321 resultados para 380207 Linguistic Structures (incl. Grammar, Phonology, Lexicon, Semantics)
Resumo:
Social media channels, such as Facebook or Twitter, allow for people to express their views and opinions about any public topics. Public sentiment related to future events, such as demonstrations or parades, indicate public attitude and therefore may be applied while trying to estimate the level of disruption and disorder during such events. Consequently, sentiment analysis of social media content may be of interest for different organisations, especially in security and law enforcement sectors. This paper presents a new lexicon-based sentiment analysis algorithm that has been designed with the main focus on real time Twitter content analysis. The algorithm consists of two key components, namely sentiment normalisation and evidence-based combination function, which have been used in order to estimate the intensity of the sentiment rather than positive/negative label and to support the mixed sentiment classification process. Finally, we illustrate a case study examining the relation between negative sentiment of twitter posts related to English Defence League and the level of disorder during the organisation’s related events.
Resumo:
This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds' algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). We enhance our procedure with a new score function that only takes into account arcs that are relevant to predict the class, as well as an optimization over the equivalent sample size during learning. These ideas may be useful for structure learning of Bayesian networks in general. A range of experiments shows that we obtain models with better prediction accuracy than naive Bayes and TAN, and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator (AODE). We release our implementation of ETAN so that it can be easily installed and run within Weka.
Resumo:
Research in emotion analysis of text suggest that emotion lexicon based features are superior to corpus based n-gram features. However the static nature of the general purpose emotion lexicons make them less suited to social media analysis, where the need to adopt to changes in vocabulary usage and context is crucial. In this paper we propose a set of methods to extract a word-emotion lexicon automatically from an emotion labelled corpus of tweets. Our results confirm that the features derived from these lexicons outperform the standard Bag-of-words features when applied to an emotion classification task. Furthermore, a comparative analysis with both manually crafted lexicons and a state-of-the-art lexicon generated using Point-Wise Mutual Information, show that the lexicons generated from the proposed methods lead to significantly better classi- fication performance.
Resumo:
The collective response of charged particles to intense fields is intrinsic to plasma accelerators and radiation sources, relativistic optics and many astrophysical phenomena. Here we show that a relativistic plasma aperture is generated in thin foils by intense laser light, resulting in the fundamental optical process of diffraction. The plasma electrons collectively respond to the resulting laser near-field diffraction pattern, producing a beam of energetic electrons with a spatial structure that can be controlled by variation of the laser pulse parameters. It is shown that static electron-beam and induced-magnetic-field structures can be made to rotate at fixed or variable angular frequencies depending on the degree of ellipticity in the laser polarization. The concept is demonstrated numerically and verified experimentally, and is an important step towards optical control of charged particle dynamics in laser-driven dense plasma sources.
Resumo:
Here we review the recent progress made in the detection, examination, characterisation and interpretation of oscillations manifesting in small-scale magnetic elements in the solar photosphere. This region of the Sun's atmosphere is especially dynamic, and importantly, permeated with an abundance of magnetic field concentrations. Such magnetic features can span diameters of hundreds to many tens of thousands of km, and are thus commonly referred to as the `building blocks' of the magnetic solar atmosphere. However, it is the smallest magnetic elements that have risen to the forefront of solar physics research in recent years. Structures, which include magnetic bright points, are often at the diffraction limit of even the largest of solar telescopes. Importantly, it is the improvements in facilities, instrumentation, imaging techniques and processing algorithms during recent years that have allowed researchers to examine the motions, dynamics and evolution of such features on the smallest spatial and temporal scales to date. It is clear that while these structures may demonstrate significant magnetic field strengths, their small sizes make them prone to the buffeting supplied by the ubiquitous surrounding convective plasma motions. Here, it is believed that magnetohydrodynamic waves can be induced, which propagate along the field lines, carrying energy upwards to the outermost extremities of the solar corona. Such wave phenomena can exist in a variety of guises, including fast and slow magneto-acoustic modes, in addition to Alfven waves. Coupled with rapid advancements in magnetohydrodynamic wave theory, we are now in an ideal position to thoroughly investigate how wave motion is generated in the solar photosphere, which oscillatory modes are most prevalent, and the role that these waves play in supplying energy to various layers of the solar atmosphere.
Resumo:
Due to its complex and dynamic fine-scale structure, the chromosphere is a particularly challenging region of the Sun's atmosphere to understand. It is now widely accepted that to model chromospheric dynamics, even on a magnetohydrodynamic (MHD) scale, while also calculating spectral line emission, one must realistically include the effects of partial ionization and radiative transfer in a multi-fluid plasma under non-LTE conditions. Accurate quantification of MHD wave energetics must befounded on a precise identification of the actual wave mode being observed. This chapter focuses on MHD kink-mode identification, MHD sausage mode identification, and MHD torsional Alfvén wave identification. It then reviews progress in determining more accurate energy flux estimations of specific MHD wave modes observed in the chromosphere. The chapter finally examines how the discovery of these MHD wave modes has helped us advance the field of chromosphericmagnetoseismology.
Resumo:
This chapter reviews the recent observations of waves and oscillations manifesting in fine-scale magnetic structures in the solar photosphere, which are often interpreted as the "building blocks' of the magnetic Sun. The authors found, through phase relationships between the various waveforms, that small-scale magnetic bright points (MBPs) in the photosphere demonstrated signatures of specific magnetoacoustic waves, in particular the sausage and kink modes. Modern magnetohydrodynamic (MHD) simulations of the lower solar atmosphere clearly show how torsional motions can easily be induced in magnetic elements in the photosphere through the processes of vortical motions and/or buffeting by neighboring granules. The authors detected significant power associated with high-frequency horizontal motions, and suggested that these cases may be especially important in the creation of a turbulent environment that efficiently promotes Alfvén wave dissipation.
Resumo:
A 3D intralaminar continuum damage mechanics based material model, combining damage mode interaction and material nonlinearity, was developed to predict the damage response of composite structures undergoing crush loading. This model captures the structural response without the need for calibration of experimentally determined material parameters. When used in the design of energy absorbing composite structures, it can reduce the dependence on physical testing. This paper validates this model against experimental data obtained from the literature and in-house testing. Results show that the model can predict the force response of the crushed composite structures with good accuracy. The simulated energy absorption in each test case was within 12% of the experimental value. Post-crush deformation and the damage morphologies, such as ply splitting, splaying and breakage, were also accurately reproduced. This study establishes the capability of this damage model for predicting the responses of composite structures under crushing loads.
Resumo:
The development of the latest generation of wide-body carbon-fibre composite passenger aircraft has heralded a new era in the utilisation of these materials. The premise of superior specific strength and stiffness, corrosion and fatigue resistance, is tempered by high development costs, slow production rates and lengthy and expensive certification programmes. Substantial effort is currently being directed towards the development of new modelling and simulation tools, at all levels of the development cycle, to mitigate these shortcomings. One of the primary challenges is to reduce the extent of physical testing, in the certification process, by adopting a ‘certification by simulation’ approach. In essence, this aspirational objective requires the ability to reliably predict the evolution and progression of damage in composites. The aerospace industry has been at the forefront of developing advanced composites modelling tools. As the automotive industry transitions towards the increased use of composites in mass-produced vehicles, similar challenges in the modelling of composites will need to be addressed, particularly in the reliable prediction of crashworthiness. While thermoset composites have dominated the aerospace industry, thermoplastics composites are likely to emerge as the preferred solution for meeting the high-volume production demands of passenger road vehicles. This keynote presentation will outline recent progress and current challenges in the development of finite-element-based predictive modelling tools for capturing impact damage, residual strength and energy absorption capacity of thermoset and thermoplastic composites for crashworthiness assessments.
Resumo:
An overview of research on the development of the hybrid test method is presented. The maturity of the hybrid test method is mapped in order to provide context to individual research in the overall development of the test method. In the pseudo dynamic (PsD) test method, the equations of motion are solved using a time stepping numerical integration technique with the inertia and damping being numerically modelled whilst restoring force is physically measured over an extended timescale. Developments in continuous PsD testing led to the real-time hybrid test method and geographically distributed hybrid tests. A key aspect to the efficiency of hybrid testing is the substructuring technique where the critical structural subassemblies that are fundamental to the overall response of the structure are physically tested whilst the remainder of the structure whose response can be more easily predicted is numerically modelled. Much of the early research focused on developing the accuracy and efficiency of the test method, whereas more recently the method has matured to a level where the test method is applied purely as a dynamic testing technique. Developments in numerical integration methods, substructuring, experimental error reduction, delay compensation and speed of testing have led to a test method now in use as full-scale real-time dynamic testing method that is reliable, accurate, efficient and cost effective.
Resumo:
BACKGROUND: Healthcare integration is a priority in many countries, yet there remains little direction on how to systematically evaluate this construct to inform further development. The examination of community-based palliative care networks provides an ideal opportunity for the advancement of integration measures, in consideration of how fundamental provider cohesion is to effective care at end of life.
AIM: This article presents a variable-oriented analysis from a theory-based case study of a palliative care network to help bridge the knowledge gap in integration measurement.
DESIGN: Data from a mixed-methods case study were mapped to a conceptual framework for evaluating integrated palliative care and a visual array depicting the extent of key factors in the represented palliative care network was formulated.
SETTING/PARTICIPANTS: The study included data from 21 palliative care network administrators, 86 healthcare professionals, and 111 family caregivers, all from an established palliative care network in Ontario, Canada.
RESULTS: The framework used to guide this research proved useful in assessing qualities of integration and functioning in the palliative care network. The resulting visual array of elements illustrates that while this network performed relatively well at the multiple levels considered, room for improvement exists, particularly in terms of interventions that could facilitate the sharing of information.
CONCLUSION: This study, along with the other evaluative examples mentioned, represents important initial attempts at empirically and comprehensively examining network-integrated palliative care and healthcare integration in general.