895 resultados para discriminant analysis and cluster analysis
Resumo:
In recent years, disaster preparedness through assessment of medical and special needs persons (MSNP) has taken a center place in public eye in effect of frequent natural disasters such as hurricanes, storm surge or tsunami due to climate change and increased human activity on our planet. Statistical methods complex survey design and analysis have equally gained significance as a consequence. However, there exist many challenges still, to infer such assessments over the target population for policy level advocacy and implementation. ^ Objective. This study discusses the use of some of the statistical methods for disaster preparedness and medical needs assessment to facilitate local and state governments for its policy level decision making and logistic support to avoid any loss of life and property in future calamities. ^ Methods. In order to obtain precise and unbiased estimates for Medical Special Needs Persons (MSNP) and disaster preparedness for evacuation in Rio Grande Valley (RGV) of Texas, a stratified and cluster-randomized multi-stage sampling design was implemented. US School of Public Health, Brownsville surveyed 3088 households in three counties namely Cameron, Hidalgo, and Willacy. Multiple statistical methods were implemented and estimates were obtained taking into count probability of selection and clustering effects. Statistical methods for data analysis discussed were Multivariate Linear Regression (MLR), Survey Linear Regression (Svy-Reg), Generalized Estimation Equation (GEE) and Multilevel Mixed Models (MLM) all with and without sampling weights. ^ Results. Estimated population for RGV was 1,146,796. There were 51.5% female, 90% Hispanic, 73% married, 56% unemployed and 37% with their personal transport. 40% people attained education up to elementary school, another 42% reaching high school and only 18% went to college. Median household income is less than $15,000/year. MSNP estimated to be 44,196 (3.98%) [95% CI: 39,029; 51,123]. All statistical models are in concordance with MSNP estimates ranging from 44,000 to 48,000. MSNP estimates for statistical methods are: MLR (47,707; 95% CI: 42,462; 52,999), MLR with weights (45,882; 95% CI: 39,792; 51,972), Bootstrap Regression (47,730; 95% CI: 41,629; 53,785), GEE (47,649; 95% CI: 41,629; 53,670), GEE with weights (45,076; 95% CI: 39,029; 51,123), Svy-Reg (44,196; 95% CI: 40,004; 48,390) and MLM (46,513; 95% CI: 39,869; 53,157). ^ Conclusion. RGV is a flood zone, most susceptible to hurricanes and other natural disasters. People in the region are mostly Hispanic, under-educated with least income levels in the U.S. In case of any disaster people in large are incapacitated with only 37% have their personal transport to take care of MSNP. Local and state government’s intervention in terms of planning, preparation and support for evacuation is necessary in any such disaster to avoid loss of precious human life. ^ Key words: Complex Surveys, statistical methods, multilevel models, cluster randomized, sampling weights, raking, survey regression, generalized estimation equations (GEE), random effects, Intracluster correlation coefficient (ICC).^
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This study explored the relationship of attitudes, needs, and health services utilization patterns of elderly veterans who were identified and categorized by their expectation for and receipt of sick-role legitimation. Three prescription types (new, change, renewal) were defined as the operational variables. A population of 676 ambulatory, chronically ill (average age 60 years) veterans were sent a questionnaire (74% response rate). In addition, retrospective medical and prescription record review was performed for a 45% sample of respondents. The results were analyzed using discriminant function and regression analysis. Fewer than 20% of the veterans responding expected to receive more prescriptions than were presently prescribed, whereas over 80% expected refill authorizations. Distinct attitudinal, need, and utilization patterns were identified. ^
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A population based ecological study was conducted to identify areas with a high number of TB and HIV new diagnoses in Harris County, Texas from 2009 through 2010 by applying Geographic Information Systems to determine whether distinguished spatial patterns exist at the census tract level through the use of exploratory mapping. As of 2010, Texas has the fourth highest occurrence of new diagnoses of HIV/AIDS and TB.[31] The Texas Department of State Health Services (DSHS) has identified HIV infected persons as a high risk population for TB in Harris County.[29] In order to explore this relationship further, GIS was utilized to identify spatial trends. ^ The specific aims were to map TB and HIV new diagnoses rates and spatially identify hotspots and high value clusters at the census tract level. The potential association between HIV and TB was analyzed using spatial autocorrelation and linear regression analysis. The spatial statistics used were ArcGIS 9.3 Hotspot Analysis and Cluster and Outlier Analysis. Spatial autocorrelation was determined through Global Moran's I and linear regression analysis. ^ Hotspots and clusters of TB and HIV are located within the same spatial areas of Harris County. The areas with high value clusters and hotspots for each infection are located within the central downtown area of the city of Houston. There is an additional hotspot area of TB located directly north of I-10 and a hotspot area of HIV northeast of Interstate 610. ^ The Moran's I Index of 0.17 (Z score = 3.6 standard deviations, p-value = 0.01) suggests that TB is statistically clustered with a less than 1% chance that this pattern is due to random chance. However, there were a high number of features with no neighbors which may invalidate the statistical properties of the test. Linear regression analysis indicated that HIV new diagnoses rates (β=−0.006, SE=0.147, p=0.970) and census tracts (β=0.000, SE=0.000, p=0.866) were not significant predictors of TB new diagnoses rates. ^ Mapping products indicate that census tracts with overlapping hotspots and high value clusters of TB and HIV should be a targeted focus for prevention efforts, most particularly within central Harris County. While the statistical association was not confirmed, evidence suggests that there is a relationship between HIV and TB within this two year period.^
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This study documents the biological signatures impressed upon the sedimentary record underlying both the 5°N upwelling system of the Somali Current and the equatorial area of the Somali Basin out of the upwelling influence. The evolution of these two distinct hydrographic systems is compared for the last 160 kyr. Correspondence and cluster analyses are performed on combined radiolarian and planktonic foraminiferal quantitative data in order to study the changes of the planktonic assemblages through time and space. The Upwelling Radiolarian Index (URI) is used as a productivity proxy. The water temperature and hydrographic structure of the upper water masses appear to be the major factors controlling the distribution patterns of the fauna. The relative abundances of three groups of foraminifera, cold water form (dextral N. pachyderma), mixed layer dwellers (G. trilobus, G. ruber, G. sacculifer, G. conglobatus, and G. glutinata), and thermocline dwellers (G. menardii, G. tumida, N. dutertrei, G. crassaformis, and P. obliquiloculata), follow distinct evolutionary patterns at the two sites during the last 160 kyr. At the equatorial site (core MD 85668), downcore fluctuations in the relative abundances of the three groups are closely related to the glacial/interglacial cyclicity and provide some insights into the interpretation of hydrographic changes. The dominance of the mixed layer foraminifera at the transition intervals between isotope stages 6/5 and 2/1, combined with weak URI values, is thought to reflect the reorganization of the oceanographic circulation. These short-term events (with a duration of < 5000 year) could be related to the rapid inflow of oxygen-depleted water through the Indonesian straits as a result of sea level rise during deglaciation. Underneath the 5°N gyre (core MD 85674), the response to global climatic changes is overprinted by the regional effect of the Somalian upwelling, which has been persistent over the last 160 kyr.
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Este trabajo se realizó en el contexto del Plan de estudios que la Facultad de Ciencias Agrarias (UNCuyo) implementó a partir de 1994 para las carreras de Ingeniería Agronómica y Licenciatura en Bromatología. Se calcularon algunos indicadores educativos (Tasa de Aprobación, Tasa de Deserción, Tasa de Recursado y Tasa de Permanencia) con el objeto de efectuar un seguimiento en la aplicación de dicho Plan de estudios, a través de una nueva metología. Para el análisis de los datos se utilizaron cuatro métodos: "Determinación de distancias entre matrices y sus respectivos valores ideales", que permitió elaborar un índice de lejanía del sistema en su conjunto; "Análisis de Componentes Principales (ACP)" seguido de un "Análisis de Conglomerados (AC)", que permitieron agrupar las materias de acuerdo con sus similitudes. Finalmente, se realizó un "Análisis Discriminante", que permitió concluir que las tasas calculadas no establecen diferencias entre las asignaturas de los ciclos Básico e Instrumental (únicamente en el caso de Ingeniería Agronómica).
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Kelp forests represent a major habitat type in coastal waters worldwide and their structure and distribution is predicted to change due to global warming. Despite their ecological and economical importance, there is still a lack of reliable spatial information on their abundance and distribution. In recent years, various hydroacoustic mapping techniques for sublittoral environments evolved. However, in turbid coastal waters, such as off the island of Helgoland (Germany, North Sea), the kelp vegetation is present in shallow water depths normally excluded from hydroacoustic surveys. In this study, single beam survey data consisting of the two seafloor parameters roughness and hardness were obtained with RoxAnn from water depth between 2 and 18 m. Our primary aim was to reliably detect the kelp forest habitat with different densities and distinguish it from other vegetated zones. Five habitat classes were identified using underwater-video and were applied for classification of acoustic signatures. Subsequently, spatial prediction maps were produced via two classification approaches: Linear discriminant analysis (LDA) and manual classification routine (MC). LDA was able to distinguish dense kelp forest from other habitats (i.e. mixed seaweed vegetation, sand, and barren bedrock), but no variances in kelp density. In contrast, MC also provided information on medium dense kelp distribution which is characterized by intermediate roughness and hardness values evoked by reduced kelp abundances. The prediction maps reach accordance levels of 62% (LDA) and 68% (MC). The presence of vegetation (kelp and mixed seaweed vegetation) was determined with higher prediction abilities of 75% (LDA) and 76% (MC). Since the different habitat classes reveal acoustic signatures that strongly overlap, the manual classification method was more appropriate for separating different kelp forest densities and low-lying vegetation. It became evident that the occurrence of kelp in this area is not simply linked to water depth. Moreover, this study shows that the two seafloor parameters collected with RoxAnn are suitable indicators for the discrimination of different densely vegetated seafloor habitats in shallow environments.
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The recent development of in-situ monitoring devices, such as UV-spectrometers, makes the study of short-term stream chemistry variation relevant, especially the study of diurnal cycles, which are not yet fully understood. Our study is based on high-frequency data from an agricultural catchment (Studienlandschaft Schwingbachtal, Germany). We propose a novel approach, i.e. the combination of cluster analysis and Linear Discriminant Analysis, to mine from these data nitrate behavior patterns. As a result, we observe a seasonality of nitrate diurnal cycles, that differs from the most common cycle seasonality described in the literature, i.e. pre-dawn peaks in spring. Our cycles appear in summer and the maximum and minimum shift to a later time in late summer/autumn. This is observed both for water- and energy-limited years, thus potentially stressing the role of evapotranspiration. This concluding hypothesis on the role of evapotranspiration on nitrate stream concentration, which was obtained through data mining, broadens the perspective on the diurnal cycling of stream nitrate concentrations.
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Las técnicas de cirugía de mínima invasión (CMI) se están consolidando hoy en día como alternativa a la cirugía tradicional, debido a sus numerosos beneficios para los pacientes. Este cambio de paradigma implica que los cirujanos deben aprender una serie de habilidades distintas de aquellas requeridas en cirugía abierta. El entrenamiento y evaluación de estas habilidades se ha convertido en una de las mayores preocupaciones en los programas de formación de cirujanos, debido en gran parte a la presión de una sociedad que exige cirujanos bien preparados y una reducción en el número de errores médicos. Por tanto, se está prestando especial atención a la definición de nuevos programas que permitan el entrenamiento y la evaluación de las habilidades psicomotoras en entornos seguros antes de que los nuevos cirujanos puedan operar sobre pacientes reales. Para tal fin, hospitales y centros de formación están gradualmente incorporando instalaciones de entrenamiento donde los residentes puedan practicar y aprender sin riesgos. Es cada vez más común que estos laboratorios dispongan de simuladores virtuales o simuladores físicos capaces de registrar los movimientos del instrumental de cada residente. Estos simuladores ofrecen una gran variedad de tareas de entrenamiento y evaluación, así como la posibilidad de obtener información objetiva de los ejercicios. Los diferentes estudios de validación llevados a cabo dan muestra de su utilidad; pese a todo, los niveles de evidencia presentados son en muchas ocasiones insuficientes. Lo que es más importante, no existe un consenso claro a la hora de definir qué métricas son más útiles para caracterizar la pericia quirúrgica. El objetivo de esta tesis doctoral es diseñar y validar un marco de trabajo conceptual para la definición y validación de entornos para la evaluación de habilidades en CMI, en base a un modelo en tres fases: pedagógica (tareas y métricas a emplear), tecnológica (tecnologías de adquisición de métricas) y analítica (interpretación de la competencia en base a las métricas). Para tal fin, se describe la implementación práctica de un entorno basado en (1) un sistema de seguimiento de instrumental fundamentado en el análisis del vídeo laparoscópico; y (2) la determinación de la pericia en base a métricas de movimiento del instrumental. Para la fase pedagógica se diseñó e implementó un conjunto de tareas para la evaluación de habilidades psicomotoras básicas, así como una serie de métricas de movimiento. La validación de construcción llevada a cabo sobre ellas mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. Adicionalmente, los resultados obtenidos en la validación de apariencia fueron en general positivos en todos los grupos considerados (noveles, residentes, expertos). Para la fase tecnológica, se introdujo el EVA Tracking System, una solución para el seguimiento del instrumental quirúrgico basado en el análisis del vídeo endoscópico. La precisión del sistema se evaluó a 16,33ppRMS para el seguimiento 2D de la herramienta en la imagen; y a 13mmRMS para el seguimiento espacial de la misma. La validación de construcción con una de las tareas de evaluación mostró buenos resultados para tiempo, camino recorrido, profundidad, velocidad media, aceleración media, economía de área y economía de volumen. La validación concurrente con el TrEndo® Tracking System por su parte presentó valores altos de correlación para 8 de las 9 métricas analizadas. Finalmente, para la fase analítica se comparó el comportamiento de tres clasificadores supervisados a la hora de determinar automáticamente la pericia quirúrgica en base a la información de movimiento del instrumental, basados en aproximaciones lineales (análisis lineal discriminante, LDA), no lineales (máquinas de soporte vectorial, SVM) y difusas (sistemas adaptativos de inferencia neurodifusa, ANFIS). Los resultados muestran que en media SVM presenta un comportamiento ligeramente superior: 78,2% frente a los 71% y 71,7% obtenidos por ANFIS y LDA respectivamente. Sin embargo las diferencias estadísticas medidas entre los tres no fueron demostradas significativas. En general, esta tesis doctoral corrobora las hipótesis de investigación postuladas relativas a la definición de sistemas de evaluación de habilidades para cirugía de mínima invasión, a la utilidad del análisis de vídeo como fuente de información y a la importancia de la información de movimiento de instrumental a la hora de caracterizar la pericia quirúrgica. Basándose en estos cimientos, se han de abrir nuevos campos de investigación que contribuyan a la definición de programas de formación estructurados y objetivos, que puedan garantizar la acreditación de cirujanos sobradamente preparados y promocionen la seguridad del paciente en el quirófano. Abstract Minimally invasive surgery (MIS) techniques have become a standard in many surgical sub-specialties, due to their many benefits for patients. However, this shift in paradigm implies that surgeons must acquire a complete different set of skills than those normally attributed to open surgery. Training and assessment of these skills has become a major concern in surgical learning programmes, especially considering the social demand for better-prepared professionals and for the decrease of medical errors. Therefore, much effort is being put in the definition of structured MIS learning programmes, where practice with real patients in the operating room (OR) can be delayed until the resident can attest for a minimum level of psychomotor competence. To this end, skills’ laboratory settings are being introduced in hospitals and training centres where residents may practice and be assessed on their psychomotor skills. Technological advances in the field of tracking technologies and virtual reality (VR) have enabled the creation of new learning systems such as VR simulators or enhanced box trainers. These systems offer a wide range of tasks, as well as the capability of registering objective data on the trainees’ performance. Validation studies give proof of their usefulness; however, levels of evidence reported are in many cases low. More importantly, there is still no clear consensus on topics such as the optimal metrics that must be used to assess competence, the validity of VR simulation, the portability of tracking technologies into real surgeries (for advanced assessment) or the degree to which the skills measured and obtained in laboratory environments transfer to the OR. The purpose of this PhD is to design and validate a conceptual framework for the definition and validation of MIS assessment environments based on a three-pillared model defining three main stages: pedagogical (tasks and metrics to employ), technological (metric acquisition technologies) and analytical (interpretation of competence based on metrics). To this end, a practical implementation of the framework is presented, focused on (1) a video-based tracking system and (2) the determination of surgical competence based on the laparoscopic instruments’ motionrelated data. The pedagogical stage’s results led to the design and implementation of a set of basic tasks for MIS psychomotor skills’ assessment, as well as the definition of motion analysis parameters (MAPs) to measure performance on said tasks. Validation yielded good construct results for parameters such as time, path length, depth, average speed, average acceleration, economy of area and economy of volume. Additionally, face validation results showed positive acceptance on behalf of the experts, residents and novices. For the technological stage the EVA Tracking System is introduced. EVA provides a solution for tracking laparoscopic instruments from the analysis of the monoscopic video image. Accuracy tests for the system are presented, which yielded an average RMSE of 16.33pp for 2D tracking of the instrument on the image and of 13mm for 3D spatial tracking. A validation experiment was conducted using one of the tasks and the most relevant MAPs. Construct validation showed significant differences for time, path length, depth, average speed, average acceleration, economy of area and economy of volume; especially between novices and residents/experts. More importantly, concurrent validation with the TrEndo® Tracking System presented high correlation values (>0.7) for 8 of the 9 MAPs proposed. Finally, the analytical stage allowed comparing the performance of three different supervised classification strategies in the determination of surgical competence based on motion-related information. The three classifiers were based on linear (linear discriminant analysis, LDA), non-linear (support vector machines, SVM) and fuzzy (adaptive neuro fuzzy inference systems, ANFIS) approaches. Results for SVM show slightly better performance than the other two classifiers: on average, accuracy for LDA, SVM and ANFIS was of 71.7%, 78.2% and 71% respectively. However, when confronted, no statistical significance was found between any of the three. Overall, this PhD corroborates the investigated research hypotheses regarding the definition of MIS assessment systems, the use of endoscopic video analysis as the main source of information and the relevance of motion analysis in the determination of surgical competence. New research fields in the training and assessment of MIS surgeons can be proposed based on these foundations, in order to contribute to the definition of structured and objective learning programmes that guarantee the accreditation of well-prepared professionals and the promotion of patient safety in the OR.
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Fourier transform infrared (FTIR) spectroscopy was applied to determine the type of surface treatment and dose used on cork stoppers and to predict the friction between stopper and bottleneck. Agglomerated cork stoppers were finished with two different doses and using two surface treatments: P (paraffin and silicone), 15 and 25 mg/stopper, and S (only silicone), 10 and 15 mg/stopper. FTIR spectra were recorded at five points for each stopper by attenuated total reflectance (ATR). Absorbances at 1,010, 2,916, and 2,963 cm -1 were obtained in each spectrum. Discriminant analysis techniques allowed the treatment, and dose applied to each stopper to be identified from the absorbance values. 91.2% success rates were obtained from individual values and 96.0% from the mean values of each stopper. Spectrometric data also allowed treatment homogeneity to be determined on the stopper surface, and a multiple regression model was used to predict the friction index (If = Fe/Fc) (R 2 = 0.93)
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We show a cluster based routing protocol in order to improve the convergence of the clusters and of the network it is proposed to use a backup cluster head. The use of a event discrete simulator is used for the implementation and the simulation of a hierarchical routing protocol called the Backup Cluster Head Protocol (BCHP). Finally it is shown that the BCHP protocol improves the convergence and availability of the network through a comparative analysis with the Ad Hoc On Demand Distance Vector (AODV)[1] routing protocol and Cluster Based Routing Protocol (CBRP)[2]
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Case-based reasoning (CBR) is a unique tool for the evaluation of possible failure of firms (EOPFOF) for its eases of interpretation and implementation. Ensemble computing, a variation of group decision in society, provides a potential means of improving predictive performance of CBR-based EOPFOF. This research aims to integrate bagging and proportion case-basing with CBR to generate a method of proportion bagging CBR for EOPFOF. Diverse multiple case bases are first produced by multiple case-basing, in which a volume parameter is introduced to control the size of each case base. Then, the classic case retrieval algorithm is implemented to generate diverse member CBR predictors. Majority voting, the most frequently used mechanism in ensemble computing, is finally used to aggregate outputs of member CBR predictors in order to produce final prediction of the CBR ensemble. In an empirical experiment, we statistically validated the results of the CBR ensemble from multiple case bases by comparing them with those of multivariate discriminant analysis, logistic regression, classic CBR, the best member CBR predictor and bagging CBR ensemble. The results from Chinese EOPFOF prior to 3 years indicate that the new CBR ensemble, which significantly improved CBRs predictive ability, outperformed all the comparative methods.
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Mulch materials of different origins have been introduced into the agricultural sector in recent years alternatively to the standard polyethylene due to its environmental impact. This study aimed to evaluate the multivariate response of mulch materials over three consecutive years in a processing tomato (Solanum lycopersicon L.) crop in Central Spain. Two biodegradable plastic mulches (BD1, BD2), one oxo-biodegradable material (OB), two types of paper (PP1, PP2), and one barley straw cover (BS) were compared using two control treatments (standard black polyethylene [PE] and manual weed control [MW]). A total of 17 variables relating to yield, fruit quality, and weed control were investigated. Several multivariate statistical techniques were applied, including principal component analysis, cluster analysis, and discriminant analysis. A group of mulch materials comprised of OB and BD2 was found to be comparable to black polyethylene regarding all the variables considered. The weed control variables were found to be an important source of discrimination. The two paper mulches tested did not share the same treatment group membership in any case: PP2 presented a multivariate response more similar to the biodegradable plastics, while PP1 was more similar to BS and MW. Based on our multivariate approach, the materials OB and BD2 can be used as an effective, more environmentally friendly alternative to polyethylene mulches.
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The early detection of spoiling metabolic products in contaminated food is a very important tool to control quality. Some volatile compounds produce unpleasant odours at very low concentrations, making their early detection very challenging. This is the case of 1,3-pentadiene produced by microorganisms through decarboxylation of the preservative sorbate. In this work, we have developed a methodology to use the data produced by a low-cost, compact MWIR (Mid-Wave IR) spectrometry device without moving parts, which is based on a linear array of 128 elements of VPD PbSe coupled to a linear variable filter (LVF) working in the spectral range between 3 and 4.6 ?m. This device is able to analyze food headspace gases through dedicated sample presentation setup. This methodology enables the detection of CO2 and the volatile compound 1,3-pentadiene, as compared to synthetic patrons. Data analysis is based on an automated multidimensional dynamic processing of the MWIR spectra. Principal component and discriminant analysis allow segregating between four yeast strains including producers and no producers. The segregation power is accounted as a measure of the discrimination quality.
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Este trabalho apresenta resultados geoquímicos multielementares de sedimentos de corrente no estado de São Paulo, obtidos através do projeto institucional do Serviço Geológico do Brasil denominado \"Levantamento Geoquímico de Baixa Densidade no Brasil\". Dados analíticos de 1422 amostras de sedimento de corrente obtidos por ICP-MS (Inductively Coupled Plasma Mass Spectrometry), para 32 elementos químicos (Al, Ba, Be, Ca, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hf, K, La, Mg, Mn, Mo, Nb, Ni, P, Pb, Rb, Sc, Sn, Sr, Th, Ti, U, V, Y, Zn e Zr), foram processadas e abordadas através da análise estatística uni e multivariada. Os resultados do tratamento dos dados através de técnicas estatísticas univariadas forneceram os valores de background geoquímico (teor de fundo) dos 32 elementos para todo estado de São Paulo. A análise georreferenciada das distribuições geoquímicas unielementares evidenciaram a compartimentação geológica da área. As duas principais províncias geológicas do estado de São Paulo, Bacia do Paraná e Complexo Cristalino, se destacam claramente na maioria das distribuições geoquímicas. Unidades geológicas de maior expressão, como a Formação Serra Geral e o Grupo Bauru também foram claramente destacadas. Outras feições geoquímicas indicaram possíveis áreas contaminadas e unidades geológicas não cartografadas. Os resultados da aplicação de métodos estatísticos multivariados aos dados geoquímicos com 24 variáveis (Al, Ba, Ce, Co, Cr, Cs, Cu, Fe, Ga, La, Mn, Nb, Ni, Pb, Rb, Sc, Sr, Th, Ti, U, V, Y, Zn e Zr) permitiram definir as principais assinaturas e associações geoquímicas existentes em todo estado de São Paulo e correlacioná-las aos principais domínios litológicos. A análise de agrupamentos em modo Q forneceu oito grupos de amostras geoquimicamente correlacionáveis, que georreferenciadas reproduziram os principais compartimentos geológicos do estado: Complexo Cristalino, Grupos Itararé e Passa Dois, Formação Serra Geral e Grupos Bauru e Caiuá. A análise discriminante multigrupos comprovou, estatisticamente, a classificação dos grupos formados pela análise de agrupamentos e forneceu as principais variáveis discriminantes: Fe, Co, Sc, V e Cu. A análise de componentes principais, abordada em conjunto com a análise fatorial pelo método de rotação varimax, forneceram os principais fatores multivariados e suas respectivas associações elementares. O georreferenciamento dos valores de escores fatoriais multivariados delimitaram as áreas onde as associações elementares ocorrem e forneceram mapas multivariados para todo o estado. Por fim, conclui-se que os métodos estatísticos aplicados são indispensáveis no tratamento, apresentação e interpretação de dados geoquímicos. Ademais, com base em uma visão integrada dos resultados obtidos, este trabalho recomenda: (1) a execução dos levantamentos geoquímicos de baixa densidade em todo país em caráter de prioridade, pois são altamente eficazes na definição de backgrounds regionais e delimitação de províncias geoquímicas com interesse metalogenético e ambiental; (2) a execução do mapeamento geológico contínuo em escala adequada (maiores que 1:100.000) em áreas que apontam para possíveis existências de unidades não cartografadas nos mapas geológicos atuais.
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A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.