The Fry method applied to an augen orthogneiss: Problems and results

The application of the Fry method to measure strain in deformed porphyritic granites is discussed. This method requires that the distribution of markers has to satisfy at least two conditions. It has to be homogeneous and isotropic. Statistics on point distribution with the help of a Morishita diagram can easily test homogeneity. Isotropy can be checked with a cumulative histogram of angles between points. Application of these tests to undeformed (Mte Capanne granite, Elba) and to deformed (Randa orthogneiss, Alps of Switzerland) porphyritic granite reveals that their K-feldspars phenocrysts both satisfy these conditions and can be used as strain markers with the Fry method. Other problems are also examined. One is the possible distribution of deformation on discrete shear-bands. Providing several tests are met, we conclude that the Fry method can be used to estimate strain in deformed porphyritic granites. (c) 2006 Elsevier Ltd. All rights reserved.

Chroma binary similarity and local alignment applied to cover song identification

We present a new technique for audio signal comparison based on tonal subsequence alignment and its application to detect cover versions (i.e., different performances of the same underlying musical piece). Cover song identification is a task whose popularity has increased in the Music Information Retrieval (MIR) community along in the past, as it provides a direct and objective way to evaluate music similarity algorithms.This article first presents a series of experiments carried outwith two state-of-the-art methods for cover song identification.We have studied several components of these (such as chroma resolution and similarity, transposition, beat tracking or Dynamic Time Warping constraints), in order to discover which characteristics would be desirable for a competitive cover song identifier. After analyzing many cross-validated results, the importance of these characteristics is discussed, and the best-performing ones are finally applied to the newly proposed method. Multipleevaluations of this one confirm a large increase in identificationaccuracy when comparing it with alternative state-of-the-artapproaches.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Commentary on the need for a research culture in the forensic sciences

Asked to comment on a collective discussion paper by Jennifer L. Mnookin et al., this Commentary identifies difficulties the authors encountered in defining or agreeing on the subject matter "forensic science" and its perceived deficiencies. They conclude that there is a need for a research culture, whereas this Commentary calls for the development of a forensic science culture through the development of forensic science education fed by research dedicated to forensic science issues. It is a call for a change of emphasis and, perhaps, of paradigm.

BIO-INSPIRED COMPUTATIONAL TECHNIQUES APPLIED TO THE CLUSTERING AND VISUALIZATION OF SPATIO-TEMPORAL GEOSPATIAL DATA

The coverage and volume of geo-referenced datasets are extensive and incessantly¦growing. The systematic capture of geo-referenced information generates large volumes¦of spatio-temporal data to be analyzed. Clustering and visualization play a key¦role in the exploratory data analysis and the extraction of knowledge embedded in¦these data. However, new challenges in visualization and clustering are posed when¦dealing with the special characteristics of this data. For instance, its complex structures,¦large quantity of samples, variables involved in a temporal context, high dimensionality¦and large variability in cluster shapes.¦The central aim of my thesis is to propose new algorithms and methodologies for¦clustering and visualization, in order to assist the knowledge extraction from spatiotemporal¦geo-referenced data, thus improving making decision processes.¦I present two original algorithms, one for clustering: the Fuzzy Growing Hierarchical¦Self-Organizing Networks (FGHSON), and the second for exploratory visual data analysis:¦the Tree-structured Self-organizing Maps Component Planes. In addition, I present¦methodologies that combined with FGHSON and the Tree-structured SOM Component¦Planes allow the integration of space and time seamlessly and simultaneously in¦order to extract knowledge embedded in a temporal context.¦The originality of the FGHSON lies in its capability to reflect the underlying structure¦of a dataset in a hierarchical fuzzy way. A hierarchical fuzzy representation of¦clusters is crucial when data include complex structures with large variability of cluster¦shapes, variances, densities and number of clusters. The most important characteristics¦of the FGHSON include: (1) It does not require an a-priori setup of the number¦of clusters. (2) The algorithm executes several self-organizing processes in parallel.¦Hence, when dealing with large datasets the processes can be distributed reducing the¦computational cost. (3) Only three parameters are necessary to set up the algorithm.¦In the case of the Tree-structured SOM Component Planes, the novelty of this algorithm¦lies in its ability to create a structure that allows the visual exploratory data analysis¦of large high-dimensional datasets. This algorithm creates a hierarchical structure¦of Self-Organizing Map Component Planes, arranging similar variables' projections in¦the same branches of the tree. Hence, similarities on variables' behavior can be easily¦detected (e.g. local correlations, maximal and minimal values and outliers).¦Both FGHSON and the Tree-structured SOM Component Planes were applied in¦several agroecological problems proving to be very efficient in the exploratory analysis¦and clustering of spatio-temporal datasets.¦In this thesis I also tested three soft competitive learning algorithms. Two of them¦well-known non supervised soft competitive algorithms, namely the Self-Organizing¦Maps (SOMs) and the Growing Hierarchical Self-Organizing Maps (GHSOMs); and the¦third was our original contribution, the FGHSON. Although the algorithms presented¦here have been used in several areas, to my knowledge there is not any work applying¦and comparing the performance of those techniques when dealing with spatiotemporal¦geospatial data, as it is presented in this thesis.¦I propose original methodologies to explore spatio-temporal geo-referenced datasets¦through time. Our approach uses time windows to capture temporal similarities and¦variations by using the FGHSON clustering algorithm. The developed methodologies¦are used in two case studies. In the first, the objective was to find similar agroecozones¦through time and in the second one it was to find similar environmental patterns¦shifted in time.¦Several results presented in this thesis have led to new contributions to agroecological¦knowledge, for instance, in sugar cane, and blackberry production.¦Finally, in the framework of this thesis we developed several software tools: (1)¦a Matlab toolbox that implements the FGHSON algorithm, and (2) a program called¦BIS (Bio-inspired Identification of Similar agroecozones) an interactive graphical user¦interface tool which integrates the FGHSON algorithm with Google Earth in order to¦show zones with similar agroecological characteristics.

Availability of a soluble phosphorus source applied to soil samples with different acidicity levels

Considerations on the interactions of P in the soil-plant system have a long history, but are still topical and not yet satisfactorily understood. One concern is the effect of liming before or after application of soluble sources on the crop yield and efficiency of available P under these conditions. The aim of this study was to evaluate the effect of soil acidity on availability of P from a soluble source, based on plant growth and chemical extractants. Nine soil samples were incubated with a dose of 200 mg kg-1 P in soil with different levels of previously adjusted acidity (pH H2O 4.5; 5.0; 5.5; 6.0 and 6.5) and compared to soils without P application. After 40 days of soil incubation with a P source, each treatment was limed again so that all pH values were adjusted to 6.5 and then sorghum was planted. After the first and second liming the P levels were determined by the extractants Mehlich-1, Bray-1 and Resin, and the fractionated inorganic P forms. In general, the different acidity levels did not influence the P availability measured by plant growth and P uptake at the studied P dose. For some soils however these values increased or decreased according to the initial soil pH (from 4.5 to 6.5). Plant growth, P uptake and P extractable by Mehlich-1 and Bray-1 were significantly correlated, unlike resin-extractable P, at pH values raised to 6.5. These latter correlations were however significant before the second liming. The P contents extracted by Mehlich-1 and Bray-1 were significantly correlated with each other in the entire test range of soil acidity, even after adjusting pH to 6.5, besides depending on the soil buffering capacity for P. Resin was also sensitive to the properties that express the soil buffering capacity for P, but less clearly than Mehlich-1 and Bray-1. The application of triple superphosphate tended to increase the levels of P-Al, P-Fe and P-Ca and the highest P levels extracted by Bray-1 were due to a higher occurrence of P-Al and P-Fe in the soils.

Loss of ammonia from nitrogen fertilizers applied to maize and soybean straw

In Brazilian agriculture, urea is the most commonly used nitrogen (N) source, in spite of having the disadvantage of losing considerable amounts of N by ammonia-N volatilization. The objectives of this study were to evaluate: N lossby ammonia volatilization from: [urea coated with copper sulfate and boric acid], [urea coated with zeolite], [urea+ammonium sulfate], [urea coated with copper sulfate and boric acid+ammonium sulfate], [common urea] and [ammonium nitrate]; and the effect of these N source son the maize yield in terms of amount and quality. The treatments were applied to the surface of a soil under no-tillage maize, in two growing seasons. The first season (2009/2010) was after a maize crop (maize straw left on the soil surface) and the second cycle (2012/2011) after a soybean crop. Due to the weather conditions during the experiments, the volatilization of ammonia-N was highest in the first four days after application of the N sources. Of all urea sources, under volatilization-favorable conditions, the loss of ammonia from urea coated with copper sulfate and boric acid was lowest, while under high rainfall, the losses from the different urea sources was similar, i.e., an adequate rainfall was favorablet o reduce volatilization. The ammonia volatilization losses were greatest in the first four days after application. Maize grain yield differed due to N application and in the treatments, but this was only observed with cultivation of maize crop residues in 2009/2010. The combination of ammonium+urea coated with copper sulfate and boric acid optimized grain yield compared to the other urea treatments. The crude protein concentration in maize was not influenced by the technologies of urea coating.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Multivariate analysis applied to the study of the relationship between soil and plant properties in a peach orchard

In the State of Rio Grande do Sul, the municipality of Pelotas is responsible for 90 % of peach production due to its suitable climate and soil conditions. However, there is the need for new studies that aim at improved fruit quality and increased yield. The aim of this study was to evaluate the relationship that exists between soil physical properties and properties in the peach plant in the years 2010 and 2011 by the technique of multivariate canonical correlation. The experiment was conducted in a peach orchard located in the municipality of Morro Redondo, RS, Brazil, where an experimental grid of 101 plants was established. In a trench dug beside each one of the 101 plants, soil samples were collected to determine silt, clay, and sand contents, soil density, total porosity, macroporosity, microporosity, and volumetric water content in the 0.00-0.10 and 0.10-0.20 m layers, as well as the depth of the A horizon. In each plant and in each year, the following properties were assessed: trunk diameter, fruit size and number of fruits per plant, average weight of the fruit per plant, fruit pulp firmness, Brix content, and yield from the orchard. Exploratory analysis of the data was undertaken by descriptive statistics, and the relationships between the physical properties of the soil and of the plant were assessed by canonical correlation analysis. The results showed that the clay and microporosity variables were those that exhibited the highest coefficients of canonical cross-loading with the plant properties in the soil layers assessed, and that the variable of mean weight of the fruit per plant was that which had the highest coefficients of canonical loading within the plant group for the two years assessed.

Multiple Geotechnological Tools Applied to Digital Mapping of Tropical Soils

ABSTRACT In recent years, geotechnologies as remote and proximal sensing and attributes derived from digital terrain elevation models indicated to be very useful for the description of soil variability. However, these information sources are rarely used together. Therefore, a methodology for assessing and specialize soil classes using the information obtained from remote/proximal sensing, GIS and technical knowledge has been applied and evaluated. Two areas of study, in the State of São Paulo, Brazil, totaling approximately 28.000 ha were used for this work. First, in an area (area 1), conventional pedological mapping was done and from the soil classes found patterns were obtained with the following information: a) spectral information (forms of features and absorption intensity of spectral curves with 350 wavelengths -2,500 nm) of soil samples collected at specific points in the area (according to each soil type); b) obtaining equations for determining chemical and physical properties of the soil from the relationship between the results obtained in the laboratory by the conventional method, the levels of chemical and physical attributes with the spectral data; c) supervised classification of Landsat TM 5 images, in order to detect changes in the size of the soil particles (soil texture); d) relationship between classes relief soils and attributes. Subsequently, the obtained patterns were applied in area 2 obtain pedological classification of soils, but in GIS (ArcGIS). Finally, we developed a conventional pedological mapping in area 2 to which was compared with a digital map, ie the one obtained only with pre certain standards. The proposed methodology had a 79 % accuracy in the first categorical level of Soil Classification System, 60 % accuracy in the second category level and became less useful in the categorical level 3 (37 % accuracy).