7 resultados para Latent trigger point

em Universidade do Minho


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"Published online before print November 20, 2015"

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telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

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Tese de Doutoramento em Ciências da Saúde

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[Excerpt] Synchronization of periodic movements like side-by-side walking [7] is frequently modeled by coupled oscillators [5] and the coupling strength is defined quantitatively [3]. In contrast, in most studies on sensorimotor synchronization (SMS), simple movements like finger taps are synchronized with simple stimuli like metronomes [4]. While the latter paradigm simplifies matters and allows for the assessment of the relative weights of sensory modalities through systematic variation of the stimuli [1], it might lack ecological validity. Conversely, using more complex movements and stimuli might complicate the specification of mechanisms underlying coupling. We merged the positive aspects of both approaches to study the contribution of auditory and visual information on synchronization during side-by-side walking. As stimuli, we used Point Light Walkers (PLWs) and auralized steps sound; both were constructed from previously captured walking individuals [2][6]. PLWs were retro-projected on a screen and matched according to gender, hip height, and velocity. The participant walked for 7.20m side by side with 1) a PLW, 2) steps sound, or 3) both displayed in temporal congruence. Instruction to participants was to synchronize with the available stimuli. [...]

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The performance of the ATLAS muon trigger system has been evaluated with proton--proton collision data collected in 2012 at the Large Hadron Collider at a centre-of-mass energy of 8 TeV. The performance was primarily evaluated using events containing a pair of muons from the decay of Z bosons. The efficiency is measured for the single-muon trigger for a kinematic region of the transverse momentum pT between 25 and 100 GeV, with a statistical uncertainty of less than 0.01% and a systematic uncertainty of 0.6%. The performance is also compared in detail to the predictions from simulation. The efficiency was measured over a wide pT range (a few GeV to several hundred GeV) by using muons from J/ψ mesons,W bosons, and top and antitop quarks. It showed highly uniform and stable performance.

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Many extensions of the Standard Model posit the existence of heavy particles with long lifetimes. This article presents the results of a search for events containing at least one long-lived particle that decays at a significant distance from its production point into two leptons or into five or more charged particles. This analysis uses a data sample of proton-proton collisions at s√ = 8 TeV corresponding to an integrated luminosity of 20.3 fb−1 collected in 2012 by the ATLAS detector operating at the Large Hadron Collider. No events are observed in any of the signal regions, and limits are set on model parameters within supersymmetric scenarios involving R-parity violation, split supersymmetry, and gauge mediation. In some of the search channels, the trigger and search strategy are based only on the decay products of individual long-lived particles, irrespective of the rest of the event. In these cases, the provided limits can easily be reinterpreted in different scenarios.

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Here we focus on factor analysis from a best practices point of view, by investigating the factor structure of neuropsychological tests and using the results obtained to illustrate on choosing a reasonable solution. The sample (n=1051 individuals) was randomly divided into two groups: one for exploratory factor analysis (EFA) and principal component analysis (PCA), to investigate the number of factors underlying the neurocognitive variables; the second to test the "best fit" model via confirmatory factor analysis (CFA). For the exploratory step, three extraction (maximum likelihood, principal axis factoring and principal components) and two rotation (orthogonal and oblique) methods were used. The analysis methodology allowed exploring how different cognitive/psychological tests correlated/discriminated between dimensions, indicating that to capture latent structures in similar sample sizes and measures, with approximately normal data distribution, reflective models with oblimin rotation might prove the most adequate.