest in cage aquaculture, and did not clearly understand the constraints. Respondents who were males, belonged to the tribes Ewe and Akan, and who had fishing experience tended to be more interested in cage aquaculture. The lack of capital, high input costs, inability to adequately market fish, theft, lack of information sources, conflict over water use, and cage destruction by storms, were identified as the main constraints to cage aquaculture adoption in Ghana. The results of the study suggest that programs aimed at encouraging new entrants into cage aquaculture should focus on demographic characteristics such as gender, and tribe. However, demographic characteristics may affect adoption decisions and it may be important to consider them as such. Some recommendation to address the major constraints in cage aquaculture include: the Fisheries Directorate should (1) develop an efficient extension program that farmers can access regularly, especially, for farmers with no other information sources, (2) provide feed subsidy to enable farmers produce fish at competitive prices, (3) facilitate the formation of fish farmers' cooperative groups that would purchase large quantities of feed, (4) encourage local production of high quality fish feed, and (5) develop credit facilities that can be accessed by individuals interested in cage aquaculture to assist potential farmers who would, otherwise, not be able to adopt cage aquaculture . In addition, fish farmers should (6) be proactive in marketing their fish by identifying potential niche markets prior to production, and (7) join cooperative groups to ease the burden of accessing loans to increase production. / Master of Science

Orientador: Carlos Roberto Padovani / Banca: Adriano Wagner Ballarin / Banca: Flávio Fekkari Aragon / Banca: José Carlos Martinez / Banca: Marie Oshiiwa / Resumo: Aspectos teóricos relacionados à Análise Discriminante Multivariada - Linear e Quadrática - foram discutidos, por meio de um extenso levantamento histórico da função discriminante, com seus primórdios no trabalho de Fisher e sua posterior evolução, enfocando o intenso desenvolvimento das técnicas classificatórias discriminantes com o advento dos computadores. Foi dada ênfase aos softwares estatísticos desenvolvidos para PC, que realizam a análise discriminante, e que representam uma grande contribuição para pesquisadores e usuários desta técnica. Considerando a dificuldade existente quanto a aplicativos computacionais acessíveis a pesquisadores da área de ciências agrárias, elaborou-se um programa que realiza a análise discriminante quadrática com as respectivas freqüências de classificação correta, bem como o manual explicativo do usuário. Verificou-se que a função discriminante quadrática trata de um procedimento bastante útil nas ciências agrárias, como, por exemplo, em estudos nas áreas de solos, cultivos diversos (soja, milho, cana de açúcar, pupunha, braquiária, frutas), criação de animais e classificação e seleção de madeiras; porém, subutilizada frente à dificuldade de programas computacionais de fácil manuseio e acesso a pesquisadores das áreas aplicadas. Os procedimentos estudados e discutidos foram ilustrados com exemplos de aplicação, utilizando dados experimentais agronômicos de espécies de Girassóis e Eucalyptus, submetidos ao aplicativo desenvolvido. / Abstract: A large historical study of the discriminant function has allowed a discussion on theoretical aspects related to the Multivaried Discriminant Analysis - Linear and Quadratic, showing its past in the work of Fisher and its later evolution, emphasizing the wide development of classificatory discriminant techniques with the happening of the computers, and specific statistic softwares which practice the discriminant analysis, representing a big contribution to researches and users of this technique. Considering the difficulty in relation to accessible softwares to researches of the agrarian area, a software which performs a linear and quadratic discriminant analysis was built with its frequencies of correct classification, as well as an explicative manual to users. The quadratic discriminant was studied as being a very useful process in agrarian sciences. Some examples of this usefulness is in studies of the ground, diversified cultivation (soybean, corn, sugarcane, pejibaye, brachiaria decumbens fruits), animal creation and wood selection, and classification; however, misused in relation to the difficulties of easy handing and access to researchers of applied areas. The studied and discussed procedures were illustrated with applications, using agronomic experimental data of Sunflower and Eucalyptus, submitted to developed software. / Doutor

Nacionalinių mokinių pasiekimų tyrimo metodologija yra nuolat plėtojama. Pasitarus su Švietimo plėtotės centro tyrimo skyriaus darbuotojais, buvo nuspręsta įsigilinti į klasterinės ir diskriminantinės analizės metodus, jų pritaikomumą nacionalinių tyrimų rezultatų analizei. Tai įtakojo šio darbo pasirinkimą ir tikslą - susipažinti su Klasterinės ir Diskriminantinės analizės metodais, pateikti ir aptarti jų taikymo pavyzdžius. Darbe išnagrinėti du daugiamačiai statistiniai metodai: klasterinė ir diskriminantinė analizė. Yra aptarti šių metodų teoriniai aspektai bei pateikti originalūs šių metodų pritaikymo mokinių pasiekimų tyrimams pavyzdžiai. Padarytos išvados apie šių metodų pritaikomumą nacionalinių mokinių pasiekimų tyrimo analizei atlikti. / National research of student marches are continually evolving. With Educational evolve center’s help I decided to analyse Cluster and Disckriminant analysis methods and how they can be used in National research analysis. This was a reason of my work purpose - to have a look at Cluster and Disckriminant analysis methods, to offer examples of practical use. There are two statistical multidimensional methods discussed in this work (Cluster and Disckriminant analysis). There are discussed theoretical side of these methods, also you can find original examples of practical use. In conclusion I discuss about practical use of these methods in national research of student marches.

Remote sensing techniques are vital for early detection of several problems such as natural disasters, ecological problems and collecting information necessary for finding optimum solutions to those problems. Remotely sensed information has also important uses in predicting the future risks, urban planning, communication.Recent developments in remote sensing instrumentation offered a challenge to the mathematical and statistical methods to process the acquired information. Classification of satellite images in the context of land cover classification is the main concern of this study. Land cover classification can be performed by statistical learning methods like additive models, decision trees, neural networks, k-means methods which are already popular in unsupervised classification and clustering of image scene inverse problems. Due to the degradation and corruption of satellite images, the classification performance is limited both by the accuracy of clustering and by the extent of the classification. In this study, we are concerned with understanding the performance of the available unsupervised methods with k-means, supervised methods with Gaussian maximum likelihood which are very popular methods in land cover classification. A broader approach to the classification problem based on finding the optimal discriminants from a larger range of functions is considered also in this work. A novel method based on threshold decomposition and Boolean discriminant functions is developed as an implementable application of this approach. All methods are applied to BILSAT and Landsat satellite images using MATLAB software.

Made available in DSpace on 2014-06-11T19:31:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2007-07-27Bitstream added on 2014-06-13T21:02:58Z : No. of bitstreams: 1 padovani_crp_dr_botfca.pdf: 793418 bytes, checksum: 8b62c9d520c0086c46554fb418856bb7 (MD5) / Nas Ciências Agronômicas, encontram-se várias situações em que são observadas diversas variáveis respostas nas parcelas ou unidades experimentais. Nestas situações, um caso de interesse prático à experimentação agronômica é o que considera a construção de regiões de similaridade entre as parcelas para a discriminação entre os grupos experimentais e ou para a classificação de novas unidades experimentais em uma dessas regiões. Os métodos de classificação ou discriminação exigem, para sua utilização prática, uma quantidade considerável de retenção de informação da estrutura de variabilidade dos dados e, principalmente, alta fidedignidade e competência nas alocações de novos indivíduos nos grupos, mostradas nas distribuições corretas destes indivíduos. Existem vários procedimentos para medir o grau de decisão correta (acurácia) das informações fornecidas pelos métodos classificatórios. Praticamente, a totalidade deles utilizam a probabilidade de classificação errônea como o indicador de qualidade, sendo alguns destes freqüentistas (probabilidade estimada pela freqüência relativa de ocorrências - métodos não paramétricos) e outros baseados nas funções densidade de probabilidade das populações (métodos paramétricos). A principal diferença entre esses procedimentos é a conceituação dada ao cálculo da probabilidade de classificação errônea. Pretende-se, no presente estudo, apresentar alguns procedimentos para estimar estas probabilidades, desenvolver um software para a obtenção das estimativas considerando a distância generalizada de Mahalanobis como o procedimento relativo à da função densidade de probabilidade para populações com distribuição multinormal . Este software será de acesso livre e de fácil manuseio para pesquisadores de áreas aplicadas, completado com o manual do usuário e com um exemplo de aplicação envolvendo divergência genética de girassol. / In the Agronomical Sciences, mainly in studies involving biomass production and rational use of energy, there are several situations in which several variable answers in the parts or experimental units are observed. In these situations, a case of practical interest to the agronomical experimentation is that one which considers the construction of similarity regions among parts and or the classification of new experimental units. The classification methods demand, for their utilization, a considerable quantity for utilization of their information retention of data and, mostly, high fidelity and competence in the new individual allocations. There are several procedures to measure accuracy degree of the information supplied by the discrimination method. Practically all of them use the miss-classification probability (erroneous classification) like the quality indicator. The main difference among these evaluation methods is the characterization of the miss-classification probability. Therefore, the aim is to present some estimate procedures of the missclassification probabilities involving repetition frequency and distribution methods and to develop a software to obtain their estimate, which is accessible and easy handling for researchers of applied areas, complementing the study with user's manual and examples in the rational energy application and biomass energy.