962 resultados para Maximum entropy method
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Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.
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The Implementation of Enterprise Resource Planning (ERP) systems require huge investments while ineffective implementations of such projects are commonly observed. A considerable number of these projects have been reported to fail or take longer than it was initially planned, while previous studies show that the aim of rapid implementation of such projects has not been successful and the failure of the fundamental goals in these projects have imposed huge amounts of costs on investors. Some of the major consequences are the reduction in demand for such products and the introduction of further skepticism to the managers and investors of ERP systems. In this regard, it is important to understand the factors determining success or failure of ERP implementation. The aim of this paper is to study the critical success factors (CSFs) in implementing ERP systems and to develop a conceptual model which can serve as a basis for ERP project managers. These critical success factors that are called “core critical success factors” are extracted from 62 published papers using the content analysis and the entropy method. The proposed conceptual model has been verified in the context of five multinational companies.
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Social streams have proven to be the mostup-to-date and inclusive information on cur-rent events. In this paper we propose a novelprobabilistic modelling framework, called violence detection model (VDM), which enables the identification of text containing violent content and extraction of violence-related topics over social media data. The proposed VDM model does not require any labeled corpora for training, instead, it only needs the in-corporation of word prior knowledge which captures whether a word indicates violence or not. We propose a novel approach of deriving word prior knowledge using the relative entropy measurement of words based on the in-tuition that low entropy words are indicative of semantically coherent topics and therefore more informative, while high entropy words indicates words whose usage is more topical diverse and therefore less informative. Our proposed VDM model has been evaluated on the TREC Microblog 2011 dataset to identify topics related to violence. Experimental results show that deriving word priors using our proposed relative entropy method is more effective than the widely-used information gain method. Moreover, VDM gives higher violence classification results and produces more coherent violence-related topics compared toa few competitive baselines.
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We present and analyze three different online algorithms for learning in discrete Hidden Markov Models (HMMs) and compare their performance with the Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of the generalization error we draw learning curves in simplified situations and compare the results. The performance for learning drifting concepts of one of the presented algorithms is analyzed and compared with the Baldi-Chauvin algorithm in the same situations. A brief discussion about learning and symmetry breaking based on our results is also presented. © 2006 American Institute of Physics.
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Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.
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The so called “Plural Uncertainty Model” is considered, in which statistical, maxmin, interval and Fuzzy model of uncertainty are embedded. For the last case external and internal contradictions of the theory are investigated and the modified definition of the Fuzzy Sets is proposed to overcome the troubles of the classical variant of Fuzzy Subsets by L. Zadeh. The general variants of logit- and probit- regression are the model of the modified Fuzzy Sets. It is possible to say about observations within the modification of the theory. The conception of the “situation” is proposed within modified Fuzzy Theory and the classifying problem is considered. The algorithm of the classification for the situation is proposed being the analogue of the statistical MLM(maximum likelihood method). The example related possible observing the distribution from the collection of distribution is considered.
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Speciation can be understood as a continuum occurring at different levels, from population to species. The recent molecular revolution in population genetics has opened a pathway towards understanding species evolution. At the same time, speciation patterns can be better explained by incorporating a geographic context, through the use of geographic information systems (GIS). Phaedranassa (Amaryllidaceae) is a genus restricted to one of the world’s most biodiverse hotspots, the Northern Andes. I studied seven Phaedranassa species from Ecuador. Six of these species are endemic to the country. The topographic complexity of the Andes, which creates local microhabitats ranging from moist slopes to dry valleys, might explain the patterns of Phaedranassa species differentiation. With a Bayesian individual assignment approach, I assessed the genetic structure of the genus throughout Ecuador using twelve microsatellite loci. I also used bioclimatic variables and species geographic coordinates under a Maximum Entropy algorithm to generate distribution models of the species. My results show that Phaedranassa species are genetically well-differentiated. Furthermore, with the exception of two species, all Phaedranassa showed non-overlapping distributions. Phaedranassa viridiflora and P. glauciflora were the only species in which the model predicted a broad species distribution, but genetic evidence indicates that these findings are likely an artifact of species delimitation issues. Both genetic differentiation and nonoverlapping geographic distribution suggest that allopatric divergence could be the general model of genetic differentiation. Evidence of sympatric speciation was found in two geographically and genetically distinct groups of P. viridiflora. Additionally, I report the first register of natural hybridization for the genus. The findings of this research show that the genetic differentiation of species in an intricate landscape as the Andes does not necessarily show a unique trend. Although allopatric speciation is the most common form of speciation, I found evidence of sympatric speciation and hybridization. These results show that the processes of speciation in the Andes have followed several pathways. The mixture of these processes contributes to the high biodiversity of the region.
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A Partial Waves Analysis (PWA) of γp → Δ ++X → pπ+ π - (η) data taken with the CLAS detector at Jefferson Lab is presented in this work. This reaction is of interest because the Δ++ restricts the isospin of the possible X states, leaving the PWA with a smaller combination of partial waves, making it ideal to look for exotic mesons. It was proposed by Isgur and Paton that photoproduction is a plausible source for the Jpc=1–+ state through flux tube excitation. The π1(1400) is such a state that has been produced with the use of hadron production but it has yet to be seen in photoproduction. A mass independent amplitude analysis of this channel was performed, followed by a mass dependent fit to extract the resonance parameters. The procedure used an event-based maximum likelihood method to maintain all correlations in the kinematics. The intensity and phase motion is mapped out for the contributing signals without requiring assumptions about the underlying processes. The strength of the PWA is in the analysis of the phase motion, which for resonance behavior is well defined. In the data presented, the ηπ– invariant mass spectrum shows contributions from the a0(980) and a2(1320) partial waves. No π1 was observed under a clear a2 signal after the angular distributions of the decay products were analyzed using an amplitude analysis. In addition, this dissertation discusses trends in the data, along with the implemented techniques.
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The genus Hemidactylus Oken, 1817 has cosmopolite distribution, with three species occurring in Brazil, two of them native, H. brasilianus and H. agrius, and one exotic, H. mabouia. Considering the studies about ecology of lizards conducted in the Ecological Station of the Seridó, from 2001 to 2011, this study aimed (1) to re-evaluate the occurrence of the species of Hemidactylus in this ESEC; (2) to analyze ecological and biological aspects of the H. agrius population; and (3) to investigate the current and potential distribution of the native species of the genus in northeastern Brazil, analyzing the suitability of ESEC to this taxon. For the first two objectives, a sampling area consisting of five transects of 200 x 20 m, was inspected in alternating daily shifts for three consecutive days, from August 2012 to August 2013. For the latter objective, occurrence points of H. agrius and H. brasilianus from literature and from the database of Herpetological Collections of the UFRN and the UNICAMP were consulted to build predictive maps via the Maximum Entropy algorithm (MaxEnt). In ESEC Seridó, 62 H. agrius individuals were collected (25 females, 18 males and 19 juveniles), and two neonates were obtained from a communal nest incubated in the laboratory. No record was made for the other two species of the genus. Hemidactylus agrius demonstrated to be a nocturnal species specialized in habitats with rocky outcrops; but this species is generalist regarding microhabitat use. In the population studied, females had an average body length greater than males, and showed higher frequencies of caudal autotomy. Regarding diet, H. agrius is a moderately generalist species that consumes arthropods, especially insect larvae, Isoptera and Araneae; and vertebrates, with a case of cannibalism registered in the population. With respect to seasonal differences, only the number of food items ingested differed between seasons. The diet was similar between sexes, but ontogenetic differences were recorded for the total volume and maximum length of the food items. Significant relationships were found between lizard body/head size measurements and the maximum length of prey consumed. Cases of polydactyly and tail bifurcation were recorded in the population, with frequencies of 1.6% and 3.1%, respectively. In relation xv to the occurrence points of the native species, 27 were identified, 14 for H. agrius and 13 for H. brasilianus. The first species presented restricted distribution, while the second showed a wide distribution. In both models generated, the ESEC Seridó area showed medium to high suitability. The results of this study confirm the absence of H. brasilianus and H. mabouia this ESEC, and reveal H. agrius as a dietary opportunist and cannibal species. Further, the results confirm the distribution patterns shown by native species of Hemidactylus, and point ESEC Seridó as an area of probable occurrence for the species of the genus, the establishing of H. brasilianus and H. mabouia are probably limited by biotic factors, a fact yet little understood
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Social structure is a key determinant of population biology and is central to the way animals exploit their environment. The risk of predation is often invoked as an important factor influencing the evolution of social structure in cetaceans and other mammals, but little direct information is available about how cetaceans actually respond to predators or other perceived threats. The playback of sounds to an animal is a powerful tool for assessing behavioral responses to predators, but quantifying behavioral responses to playback experiments requires baseline knowledge of normal behavioral patterns and variation. The central goal of my dissertation is to describe baseline foraging behavior for the western Atlantic short-finnned pilot whales (Globicephala macrohynchus) and examine the role of social organization in their response to predators. To accomplish this I used multi-sensor digital acoustic tags (DTAGs), satellite-linked time-depth recorders (SLTDR), and playback experiments to study foraging behavior and behavioral response to predators in pilot whales. Fine scale foraging strategies and population level patterns were identified by estimating the body size and examining the location and movement around feeding events using data collected with DTAGs deployed on 40 pilot whales in summers of 2008-2014 off the coast of Cape Hatteras, North Carolina. Pilot whales were found to forage throughout the water column and performed feeding buzzes at depths ranging from 29-1176 meters. The results indicated potential habitat segregation in foraging depth in short-finned pilot whales with larger individuals foraging on average at deeper depths. Calculated aerobic dive limit for large adult males was approximately 6 minutes longer than that of females and likely facilitated the difference in foraging depth. Furthermore, the buzz frequency and speed around feeding attempts indicate this population pilot whales are likely targeting multiple small prey items. Using these results, I built decision trees to inform foraging dive classification in coarse, long-term dive data collected with SLTDRs deployed on 6 pilot whales in the summers of 2014 and 2015 in the same area off the coast of North Carolina. I used these long term foraging records to compare diurnal foraging rates and depths, as well as classify bouts with a maximum likelihood method, and evaluate behavioral aerobic dive limits (ADLB) through examination of dive durations and inter-dive intervals. Dive duration was the best predictor of foraging, with dives >400.6 seconds classified as foraging, and a 96% classification accuracy. There were no diurnal patterns in foraging depth or rates and average duration of bouts was 2.94 hours with maximum bout durations lasting up to 14 hours. The results indicated that pilot whales forage in relatively long bouts and the ADLB indicate that pilot whales rarely, if ever exceed their aerobic limits. To evaluate the response to predators I used controlled playback experiments to examine the behavioral responses of 10 of the tagged short-finned pilot whales off Cape Hatteras, North Carolina and 4 Risso’s dolphins (Grampus griseus) off Southern California to the calls of mammal-eating killer whales (MEK). Both species responded to a subset of MEK calls with increased movement, swim speed and increased cohesion of the focal groups, but the two species exhibited different directional movement and vocal responses. Pilot whales increased their call rate and approached the sound source, but Risso’s dolphins exhibited no change in their vocal behavior and moved in a rapid, directed manner away from the source. Thus, at least to a sub-set of mammal-eating killer whale calls, these two study species reacted in a manner that is consistent with their patterns of social organization. Pilot whales, which live in relatively permanent groups bound by strong social bonds, responded in a manner that built on their high levels of social cohesion. In contrast, Risso’s dolphins exhibited an exaggerated flight response and moved rapidly away from the sound source. The fact that both species responded strongly to a select number of MEK calls, suggests that structural features of signals play critical contextual roles in the probability of response to potential threats in odontocete cetaceans.
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No estudo de séries temporais, os processos estocásticos usuais assumem que as distribuições marginais são contínuas e, em geral, não são adequados para modelar séries de contagem, pois as suas características não lineares colocam alguns problemas estatísticos, principalmente na estimação dos parâmetros. Assim, investigou-se metodologias apropriadas de análise e modelação de séries com distribuições marginais discretas. Neste contexto, Al-Osh and Alzaid (1987) e McKenzie (1988) introduziram na literatura a classe dos modelos autorregressivos com valores inteiros não negativos, os processos INAR. Estes modelos têm sido frequentemente tratados em artigos científicos ao longo das últimas décadas, pois a sua importância nas aplicações em diversas áreas do conhecimento tem despertado um grande interesse no seu estudo. Neste trabalho, após uma breve revisão sobre séries temporais e os métodos clássicos para a sua análise, apresentamos os modelos autorregressivos de valores inteiros não negativos de primeira ordem INAR (1) e a sua extensão para uma ordem p, as suas propriedades e alguns métodos de estimação dos parâmetros nomeadamente, o método de Yule-Walker, o método de Mínimos Quadrados Condicionais (MQC), o método de Máxima Verosimilhança Condicional (MVC) e o método de Quase Máxima Verosimilhança (QMV). Apresentamos também um critério automático de seleção de ordem para modelos INAR, baseado no Critério de Informação de Akaike Corrigido, AICC, um dos critérios usados para determinar a ordem em modelos autorregressivos, AR. Finalmente, apresenta-se uma aplicação da metodologia dos modelos INAR em dados reais de contagem relativos aos setores dos transportes marítimos e atividades de seguros de Cabo Verde.
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Se hace un análisis del estado poblacional del cangrejo violáceo Platyxanthus orbignyi (Milne Edwards y Lucas, 1843) del litoral de Lambayeque – Perú para el periodo 2001-2010 por medio de: 1) El modelo dinámico de biomasa de Schaefer en su versión de error de observación; a este modelo se le introdujo la variable ambiental anomalía de la temperatura superficial del mar (ATSM) del área de San José (Lambayeque) y se obtuvo 2) el modelo dinámico con variable ambiental, ambos basados en datos de captura, esfuerzo y CPUE. Se utilizó el método de máxima verosimilitud en el proceso de ajuste y el bootstrap para determinar los intervalos de confianza de los parámetros. Los parámetros poblacionales y pesqueros estimados por el modelo dinámico de biomasa de Schaefer (MDB) fueron: K: 750 000 kg, r : 0,21 y q: 8,36 x 10-6 y por el modelo dinámico con variable ambiental (MDVA) los parámetros fueron K: 765 000 kg, r: 0,23 y q: 8,02 x 10-6. Con los valores de los parámetros estimados mediante el MDB y el MDVA se calcularon los principales puntos biológicos de referencia (PBR) los cuales fueron: MRS: 39 822 kg, BMRS: 375 000 kg, fMRS: 12 561 nasas, FMRS: 0,11, F0.1: 0,10 para el MDB; y MRS: 44 069 kg, BMRS: 382 500 kg, fMRS: 13 782 nasas, FMRS: 0,12, F0.1: 0,10 para el MDVA. Los resultados indican que el estado actual de la pesquería del cangrejo violáceo del Litoral de Lambayeque se encuentra muy cerca al nivel óptimo. En vista de que no se dispone de información de evaluaciones directas de este recurso que confirme o no los resultados del MDB y MDVA y en virtud de la calidad de datos, se sugiere que el manejo de la pesquería sea del tipo adaptativo alrededor del punto de referencia F0.1 y teniendo en cuenta las condiciones ambientales.
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The internationalization as an organizational phenomenon fundamentally strategic had as theoretical contributions some Schools that throughout the decades 60, 70, and 80 developed behavioral and economic approaches in order to explain the process. The behavioral approach deals with the perception of phenomenon as a gradual process from the perspective of the executives behavior (JOHANSON and VAHLNE, 1977; HALLÉN and WIEDERSHEIM - PAUL, 1979; CZINKOTA, 1985). This phenomenon in permanent theoretical and managerial evolution made an opportunity to build this investigation, whose goal is to analyse the impact comes from organizational capabilities and the external environment on the international performance of exporting firms. For both, were used as theoretical basis two types of analysis for the comprehension of international performance: Strategic Management - Industrial Organization and Resource-Based View and International Businesses - Current Economic and Behavioral. It was made a cross-sectional survey-based explanatory research, including 150 exporting companies with operations in the Northeast of Brazil. A conceptual model was made with eight constructs and eight research hypotheses, representative of the effects of external factors on international performance. The data were processed using the Exploratory Factor Analysis and Structural Equation Modeling. The structural equations model was reespecified and estimated through the use of the maximum-likelihood method up to achieve adequated values of indexes of adjustment. As the main theoretical contribution, were identified organizational and physical resources which shows the importance of the management skills development, of the learning capability and capability to establish strategic alliances abroad. That because the knowledge, as the operational point of view as in its strategic application, offers to organization conditions of market positioning which can create opportunities sustainable competitive advantages and which impact the performance of international companies
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Thesis (Master's)--University of Washington, 2016-08
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The subject of quark transverse spin and transverse momentum distribution are two current research frontier in understanding the spin structure of the nucleons. The goal of the research reported in this dissertation is to extract new information on the quark transversity distribution and the novel transverse-momentum-dependent Sivers function in the neutron. A semi-inclusive deep inelastic scattering experiment was performed at the Hall A of the Jefferson laboratory using 5.9 GeV electron beam and a transversely polarized ^{3}He target. The scattered electrons and the produced hadrons (pions, kaons, and protons) were detected in coincidence with two large magnetic spectrometers. By regularly flipping the spin direction of the transversely polarized target, the single-spin-asymmetry (SSA) of the semi-inclusive deep inelastic reaction ^{3}He^{uparrow}(e,e'h^{\pm})X was measured over the kinematic range 0.13 < x < 0.41 and 1.3 < Q^{2} < 3.1 (GeV)^{2}. The SSA contains several different azimuthal angular modulations which are convolutions of quarks distribution functions in the nucleons and the quark fragmentation functions into hadrons. It is from the extraction of the various ``moments'' of these azimuthal angular distributions (Collins moment and Sivers moment) that we obtain information on the quark transversity distribution and the novel T-odd Sivers function. In this dissertation, I first introduced the theoretical background and experimental status of nucleon spins and the physics of SSA. I will then present the experimental setup and data collection of the JLab E06-010 experiment. Details of data analysis will be discussed next with emphasis on the kaon particle identification and the Ring-Imaging Cherenkov detector which are my major responsibilities in this experiment. Finally, results on the kaon Collins and Sivers moments extracted from the Maximum Likelihood method will be presented and interpreted. I will conclude with a discussion on the future prospects for this research.