Emprego de redes neurais artificiais supervisionadas e não supervisionadas no estudo de parâmetros reológicos de excipientes farmacêuticos sólidos

In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Organização temática da doutrina jurídica: elementos metodológicos para uma proposta de extensão da classificação decimal de direito

Specificity and updating of the bibliographic classification systems can be considered a determinant factor to the quality of organization and representation of the legal documentation. In the specific case of Brazil, the Brazilian Law Decimal Classification, does not foresee specific subdivisions for Labor Law procedures. In this sense, it carries out a terminological work based on table of contents of doctrinal Labor Law books of the mentioned area, which are compared to the conceptual structure of the Brazilian Law Decimal Classification. As a result, it presents an extension proposal for Labor Procedures as well as a methodological background for further extensions and updates.

Leaf anatomy as a contribution to the taxonomy of Salacioideae N.Hall, ex Thorne & Reveal (Celastraceae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mapeamento do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing ana geoprocessmg allow detection, spatial representation and quantification of the alterations caused by the human action on the nature, contributing to the monitoring and planning of those activities that may cause damages to the environment. This study apply methodologies based on digital processing of orbital images for the mapping of the land use, vegetation and anthropic activities that cause impacts in the environment. It was considered a test area in the district of Assistência and surroundings, in Rio Claro (SP) region. The methodology proposed was checked through the crossing of maps in the software GIS - Idrisi. These maps either obtained with conventional interpretation of aerial photos of 1995, digitized in the software CAD Overlay and geo-referenced in the AutoCAD Map, or with the application of digital classification systems on SPOT-XS and PAN orbital images of 1995, followed by field observations. The crossing of conventional and digital maps of a same area with the CIS allows to verify the overall results obtained through the computational handling of orbital images. With the use of digital processing techniques, specially multiespectral classification, it is possible to detect automatically and visually the impacts related to the mineral extraction, as well as to survey the land use, vegetation and environmental impacts.

Conceito e classificação da dormência em sementes

Despite being known to science for quite a long time, the phenomenon of seed dormancy still baffles the scientific community for the multiple complex underlying mechanisms. The current classification systems of seed dormancy attempt to condense all that is known about the phenomenon in an attempt to generate a conceptual database that would enable facilitated interpretation of upcoming information and allow for a better contextuation of research in this field. The present paper is a preliminary overview of the current panorama of concepts and classification systems of seed dormancy that intends to serve as a standpoint for future research in this field.

Optimum-Path Forest pruning parameter estimation through Harmony Search

Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.

Histomorphometrical and molecular evaluation of endosseous dental implants sites in humans: Correlation with clinical and radiographic aspects

Objective: To evaluate the correlations between clinical-radiographical aspects and histomorphometric-molecular parameters of endosseous dental implant sites in humans. Material and methods: The study sample consisted of bone implant sites from the jawbones of 32 volunteers, which were classified according to two different systems: (1) based only on periapical and panoramic images (PP); (2) as proposed by Lekholm & Zarb (L&Z). Bone biopsies were removed using trephine during the first drilling for implant placement. Samples were stained with haematoxylin-eosin (HE), and histomorphometric analysis was performed to obtain the following parameters: trabecular thickness (Tb.Th), trabecular number, bone volume density (BV/TV), bone specific surface (BS/BV), bone surface density and trabecular separation (Tb.Sp). In addition, immunohistochemistry analysis was performed on bone tissue samples for the proteins, Receptor activator of nuclear factor kappa-B (RANK), RANK ligand (RANKL), osteoprotegerin (OPG) and Osteocalcin (OC). Also, the determination of the relative levels of gene expression was performed using Reverse transcription-real-time Polymerase Chain Reaction (RT-PCR). Results: PP and L&Z classification systems revealed a moderate correlation with BV/TV, BS/BV, Tb.Th and Tb.Sp. L&Z's system identified differences among bone types when BV/TV, BS/BV, Tb.Th and Tb.Sp were compared. A weak correlation between PP/L&Z classifications and the expression of bone metabolism regulators (RANK, RANKL, OPG e OC) was found. The analysis of mRNA expression showed no difference between the bone types evaluated. Conclusions: Our results suggest that PP and L&Z subjective bone-type classification systems are related to histomorphometric aspects. These data may contribute to the validation of these classifications. Bone remodelling regulatory molecules do not seem to influence morphological aspects of the jawbone © 2011 John Wiley & Sons A/S.

An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

Estabelecimento de um índice de sensibilidade ambiental ao óleo em ambientes fluviais, com o suporte da ferramenta MORPH

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de recursos trabalhistas: uma análise crítica da classificação decimal de direito com vistas a uma proposta metodológica de extensão

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação oficial e extra-oficial: raça e cor em debate

Este artigo busca propiciar um quadro histórico e teórico síntese sobre como a categoria cor se tornou o aspecto privilegiado da percepção da diferença entre os grupos sociais brasileiros, assim como o discurso científico e o senso comum para expressá-la no país. Nesse sentido, procura-se entender como esta categoria foi utilizada para fornecer alguns limites e possibilidades para as idéias de nação e de cidadania no Brasil, a partir dos sistemas de classificação oficial e extra-oficial, no período de 1870 até 1990.

Teoria da classificação e ontologias: em busca do diálogo necessário

The theory of classification must be committed to new approaches such as ontologies and collaborative classification. Therefore, it was conducted a research of exploratory and reflective aspects, in order to increase the understanding of the phenomenon and to get a greater familiarity with the problem, looking for its more precise delimitation. The reflection shows that it is still necessary to invest in the dialogical approach of knowledge organization tools and that it is necessary to rethink the studies on classification in the context of digital technologies, especially ontologies, which have aspects of derivation, though not always declared, from classification systems.

Mapeando o conhecimento em sistemas de classificação de bibliotecas

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the “10 Pillars of Knowledge: Map of Human Knowledge”, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Bias in the indexing languages Theorethical approaches about feminine issues

The process of knowledge representation as well as its procedures or tools and its products are not neutral in terms of values; instead they imply moral values. In this context, bias in representation related to prejudice and discrimination, to gender issues, to dicotomic categorization in classification systems or in thesauri and to lack of cultural warrant may arise. Concerning the problem of bias in indexing languages, starting from the initial theoretical reflexions of Brey (1999), Berman (1993), Olson (1998; 2002), Lopez-Huertas Perez & Torres Ramirez (2005), Guimaraes (2006), Hjorland (2008) and Milani et al. (2009), the proposal is to present a preliminary categorization aiming at facilitating the identification of bias concerning feminine issues in indexing languages, to offer a contribution to the theoretical universe of the specific questions of knowledge organization and to present a theme to be discussed by educators and professionals in the areas of cataloging, classification and indexing. If in a society which intends to be politically correct, social attitudes towards stigmatized citizens should be modified, then, the universe of indexing languages, taken as tools of knowledge representation, is a fertile field to sow this reflexion.