Seleção seqüencial de descritores por análise da semântica para recuperação de imagens baseada no conteúdo

With the rapid growth of databases of various types (text, multimedia, etc..), There exist a need to propose methods for ordering, access and retrieve data in a simple and fast way. The images databases, in addition to these needs, require a representation of the images so that the semantic content characteristics are considered. Accordingly, several proposals such as the textual annotations based retrieval has been made. In the annotations approach, the recovery is based on the comparison between the textual description that a user can make of images and descriptions of the images stored in database. Among its drawbacks, it is noted that the textual description is very dependent on the observer, in addition to the computational effort required to describe all the images in database. Another approach is the content based image retrieval - CBIR, where each image is represented by low-level features such as: color, shape, texture, etc. In this sense, the results in the area of CBIR has been very promising. However, the representation of the images semantic by low-level features is an open problem. New algorithms for the extraction of features as well as new methods of indexing have been proposed in the literature. However, these algorithms become increasingly complex. So, doing an analysis, it is natural to ask whether there is a relationship between semantics and low-level features extracted in an image? and if there is a relationship, which descriptors better represent the semantic? which leads us to a new question: how to use descriptors to represent the content of the images?. The work presented in this thesis, proposes a method to analyze the relationship between low-level descriptors and semantics in an attempt to answer the questions before. Still, it was observed that there are three possibilities of indexing images: Using composed characteristic vectors, using parallel and independent index structures (for each descriptor or set of them) and using characteristic vectors sorted in sequential order. Thus, the first two forms have been widely studied and applied in literature, but there were no records of the third way has even been explored. So this thesis also proposes to index using a sequential structure of descriptors and also the order of these descriptors should be based on the relationship that exists between each descriptor and semantics of the users. Finally, the proposed index in this thesis revealed better than the traditional approachs and yet, was showed experimentally that the order in this sequence is important and there is a direct relationship between this order and the relationship of low-level descriptors with the semantics of the users

Linguagens documentárias

BOIASKI, Daniela ; GUIPSON, Larissa; MARTINS, Silvestre Gomes; MARIA, Taíse ; VANTI, Nadia. Linguagens documentárias. In: SEMINÁRIO DE PESQUISA DO CENTRO DE CIÊNCIAS SOCIAIS APLICADA,15., 2009, Natal. Anais Eletrônico...Natal: CCSA, 2009.

Diagnóstico, estadiamento e tratamento cirúrgico do adenocarcinoma de pâncreas

O adenocarcinoma pancreático é um dos tumores sólidos de pior prognóstico, sendo o tratamento cirúrgico o único potencialmente curativo. Na grande maioria dos pacientes o tumor é diagnosticado em fase avançada, comumente na presença de doença metastática. A introdução de modernos métodos diagnósticos associados ao aperfeiçoamento dos já existentes tem gerado controvérsia quanto à melhor maneira de se estabelecer o diagnóstico e estadiamento do tumor. Da mesma forma, o papel da cirurgia na paliação e aspectos técnicos da ressecção de lesões localizadas estão longe de alcançarem consenso na prática. Método - Revisão da literatura sobre os aspectos controversos relacionados ao tema e um algoritmo para a abordagem dos pacientes com suspeita de tumor de pâncreas são apresentados. Foram utilizados os descritores: “adenocarcinoma” e “pâncreas” para pesquisa no PubMed (www.pubmed.com) e na Bireme (www.bireme.br) e a seguir selecionadas as publicações pertinentes a cada tópico escolhido com atenção especial para metanálises, estudos clínicos controlados, revisões sitemáticas e ainda publicações de grandes centros especializados em doenças pancreáticas. Conclusões - Na suspeita de adenocarcinoma de pâncreas é possível realizar estadiamento muito próximo do real sem a necessidade da exploração cirúrgica sistemática em virtude da disponibilidade na prática de exames modernos e eficientes. Isso permite que paliação menos invasiva seja praticada na maioria dos pacientes com lesões avançadas e incuráveis. Nos em que a cura é possível, a operação deve ser realizada objetivando-se, essencialmente, a remoção da lesão com margens livres e com aceitáveis índices de morbi-mortalidade

Integridade da pele em idosos: revisão da literatura segundo as cartas de promoção da saúde

Trata-se de uma revisão bibliográfica que objetivou relacionar as medidas educativas para a promoção da integridade da pele em idosos com as Cartas de Promoção da Saúde. Realizou-se a busca nas bases de dados CINAHL, SCOPUS, LILACS e COCHRANE, nos portais CAPES e BVS e na biblioteca PUBMED, mediante a aplicação dos descritores Health Education; Skin e Aged. Os resultados dos 7 artigos analisados apontaram como principais medidas educativas: inspeção diária da pele, cuidados com calçados e com os pés, uso regular de protetor solar e mudanças de decúbito. Essas medidas estavam relacionadas com as seguintes Cartas de Promoção da Saúde: Ottawa, Declaração de Santafé de Bogotá e Declaração de Jacarta. Conclui-se que as medidas educativas, baseadas nas Cartas, são de grande relevância para a criação de uma cultura de saúde, com enfoque na população e no indivíduo como agentes executores imprescindíveis para o alcance da promoção da saúde

Morbimortalidade perinatal associada à infecção clamidiana: uma revisão sistemática

Universidade Federal do Rio Grande do Norte

Comparação da incidência de câncer em infectados pelo HIV e em transplantados com a população geral

Introdução: Estudos demonstram uma relação entre a queda da imunidade e o aumento da incidência de câncer. Objetivo: Comparar a incidência de câncer em pacientes infectados pelo HIV e em transplantados com a da população geral. Métodos: Foi realizada revisão sistemática com metanálise, combinando descritores específicos nas bases de dados Pubmed, Scielo, Cancerlit e Google Scholar, buscando alta sensibilidade para responder o objetivo da pesquisa. Os artigos considerados de alta qualidade metodológica por apresentarem todos os critérios de inclusão foram avaliados por metanálise. Resultados: Foram incluídos 25 estudos envolvendo 866776 pessoas com HIV/AIDS e transplantados, em que foram diagnosticados 21260 novos casos de carcinoma. Observou-se que o risco para o surgimento de novos casos de câncer foi maior entre indivíduos com HIV/AIDS (SIR= 4, IC95% 3,78-4,24) e entre os transplantados (SIR= 3,28, IC95% 3,06-3,52) quando comparado com a população em geral. Conclusão: A incidência similar em ambas as populações pesquisadas sugere que o comprometimento do sistema imune, comum em ambas, é responsável pelo risco aumentado de novos casos de câncer. Investimentos em pesquisas que desenvolvam estratégias de prevenção mais eficazes para os dois grupos são necessários, pois podem contribuir para a redução da incidência e para a diminuição da mortalidade.

Qualidade de vida do servidor da Universidade Federal do Rio Grande do Norte em condição crônica de saúde

The study aimed to analyze the influence of chronic health conditions (CHC) on quality of life (QOL) of UFRN servers assaulted by CHC. It is a descriptive and cross-sectional study with prospective data and quantitative approach, accomplished in the ambulatory clinic of the Department of Server Assistance (DSA) of the Pro-Rectory of Human Resources, during three months. The sample was composed by accessibility, totaling 215 people, being 153 active and 62 inactive servers, in chronic health condition. The data were collected through the application of the sociodemographic characterization, health, environmental and laboral form, the Medical Outcome Study 36-Item Short Form (SF-36). The study was evaluated by the HUOL Ethics Committee (CAAE no. 0046.0.294.000.10), obtaining assent. The results were analyzed in the SPSS 15.0 program through the descriptive and inferential statistics. It was identified servants predominantly male (59,1%), under 60 years old, married or in stable union, Catholics, brown color, living in the capital and residents in own home. Regarding labor issues, there was a predominance of active servers technical-administrative with intermediate and medium level positions and small proportion of docents. Among the CHC, the non-communicable diseases - NCDs (95.8%) had a higher frequency, followed by persistent mental disorders - PMDs (18.6%) and, finally, the continuous and structural physical deficiency - CSPD (16.9 %). The QOL of servers was considered good, with a mean score of 72.5 points in the total score, with the most affected domains: physical (59.1), general health (66.2), bodily pain (66.3) and functional aspects (72.0). The mental health dimension (76.5) had a better average than the physical dimension (68.0 points). It was found that the decrease in QOL scores is significant statistically related to higher number of CHC (ρ <0.001), with no statistical significance regarding the functional situation (p = 0.259). The administrative technicians of elementary, primary, secondary levels and docents had the worst QOL scores. After the correlation analysis of CHC with the domains and dimensions of the SF-36, there was statistically significant, negative and weak correlation of the domains: functional aspect (ρ = 0.002, r = -0.207), physical aspects (ρ = 0.007; r = -0.183), vitality (ρ = 0.002, r = -0.213), social function (ρ = 0.000, r = -0.313), emotional aspects (ρ = 0.000, r = -0.293), mental health (ρ = 0.000 , r = -0.238), physical health dimension (ρ = 0.002, r = -0.210) and mental health dimension (ρ = 0.000, r = -0.298). The presence of PMD isolated or together, contributed to a lower SF-36 scores, being the domains variation of mean significant, except for bodily pain, general health and physical aspects. By correlating the categories of CHC and QOL, there was a weak correlation (r ≤ -0.376) and significant (ρ ≤ 0.011), mainly related to the NCD, PMDs and NCD + PMD, affecting the mental health, social function, emotional aspects, vitality and functional aspect domains. Front of the results, it was concludes that the servers quality of life is influenced by the CHC. Thus, it was inferred that the presence of CHC causes a negative effect on quality of life, leading the active and inactive servers to exposure their overall life activities and work over the years, due to the morbidity affected, mainly related to NCDs and PMDs. Descriptors: Quality of life. Chronic disease. Occupational Health. Nursing

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

A Proficiência escritora em matemática trabalhada nos livros didáticos dos 4º e 5º anos do ensino fundamental

Universidade Federal do Rio Grande do Norte

Avaliação da dor pós-operatória: análise em pacientes submetidos a cirurgias abdominais em um hospital universitário de Natal/RN

It is an exploratory and descriptive study made by a quantitative approach, developed among February and May 2010, aiming to assess the pain of patients underwent abdominal surgeries in a University Hospital, in Natal/RN; to identify the local and intensity of the pain based on Numerical Estimative Scale; to analyze the pain related to the sensorial-discriminative, motivational-affective and cognitive-assessment dimensions, using the McGill Questionnaire pain; to establish a relation between the pain process and age, gender, religion, and king of surgery; to identify the medicines efficiency used to control postoperative pain. The sample was composed by 253 patients underwent abdominal surgeries. The results showed a total of 63.63% females between 38 and 47 years of age (21.34%); illiterates (21.73%); married (64.03%), living in Natal and surroundings (67.97%) and Catholics (74.30%). In their first assessment, 84.19% showed postoperative pain; the pain was considered light in 18.97% of them, moderate in 21.74% and severe in 43.48%. The mean number of descriptors chosen through the McGill Questionnaire Pain was 10.78 (DP= 6.09) and pain rating 23.65 (DP= 15.93). The descriptors selected with higher frequency were: sickening pain (69.01%), tired (65.25%), thin (62.44%), bored (58.69%), ardor (46.48%), pointed (38.50%) and colic (35.21%). In their second assessment, 57.71% of patients didn t relate any postoperative pain and 42.29% were still complaining about the pain. After taking analgesic medication, just 41.90% of patients who had complete pain relief. The Pharmacological groups most used were: simple analgesic (37.86%), weak opioids (32.98%), AINES (19.85%) and strong opioid (9.31%). It was not found a significant postoperative pain variation related to the sexes, religion and kind of surgery. It was concluded there were a high level in the number of patients with postoperative pain, mainly in a severe scale. Less than half of patients had the pain relief. Then, it was observed there was not coherence between the pain intensity and the analgesic it was used. To solve or relieve this kind of problems is necessary a permanent education to the health professionals who works in this area

Análise e classificação de imagens de lesões da pele por atributos de cor, forma e textura utilizando máquina de vetor de suporte

The skin cancer is the most common of all cancers and the increase of its incidence must, in part, caused by the behavior of the people in relation to the exposition to the sun. In Brazil, the non-melanoma skin cancer is the most incident in the majority of the regions. The dermatoscopy and videodermatoscopy are the main types of examinations for the diagnosis of dermatological illnesses of the skin. The field that involves the use of computational tools to help or follow medical diagnosis in dermatological injuries is seen as very recent. Some methods had been proposed for automatic classification of pathology of the skin using images. The present work has the objective to present a new intelligent methodology for analysis and classification of skin cancer images, based on the techniques of digital processing of images for extraction of color characteristics, forms and texture, using Wavelet Packet Transform (WPT) and learning techniques called Support Vector Machine (SVM). The Wavelet Packet Transform is applied for extraction of texture characteristics in the images. The WPT consists of a set of base functions that represents the image in different bands of frequency, each one with distinct resolutions corresponding to each scale. Moreover, the characteristics of color of the injury are also computed that are dependants of a visual context, influenced for the existing colors in its surround, and the attributes of form through the Fourier describers. The Support Vector Machine is used for the classification task, which is based on the minimization principles of the structural risk, coming from the statistical learning theory. The SVM has the objective to construct optimum hyperplanes that represent the separation between classes. The generated hyperplane is determined by a subset of the classes, called support vectors. For the used database in this work, the results had revealed a good performance getting a global rightness of 92,73% for melanoma, and 86% for non-melanoma and benign injuries. The extracted describers and the SVM classifier became a method capable to recognize and to classify the analyzed skin injuries

Classificação de distúrbios na rede elétrica usando redes neurais e wavelets

Post dispatch analysis of signals obtained from digital disturbances registers provide important information to identify and classify disturbances in systems, looking for a more efficient management of the supply. In order to enhance the task of identifying and classifying the disturbances - providing an automatic assessment - techniques of digital signal processing can be helpful. The Wavelet Transform has become a very efficient tool for the analysis of voltage or current signals, obtained immediately after disturbance s occurrences in the network. This work presents a methodology based on the Discrete Wavelet Transform to implement this process. It uses a comparison between distribution curves of signals energy, with and without disturbance. This is done for different resolution levels of its decomposition in order to obtain descriptors that permit its classification, using artificial neural networks

Reconhecimento de voz através de unidades menores do que a palavra, utilizando Wavelet Packet e SVM, em uma nova estrutura hierárquica de decisão

The automatic speech recognition by machine has been the target of researchers in the past five decades. In this period have been numerous advances, such as in the field of recognition of isolated words (commands), which has very high rates of recognition, currently. However, we are still far from developing a system that could have a performance similar to the human being (automatic continuous speech recognition). One of the great challenges of searches for continuous speech recognition is the large amount of pattern. The modern languages such as English, French, Spanish and Portuguese have approximately 500,000 words or patterns to be identified. The purpose of this study is to use smaller units than the word such as phonemes, syllables and difones units as the basis for the speech recognition, aiming to recognize any words without necessarily using them. The main goal is to reduce the restriction imposed by the excessive amount of patterns. In order to validate this proposal, the system was tested in the isolated word recognition in dependent-case. The phonemes characteristics of the Brazil s Portuguese language were used to developed the hierarchy decision system. These decisions are made through the use of neural networks SVM (Support Vector Machines). The main speech features used were obtained from the Wavelet Packet Transform. The descriptors MFCC (Mel-Frequency Cepstral Coefficient) are also used in this work. It was concluded that the method proposed in this work, showed good results in the steps of recognition of vowels, consonants (syllables) and words when compared with other existing methods in literature

Detecção e classificação de modos de operação do bombeio mecânico via cartas dinamométricas

The precision and the fast identification of abnormalities of bottom hole are essential to prevent damage and increase production in the oil industry. This work presents a study about a new automatic approach to the detection and the classification of operation mode in the Sucker-rod Pumping through dynamometric cards of bottom hole. The main idea is the recognition of the well production status through the image processing of the bottom s hole dynamometric card (Boundary Descriptors) and statistics and similarity mathematics tools, like Fourier Descriptor, Principal Components Analysis (PCA) and Euclidean Distance. In order to validate the proposal, the Sucker-Rod Pumping system real data are used

Sistema inteligente para detecção de vazamentos em dutos de petróleo usando transformada Wavelet e redes neurais

This work consists in the use of techniques of signals processing and artificial neural networks to identify leaks in pipes with multiphase flow. In the traditional methods of leak detection exists a great difficulty to mount a profile, that is adjusted to the found in real conditions of the oil transport. These difficult conditions go since the unevenly soil that cause columns or vacuum throughout pipelines until the presence of multiphases like water, gas and oil; plus other components as sand, which use to produce discontinuous flow off and diverse variations. To attenuate these difficulties, the transform wavelet was used to map the signal pressure in different resolution plan allowing the extraction of descriptors that identify leaks patterns and with then to provide training for the neural network to learning of how to classify this pattern and report whenever this characterize leaks. During the tests were used transient and regime signals and pipelines with punctures with size variations from ½' to 1' of diameter to simulate leaks and between Upanema and Estreito B, of the UN-RNCE of the Petrobras, where it was possible to detect leaks. The results show that the proposed descriptors considered, based in statistical methods applied in domain transform, are sufficient to identify leaks patterns and make it possible to train the neural classifier to indicate the occurrence of pipeline leaks