Morfodinâmica costeira e o uso da orla oceânica de Salinópolis (Nordeste do Pará)

Os aspectos morfodinâmicos relacionados à erosão ou acresção da linha de costa são alguns dos assuntos analisados na gestão das zonas costeiras que vêem sendo tratada em todo mundo no sentido de monitorar e proteger essas zonas. Esta tese objetiva analisar o comportamento da morfodinâmica costeira de Salinópolis, relacionando-o ao uso da orla oceânica. A área de estudo foi compartimentada em três setores: Oeste (praias da Corvina e do Maçarico), Central (praia do Farol Velho) e Leste (praia do Atalaia). A metodologia consistiu na: (a) aquisição e tratamento de imagens multitemporais (1988-2001-2013) do satélite Landsat 5 TM, 7 ETM e 8 OLI; (b) aplicação de entrevistas/questionários com banhistas, (c) aquisição de dados de campo durante as estações chuvosa (26, 27, 28/04/2013) e menos chuvosa (04, 05, 06/10/2013); e (d) análise laboratorial para o tratamento dos dados adquiridos em campo (topografia das praias estudadas, amostragem de sedimentos superficiais das mesmas e com o uso de armadilhas, e medições oceanográficas de ondas, marés, correntes e turbidez). Foram feitas as representações gráficas dos perfis topográficos das praias, calculados os parâmetros estatísticos granulométricos de Folk & Ward (1957), as taxas do transporte sedimentar nas praias e os parâmetros morfométricos de Short & Hesp (1982), estes últimos foram calculados com o intuito de relacioná-los aos estados morfodinâmicos de praias propostos por Wright & Short (1984) e Masselink & Short (1993). Para a classificação da costa oceânica de Salinópolis em termos de uso e ocupação foi utilizado o decreto nº 5.300 de 7 de dezembro de 2004. A partir das pesquisas sobre a urbanização na costa e das obras situadas nos ambientes costeiros foi utilizada uma matriz proposta por Farinaccio & Tessler (2010) que lista uma série de impactos ambientais, e o quadro de geoindicadores do comportamento da linha de costa proposto por Bush et al. (1999), para a identificação de locais com vulnerabilidade à erosão ou acresção. Para as condições oceanográficas em cada praia e periculosidade ao banho nas mesmas, foram integralizados os dados de ondas, de correntes, de morfodinâmica praial e questionários aplicados com banhistas. Atualmente, a orla oceânica de Salinópolis possui diferentes características quanto à utilização e conservação, abrangendo desde a tipologia de orlas naturais (Classe A) até orlas com urbanização consolidada (Classe C). A primeira ocorre nos extremos da área de estudo e, a segunda, na região da sede municipal. Quatro tipos de praias foram identificados segundo a exposição marítima e o grau das condições oceanográficas: tipo 1 (Maçarico), tipo 2 (Corvina), tipo 3 (Farol Velho) e tipo 4 (Atalaia). O trecho de costa com maiores impactos ambientais e com elevada erosão costeira localiza-se na praia do Farol Velho. O grau de periculosidade ao banho foi de 4 (praia do Maçarico) a 7 (praia do Atalaia) – médio a alto grau de risco. As praias de Salinópolis apresentam declives suaves (< 1,5°), grandes variações na linha de costa entre as estações do ano (9,6 a 88, 4 m) e volume sedimentar variável dependendo do grau de exposição das praias ao oceano aberto. Predominou o estado morfodinâmico dissipativo (Ω>5,5) para estas praias, mas com ocorrência do estado de banco e calha longitudinais (4,7<Ω<5,5) no setor oeste. As macromarés na área de estudo apresentaram altura máxima de 5,3 m (Setor Central, durante a estação menos chuvosa) e mínima de 4 m no mesmo setor, durante a estação chuvosa. As correntes longitudinais foram mais intensas no setor leste (>0,45 m/s) durante as duas estaçoes do ano. As alturas de ondas foram também maiores no setor leste (máximo de 1,05 m durante a maré enchente na estação menos chuvosa) e os períodos de ondas foram mais curtos (<4,5 s) no setor oeste. A média granulométrica obtida dos sedimentos coletados na face praial apresentou escala mais freqüente entre 2,6 a 2,8 phi, indicando a predominância de areia fina. O grau de seleção predominante dos sedimentos foi de 0,2 a 0,5 phi (muito bem selecionados e bem selecionados), e da assimetria foi de positiva (0,10 a 0,30) e de aproximadamente simétrica (-0,10 a 0,10). O grau de curtose variou desde muito platicúrtica (<0,67) a muito leptocúrtica (1,50 a 3,00). Foram observados eventos de acresção sedimentar da estação chuvosa a menos chuvosa. De 22/07/1988 a 28/08/2013 (25 anos) também houve predomínio de acresção, onde o avanço médio linear da linha de costa foi de 190,26 m. O recuo médio linear obtido para toda área de estudo foi de -42,25 m. Áreas com maior erosão são pontuais: divisas das praias da Corvina e Maçarico, e Farol Velho e Atalaia. Os traps portáteis indicaram uma maior quantidade de sedimentos transportados longitudinalmente na estação menos chuvosa (Mín. 280 g/m³: enchente, setor oeste; Máx. 1098 g/m³: vazante, setor leste). Nos traps de espraiamento, o balanço entre a quantidade de sedimentos entrando e saindo nas praias foi menor no setor central (Mín. 80 g/m³: vazante, estação menos chuvosa; Máx. 690 g/m³: enchente, estação menos chuvosa). A circulação costeira sedimentar é proveniente, principalmente, do efeito das marés, com direção governada pela enchente e vazante dos rios que atravessam a costa. Os dados indicam o transporte longitudinal de sedimentos da ilha de Atalaia e rio Sampaio para o setor oeste e as margens das faixas praiais.

Determinação de áreas prioritárias para o restabelecimento da cobertura florestal, apoiada no uso de geotecnologias

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-scale lacunarity as an alternative to quantify and diagnose the behavior of prostate cancer

Prostate cancer is a serious public health problem accounting for up to 30% of clinical tumors in men. The diagnosis of this disease is made with clinical, laboratorial and radiological exams, which may indicate the need for transrectal biopsy. Prostate biopsies are discerningly evaluated by pathologists in an attempt to determine the most appropriate conduct. This paper presents a set of techniques for identifying and quantifying regions of interest in prostatic images. Analyses were performed using multi-scale lacunarity and distinct classification methods: decision tree, support vector machine and polynomial classifier. The performance evaluation measures were based on area under the receiver operating characteristic curve (AUC). The most appropriate region for distinguishing the different tissues (normal, hyperplastic and neoplasic) was defined: the corresponding lacunarity values and a rule's model were obtained considering combinations commonly explored by specialists in clinical practice. The best discriminative values (AUC) were 0.906, 0.891 and 0.859 between neoplasic versus normal, neoplasic versus hyperplastic and hyperplastic versus normal groups, respectively. The proposed protocol offers the advantage of making the findings comprehensible to pathologists. (C) 2014 Elsevier Ltd. All rights reserved.

Pruning methods to MLP neural networks considering proportional apparent error rate for classification problems with unbalanced data

This article deals with classification problems involving unequal probabilities in each class and discusses metrics to systems that use multilayer perceptrons neural networks (MLP) for the task of classifying new patterns. In addition we propose three new pruning methods that were compared to other seven existing methods in the literature for MLP networks. All pruning algorithms presented in this paper have been modified by the authors to do pruning of neurons, in order to produce fully connected MLP networks but being small in its intermediary layer. Experiments were carried out involving the E. coli unbalanced classification problem and ten pruning methods. The proposed methods had obtained good results, actually, better results than another pruning methods previously defined at the MLP neural network area. (C) 2014 Elsevier Ltd. All rights reserved.

A multisensor, multitemporal approach for monitoring herbaceous vegetation growth in the Amazon floodplain

The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.

Classification of intact fresh plums according to sweetness using time-domain nuclear magnetic resonance and chemometrics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Cone-beam evaluation of pharyngeal airway space in class I, II, and III patients

The purpose of this study is to make a 3-dimensional (3-D) evaluation of the pharyngeal airway space (PAS) in patients with class I, II, and III malocclusion. Sixty patients were evaluated. The patients were divided in 3 groups according to their occlusion classification. The volume and area of PAS were evaluated using the software Dolphin 3-D Imaging in the preoperative period for orthognathic surgery. PAS volume and area were influenced by different patterns of malocclusion. The mean volume and area for class III patients were statistically bigger than for classes I and II patients (P < .001). There was also a significant difference for volume values between class I and II patients, being the bigger volume for the class I patients (P < .05). It was possible to conclude that the class III patients presented a bigger PAS compared with classes I and II patients.

Class Notes for Math 901/902: Abstract Algebra, Instructor Tom Marley

Topics include: Free groups and presentations; Automorphism groups; Semidirect products; Classification of groups of small order; Normal series: composition, derived, and solvable series; Algebraic field extensions, splitting fields, algebraic closures; Separable algebraic extensions, the Primitive Element Theorem; Inseparability, purely inseparable extensions; Finite fields; Cyclotomic field extensions; Galois theory; Norm and trace maps of an algebraic field extension; Solvability by radicals, Galois' theorem; Transcendence degree; Rings and modules: Examples and basic properties; Exact sequences, split short exact sequences; Free modules, projective modules; Localization of (commutative) rings and modules; The prime spectrum of a ring; Nakayama's lemma; Basic category theory; The Hom functors; Tensor products, adjointness; Left/right Noetherian and Artinian modules; Composition series, the Jordan-Holder Theorem; Semisimple rings; The Artin-Wedderburn Theorem; The Density Theorem; The Jacobson radical; Artinian rings; von Neumann regular rings; Wedderburn's theorem on finite division rings; Group representations, character theory; Integral ring extensions; Burnside's paqb Theorem; Injective modules.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Elemental abundances and classification of carbon-enhanced metal-poor stars

We present a detailed study of carbon-enhanced metal-poor (CEMP) stars, based on high-resolution spectroscopic observations of a sample of 18 stars. The stellar spectra for this sample were obtained at the 4.2 m William Herschel Telescope in 2001 and 2002, using the Utrecht Echelle Spectrograph, at a resolving power R similar to 52 000 and S/N similar to 40, covering the wavelength range lambda lambda 3700-5700 angstrom. The atmospheric parameters determined for this sample indicate temperatures ranging from 4750 K to 7100 K, log g from 1.5 to 4.3, and metallicities -3.0 <= [Fe/H]<=-1.7. Elemental abundances for C, Na, Mg, Sc, Ti, Cr, Cu, Zn, Sr, Y, Zr, Ba, La, Ce, Nd, Sm, Eu, Gd, Dy are determined. Abundances for an additional 109 stars were taken from the literature and combined with the data of our sample. The literature sample reveals a lack of reliable abundance estimates for species that might be associated with the r-process elements for about 67% of CEMP stars, preventing a complete understanding of this class of stars, since [Ba/Eu] ratios are used to classify them. Although eight stars in our observed sample are also found in the literature sample, Eu abundances or limits are determined for four of these stars for the first time. From the observed correlations between C, Ba, and Eu, we argue that the CEMP-r/s class has the same astronomical origin as CEMP-s stars, highlighting the need for a more complete understanding of Eu production.

Network-based high level data classification

Traditional supervised data classification considers only physical features (e. g., distance or similarity) of the input data. Here, this type of learning is called low level classification. On the other hand, the human (animal) brain performs both low and high orders of learning and it has facility in identifying patterns according to the semantic meaning of the input data. Data classification that considers not only physical attributes but also the pattern formation is, here, referred to as high level classification. In this paper, we propose a hybrid classification technique that combines both types of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features or class topologies, while the latter measures the compliance of the test instances to the pattern formation of the data. Our study shows that the proposed technique not only can realize classification according to the pattern formation, but also is able to improve the performance of traditional classification techniques. Furthermore, as the class configuration's complexity increases, such as the mixture among different classes, a larger portion of the high level term is required to get correct classification. This feature confirms that the high level classification has a special importance in complex situations of classification. Finally, we show how the proposed technique can be employed in a real-world application, where it is capable of identifying variations and distortions of handwritten digit images. As a result, it supplies an improvement in the overall pattern recognition rate.

Evolving decision trees with beam search-based initialization and lexicographic multi-objective evaluation

Decision tree induction algorithms represent one of the most popular techniques for dealing with classification problems. However, traditional decision-tree induction algorithms implement a greedy approach for node splitting that is inherently susceptible to local optima convergence. Evolutionary algorithms can avoid the problems associated with a greedy search and have been successfully employed to the induction of decision trees. Previously, we proposed a lexicographic multi-objective genetic algorithm for decision-tree induction, named LEGAL-Tree. In this work, we propose extending this approach substantially, particularly w.r.t. two important evolutionary aspects: the initialization of the population and the fitness function. We carry out a comprehensive set of experiments to validate our extended algorithm. The experimental results suggest that it is able to outperform both traditional algorithms for decision-tree induction and another evolutionary algorithm in a variety of application domains.

Texture analysis by multi-resolution fractal descriptors

This work proposes a novel texture descriptor based on fractal theory. The method is based on the Bouligand- Minkowski descriptors. We decompose the original image recursively into four equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The proposed descriptors are provided by concatenating such measures. The method is tested in a classification experiment under well known datasets, that is, Brodatz and Vistex. The results demonstrate that the novel technique achieves better results than classical and state-of-the-art texture descriptors, such as Local Binary Patterns, Gabor-wavelets and co-occurrence matrix.

On existence and uniqueness of positive solutions to a class of fractional boundary value problems

[EN] The purpose of this paper is to investigate the existence and uniqueness of positive solutions for the following fractional boundary value problem D 0 + α u ( t ) + f ( t , u ( t ) ) = 0 , 0 < t < 1 , u ( 0 ) = u ( 1 ) = u ′ ( 0 ) = 0 , where 2 < α ≤ 3 and D 0 + α is the Riemann-Liouville fractional derivative. Our analysis relies on a fixed-point theorem in partially ordered metric spaces. The autonomous case of this problem was studied in the paper [Zhao et al., Abs. Appl. Anal., to appear], but in Zhao et al. (to appear), the question of uniqueness of the solution is not treated. We also present some examples where we compare our results with the ones obtained in Zhao et al. (to appear). 2010 Mathematics Subject Classification: 34B15