188 resultados para plausibility


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Gemstone Team LEAF (Light Energy Acquisition of the Future)

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Pezdek, Blandon-Gitlin, and Gabbay (2006) found that perceptions of the plausibility of events increase the likelihood that imagination may induce false memories of those events. Using a survey conducted by Gallup, we asked a large sample of the general population how plausible it would be for a person with longstanding emotional problems and a need for psychotherapy to be a victim of childhood sexual abuse, even though the person could not remember the abuse. Only 18% indicated that it was implausible or very implausible, whereas 67% indicated that such an occurrence was either plausible or very plausible. Combined with Pezdek et al.s' findings, and counter to their conclusions, our findings imply that there is a substantial danger of inducing false memories of childhood sexual abuse through imagination in psychotherapy.

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Fredholm integral equations of the first kind are the mathematical model common to several electromagnetic, optical and acoustical inverse scattering problems. In most of these problems the solution must be positive in order to satisfy physical plausibility. We consider ill-posed deconvolution problems and investigate several linear regularization algorithms which provide positive approximate solutions at least in the absence of errors on the data.

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In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, we reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: "The Jama Model. On Legal Narratives and Interpretation Patterns"), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story, is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability was infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for AI researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially bayesian probability) in accounts of evidence has been flouishing among legal scholars. Nowadays both the the Bayesians (e.g. Peter Tillers) and Bayesioskeptics (e.g. Ron Allen) among those legal scholars whoare involved in the controversy are willing to give AI researchers a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application or probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making (Rosoni 1995). Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

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In judicial decision making, the doctrine of chances takes explicitly into account the odds. There is more to forensic statistics, as well as various probabilistic approaches, which taken together form the object of an enduring controversy in the scholarship of legal evidence. In this paper, I reconsider the circumstances of the Jama murder and inquiry (dealt with in Part I of this paper: 'The JAMA Model and Narrative Interpretation Patterns'), to illustrate yet another kind of probability or improbability. What is improbable about the Jama story is actually a given, which contributes in terms of dramatic underlining. In literary theory, concepts of narratives being probable or improbable date back from the eighteenth century, when both prescientific and scientific probability were infiltrating several domains, including law. An understanding of such a backdrop throughout the history of ideas is, I claim, necessary for Artificial Intelligence (AI) researchers who may be tempted to apply statistical methods to legal evidence. The debate for or against probability (and especially Bayesian probability) in accounts of evidence has been flourishing among legal scholars; nowadays both the Bayesians (e.g. Peter Tillers) and the Bayesio-skeptics (e.g. Ron Allen), among those legal scholars who are involved in the controversy, are willing to give AI research a chance to prove itself and strive towards models of plausibility that would go beyond probability as narrowly meant. This debate within law, in turn, has illustrious precedents: take Voltaire, he was critical of the application of probability even to litigation in civil cases; take Boole, he was a starry-eyed believer in probability applications to judicial decision making. Not unlike Boole, the founding father of computing, nowadays computer scientists approaching the field may happen to do so without full awareness of the pitfalls. Hence, the usefulness of the conceptual landscape I sketch here.

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El rol desempeñado por la opinión pública en el desarrollo de la política criminal actual justifica el incremento de investigaciones destinadas a evaluar las actitudes de los ciudadanos hacia el castigo. No obstante, los avances en este ámbito han sido limitados debido a la utilización de rudimentarios instrumentos de medida. Por ello, el presente trabajo tiene como propósito explorar el efecto que generan en la opinión ciudadana ciertas variables referidas al hecho delictivo y al infractor, precisando su contribución relativa y la interacción existente entre ellas. Para satisfacer este objetivo se recurrió a un diseño factorial de la encuesta, creando una población de 256 casos-escenario fruto de la combinación de cuatro factores: la edad del joven, su historial delictivo, el grado de implicación en el hecho y el tipo de delito cometido. Los mismos fueron distribuidos en grupos de ocho casos ordenados aleatoriamente y fueron suministrados a 32 sujetos. Posteriormente se aplicaron análisis de regresión logística binaria. Los resultados obtenidos revelan que la naturaleza violenta de los hechos, la implicación activa de los jóvenes y el historial delictivo son predictores importantes de las condenas punitivas. Sin embargo la edad, una variable fundamental en la configuración de la justicia juvenil, no resulta significativa. De este modo, el trabajo muestra el potencial explicativo de este conjunto de factores y debate sus implicaciones teóricas y metodológicas para la investigación futura en este terreno.

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Modern scientific world-view has undermined traditional myths, the functional survival of which seems to depend today in the West on a positivist justification. This would place them in the field of real History, through their study and revitalization by pseudoscientific disciplines such as the Atlantis and the ancient astronaut hypotheses. These have inspired new epic poems in (regular) verse that combine classic and/or biblical myths with a (pseudo)scientific modern world-view. For example, the critical rewriting of Noah’s myth by using the ancient astronaut hypothesis as a fictional device to produce a contemporary kind of plausibility allowed Abel Montagut to renew epic poetry, updating it also by adopting science fiction chronotopes in order to structure his fictional construction and to generate a high ethical sense for our time. Thus, his Poemo de Utnoa (1993) / La gesta d’Utnoa (1996), which has become a major classic of the literature in Esperanto thanks to its original version in this language, is a landmark of both science fiction and neo-biblical epics. This poem is written from a secular and purely literary perspective.

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Continuous large-scale changes in technology and the globalization of markets have resulted in the need for many SMEs to use innovation as a means of seeking competitive advantage where innovation includes both technological and organizational perspectives (Tapscott, 2009). However, there is a paucity of systematic and empirical research relating to the implementation of innovation management in the context of SMEs. The aim of this article is to redress this imbalance via an empirical study created to develop and test a model of innovation implementation in SMEs. This study uses Structural Equation Modelling (SEM) to test the plausibility of an innovation model, developed from earlier studies, as the basis of a questionnaire survey of 395 SMEs in the UK. The resultant model and construct relationship results are further probed using an explanatory multiple case analysis to explore ‘how’ and ‘why’ type questions within the model and construct relationships. The findings show that the
effects of leadership, people and culture on innovation implementation are mediated by business improvement activities relating to Total Quality Management/Continuous Improvement (TQM/CI) and product and process developments. It is concluded that SMEs have an opportunity to leverage existing quality and process improvement activities to move beyond continuous
improvement outcomes towards effective innovation implementation. The article concludes by suggesting areas suitable for further research.

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From late 2008 onwards, in the space of six months, international financial regulatory networks centred around the Swiss city of Basel presided over a startlingly rapid ideational shift, the significance and importance of which remains to be deciphered. From being relatively unpopular and very much on the sidelines, the idea of macroprudential regulation (MPR) moved to the centre of the policy agenda and came to represent a new Basel consensus, as the principal interpretative frame, for financial technocrats and regulators seeking to diagnose and understand the financial crisis and to advance institutional blueprints for regulatory reform. This article sets out to explain how and why that ideational shift occurred. It identifies four scoping conditions of presence, position, promotion, and plausibility, that account for the successful rise to prominence of macroprudential ideas through an insiders' coup d'état. The final section of the article argues that this macroprudential shift is an example of a ‘gestalt flip’ or third order change in Peter Hall's terms, but it is not yet a paradigm shift, because the development of first order policy settings and second order policy instruments is still ongoing, giving the macroprudential ideational shift a highly contested and contingent character.

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The features of two popular models used to describe the observed response characteristics of typical oxygen optical sensors based on luminescence quenching are examined critically. The models are the 'two-site' and 'Gaussian distribution in natural lifetime, tau(o),' models. These models are used to characterise the response features of typical optical oxygen sensors; features which include: downward curving Stern-Volmer plots and increasingly non-first order luminescence decay kinetics with increasing partial pressures of oxygen, pO(2). Neither model appears able to unite these latter features, let alone the observed disparate array of response features exhibited by the myriad optical oxygen sensors reported in the literature, and still maintain any level of physical plausibility. A model based on a Gaussian distribution in quenching rate constant, k(q), is developed and, although flawed by a limited breadth in distribution, rho, does produce Stern-Volmer plots which would cover the range in curvature seen with real optical oxygen sensors. A new 'log-Gaussian distribution in tau(o) or k(q)' model is introduced which has the advantage over a Gaussian distribution model of placing no limitation on the value of rho. Work on a 'log-Gaussian distribution in tau(o)' model reveals that the Stern-Volmer quenching plots would show little degree in curvature, even at large rho values and the luminescence decays would become increasingly first order with increasing pO(2). In fact, with real optical oxygen sensors, the opposite is observed and thus the model appears of little value. In contrast, a 'log-Gaussian distribution in k(o)' model does produce the trends observed with real optical oxygen sensors; although it is technically restricted in use to those in which the kinetics of luminescence decay are good first order in the absence of oxygen. The latter model gives a good fit to the major response features of sensors which show the latter feature, most notably the [Ru(dpp)(3)(2+)(Ph4B-)(2)] in cellulose optical oxygen sensors. The scope of a log-Gaussian model for further expansion and, therefore, application to optical oxygen sensors, by combining both a log-Gaussian distribution in k(o) with one in tau(o) is briefly discussed.

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Morphometric study of modern ice masses is useful because many reconstructions of glaciers traditionally draw on their shape for guidance Here we analyse data derived from the surface profiles of 200 modern ice masses-valley glaciers icefields ice caps and ice sheets with length scales from 10º to 10³ km-from different parts of the world Four profile attributes are investigated relief span and two parameters C* and C that result from using Nye s (1952) theoretical parabola as a profile descriptor C* and C respectively measure each profile s aspect ratio and steepness and are found to decrease in size and variability with span This dependence quantifies the competing influences of unconstrained spreading behaviour of ice flow and bed topography on the profile shape of ice masses which becomes more parabolic as span Increases (with C* and C tending to low values of 2.5-3.3 m ½) The same data reveal coherent minimum bounds in C* and C for modern ice masses that we develop into two new methods of palaeo glacier reconstruction In the first method glacial limits are known from moraines and the bounds are used to constrain the lowest palaeo ice surface consistent with modern profiles We give an example of applying this method over a three-dimensional glacial landscape in Kamchatka In the second method we test the plausibility of existing reconstructions by comparing their C* and C against the modern minimum bounds Of the 86 published palaeo ice masses that we put to this test 88% are found to be plausible The search for other morphometric constraints will help us formalise glacier reconstructions and reduce their uncertainty and subjectiveness

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In this paper, we introduce an application of matrix factorization to produce corpus-derived, distributional
models of semantics that demonstrate cognitive plausibility. We find that word representations
learned by Non-Negative Sparse Embedding (NNSE), a variant of matrix factorization, are sparse,
effective, and highly interpretable. To the best of our knowledge, this is the first approach which
yields semantic representation of words satisfying these three desirable properties. Though extensive
experimental evaluations on multiple real-world tasks and datasets, we demonstrate the superiority
of semantic models learned by NNSE over other state-of-the-art baselines.

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Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.

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This paper proposes a discrete mixture model which assigns individuals, up to a probability, to either a class of random utility (RU) maximizers or a class of random regret (RR) minimizers, on the basis of their sequence of observed choices. Our proposed model advances the state of the art of RU-RR mixture models by (i) adding and simultaneously estimating a membership model which predicts the probability of belonging to a RU or RR class; (ii) adding a layer of random taste heterogeneity within each behavioural class; and (iii) deriving a welfare measure associated with the RU-RR mixture model and consistent with referendum-voting, which is the adequate mechanism of provision for such local public goods. The context of our empirical application is a stated choice experiment concerning traffic calming schemes. We find that the random parameter RU-RR mixture model not only outperforms its fixed coefficient counterpart in terms of fit-as expected-but also in terms of plausibility of membership determinants of behavioural class. In line with psychological theories of regret, we find that, compared to respondents who are familiar with the choice context (i.e. the traffic calming scheme), unfamiliar respondents are more likely to be regret minimizers than utility maximizers. © 2014 Elsevier Ltd.

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Within the complex of deep, hypersaline anoxic lakes (DHALs) of the Mediterranean Ridge, we identified a new, unexplored DHAL and named it ‘Lake Kryos’ after a nearby depression. This lake is filled with magnesium chloride (MgCl2)-rich, athalassohaline brine (salinity > 470 practical salinity units), presumably formed by the dissolution of Messinian bischofite. Compared with the DHAL Discovery, it contains elevated concentrations of kosmotropic sodium and sulfate ions, which are capable of reducing the net chaotropicily of MgCl2-rich solutions. The brine of Lake Kryos may therefore be biologically permissive at MgCl2 concentrations previously considered incompatible with life. We characterized the microbiology of the seawater–Kryos brine interface and managed to recover mRNA from the 2.27–3.03 MMgCl2 layer (equivalent to 0.747–0.631 water activity), thereby expanding the established chaotropicity window-for-life. The primary bacterial taxa present there were Kebrit Deep Bacteria 1 candidate division and DHAL-specific group of organisms, distantly related toDesulfohalobium. Two euryarchaeal candidate divisions, Mediterranean Sea Brine Lakes group 1 and halophilic cluster 1, accounted for > 85% of the rRNA-containing archaeal clones derived from the 2.27–3.03 M MgCl2 layer, but were minority community-members in the overlying interface-layers. These findings shed light on the plausibility of life in highly chaotropic environments, geochemical windows for microbial extremophiles, and have implications for habitability elsewhere in the Solar System.