Motivação para amamentação em função da escolaridade materna

Enquadramento: Atualmente a prevalência da amamentação à saída da maternidade é elevada, no entanto não temos valores semelhantes quanto ao aleitamento materno exclusivo, nem no seu prolongamento até aos dois anos. Objetivos: Verificar as relações entre a motivação das puérperas para a amamentação e variáveis sociodemográficas e obstétricas e analisar a influência das variáveis sociodemográficas e obstétricas na motivação para a amamentação quando mediadas pela escolaridade da puérpera. Material e métodos: Estudo não experimental, quantitativo, descritivo correlacional e analítico. O tipo de amostragem é não probabilístico por conveniência. O instrumento de colheita de dados foi o questionário, aplicado a 479 puérperas (média de idade 30,56 anos) no dia da alta hospitalar. O questionário permitiu fazer a caracterização da amostra em termos sociodemográficos e obstétricos. Foi ainda utilizada a escala de Motivação para Amamentação de Nelas, Ferreira & Duarte (2008). Resultados: Os resultados obtidos revelam que 86,6% são casadas ou vivem em união de fato e pertencem a uma família nuclear (89,1%). Na amostra, 59,5% tem o Ensino Superior e 73.9% encontra-se empregada e 55,3% reside em meio urbano. A maioria (43,0%), esteve grávida só uma vez e 34.4% já tinha tido uma gestação anterior. São mães pela primeira vez 48,0%, 79,3% realizou seis ou mais consultas tal como o preconizado, e 92,4% planeou a gravidez. A maioria dos partos foi de termo (68,4%). A quase totalidade (9 em cada 10) revela elevada motivação para amamentar. A idade, o estado civil, a residência e as habilitações literárias não influenciam a motivação geral para a amamentação As puérperas desempregadas são as mais motivadas. As puérperas mais motivadas tiveram duas ou mais gestações, e são multíparas. Não foi provada a relação entre as outras variáveis obstétricas e a motivação para a amamentação. A variável mediadora apenas teve impacto com o local de residência, onde as participantes residentes em meio urbano e com ensino superior são as mais motivadas na dimensão fisiológica, seguidas das residentes em meio urbano e com habilitações literárias até ao ensino secundário. Conclusões: Sugerimos a criação de um grupo de trabalho com atuação na comunidade escolar para capacitar os jovens sobre a importância do aleitamento materno, recriando uma 8 cultura de amamentação assente nas orientações emanadas na política de aleitamento materno dos Hospitais amigos dos bebés. Palavras-chave: Amamentação, Motivação, Escolaridade.

Detecção de região saliente em imagens usando dissimilaridade de cor e amostragem por pixeis aleatórios

The purpose of this work is to demonstrate and to assess a simple algorithm for automatic estimation of the most salient region in an image, that have possible application in computer vision. The algorithm uses the connection between color dissimilarities in the image and the image’s most salient region. The algorithm also avoids using image priors. Pixel dissimilarity is an informal function of the distance of a specific pixel’s color to other pixels’ colors in an image. We examine the relation between pixel color dissimilarity and salient region detection on the MSRA1K image dataset. We propose a simple algorithm for salient region detection through random pixel color dissimilarity. We define dissimilarity by accumulating the distance between each pixel and a sample of n other random pixels, in the CIELAB color space. An important result is that random dissimilarity between each pixel and just another pixel (n = 1) is enough to create adequate saliency maps when combined with median filter, with competitive average performance if compared with other related methods in the saliency detection research field. The assessment was performed by means of precision-recall curves. This idea is inspired on the human attention mechanism that is able to choose few specific regions to focus on, a biological system that the computer vision community aims to emulate. We also review some of the history on this topic of selective attention.

EIR – sistema inteligente para detecção e classificação de calcificações em mamografias

Dissertação (mestrado)—Universidade de Brasília, Faculdade Gama, Programa de Pós-Graduação em Engenharia Biomédica, 2016.

Using syntactic and semantic features for classifying mo- dal values in the portuguese language

This paper presents a study made in a field poorly explored in the Portuguese language – modality and its automatic tagging. Our main goal was to find a set of attributes for the creation of automatic tag- gers with improved performance over the bag-of-words (bow) approach. The performance was measured using precision, recall and F1. Because it is a relatively unexplored field, the study covers the creation of the corpus (composed by eleven verbs), the use of a parser to extract syntac- tic and semantic information from the sentences and a machine learning approach to identify modality values. Based on three different sets of attributes – from trigger itself and the trigger’s path (from the parse tree) and context – the system creates a tagger for each verb achiev- ing (in almost every verb) an improvement in F1 when compared to the traditional bow approach.

Theoretical analysis of hidden photon searches in high-precision experiments

Although the Standard Model of particle physics (SM) provides an extremely successful description of the ordinary matter, one knows from astronomical observations that it accounts only for around 5% of the total energy density of the Universe, whereas around 30% are contributed by the dark matter. Motivated by anomalies in cosmic ray observations and by attempts to solve questions of the SM like the (g-2)_mu discrepancy, proposed U(1) extensions of the SM gauge group have raised attention in recent years. In the considered U(1) extensions a new, light messenger particle, the hidden photon, couples to the hidden sector as well as to the electromagnetic current of the SM by kinetic mixing. This allows for a search for this particle in laboratory experiments exploring the electromagnetic interaction. Various experimental programs have been started to search for hidden photons, such as in electron-scattering experiments, which are a versatile tool to explore various physics phenomena. One approach is the dedicated search in fixed-target experiments at modest energies as performed at MAMI or at JLAB. In these experiments the scattering of an electron beam off a hadronic target e+(A,Z)->e+(A,Z)+l^+l^- is investigated and a search for a very narrow resonance in the invariant mass distribution of the lepton pair is performed. This requires an accurate understanding of the theoretical basis of the underlying processes. For this purpose it is demonstrated in the first part of this work, in which way the hidden photon can be motivated from existing puzzles encountered at the precision frontier of the SM. The main part of this thesis deals with the analysis of the theoretical framework for electron scattering fixed-target experiments searching for hidden photons. As a first step, the cross section for the bremsstrahlung emission of hidden photons in such experiments is studied. Based on these results, the applicability of the Weizsäcker-Williams approximation to calculate the signal cross section of the process, which is widely used to design such experimental setups, is investigated. In a next step, the reaction e+(A,Z)->e+(A,Z)+l^+l^- is analyzed as signal and background process in order to describe existing data obtained by the A1 experiment at MAMI with the aim to give accurate predictions of exclusion limits for the hidden photon parameter space. Finally, the derived methods are used to find predictions for future experiments, e.g., at MESA or at JLAB, allowing for a comprehensive study of the discovery potential of the complementary experiments. In the last part, a feasibility study for probing the hidden photon model by rare kaon decays is performed. For this purpose, invisible as well as visible decays of the hidden photon are considered within different classes of models. This allows one to find bounds for the parameter space from existing data and to estimate the reach of future experiments.

Termination and cost analysis: Complexity and precision issues

The research in this thesis is related to static cost and termination analysis. Cost analysis aims at estimating the amount of resources that a given program consumes during the execution, and termination analysis aims at proving that the execution of a given program will eventually terminate. These analyses are strongly related, indeed cost analysis techniques heavily rely on techniques developed for termination analysis. Precision, scalability, and applicability are essential in static analysis in general. Precision is related to the quality of the inferred results, scalability to the size of programs that can be analyzed, and applicability to the class of programs that can be handled by the analysis (independently from precision and scalability issues). This thesis addresses these aspects in the context of cost and termination analysis, from both practical and theoretical perspectives. For cost analysis, we concentrate on the problem of solving cost relations (a form of recurrence relations) into closed-form upper and lower bounds, which is the heart of most modern cost analyzers, and also where most of the precision and applicability limitations can be found. We develop tools, and their underlying theoretical foundations, for solving cost relations that overcome the limitations of existing approaches, and demonstrate superiority in both precision and applicability. A unique feature of our techniques is the ability to smoothly handle both lower and upper bounds, by reversing the corresponding notions in the underlying theory. For termination analysis, we study the hardness of the problem of deciding termination for a speci�c form of simple loops that arise in the context of cost analysis. This study gives a better understanding of the (theoretical) limits of scalability and applicability for both termination and cost analysis.

An illustration of variable precision rough sets model:an analysis of the findings of the UK Monopolies and Mergers Commission

This paper introduces a new technique in the investigation of limited-dependent variable models. This paper illustrates that variable precision rough set theory (VPRS), allied with the use of a modern method of classification, or discretisation of data, can out-perform the more standard approaches that are employed in economics, such as a probit model. These approaches and certain inductive decision tree methods are compared (through a Monte Carlo simulation approach) in the analysis of the decisions reached by the UK Monopolies and Mergers Committee. We show that, particularly in small samples, the VPRS model can improve on more traditional models, both in-sample, and particularly in out-of-sample prediction. A similar improvement in out-of-sample prediction over the decision tree methods is also shown.

Lexical database enrichment through semi-automated morphological analysis

Derivational morphology proposes meaningful connections between words and is largely unrepresented in lexical databases. This thesis presents a project to enrich a lexical database with morphological links and to evaluate their contribution to disambiguation. A lexical database with sense distinctions was required. WordNet was chosen because of its free availability and widespread use. Its suitability was assessed through critical evaluation with respect to specifications and criticisms, using a transparent, extensible model. The identification of serious shortcomings suggested a portable enrichment methodology, applicable to alternative resources. Although 40% of the most frequent words are prepositions, they have been largely ignored by computational linguists, so addition of prepositions was also required. The preferred approach to morphological enrichment was to infer relations from phenomena discovered algorithmically. Both existing databases and existing algorithms can capture regular morphological relations, but cannot capture exceptions correctly; neither of them provide any semantic information. Some morphological analysis algorithms are subject to the fallacy that morphological analysis can be performed simply by segmentation. Morphological rules, grounded in observation and etymology, govern associations between and attachment of suffixes and contribute to defining the meaning of morphological relationships. Specifying character substitutions circumvents the segmentation fallacy. Morphological rules are prone to undergeneration, minimised through a variable lexical validity requirement, and overgeneration, minimised by rule reformulation and restricting monosyllabic output. Rules take into account the morphology of ancestor languages through co-occurrences of morphological patterns. Multiple rules applicable to an input suffix need their precedence established. The resistance of prefixations to segmentation has been addressed by identifying linking vowel exceptions and irregular prefixes. The automatic affix discovery algorithm applies heuristics to identify meaningful affixes and is combined with morphological rules into a hybrid model, fed only with empirical data, collected without supervision. Further algorithms apply the rules optimally to automatically pre-identified suffixes and break words into their component morphemes. To handle exceptions, stoplists were created in response to initial errors and fed back into the model through iterative development, leading to 100% precision, contestable only on lexicographic criteria. Stoplist length is minimised by special treatment of monosyllables and reformulation of rules. 96% of words and phrases are analysed. 218,802 directed derivational links have been encoded in the lexicon rather than the wordnet component of the model because the lexicon provides the optimal clustering of word senses. Both links and analyser are portable to an alternative lexicon. The evaluation uses the extended gloss overlaps disambiguation algorithm. The enriched model outperformed WordNet in terms of recall without loss of precision. Failure of all experiments to outperform disambiguation by frequency reflects on WordNet sense distinctions.

Semantic sentiment analysis of Twitter

Sentiment analysis over Twitter offer organisations a fast and effective way to monitor the publics' feelings towards their brand, business, directors, etc. A wide range of features and methods for training sentiment classifiers for Twitter datasets have been researched in recent years with varying results. In this paper, we introduce a novel approach of adding semantics as additional features into the training set for sentiment analysis. For each extracted entity (e.g. iPhone) from tweets, we add its semantic concept (e.g. Apple product) as an additional feature, and measure the correlation of the representative concept with negative/positive sentiment. We apply this approach to predict sentiment for three different Twitter datasets. Our results show an average increase of F harmonic accuracy score for identifying both negative and positive sentiment of around 6.5% and 4.8% over the baselines of unigrams and part-of-speech features respectively. We also compare against an approach based on sentiment-bearing topic analysis, and find that semantic features produce better Recall and F score when classifying negative sentiment, and better Precision with lower Recall and F score in positive sentiment classification.

IT as enabler of sustainable farming:an empirical analysis of farmers' adoption decision of precision agriculture technology

Precision agriculture (PA) describes a suite of IT based tools which allow farmers to electronically monitor soil and crop conditions and analyze treatment options. This study tests a model explaining the difficulties of PA technology adoption. The model draws on theories of technology acceptance and diffusion of innovation and is validated using survey data from farms in Canada. Findings highlight the importance of compatibility among PA technology components and the crucial role of farmers' expertise. The model provides the theoretical and empirical basis for developing policies and initiatives to support PA technology adoption.

Non-conventional advertising formats in television versus spots: An analysis based on the generated recall

Advertising investment and audience figures indicate that television continues to lead as a mass advertising medium. However, its effectiveness is questioned due to problems such as zapping, saturation and audience fragmentation. This has favoured the development of non-conventional advertising formats. This study provides empirical evidence for the theoretical development. This investigation analyzes the recall generated by four non-conventional advertising formats in a real environment: short programme (branded content), television sponsorship, internal and external telepromotion versus the more conventional spot. The methodology employed has integrated secondary data with primary data from computer assisted telephone interviewing (CATI) were performed ad-hoc on a sample of 2000 individuals, aged 16 to 65, representative of the total television audience. Our findings show that non-conventional advertising formats are more effective at a cognitive level, as they generate higher levels of both unaided and aided recall, in all analyzed formats when compared to the spot.

Swath bathymetry using phase difference: Theoretical analysis of acoustical measurement precision

The phase difference principle is widely applied nowadays to sonar systems used for sea floor bathymetry, The apparent angle of a target point is obtained from the phase difference measured between two close receiving arrays. Here we study the influence of the phase difference estimation errors caused by the physical structure of the backscattered signals. It is shown that, under certain current conditions, beyond the commonly considered effects of additive external noise and baseline decorrelation, the processing may be affected by the shifting footprint effect: this is due to the fact that the two interferometer receivers get simultaneous echo contributions coming from slightly shifted seabed parts, which results in a degradation of the signal coherence and, hence, of the phase difference measurement. This geometrical effect is described analytically and checked with numerical simulations, both for square- and sine-shaped signal envelopes. Its relative influence depends on the geometrical configuration and receiver spacing; it may be prevalent in practical cases associated with bathymetric sonars. The cases of square and smooth signal envelopes are both considered. The measurements close to nadir, which are known to be especially difficult with interferometry systems, are addressed in particular.

The State of our Toolbox: A Meta-analysis of Reliability Measurement Precision

My study investigated internal consistency estimates of psychometric surveys as an operationalization of the state of measurement precision of constructs in industrial and organizational (I/O) psychology. Analyses were conducted of samples used in research articles published in the Journal of Applied Psychology between 1975 and 2010 in five year intervals (K = 934) from 480 articles yielding 1427 coefficients. Articles and their respective samples were coded for test-taker characteristics (e.g., age, gender, and ethnicity), research settings (e.g., lab and field studies), and actual tests (e.g., number of items and scale anchor points). A reliability and inter-item correlations depository was developed for I/O variables and construct groups. Personality measures had significantly lower inter-item correlations than other construct groups. Also, internal consistency estimates and reporting practices were evaluated over time, demonstrating an improvement in measurement precision and missing data.