979 resultados para Context sensitivity
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This paper examines the intellectual and professional contribution of comparative and international studies to the field of education. It explores the nature of the challenges that are currently being faced, and assesses its potential for the advancement of future teaching, research and professional development. Attention is paid to the place of comparative and international education (CIE)-past and present-in teacher education, in postgraduate studies, and in the realms of policy and practice, theory and research. Consideration is first given to the nature and history of CIE, to its initial contributions to the field of education in the UK, and to its chief mechanisms and sites of production. Influential methodological and theoretical developments are examined, followed by an exploration of emergent questions, controversies and dilemmas that could benefit from sustained comparative analysis in the future. Conclusions consider implications for the place of CIE in the future of educational studies as a whole; for relations between and beyond the 'disciplines of education'; and for the development of sustainable research capacity in this field.
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A method for context-sensitive analysis of binaries that may have obfuscated procedure call and return operations is presented. Such binaries may use operators to directly manipulate stack instead of using native call and ret instructions to achieve equivalent behavior. Since definition of context-sensitivity and algorithms for context-sensitive analysis have thus far been based on the specific semantics associated to procedure call and return operations, classic interprocedural analyses cannot be used reliably for analyzing programs in which these operations cannot be discerned. A new notion of context-sensitivity is introduced that is based on the state of the stack at any instruction. While changes in 'calling'-context are associated with transfer of control, and hence can be reasoned in terms of paths in an interprocedural control flow graph (ICFG), the same is not true of changes in 'stack'-context. An abstract interpretation based framework is developed to reason about stack-contexts and to derive analogues of call-strings based methods for the context-sensitive analysis using stack-context. The method presented is used to create a context-sensitive version of Venable et al.'s algorithm for detecting obfuscated calls. Experimental results show that the context-sensitive version of the algorithm generates more precise results and is also computationally more efficient than its context-insensitive counterpart. Copyright © 2010 ACM.
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Since Sharir and Pnueli, algorithms for context-sensitivity have been defined in terms of 'valid' paths in an interprocedural flow graph. The definition of valid paths requires atomic call and ret statements, and encapsulated procedures. Thus, the resulting algorithms are not directly applicable when behavior similar to call and ret instructions may be realized using non-atomic statements, or when procedures do not have rigid boundaries, such as with programs in low level languages like assembly or RTL. We present a framework for context-sensitive analysis that requires neither atomic call and ret instructions, nor encapsulated procedures. The framework presented decouples the transfer of control semantics and the context manipulation semantics of statements. A new definition of context-sensitivity, called stack contexts, is developed. A stack context, which is defined using trace semantics, is more general than Sharir and Pnueli's interprocedural path based calling-context. An abstract interpretation based framework is developed to reason about stack-contexts and to derive analogues of calling-context based algorithms using stack-context. The framework presented is suitable for deriving algorithms for analyzing binary programs, such as malware, that employ obfuscations with the deliberate intent of defeating automated analysis. The framework is used to create a context-sensitive version of Venable et al.'s algorithm for analyzing x86 binaries without requiring that a binary conforms to a standard compilation model for maintaining procedures, calls, and returns. Experimental results show that a context-sensitive analysis using stack-context performs just as well for programs where the use of Sharir and Pnueli's calling-context produces correct approximations. However, if those programs are transformed to use call obfuscations, a contextsensitive analysis using stack-context still provides the same, correct results and without any additional overhead. © Springer Science+Business Media, LLC 2011.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Ubiquitous Computing promises seamless access to a wide range of applications and Internet based services from anywhere, at anytime, and using any device. In this scenario, new challenges for the practice of software development arise: Applications and services must keep a coherent behavior, a proper appearance, and must adapt to a plenty of contextual usage requirements and hardware aspects. Especially, due to its interactive nature, the interface content of Web applications must adapt to a large diversity of devices and contexts. In order to overcome such obstacles, this work introduces an innovative methodology for content adaptation of Web 2.0 interfaces. The basis of our work is to combine static adaption - the implementation of static Web interfaces; and dynamic adaptation - the alteration, during execution time, of static interfaces so as for adapting to different contexts of use. In hybrid fashion, our methodology benefits from the advantages of both adaptation strategies - static and dynamic. In this line, we designed and implemented UbiCon, a framework over which we tested our concepts through a case study and through a development experiment. Our results show that the hybrid methodology over UbiCon leads to broader and more accessible interfaces, and to faster and less costly software development. We believe that the UbiCon hybrid methodology can foster more efficient and accurate interface engineering in the industry and in the academy.
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Neurons in the songbird forebrain nucleus HVc are highly sensitive to auditory temporal context and have some of the most complex auditory tuning properties yet discovered. HVc is crucial for learning, perceiving, and producing song, thus it is important to understand the neural circuitry and mechanisms that give rise to these remarkable auditory response properties. This thesis investigates these issues experimentally and computationally.
Extracellular studies reported here compare the auditory context sensitivity of neurons in HV c with neurons in the afferent areas of field L. These demonstrate that there is a substantial increase in the auditory temporal context sensitivity from the areas of field L to HVc. Whole-cell recordings of HVc neurons from acute brain slices are described which show that excitatory synaptic transmission between HVc neurons involve the release of glutamate and the activation of both AMPA/kainate and NMDA-type glutamate receptors. Additionally, widespread inhibitory interactions exist between HVc neurons that are mediated by postsynaptic GABA_A receptors. Intracellular recordings of HVc auditory neurons in vivo provides evidence that HV c neurons encode information about temporal structure using a variety of cellular and synaptic mechanisms including syllable-specific inhibition, excitatory post-synaptic potentials with a range of different time courses, and burst-firing, and song-specific hyperpolarization.
The final part of this thesis presents two computational approaches for representing and learning temporal structure. The first method utilizes comput ational elements that are analogous to temporal combination sensitive neurons in HVc. A network of these elements can learn using local information and lateral inhibition. The second method presents a more general framework which allows a network to discover mixtures of temporal features in a continuous stream of input.
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In any enterprise, decisions need be made during the life cycle of information about its management. This requires information evaluation to take place; a little-understood process. For evaluation support to be both effective and resource efficient, some sort of automatic or semi-automatic evaluation method would be invaluable. Such a method would require an understanding of the diversity of the contexts in which evaluation takes place so that evaluation support can have the necessary context-sensitivity. This paper identifies the dimensions influencing the information evaluation process and defines the elements that characterise them, thus providing the foundations for a context-sensitive evaluation framework.
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The standard Kratzerian analysis of modal auxiliaries, such as ‘may’ and ‘can’, takes them to be univocal and context-sensitive. Our first aim is to argue for an alternative view, on which such expressions are polysemous. Our second aim is to thereby shed light on the distinction between semantic context-sensitivity and polysemy. To achieve these aims, we examine the mechanisms of polysemy and context-sensitivity and provide criteria with which they can be held apart. We apply the criteria to modal auxiliaries and show that the default hypothesis should be that they are polysemous, and not merely context-sensitive. We then respond to arguments against modal ambiguity (and thus against polysemy). Finally, we show why modal polysemy has significant philosophical implications.
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This paper identifies and examines issues of relevance for increasing effectiveness of entrepreneurial management research. These issues emerged from research into entrepreneurial behaviour and underlying motivations in Sri Lanka. Understanding of socially- and culturally-bound social actors, social actions and social outputs in entrepreneurial activity requires context-sensitivity, expressed through cognisance of institutional characteristics, the interface between cultural values and business, and historical and cultural forces which impact on entrepreneurship. We suggest that this requires exploration through bottom-up translations of actions consistent with the beliefs and values of the actors involved, employing qualitative methodology to ground the reality of human behaviour in deep-rooted cultural and social contexts. Thorough interpretation of holistic case studies that are capable of capturing the actors' viewpoints brings appropriate insights to the field of entrepreneurship.
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Overconsumption of snack foods has been linked to rising rates of obesity, with our ‘obesogenic’ environment and its abundance of palatable, high-calorie foods and associated cues especially implicated. However, it is clear that some individuals are particularly susceptible to overconsumption and weight gain. It was hypothesised that individuals sensitive to the rewarding properties of palatable foods, and associated stimuli, would show elevated consumption. Snack food intake was measured in 50 adults (mean age 34.5 years, BMI 23.9 kg/m2, 56% female) in a repeated measures design, both with and without a ‘food cue’. Trait (BIS/BAS scales), behavioural (computerised CARROT) and food reward were assessed. Sensitivity to food reward, but not generalised reward, was positively associated with snack food intake. This relationship was not affected by the presence of a food cue. Findings are discussed in the context of implications for weight management.
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We investigate the utility to computational Bayesian analyses of a particular family of recursive marginal likelihood estimators characterized by the (equivalent) algorithms known as "biased sampling" or "reverse logistic regression" in the statistics literature and "the density of states" in physics. Through a pair of numerical examples (including mixture modeling of the well-known galaxy dataset) we highlight the remarkable diversity of sampling schemes amenable to such recursive normalization, as well as the notable efficiency of the resulting pseudo-mixture distributions for gauging prior-sensitivity in the Bayesian model selection context. Our key theoretical contributions are to introduce a novel heuristic ("thermodynamic integration via importance sampling") for qualifying the role of the bridging sequence in this procedure, and to reveal various connections between these recursive estimators and the nested sampling technique.
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Long considered important for professionals working with minority and under-represented populations, cross-cultural competency has become a requisite for all health care providers. As society in the US increasingly diversifies, there is a crucial need to prepare health care professionals to effectively treat this changing population. The Massachusetts General Hospital Textbook on Diversity and Cultural Sensitivity in Mental Health addresses the importance and relevance of cultural sensitivity in US mental health. Prominent researchers and clinicians examine the cultural and cross-cultural mental health issues of Native American, Latino, Asian, African American, Middle Eastern, Refugee and LGBQT communities. The discussion includes understanding the complexities in making mental health diagnoses and the various meanings it has for the socio-cultural group described, as well as biopsychosocial treatment options and challenges. In understanding the specific populations, the analysis delves into overarching concepts that may apply to specific populations and to those at the intersection of multiple cultures. An invaluable resource for mental health professionals, including clinicians, researchers, educators, leaders and advocates in the United States, The Massachusetts General Hospital Textbook on Diversity and Cultural Sensitivity in Mental Health provides the necessary understanding and insights for research and clinical practice in specific cultural and multicultural groups.