893 resultados para data driven approach


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A general procedure was developed for the simultaneous separation of flavonoids and naphthopyrones from the polar extracts of the capitula from Brazilian everlasting plants is described. The ethanolic extracts of several species from the Paepalanthus genus (Eriocaulaceae) were fractionated by droplet countercurrent chromatography followed by column chromatography on pvp and sephadex LH-20. The isolated compounds were identified by spectrometric analysis and comparison with literature data. This approach led to the isolation of 9-O-β-D-glucopyranosylpaepalantine (1), 9-O-β-D-glucopyranosyl (1→6)allopyranosylpaepalantine (2), along with the flavonoids 6-methoxykaempferol (3), 3-O-β-D-glucopyranosyl-6-methoxykaempferol (4), patuletin (5), 3-Oβ-D-rutinosylpatuletin (6), 7-O-β-D-glucopyranosylquercetagetin (7), 5,7,4'-trihydroxy-6,3'-dimethoxyflavone (8) and 5,7,4'-trihydroxy-6,3'-dimethoxyflavonol (9).

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We present a measurement of the semileptonic mixing asymmetry for B0 mesons, asld, using two independent decay channels: B0→μ +D -X, with D -→K +π -π -; and B0→μ +D *-X, with D * -→D ̄0π -, D ̄0→ K +π - (and charge conjugate processes). We use a data sample corresponding to 10.4fb -1 of pp̄ collisions at √s=1.96TeV, collected with the D0 experiment at the Fermilab Tevatron collider. We extract the charge asymmetries in these two channels as a function of the visible proper decay length of the B0 meson, correct for detector-related asymmetries using data-driven methods, and account for dilution from charge-symmetric processes using Monte Carlo simulation. The final measurement combines four signal visible proper decay length regions for each channel, yielding asld=[0.68±0.45(stat)±0.14(syst)]%. This is the single most precise measurement of this parameter, with uncertainties smaller than the current world average of B factory measurements. © 2012 American Physical Society.

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O processamento de voz tornou-se uma tecnologia cada vez mais baseada na modelagem automática de vasta quantidade de dados. Desta forma, o sucesso das pesquisas nesta área está diretamente ligado a existência de corpora de domínio público e outros recursos específicos, tal como um dicionário fonético. No Brasil, ao contrário do que acontece para a língua inglesa, por exemplo, não existe atualmente em domínio público um sistema de Reconhecimento Automático de Voz (RAV) para o Português Brasileiro com suporte a grandes vocabulários. Frente a este cenário, o trabalho tem como principal objetivo discutir esforços dentro da iniciativa FalaBrasil [1], criada pelo Laboratório de Processamento de Sinais (LaPS) da UFPA, apresentando pesquisas e softwares na área de RAV para o Português do Brasil. Mais especificamente, o presente trabalho discute a implementação de um sistema de reconhecimento de voz com suporte a grandes vocabulários para o Português do Brasil, utilizando a ferramenta HTK baseada em modelo oculto de Markov (HMM) e a criação de um módulo de conversão grafema-fone, utilizando técnicas de aprendizado de máquina.

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In a world that is increasingly working with software, the need arises for effective approaches that encourage software reuse. The reuse practice must be aligned to a set of practices, procedures and methodologies that create a stable and high quality product. These questions produce new styles and approaches in the software engineering. In this way, this thesis aims to address concepts related to development and model-driven architecture. The model-driven approach provides significant aspects of the automated development, which helps it with produced models built in the specification phase. The definition of terms such as model, architecture and platform makes the focus becomes clearer, because for MDA and MDD is important to split between technical and business issues. Important processes are covered, so you can highlight the artifacts that are built into each stage of model-driven development. The stages of development: CSM, PIM, PSM and ISM, detailing the purpose of each phase in oriented models, making the end of each stage are gradually produced artifacts that may be specialized. The models are handled by different prospects for modeling, abstracting the concepts and building a set of details that portrays a specific scenario. This retraction can be a graphical or textual representation, however, in most cases is chosen a language modeling, for example, UML. In order to provide a practical view, this dissertation shows some tools that improve the construction of models and the code generate that assists in the development, keeping the documentation systemic. Finally, the paper presents a case study that refers to the theoretical aspects discussed throughout the dissertation, therefore it is expected that the architecture and the model-driven development may be able to explain important features to consider in software engineering

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A measurement of differential cross sections for the production of a pair of isolated photons in proton-proton collisions at root s = 7 TeV is presented. The data sample corresponds to an integrated luminosity of 5.0 fb(-1) collected with the CMS detector. A data-driven isolation template method is used to extract the prompt diphoton yield. The measured cross section for two isolated photons, with transverse energy above 40 and 25 GeV respectively, in the pseudorapidity range vertical bar eta vertical bar < 2.5, vertical bar eta vertical bar (sic) [1.44, 1.57] and with an angular separation Delta R > 0.45, is 17.2 +/-0.2 (stat) +/-1.9 (syst) +/- 0.4 (lumi) pb. Differential cross sections are measured as a function of the diphoton invariant mass, the diphoton transverse momentum, the azimuthal angle difference between the two photons, and the cosine of the polar angle in the Collins-Soper reference frame of the diphoton system. The results are compared to theoretical predictions at leading, next-to-leading, and next-to-next-to-leading order in quantum chromodynamics.

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Objective. To define inactive disease (ID) and clinical remission (CR) and to delineate variables that can be used to measure ID/CR in childhood-onset systemic lupus erythematosus (cSLE). Methods. Delphi questionnaires were sent to an international group of pediatric rheumatologists. Respondents provided information about variables to be used in future algorithms to measure ID/CR. The usefulness of these variables was assessed in 35 children with ID and 31 children with minimally active lupus (MAL). Results. While ID reflects cSLE status at a specific point in time, CR requires the presence of ID for >6 months and considers treatment. There was consensus that patients in ID/CR can have <2 mild nonlimiting symptoms (i.e., fatigue, arthralgia, headaches, or myalgia) but not Raynaud's phenomenon, chest pain, or objective physical signs of cSLE; antinuclear antibody positivity and erythrocyte sedimentation rate elevation can be present. Complete blood count, renal function testing, and complement C3 all must be within the normal range. Based on consensus, only damage-related laboratory or clinical findings of cSLE are permissible with ID. The above parameters were suitable to differentiate children with ID/CR from those with MAL (area under the receiver operating characteristic curve >0.85). Disease activity scores with or without the physician global assessment of disease activity and patient symptoms were well suited to differentiate children with ID from those with MAL. Conclusion. Consensus has been reached on common definitions of ID/CR with cSLE and relevant patient characteristics with ID/CR. Further studies must assess the usefulness of the data-driven candidate criteria for ID in cSLE.

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Abstract Background Accurate malaria diagnosis is mandatory for the treatment and management of severe cases. Moreover, individuals with asymptomatic malaria are not usually screened by health care facilities, which further complicates disease control efforts. The present study compared the performances of a malaria rapid diagnosis test (RDT), the thick blood smear method and nested PCR for the diagnosis of symptomatic malaria in the Brazilian Amazon. In addition, an innovative computational approach was tested for the diagnosis of asymptomatic malaria. Methods The study was divided in two parts. For the first part, passive case detection was performed in 311 individuals with malaria-related symptoms from a recently urbanized community in the Brazilian Amazon. A cross-sectional investigation compared the diagnostic performance of the RDT Optimal-IT, nested PCR and light microscopy. The second part of the study involved active case detection of asymptomatic malaria in 380 individuals from riverine communities in Rondônia, Brazil. The performances of microscopy, nested PCR and an expert computational system based on artificial neural networks (MalDANN) using epidemiological data were compared. Results Nested PCR was shown to be the gold standard for diagnosis of both symptomatic and asymptomatic malaria because it detected the major number of cases and presented the maximum specificity. Surprisingly, the RDT was superior to microscopy in the diagnosis of cases with low parasitaemia. Nevertheless, RDT could not discriminate the Plasmodium species in 12 cases of mixed infections (Plasmodium vivax + Plasmodium falciparum). Moreover, the microscopy presented low performance in the detection of asymptomatic cases (61.25% of correct diagnoses). The MalDANN system using epidemiological data was worse that the light microscopy (56% of correct diagnoses). However, when information regarding plasma levels of interleukin-10 and interferon-gamma were inputted, the MalDANN performance sensibly increased (80% correct diagnoses). Conclusions An RDT for malaria diagnosis may find a promising use in the Brazilian Amazon integrating a rational diagnostic approach. Despite the low performance of the MalDANN test using solely epidemiological data, an approach based on neural networks may be feasible in cases where simpler methods for discriminating individuals below and above threshold cytokine levels are available.

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Zielvorgaben der vorliegenden Arbeit war die Identifikation neuer selektiv in Tumoren aktivierter Gene sowie die Entwicklung eines methodischen Prozesses, um die molekularen Effekte der fehlerhaften Aktivierung solcher Gene zu untersuchen. Für die erste Fragestellung haben wir zwei komplementäre Methoden entwickelt. Zum einen haben wir nach neuen Mitglieder der Cancer/Germline (CG) Familie von Genen gesucht, die bereits attraktive Zielstrukturen laufender Phase I/IIa Studien sind. Zu diesem Zweck wurde ein bioinformatischer Data Mining Ansatz generiert. Dieser führte zur erfolgreichen in silico Klonierung neuer CG Gene. Zur Identifikation von in Tumorzellen überexprimierten Genen nutzten wir einen cDNA Mikroarray mit 1152 ausgewählten Genen mit direkter oder indirekter tumorimmunologischer oder tumorbiologischer Relevanz. Die komparative transkriptionelle Untersuchung von humanen Tumor- und Normalgeweben mit diesem Array führte zur Wiederentdeckung bereits bekannter, aber auch zur Aufdeckung bisher nicht beschriebener tumor-assoziierter Transkriptionsveränderungen. Der zweite große Schwerpunkt dieser Arbeit war die Technologieentwicklung eines versatilen Prozesses zur Untersuchung von molekularen Effekten eines aberrant in Zellen exprimierten Gens. Zur Simulation dieser Situation stellten wir in vitro transkribierte RNA dieses Gens her und elektroporierten diese in Zielzellen. Transkriptionsanalysen solcher Transfektanden mit Affymetrix Oligonukleotid Mikroarray deckten auf gesamt-genomischer Ebene ganze Kaskaden konsekutiver, transkriptioneller Alterationen auf.

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In the first chapter, we consider the joint estimation of objective and risk-neutral parameters for SV option pricing models. We propose a strategy which exploits the information contained in large heterogeneous panels of options, and we apply it to S&P 500 index and index call options data. Our approach breaks the stochastic singularity between contemporaneous option prices by assuming that every observation is affected by measurement error. We evaluate the likelihood function by using a MC-IS strategy combined with a Particle Filter algorithm. The second chapter examines the impact of different categories of traders on market transactions. We estimate a model which takes into account traders’ identities at the transaction level, and we find that the stock prices follow the direction of institutional trading. These results are carried out with data from an anonymous market. To explain our estimates, we examine the informativeness of a wide set of market variables and we find that most of them are unambiguously significant to infer the identity of traders. The third chapter investigates the relationship between the categories of market traders and three definitions of financial durations. We consider trade, price and volume durations, and we adopt a Log-ACD model where we include information on traders at the transaction level. As to trade durations, we observe an increase of the trading frequency when informed traders and the liquidity provider intensify their presence in the market. For price and volume durations, we find the same effect to depend on the state of the market activity. The fourth chapter proposes a strategy to express order aggressiveness in quantitative terms. We consider a simultaneous equation model to examine price and volume aggressiveness at Euronext Paris, and we analyse the impact of a wide set of order book variables on the price-quantity decision.

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Obiettivo del lavoro è migliorare la lettura della ruralità europea. A fronte delle profonde trasformazioni avvenute, oggi non è più possibile analizzare i territori rurali adottando un mero approccio dicotomico che semplicemente li distingua dalle città. Al contrario, il lavoro integra l’analisi degli aspetti socio-economici con quella degli elementi territoriali, esaltando le principali dimensioni che caratterizzano le tante tipologie di ruralità oggi presenti in Europa. Muovendo dal dibattito sulla classificazione delle aree rurali, si propone dapprima un indicatore sintetico di ruralità che, adottando la logica fuzzy, considera congiuntamente aspetti demografici (densità), settoriali (rilevanza dell’attività agricola), territoriali e geografici (accessibilità e uso del suolo). Tale tecnica permette di ricostruire un continuum di gradi di ruralità, distinguendo così, all’interno dell’Unione Europea (circa 1.300 osservazioni), le aree più centrali da quelle progressivamente più rurali e periferiche. Successivamente, attraverso un’analisi cluster vengono individuate tipologie di aree omogenee in termini di struttura economica, paesaggio, diversificazione dell’attività agricola. Tali cluster risentono anche della distribuzione geografica delle aree stesse: vengono infatti distinti gruppi di regioni centrali da gruppi di regioni più periferiche. Tale analisi evidenzia soprattutto come il binomio ruralità-arretratezza risulti ormai superato: alcune aree rurali, infatti, hanno tratto vantaggio dalle trasformazioni che hanno interessato l’Unione Europea negli ultimi decenni (diffusione dell’ICT o sviluppo della manifattura). L’ultima parte del lavoro offre strumenti di analisi a supporto dell’azione politica comunitaria, analizzando la diversa capacità delle regioni europee di rispondere alle sfide lanciate dalla Strategia Europa 2020. Un’analisi in componenti principali sintetizza le principali dimensioni di tale performance regionale: i risultati sono poi riletti alla luce delle caratteristiche strutturali dei territori europei. Infine, una più diretta analisi spaziale dei dati permette di evidenziare come la geografia influenzi ancora profondamente la capacità dei territori di rispondere alle nuove sfide del decennio.

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The production of the Z boson in proton-proton collisions at the LHC serves as a standard candle at the ATLAS experiment during early data-taking. The decay of the Z into an electron-positron pair gives a clean signature in the detector that allows for calibration and performance studies. The cross-section of ~ 1 nb allows first LHC measurements of parton density functions. In this thesis, simulations of 10 TeV collisions at the ATLAS detector are studied. The challenges for an experimental measurement of the cross-section with an integrated luminositiy of 100 pb−1 are discussed. In preparation for the cross-section determination, the single-electron efficiencies are determined via a simulation based method and in a test of a data-driven ansatz. The two methods show a very good agreement and differ by ~ 3% at most. The ingredients of an inclusive and a differential Z production cross-section measurement at ATLAS are discussed and their possible contributions to systematic uncertainties are presented. For a combined sample of signal and background the expected uncertainty on the inclusive cross-section for an integrated luminosity of 100 pb−1 is determined to 1.5% (stat) +/- 4.2% (syst) +/- 10% (lumi). The possibilities for single-differential cross-section measurements in rapidity and transverse momentum of the Z boson, which are important quantities because of the impact on parton density functions and the capability to check for non-pertubative effects in pQCD, are outlined. The issues of an efficiency correction based on electron efficiencies as function of the electron’s transverse momentum and pseudorapidity are studied. A possible alternative is demonstrated by expanding the two-dimensional efficiencies with the additional dimension of the invariant mass of the two leptons of the Z decay.

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Falls are common and burdensome accidents among the elderly. About one third of the population aged 65 years or more experience at least one fall each year. Fall risk assessment is believed to be beneficial for fall prevention. This thesis is about prognostic tools for falls for community-dwelling older adults. We provide an overview of the state of the art. We then take different approaches: we propose a theoretical probabilistic model to investigate some properties of prognostic tools for falls; we present a tool whose parameters were derived from data of the literature; we train and test a data-driven prognostic tool. Finally, we present some preliminary results on prediction of falls through features extracted from wearable inertial sensors. Heterogeneity in validation results are expected from theoretical considerations and are observed from empirical data. Differences in studies design hinder comparability and collaborative research. According to the multifactorial etiology of falls, assessment on multiple risk factors is needed in order to achieve good predictive accuracy.

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The Standard Model of particle physics was developed to describe the fundamental particles, which form matter, and their interactions via the strong, electromagnetic and weak force. Although most measurements are described with high accuracy, some observations indicate that the Standard Model is incomplete. Numerous extensions were developed to solve these limitations. Several of these extensions predict heavy resonances, so-called Z' bosons, that can decay into an electron positron pair. The particle accelerator Large Hadron Collider (LHC) at CERN in Switzerland was built to collide protons at unprecedented center-of-mass energies, namely 7 TeV in 2011. With the data set recorded in 2011 by the ATLAS detector, a large multi-purpose detector located at the LHC, the electron positron pair mass spectrum was measured up to high masses in the TeV range. The properties of electrons and the probability that other particles are mis-identified as electrons were studied in detail. Using the obtained information, a sophisticated Standard Model expectation was derived with data-driven methods and Monte Carlo simulations. In the comparison of the measurement with the expectation, no significant deviations from the Standard Model expectations were observed. Therefore exclusion limits for several Standard Model extensions were calculated. For example, Sequential Standard Model (SSM) Z' bosons with masses below 2.10 TeV were excluded with 95% Confidence Level (C.L.).

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The Standard Model of particle physics is a very successful theory which describes nearly all known processes of particle physics very precisely. Nevertheless, there are several observations which cannot be explained within the existing theory. In this thesis, two analyses with high energy electrons and positrons using data of the ATLAS detector are presented. One, probing the Standard Model of particle physics and another searching for phenomena beyond the Standard Model.rnThe production of an electron-positron pair via the Drell-Yan process leads to a very clean signature in the detector with low background contributions. This allows for a very precise measurement of the cross-section and can be used as a precision test of perturbative quantum chromodynamics (pQCD) where this process has been calculated at next-to-next-to-leading order (NNLO). The invariant mass spectrum mee is sensitive to parton distribution functions (PFDs), in particular to the poorly known distribution of antiquarks at large momentum fraction (Bjoerken x). The measurementrnof the high-mass Drell-Yan cross-section in proton-proton collisions at a center-of-mass energy of sqrt(s) = 7 TeV is performed on a dataset collected with the ATLAS detector, corresponding to an integrated luminosity of 4.7 fb-1. The differential cross-section of pp -> Z/gamma + X -> e+e- + X is measured as a function of the invariant mass in the range 116 GeV < mee < 1500 GeV. The background is estimated using a data driven method and Monte Carlo simulations. The final cross-section is corrected for detector effects and different levels of final state radiation corrections. A comparison isrnmade to various event generators and to predictions of pQCD calculations at NNLO. A good agreement within the uncertainties between measured cross-sections and Standard Model predictions is observed.rnExamples of observed phenomena which can not be explained by the Standard Model are the amount of dark matter in the universe and neutrino oscillations. To explain these phenomena several extensions of the Standard Model are proposed, some of them leading to new processes with a high multiplicity of electrons and/or positrons in the final state. A model independent search in multi-object final states, with objects defined as electrons and positrons, is performed to search for these phenomenas. Therndataset collected at a center-of-mass energy of sqrt(s) = 8 TeV, corresponding to an integrated luminosity of 20.3 fb-1 is used. The events are separated in different categories using the object multiplicity. The data-driven background method, already used for the cross-section measurement was developed further for up to five objects to get an estimation of the number of events including fake contributions. Within the uncertainties the comparison between data and Standard Model predictions shows no significant deviations.

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L'informatica e le sue tecnologie nella società moderna si riassumono spesso in un assioma fuorviante: essa, infatti, è comunemente legata al concetto che ciò che le tecnologie ci offrono può essere accessibile da tutti e sfruttato, all'interno della propria quotidianità, in modi più o meno semplici. Anche se quello appena descritto è un obiettivo fondamentale del mondo high-tech, occorre chiarire subito una questione: l'informatica non è semplicemente tutto ciò che le tecnologie ci offrono, perchè questo pensiero sommario fa presagire ad un'informatica "generalizzante"; l'informatica invece si divide tra molteplici ambiti, toccando diversi mondi inter-disciplinari. L'importanza di queste tecnologie nella società moderna deve spingerci a porre domande, riflessioni sul perchè l'informatica, in tutte le sue sfaccettature, negli ultimi decenni, ha portato una vera e propria rivoluzione nelle nostre vite, nelle nostre abitudini, e non di meno importanza, nel nostro contesto lavorativo e aziendale, e non ha alcuna intenzione (per fortuna) di fermare le proprie possibilità di sviluppo. In questo trattato ci occuperemo di definire una particolare tecnica moderna relativa a una parte di quel mondo complesso che viene definito come "Intelligenza Artificiale". L'intelligenza Artificiale (IA) è una scienza che si è sviluppata proprio con il progresso tecnologico e dei suoi potenti strumenti, che non sono solo informatici, ma soprattutto teorico-matematici (probabilistici) e anche inerenti l'ambito Elettronico-TLC (basti pensare alla Robotica): ecco l'interdisciplinarità. Concetto che è fondamentale per poi affrontare il nocciolo del percorso presentato nel secondo capitolo del documento proposto: i due approcci possibili, semantico e probabilistico, verso l'elaborazione del linguaggio naturale(NLP), branca fondamentale di IA. Per quanto darò un buono spazio nella tesi a come le tecniche di NLP semantiche e statistiche si siano sviluppate nel tempo, verrà prestata attenzione soprattutto ai concetti fondamentali di questi ambiti, perché, come già detto sopra, anche se è fondamentale farsi delle basi e conoscere l'evoluzione di queste tecnologie nel tempo, l'obiettivo è quello a un certo punto di staccarsi e studiare il livello tecnologico moderno inerenti a questo mondo, con uno sguardo anche al domani: in questo caso, la Sentiment Analysis (capitolo 3). Sentiment Analysis (SA) è una tecnica di NLP che si sta definendo proprio ai giorni nostri, tecnica che si è sviluppata soprattutto in relazione all'esplosione del fenomeno Social Network, che viviamo e "tocchiamo" costantemente. L'approfondimento centrale della tesi verterà sulla presentazione di alcuni esempi moderni e modelli di SA che riguardano entrambi gli approcci (statistico e semantico), con particolare attenzione a modelli di SA che sono stati proposti per Twitter in questi ultimi anni, valutando quali sono gli scenari che propone questa tecnica moderna, e a quali conseguenze contestuali (e non) potrebbe portare questa particolare tecnica.