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    EmoSpell, a morphological and emotional word analyzer
    ( 2018) Maia,MI ; José Paulo Leal
    The analysis of sentiments, emotions, and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative, or neutral. To identify the emotional load intended by the author, it is necessary to also categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three different levels of emotions-global, specific, and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources: the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Additionally, this paper details the Web application and Web service that exploit this dictionary. It also presents a validation of the proposed approach using a corpus of student texts with different emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. © 2018 by the authors.
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    One-Way Functions Using Algorithmic and Classical Information Theories
    ( 2013) Luís Filipe Antunes ; Matos,A ; Alexandre Miranda Pinto ; Souto,A ; Andreia Sofia Teixeira
    We prove several results relating injective one-way functions, time-bounded conditional Kolmogorov complexity, and time-bounded conditional entropy. First we establish a connection between injective, strong and weak one-way functions and the expected value of the polynomial time-bounded Kolmogorov complexity, denoted here by E(K-t (x vertical bar f (x))). These results are in both directions. More precisely, conditions on E(K-t (x vertical bar f (x))) that imply that f is a weak one-way function, and properties of E(K-t (x vertical bar f (x))) that are implied by the fact that f is a strong one-way function. In particular, we prove a separation result: based on the concept of time-bounded Kolmogorov complexity, we find an interval in which every function f is a necessarily weak but not a strong one-way function. Then we propose an individual approach to injective one-way functions based on Kolmogorov complexity, defining Kolmogorov one-way functions and prove some relationships between the new proposal and the classical definition of one-way functions, showing that a Kolmogorov one-way function is also a deterministic one-way function. A relationship between Kolmogorov one-way functions and the conjecture of polynomial time symmetry of information is also proved. Finally, we relate E(K-t (x vertical bar f (x))) and two forms of time-bounded entropy, the unpredictable entropy H-unp, in which "one-wayness" of a function can be easily expressed, and the Yao(+) entropy, a measure based on compression/decompression schema in which only the decompressor is restricted to be time-bounded.
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    Information-based measure of disagreement for more than two observers: a useful tool to compare the degree of observer disagreement
    ( 2013) Teresa Sarmento Henriques ; Luís Filipe Antunes ; Bernardes,J ; Matias,M ; Sato,D ; Santos,C
    Background: Assessment of disagreement among multiple measurements for the same subject by different observers remains an important problem in medicine. Several measures have been applied to assess observer agreement. However, problems arise when comparing the degree of observer agreement among different methods, populations or circumstances. Methods: The recently introduced information-based measure of disagreement (IBMD) is a useful tool for comparing the degree of observer disagreement. Since the proposed IBMD assesses disagreement between two observers only, we generalized this measure to include more than two observers. Results: Two examples (one with real data and the other with hypothetical data) were employed to illustrate the utility of the proposed measure in comparing the degree of disagreement. Conclusion: The IBMD allows comparison of the disagreement in non-negative ratio scales across different populations and the generalization presents a solution to evaluate data with different number of observers for different cases, an important issue in real situations. A website for online calculation of IBMD and respective 95% confidence interval was additionally developed. The website is widely available to mathematicians, epidemiologists and physicians to facilitate easy application of this statistical strategy to their own data.
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    Entropy and compression: two measures of complexity
    ( 2013) Teresa Sarmento Henriques ; Goncalves,H ; Luís Filipe Antunes ; Matias,M ; Bernardes,J ; Santos,C
    Rationale, aims and objectivesTraditional complexity measures are used to capture the amount of structured information present in a certain phenomenon. Several approaches developed to facilitate the characterization of complexity have been described in the related literature. Fetal heart rate (FHR) monitoring has been used and improved during the last decades. The importance of these studies lies on an attempt to predict the fetus outcome, but complexity measures are not yet established in clinical practice. In this study, we have focused on two conceptually different measures: Shannon entropy, a probabilistic approach, and Kolmogorov complexity, an algorithmic approach. The main aim of the current investigation was to show that approximation to Kolmogorov complexity through different compressors, although applied to a lesser extent, may be as useful as Shannon entropy calculated by approximation through different entropies, which has been successfully applied to different scientific areas. MethodsTo illustrate the applicability of both approaches, two entropy measures, approximate and sample entropy, and two compressors, paq8l and bzip2, were considered. These indices were applied to FHR tracings pertaining to a dataset composed of 48 delivered fetuses with umbilical artery blood (UAB) pH in the normal range (pH7.20), 10 delivered mildly acidemic fetuses and 10 moderate-to-severe acidemic fetuses. The complexity indices were computed on the initial and final segments of the last hour of labour, considering 5- and 10-minute segments. ResultsIn our sample set, both entropies and compressors were successfully utilized to distinguish fetuses at risk of hypoxia from healthy ones. Fetuses with lower UAB pH presented significantly lower entropy and compression indices, more markedly in the final segments. ConclusionsThe combination of these conceptually different measures appeared to present an improved approach in the characterization of different pathophysiological states, reinforcing the theory that entropies and compressors measure different complexity features. In view of these findings, we recommend a combination of the two approaches.
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    Boosting the Detection of Transposable Elements Using Machine Learning
    ( 2013) Loureiro,T ; Rui Camacho ; Vieira,J ; Nuno Fonseca
    Transposable Elements (TE) are sequences of DNA that move and transpose within a genome. TEs, as mutation agents, are quite important for their role in both genome alteration diseases and on species evolution. Several tools have been developed to discover and annotate TEs but no single one achieves good results on all different types of TEs. In this paper we evaluate the performance of several TEs detection and annotation tools and investigate if Machine Learning techniques can be used to improve their overall detection accuracy. The results of an in silico evaluation of TEs detection and annotation tools indicate that their performance can be improved by using machine learning classifiers. © Springer International Publishing Switzerland 2013.