Classificação de padrões através de um comitê de máquinas aprimorado por aprendizagem por reforço

Reinforcement learning is a machine learning technique that, although finding a large number of applications, maybe is yet to reach its full potential. One of the inadequately tested possibilities is the use of reinforcement learning in combination with other methods for the solution of pattern classification problems. It is well documented in the literature the problems that support vector machine ensembles face in terms of generalization capacity. Algorithms such as Adaboost do not deal appropriately with the imbalances that arise in those situations. Several alternatives have been proposed, with varying degrees of success. This dissertation presents a new approach to building committees of support vector machines. The presented algorithm combines Adaboost algorithm with a layer of reinforcement learning to adjust committee parameters in order to avoid that imbalances on the committee components affect the generalization performance of the final hypothesis. Comparisons were made with ensembles using and not using the reinforcement learning layer, testing benchmark data sets widely known in area of pattern classification

Classificação Automática de Modulação Digital com uso de Correntropia para Ambientes de Rádio Cognitivo

Modern wireless systems employ adaptive techniques to provide high throughput while observing desired coverage, Quality of Service (QoS) and capacity. An alternative to further enhance data rate is to apply cognitive radio concepts, where a system is able to exploit unused spectrum on existing licensed bands by sensing the spectrum and opportunistically access unused portions. Techniques like Automatic Modulation Classification (AMC) could help or be vital for such scenarios. Usually, AMC implementations rely on some form of signal pre-processing, which may introduce a high computational cost or make assumptions about the received signal which may not hold (e.g. Gaussianity of noise). This work proposes a new method to perform AMC which uses a similarity measure from the Information Theoretic Learning (ITL) framework, known as correntropy coefficient. It is capable of extracting similarity measurements over a pair of random processes using higher order statistics, yielding in better similarity estimations than by using e.g. correlation coefficient. Experiments carried out by means of computer simulation show that the technique proposed in this paper presents a high rate success in classification of digital modulation, even in the presence of additive white gaussian noise (AWGN)

Algoritmos genéticos aplicados a um comitê de LS-SVM em problemas de classificação

The pattern classification is one of the machine learning subareas that has the most outstanding. Among the various approaches to solve pattern classification problems, the Support Vector Machines (SVM) receive great emphasis, due to its ease of use and good generalization performance. The Least Squares formulation of SVM (LS-SVM) finds the solution by solving a set of linear equations instead of quadratic programming implemented in SVM. The LS-SVMs provide some free parameters that have to be correctly chosen to achieve satisfactory results in a given task. Despite the LS-SVMs having high performance, lots of tools have been developed to improve them, mainly the development of new classifying methods and the employment of ensembles, in other words, a combination of several classifiers. In this work, our proposal is to use an ensemble and a Genetic Algorithm (GA), search algorithm based on the evolution of species, to enhance the LSSVM classification. In the construction of this ensemble, we use a random selection of attributes of the original problem, which it splits the original problem into smaller ones where each classifier will act. So, we apply a genetic algorithm to find effective values of the LS-SVM parameters and also to find a weight vector, measuring the importance of each machine in the final classification. Finally, the final classification is obtained by a linear combination of the decision values of the LS-SVMs with the weight vector. We used several classification problems, taken as benchmarks to evaluate the performance of the algorithm and compared the results with other classifiers

Medição da densidade óssea através de ondas eletromagnéticas e classificação por MVS

This work holds the purpose of presenting an auxiliary way of bone density measurement through the attenuation of electromagnetic waves. In order to do so, an arrangement of two microstrip antennas with rectangular configuration has been used, operating in a frequency of 2,49 GHz, and fed by a microstrip line on a substrate of fiberglass with permissiveness of 4.4 and height of 0,9 cm. Simulations were done with silica, bone meal, silica and gypsum blocks samples to prove the variation on the attenuation level of different combinations. Because of their good reproduction of the human beings anomaly aspects, samples of bovine bone were used. They were subjected to weighing, measurement and microwave radiation. The samples had their masses altered after mischaracterization and the process was repeated. The obtained data were inserted in a neural network and its training was proceeded with the best results gathered by correct classification on 100% of the samples. It comes to the conclusion that through only one non-ionizing wave in the 2,49 GHz zone it is possible to evaluate the attenuation level in the bone tissue, and that with the appliance of neural network fed with obtained characteristics in the experiment it is possible to classify a sample as having low or high bone density

Arquiteturas eficientes para sensoriamento espectral e classificação automática de modulações usando características cicloestacionárias

The increasing demand for high performance wireless communication systems has shown the inefficiency of the current model of fixed allocation of the radio spectrum. In this context, cognitive radio appears as a more efficient alternative, by providing opportunistic spectrum access, with the maximum bandwidth possible. To ensure these requirements, it is necessary that the transmitter identify opportunities for transmission and the receiver recognizes the parameters defined for the communication signal. The techniques that use cyclostationary analysis can be applied to problems in either spectrum sensing and modulation classification, even in low signal-to-noise ratio (SNR) environments. However, despite the robustness, one of the main disadvantages of cyclostationarity is the high computational cost for calculating its functions. This work proposes efficient architectures for obtaining cyclostationary features to be employed in either spectrum sensing and automatic modulation classification (AMC). In the context of spectrum sensing, a parallelized algorithm for extracting cyclostationary features of communication signals is presented. The performance of this features extractor parallelization is evaluated by speedup and parallel eficiency metrics. The architecture for spectrum sensing is analyzed for several configuration of false alarm probability, SNR levels and observation time for BPSK and QPSK modulations. In the context of AMC, the reduced alpha-profile is proposed as as a cyclostationary signature calculated for a reduced cyclic frequencies set. This signature is validated by a modulation classification architecture based on pattern matching. The architecture for AMC is investigated for correct classification rates of AM, BPSK, QPSK, MSK and FSK modulations, considering several scenarios of observation length and SNR levels. The numerical results of performance obtained in this work show the eficiency of the proposed architectures

Produção de enzimas por fungos em fermentação semi-sólida utilizando bagaço de coco e pedúnculo de caju como substratos

The production of enzymes by microorganisms using organic residues is important and it can be associated with several applications such as food and chemical industries and so on. The objective of this work is the production of CMCase, Xylanase, Avicelase and FPase enzymes by solid state fermentation (SSF) using as substrates: bagasse of coconut and dried cashew stem. The microorganisms employed are Penicillium chrysogenum and an isolated fungus from the coconut bark (Aspergillus fumigatus). Through the factorial design methodology and response surface analysis it was possible to study the influence of the humidity and pH. For Penicillium chrysogenum and the isolated fungus, the coconut bagasse was used as culture medium. In another fermentation, it was used the mixture of coconut bagasse and cashew stem. Fermentations were conducted using only the coconut bagasse as substrate in cultures with Penicillium chrysogenum fungus and the isolated one. A mixture with 50% of coconut and 50% of cashew stem was employed only for Penicillium chrysogenum fungus, the cultivation conditions were: 120 hours at 30 °C in BOD, changing humidity and pH values. In order to check the influence of the variables: humidity and pH, a 2 2 factorial experimental design was developed, and then two factors with two levels for each factor and three repetitions at the central point. The levels of the independent variables used in ascending order (-1, 0, +1), to humidity, 66%, 70.5% and 75% and pH 3, 5 and 7, respectively. The software STATISTICA TM (version 7.0, StatSoft, Inc.) was used to calculate the main effects of the variables and their interactions. The response surface methodology was used to optimize the conditions of the SSF. A chemical and a physic-chemical characterization of the coconut bagasse have determined the composition of cellulose (%) = 39.09; Hemicellulose (%) = 23.80, Total Lignin (%) = 36.22 and Pectin (%) = 1.64. To the characterization of cashew stem, the values were cellulose (g) = 15.91 Hemicellulose (%) = 16.77, Total Lignin (%) = 30.04 and Pectin (%) = 15.24. The results indicate the potential of the materials as substrate for semisolid fermentation enzyme production. The two microorganisms used are presented as good producers of cellulases. The results showed the potential of the fungus in the production of CMCase enzyme, with a maximum of 0.282 UI/mL and the Avicelase enzyme the maximum value ranged from 0.018 to 0.020 UI/ mL, using only coconut bagasse as substrate. The Penicillium chrysogenum fungus has showed the best results for CMCase = 0.294 UI/mL, FPase = 0.058 UI/mL, Avicelase = 0.010 UI/mL and Xylanase = 0.644 UI/ mL enzyme, using coconut bagasse and cashew stem as substrates. The Penicllium chrysogenum fungus showed enzymatic activities using only the coconut as substrate for CMCase = 0.233 UI/mL, FPase = 0.031 to 0.032 UI/ mL, Avicelase = 0.018 to 0.020 UI/mL and Xylanase = 0.735 UI/ mL. Thus, it can be concluded that the used organisms and substrates have offered potential for enzyme production processes in a semi-solid cultivation

Estudo comportamental, hormonal e histopatológico de animais com perda de peso progressina (SEP) e da variável peso associada a uma nova classificação ontogenética em Callithrix jacchus

The use of non-human primates in scientific research has contributed significantly to the biomedical area and, in the case of Callithrix jacchus, has provided important evidence on physiological mechanisms that help explain its biology, making the species a valuable experimental model in different pathologies. However, raising non-human primates in captivity for long periods of time is accompanied by behavioral disorders and chronic diseases, as well as progressive weight loss in most of the animals. The Primatology Center of the Universidade Federal do Rio Grande do Norte (UFRN) has housed a colony of C. jacchus for nearly 30 years and during this period these animals have been weighed systematically to detect possible alterations in their clinical conditions. This procedure has generated a volume of data on the weight of animals at different age ranges. These data are of great importance in the study of this variable from different perspectives. Accordingly, this paper presents three studies using weight data collected over 15 years (1985-2000) as a way of verifying the health status and development of the animals. The first study produced the first article, which describes the histopathological findings of animals with probable diagnosis of permanent wasting marmoset syndrome (WMS). All the animals were carriers of trematode parasites (Platynosomum spp) and had obstruction in the hepatobiliary system; it is suggested that this agent is one of the etiological factors of the syndrome. In the second article, the analysis focused on comparing environmental profile and cortisol levels between the animals with normal weight curve evolution and those with WMS. We observed a marked decrease in locomotion, increased use of lower cage extracts and hypocortisolemia. The latter is likely associated to an adaptation of the mechanisms that make up the hypothalamus-hypophysis-adrenal axis, as observed in other mammals under conditions of chronic malnutrition. Finally, in the third study, the animals with weight alterations were excluded from the sample and, using computational tools (K-means and SOM) in a non-supervised way, we suggest found new ontogenetic development classes for C. jacchus. These were redimensioned from five to eight classes: infant I, infant II, infant III, juvenile I, juvenile II, sub-adult, young adult and elderly adult, in order to provide a more suitable classification for more detailed studies that require better control over the animal development

Publicação e avaliação de periódicos científicos: paradoxos da classificação Qualis em Psicologia

Recently, Brazilian scientific production has increased greatly, due to demands for productivity from scientific agencies. However, this high increases requires a more qualified production, since it s essential that publications are relevant and original. In the psychological field, the assessment scientific journals of the CAPES/ANPEPP Commission had a strong effect on the scientific community and raised questions about the chosen evaluation method. Considering this impact, the aim of this research is a meta-analysis on the assessment of Psychological journals by CAPES to update the Qualis database. For this research, Psychology scientific editors (38 questionnaires were applied by e-mail) were consulted, also 5 librarians who work with scientific journals assessment (semi-structured interviews) and 8 members who acted as referees in the CAPES/ANPEPP Commission (open questions were sent by e-mail). The results are shown through 3 analysis: general evaluation of the Qualis process (including the Assessment Committee constitution), evaluation criteria used in the process and the effect of the evaluation on the scientific community (changes on the editing scene included). Some important points emerged: disagreement among different actors about the suitability of this evaluation model; the recognition of the improvement of scientific journals, mainly toward normalization and diffusion; the verification that the model does not point the quality of the journal, i.e., the content of the scientific articles published in the journal; the disagreement with the criteria used, seemed necessary and useful but needed to be discussed and cleared between the scientific community. Despite these points, the scientific journals evaluation still is the main method to assure quality for Psychology publications

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Uso de confiabilidade na rotulação de exemplos em problemas de classificação multirrótulo com aprendizado semissupervisionado

The techniques of Machine Learning are applied in classification tasks to acquire knowledge through a set of data or information. Some learning methods proposed in literature are methods based on semissupervised learning; this is represented by small percentage of labeled data (supervised learning) combined with a quantity of label and non-labeled examples (unsupervised learning) during the training phase, which reduces, therefore, the need for a large quantity of labeled instances when only small dataset of labeled instances is available for training. A commom problem in semi-supervised learning is as random selection of instances, since most of paper use a random selection technique which can cause a negative impact. Much of machine learning methods treat single-label problems, in other words, problems where a given set of data are associated with a single class; however, through the requirement existent to classify data in a lot of domain, or more than one class, this classification as called multi-label classification. This work presents an experimental analysis of the results obtained using semissupervised learning in troubles of multi-label classification using reliability parameter as an aid in the classification data. Thus, the use of techniques of semissupervised learning and besides methods of multi-label classification, were essential to show the results

Dinâmica sazional de fungos micorrízicos arbusculares (Glomeromycota) em cerradão e brejo de altitude na Chapada do Araripe, CE

Arbuscular mycorrhizal fungi (AMF) are obligatory symbiotic organisms that associate with roots of a large number of plant taxa, and are found in all terrestrial ecosystems. These fungi promote greater tolerance to environmental stresses to associated plant, favoring the establishment of plant communities, especially where soil fertility is a limiting factor, as in the Caatinga, an exclusively Brazilian domain that has been focus of research due to its great biodiversity that can help clarify the history of vegetation in South America. Because of the ecological importance of AMF, the limited number of jobs and the potential diversity of the Caatinga, this work aims to inventory the diversity and determine AMF communities in areas with different faces occurrent in FLONA Araripe, Ceará (CE). The sample collection occurred in four periods at the beginning and end of the dry season (August and December 2011, respectively) and rainy (February and June 2012, respectively) in an area of marsh and woodland altitude of the Araripe, Crato, CE. The glomerosporos were extracted by wet sieving and centrifugation in water and sucrose (50%) mounted between slide and coverslip using PVLG and PVLG + Reagent Melzer. In total, we found 46 species of AMF distributed in eight families and 16 genera: Acaulospora (6), Ambispora (1), Cetraspora (2), Dentiscutata (5), Fuscutata (2), Gigaspora (6), Glomus (13) Intraornatospora (1), Kuklospora (1), Orbispora (1), Paradentiscutata (1), Quatunica (1), Racocetra (1), Scutellospora (2), Septoglomus (2) and a new genus. analysis showed that ecological each area of study has its own seasonal dynamics, with an area of woodland with a greater diversity of species throughout the year, while the marsh elevation showed greater variation in species found among the collection periods, showing that vegetation and rainfall has strong influence on the seasonal dynamics of AMF, as well as the availability of nutrients and soil pH so

Fungos gasteroides (Basidiomycota, Agaricomycetes) de três áreas de semiárido no Estado do Ceará, Brasil

Gasteroid fungi include several distinct lineages of basidiomycetes that were grouped by presenting some striking features in common like angiocarpic development and passive release of basidiospores. For a long period these fungi were accomodate in Gasteromycetes class. However, biochemistry and molecular studies showed the polyphyly of this group and curriently this class lies devoid of taxonomic value. These organisms influence the ecology of the various biomes, however, are poorly studied and knowledge of their diversity in neotropical ecosystems remains insufficient, despite studies that have been developed in recent years. The Brazilian semiarid region has many areas with an unexplored mycobiota. Ceará State has many areas of extreme biological importance and for this study three protected areas were chosen: Área de Proteção Ambiental da Serra da Ibiapaba, Parque Nacional de Ubajara and Área de Proteção Ambiental de Baturité. Therefore, the aim of this study was to inventory gasteroid fungi ocorring in these three areas in the semiarid region of Ceará. The expeditions, herborization and analysis of specimes were based in traditional methodology used to identify gasteroid fungi. Were identified 16 species belong to 5 families: Agaricaceae, Clathraceae, Geastraceae, Nidulariceae and Phallaceae. Morganella nuda Alfredo & Baseia is recorded for the second time in the world, Blumenavia angolensis (Welw. & Curr) Dring and Mutinus elegans (Mont.) E. Fisch. corresponds to a first record in the Brazilian Northeastern. Except for Abrachium floriforme (Baseia & Calonge) Baseia & T.S. Cabral and Geastrum lloydianum Rick, all remaining species are new records for Ceará, increasing the list of gasteroid fungi in the region of 3 for 17 species. Identified species were deposited in the collection of the Herbarium of Universidade Federal do Rio Grande do Norte. Although these areas have proved conducive to the study of gasteroid fungi, more efforts are still needed to increase knowledge of these fungi in the region

Investigando a combinação de técnicas de aprendizado semissupervisionado e classificação hierárquica multirrótulo

Data classification is a task with high applicability in a lot of areas. Most methods for treating classification problems found in the literature dealing with single-label or traditional problems. In recent years has been identified a series of classification tasks in which the samples can be labeled at more than one class simultaneously (multi-label classification). Additionally, these classes can be hierarchically organized (hierarchical classification and hierarchical multi-label classification). On the other hand, we have also studied a new category of learning, called semi-supervised learning, combining labeled data (supervised learning) and non-labeled data (unsupervised learning) during the training phase, thus reducing the need for a large amount of labeled data when only a small set of labeled samples is available. Thus, since both the techniques of multi-label and hierarchical multi-label classification as semi-supervised learning has shown favorable results with its use, this work is proposed and used to apply semi-supervised learning in hierarchical multi-label classication tasks, so eciently take advantage of the main advantages of the two areas. An experimental analysis of the proposed methods found that the use of semi-supervised learning in hierarchical multi-label methods presented satisfactory results, since the two approaches were statistically similar results

Proposição e aplicação de um core set da classificação internacional de funcionalidade, incapacidade e saúde (CIF) para saúde física de idosos

Para aumentar a viabilidade do uso da Classificação Internacional de Funcionalidade, Incapacidade e Saúde (CIF), core sets começaram a ser desenvolvidos, e objetivam estabelecer uma seleção de categorias adaptada para representar os padrões de avaliação multiprofissional de grupos específicos de pacientes. Com o objetivo de propor um core set da CIF para classificar a saúde física de idosos, formou-se uma comissão de especialistas para julgar o instrumento por meio da técnica Delphi, o que mostra a interface multidisciplinar do projeto. Finalizada a participação da comissão, o core set foi proposto contendo 30 categorias. Após aplicação em uma amostra com 340 idosos dos municípios de Natal/RN e Santa Cruz/RN, o core set foi submetido à análise fatorial, tendo ficado com 19 categorias. A análise ainda proporcionou gerar uma pontuação para cada idoso por meio do escore fatorial, tendo provado ser uma forma fidedigna e confiável de se pontuar um core set.

Técnica para segmentação automática de imagens microscópicas de componentes sanguíneos e classificação diferencial de leucócitos baseada em lógica fuzzy

Automatic detection of blood components is an important topic in the field of hematology. The segmentation is an important stage because it allows components to be grouped into common areas and processed separately and leukocyte differential classification enables them to be analyzed separately. With the auto-segmentation and differential classification, this work is contributing to the analysis process of blood components by providing tools that reduce the manual labor and increasing its accuracy and efficiency. Using techniques of digital image processing associated with a generic and automatic fuzzy approach, this work proposes two Fuzzy Inference Systems, defined as I and II, for autosegmentation of blood components and leukocyte differential classification, respectively, in microscopic images smears. Using the Fuzzy Inference System I, the proposed technique performs the segmentation of the image in four regions: the leukocyte’s nucleus and cytoplasm, erythrocyte and plasma area and using the Fuzzy Inference System II and the segmented leukocyte (nucleus and cytoplasm) classify them differentially in five types: basophils, eosinophils, lymphocytes, monocytes and neutrophils. Were used for testing 530 images containing microscopic samples of blood smears with different methods. The images were processed and its accuracy indices and Gold Standards were calculated and compared with the manual results and other results found at literature for the same problems. Regarding segmentation, a technique developed showed percentages of accuracy of 97.31% for leukocytes, 95.39% to erythrocytes and 95.06% for blood plasma. As for the differential classification, the percentage varied between 92.98% and 98.39% for the different leukocyte types. In addition to promoting auto-segmentation and differential classification, the proposed technique also contributes to the definition of new descriptors and the construction of an image database using various processes hematological staining