19 resultados para embedded level set

em Aston University Research Archive


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Liquid-level sensing technologies have attracted great prominence, because such measurements are essential to industrial applications, such as fuel storage, flood warning and in the biochemical industry. Traditional liquid level sensors are based on electromechanical techniques; however they suffer from intrinsic safety concerns in explosive environments. In recent years, given that optical fiber sensors have lots of well-established advantages such as high accuracy, costeffectiveness, compact size, and ease of multiplexing, several optical fiber liquid level sensors have been investigated which are based on different operating principles such as side-polishing the cladding and a portion of core, using a spiral side-emitting optical fiber or using silica fiber gratings. The present work proposes a novel and highly sensitive liquid level sensor making use of polymer optical fiber Bragg gratings (POFBGs). The key elements of the system are a set of POFBGs embedded in silicone rubber diaphragms. This is a new development building on the idea of determining liquid level by measuring the pressure at the bottom of a liquid container, however it has a number of critical advantages. The system features several FBG-based pressure sensors as described above placed at different depths. Any sensor above the surface of the liquid will read the same ambient pressure. Sensors below the surface of the liquid will read pressures that increase linearly with depth. The position of the liquid surface can therefore be approximately identified as lying between the first sensor to read an above-ambient pressure and the next higher sensor. This level of precision would not in general be sufficient for most liquid level monitoring applications; however a much more precise determination of liquid level can be made by linear regression to the pressure readings from the sub-surface sensors. There are numerous advantages to this multi-sensor approach. First, the use of linear regression using multiple sensors is inherently more accurate than using a single pressure reading to estimate depth. Second, common mode temperature induced wavelength shifts in the individual sensors are automatically compensated. Thirdly, temperature induced changes in the sensor pressure sensitivity are also compensated. Fourthly, the approach provides the possibility to detect and compensate for malfunctioning sensors. Finally, the system is immune to changes in the density of the monitored fluid and even to changes in the effective force of gravity, as might be obtained in an aerospace application. The performance of an individual sensor was characterized and displays a sensitivity (54 pm/cm), enhanced by more than a factor of 2 when compared to a sensor head configuration based on a silica FBG published in the literature, resulting from the much lower elastic modulus of POF. Furthermore, the temperature/humidity behavior and measurement resolution were also studied in detail. The proposed configuration also displays a highly linear response, high resolution and good repeatability. The results suggest the new configuration can be a useful tool in many different applications, such as aircraft fuel monitoring, and biochemical and environmental sensing, where accuracy and stability are fundamental. © (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

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This paper complements the preceding one by Clarke et al, which looked at the long-term impact of retail restructuring on consumer choice at the local level. Whereas the previous paper was based on quantitative evidence from survey research, this paper draws on the qualitative phases of the same three-year study, and in it we aim to understand how the changing forms of retail provision are experienced at the neighbourhood and household level. The empirical material is drawn from focus groups, accompanied shopping trips, diaries, interviews, and kitchen visits with eight households in two contrasting neighbourhoods in the Portsmouth area. The data demonstrate that consumer choice involves judgments of taste, quality, and value as well as more ‘objective’ questions of convenience, price, and accessibility. These judgments are related to households’ differential levels of cultural capital and involve ethical and moral considerations as well as more mundane considerations of practical utility. Our evidence suggests that many of the terms that are conventionally advanced as explanations of consumer choice (such as ‘convenience’, ‘value’, and ‘habit’) have very different meanings according to different household circumstances. To understand these meanings requires us to relate consumers’ at-store behaviour to the domestic context in which their consumption choices are embedded. Bringing theories of practice to bear on the nature of consumer choice, our research demonstrates that consumer choice between stores can be understood in terms of accessibility and convenience, whereas choice within stores involves notions of value, price, and quality. We also demonstrate that choice between and within stores is strongly mediated by consumers’ household contexts, reflecting the extent to which shopping practices are embedded within consumers’ domestic routines and complex everyday lives. The paper concludes with a summary of the overall findings of the project, and with a discussion of the practical and theoretical implications of the study.

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The following thesis instigates the discussion on corporate social responsibility (CSR) through a review of literature on the conceptualisation, determinants, and remunerations of organisational CSR engagement. The case is made for the need to draw attention to the micro-levels of CSR, and consequently focus on employee social responsibility at multiple levels of analysis. In order to further research efforts in this area, the prerequisite of an employee social responsibility behavioural measurement tool is acknowledged. Accordingly, the subsequent chapters outline the process of scale development and validation, resulting in a robust, reliable and valid employee social responsibility scale. This scale is then put to use in a field study, and the noteworthy roles of the antecedent and boundary conditions of transformational leadership, assigned CSR priority, and CSR climate are confirmed at the group and individual level. Directionality of these relationships is subsequently alluded to in a time-lagged investigation, set within a simulated business environment. The thesis collates and discusses the contributions of the findings from the research series, which highlight a consistent three-way interaction effect of transformational leadership, assigned CSR priority and CSR climate. Specifically, efforts are made to outline various avenues for future research, given the infancy of the micro-level study of employee social responsibility.

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A sudden increase in the amplitude of a component often causes its segregation from a complex tone, and shorter rise times enhance this effect. We explored whether this also occurs in implant listeners (n?=?8). Condition 1 used a 3.5-s “complex tone” comprising concurrent stimulation on five electrodes distributed across the array of the Nucleus CI24 implant. For each listener, the baseline stimulus level on each electrode was set at 50% of the dynamic range (DR). Two 1-s increments of 12.5%, 25%, or 50% DR were introduced in succession on adjacent electrodes within the “inner” three of those activated. Both increments had rise and fall times of 30 and 970 ms or vice versa. Listeners reported which increment was higher in pitch. Some listeners performed above chance for all increment sizes, but only for 50% increments did all listeners perform above chance. No significant effect of rise time was found. Condition 2 replaced amplitude increments with decrements. Only three listeners performed above chance even for 50% decrements. One exceptional listener performed well for 50% decrements with fall and rise times of 970 and 30 ms but around chance for fall and rise times of 30 and 970 ms, indicating successful discrimination based on a sudden rise back to baseline stimulation. Overall, the results suggest that implant listeners can use amplitude changes against a constant background to pick out components from a complex, but generally these must be large compared with those required in normal hearing. For increments, performance depended mainly on above-baseline stimulation of the target electrodes, not rise time. With one exception, performance for decrements was typically very poor.

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Recently researchers have started to investigate the cognitive strategic orientations of individual top managers and have pointed out these may be key in determining the direction and success of their organizations in terms of performance, but they have been unable to effectively operationalize this notion in empirical research and this is holding up knowledge development. To make a contribution that helps overcome this limitation a theoretical framework is developed which specifies the different possible cognitive strategic orientations of top managers as well as those of managers at lower organizational levels involved in the strategy process. This theoretical framework is investigated in the empirical phase of the study into strategic orientations in practice. Additional contributions to knowledge of strategic orientation are made in three main domains. Firstly, current knowledge of strategic orientation is largely limited to analysis at the level of the firm whereas there is a lack of understanding of any relationships with practice at lower organizational levels. The exploratory research undertaken for this thesis contributes to new knowledge of different rational, developmental and interactive strategic orientations of front-line managers and this contributes to a cognitive explanation for emergent strategy linked to strategy processes embedded in practice. In theorising the presence of different strategic orientations in practice the discussion highlights the importance of network and spatial embeddedness within enacted environments. Secondly, a contribution to further knowledge of the links between strategy processes and the content of strategies within a retail context is made. The research highlights different strategy processes used in practice by retail front-line managers in a branch network of stores and these are linked to consequences such as different objectives, performance expectations and the fulfilment of personal goals. Thirdly, a contribution to research methodology is made by addressing problems associated with the comparison of cognitive maps.

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This thesis examines the dynamics of firm-level financing and investment decisions for six Southeast Asian countries. The study provides empirical evidence on the impacts of changes in the firm-level financing decisions during the period of financial liberalization by considering the debt and equity financing decisions of a set of non-financial firms. The empirical results show that firms in Indonesia, Pakistan, and South Korea have relatively faster speed of adjustment than other Southeast Asian countries to attain optimal debt and equity ratios in response to banking sector and stock market liberalization. In addition, contrary to widely held belief that firms adjust their financial ratios to industry levels, the results indicate that industry factors do not significantly impact on the speed of capital structure adjustments. This study also shows that non-linear estimation methods are more appropriate than linear estimation methods for capturing changes in capital structure. The empirical results also show that international stock market integration of these countries has significantly reduced the equity risk premium as well as the firm-level cost of equity capital. Thus stock market liberalization is associated with a decrease in the cost of equity capital of the firms. Developments in the securities markets infrastructure have also reduced the cost of equity capital. However, with increased integration there is the possibility of capital outflows from the emerging markets, which might reverse the pattern of decrease in cost of capital in these markets.

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Influential models of edge detection have generally supposed that an edge is detected at peaks in the 1st derivative of the luminance profile, or at zero-crossings in the 2nd derivative. However, when presented with blurred triangle-wave images, observers consistently marked edges not at these locations, but at peaks in the 3rd derivative. This new phenomenon, termed ‘Mach edges’ persisted when a luminance ramp was added to the blurred triangle-wave. Modelling of these Mach edge detection data required the addition of a physiologically plausible filter, prior to the 3rd derivative computation. A viable alternative model was examined, on the basis of data obtained with short-duration, high spatial-frequency stimuli. Detection and feature-making methods were used to examine the perception of Mach bands in an image set that spanned a range of Mach band detectabilities. A scale-space model that computed edge and bar features in parallel provided a better fit to the data than 4 competing models that combined information across scale in a different manner, or computed edge or bar features at a single scale. The perception of luminance bars was examined in 2 experiments. Data for one image-set suggested a simple rule for perception of a small Gaussian bar on a larger inverted Gaussian bar background. In previous research, discriminability (d’) has typically been reported to be a power function of contrast, where the exponent (p) is 2 to 3. However, using bar, grating, and Gaussian edge stimuli, with several methodologies, values of p were obtained that ranged from 1 to 1.7 across 6 experiments. This novel finding was explained by appealing to low stimulus uncertainty, or a near-linear transducer.

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Natural language understanding (NLU) aims to map sentences to their semantic mean representations. Statistical approaches to NLU normally require fully-annotated training data where each sentence is paired with its word-level semantic annotations. In this paper, we propose a novel learning framework which trains the Hidden Markov Support Vector Machines (HM-SVMs) without the use of expensive fully-annotated data. In particular, our learning approach takes as input a training set of sentences labeled with abstract semantic annotations encoding underlying embedded structural relations and automatically induces derivation rules that map sentences to their semantic meaning representations. The proposed approach has been tested on the DARPA Communicator Data and achieved 93.18% in F-measure, which outperforms the previously proposed approaches of training the hidden vector state model or conditional random fields from unaligned data, with a relative error reduction rate of 43.3% and 10.6% being achieved.

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The role of interest and agency in the creation and transformation of institutions, in particular the “paradox of embedded agency” (Seo & Creed, 2002) have long puzzled institutional scholars. Most recently, Lawrence and Suddaby (2006) coined the term “institutional work” to describe various strategies for creating, maintaining and disrupting institutions. This label, while useful to integrate existing research, highlights institutionalists’ lack of attention to work as actors’ everyday occupational tasks and activities. Thus, the objective of this study is to take institutional work literally and ask: How does practical work come to constitute institutional work? Drawing on concepts of “situated change” (Orlikowski, 1996) I supplement existing macro-level perspectives of change with a microscopic, practice-based alternative. I examine the everyday work of English and German banking lawyers in a global law firm. Located at the intersection of local laws, international financial markets, commercial logics and professional norms, banking lawyers’ work regularly bridges different normative settings. Hence, they must constructively negotiate contradictory meanings, practices and logics to develop shared routines that resonate with different normative frameworks and facilitate task accomplishment. Based on observation and interview data, the paper distils a process model of banking transac-tions that highlights the critical interfaces forcing English and German banking lawyers into cross-border sensemaking. It distinguishes two accounts of cross-border sensemaking: the “old story” in which contradictory practices and norms collide and the “new story” of a synthetic set of practices for collaboratively “editing” (Sahlin-Andersson, 1996) legal documentation. Data show how new practices gain shape and legitimacy over a series of dialectic contests unfolding at work and how, in turn, these contests shift institutional logics as lawyers ‘get the deal done’. These micro-mechanisms suggest that as practical and institutional work blend, everyday work-ing practices come to constitute a form of institutional agency that is situated, emergent, dialectic and, therefore, embedded.

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This thesis addresses the question of how business schoolsestablished as public privatepartnerships (PPPs) within a regional university in the English-speaking Caribbean survived for over twenty-one years and achieved legitimacy in their environment. The aim of the study was to examine how public and private sector actors contributed to the evolution of the PPPs. A social network perspective provided a broad relational focus from which to explore the phenomenon and engage disciplinary and middle-rangetheories to develop explanations. Legitimacy theory provided an appropriate performance dimension from which to assess PPP success. An embedded multiple-case research design, with three case sites analysed at three levels including the country and university environment, the PPP as a firm and the subgroup level constituted the methodological framing of the research process. The analysis techniques included four methods but relied primarily on discourse and social network analysis of interview data from 40 respondents across the three sites. A staged analysis of the evolution of the firm provided the ‘time and effects’ antecedents which formed the basis for sense-making to arrive at explanations of the public-private relationship-influenced change. A conceptual model guided the study and explanations from the cross-case analysis were used to refine the process model and develop a dynamic framework and set of theoretical propositions that would underpin explanations of PPP success and legitimacy in matched contexts through analytical generalisation. The study found that PPP success was based on different models of collaboration and partner resource contribution that arose from a confluence of variables including the development of shared purpose, private voluntary control in corporate governance mechanisms and boundary spanning leadership. The study contributes a contextual theory that explains how PPPs work and a research agenda of ‘corporate governance as inspiration’ from a sociological perspective of ‘liquid modernity’. Recommendations for policy and management practice were developed.

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A novel and highly sensitive liquid level sensor based on a polymer optical fiber Bragg grating (POFBG) is experimentally demonstrated. Two different configurations are studied and both configurations show the potential to interrogate liquid level by measuring the strain induced in a POFBG embedded in a silicone rubber diaphragm, which deforms due to hydrostatic pressure variations. The sensor exhibits a highly linear response over the sensing range and a good repeatability. For comparison, a similar sensor using a FBG inscribed in silica fiber is fabricated, which displays a sensitivity that is a factor of 5 smaller than the POFBG. The temperature sensitivity is studied and a novel multi-sensor arrangement proposed which has the potential to provide level readings independent of temperature and the liquid density.

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Motivation: In molecular biology, molecular events describe observable alterations of biomolecules, such as binding of proteins or RNA production. These events might be responsible for drug reactions or development of certain diseases. As such, biomedical event extraction, the process of automatically detecting description of molecular interactions in research articles, attracted substantial research interest recently. Event trigger identification, detecting the words describing the event types, is a crucial and prerequisite step in the pipeline process of biomedical event extraction. Taking the event types as classes, event trigger identification can be viewed as a classification task. For each word in a sentence, a trained classifier predicts whether the word corresponds to an event type and which event type based on the context features. Therefore, a well-designed feature set with a good level of discrimination and generalization is crucial for the performance of event trigger identification. Results: In this article, we propose a novel framework for event trigger identification. In particular, we learn biomedical domain knowledge from a large text corpus built from Medline and embed it into word features using neural language modeling. The embedded features are then combined with the syntactic and semantic context features using the multiple kernel learning method. The combined feature set is used for training the event trigger classifier. Experimental results on the golden standard corpus show that >2.5% improvement on F-score is achieved by the proposed framework when compared with the state-of-the-art approach, demonstrating the effectiveness of the proposed framework. © 2014 The Author 2014. The source code for the proposed framework is freely available and can be downloaded at http://cse.seu.edu.cn/people/zhoudeyu/ETI_Sourcecode.zip.

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A highly sensitive liquid level monitoring system based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported for the first time. The configuration is based on five mPOFBGs inscribed in the same fiber in the 850 nm spectral region, showing the potential to interrogate liquid level by measuring the strain induced in each mPOFBG embedded in a silicone rubber (SR) diaphragm, which deforms due to hydrostatic pressure variations. The sensor exhibits a highly linear response over the sensing range, a good repeatability, and a high resolution. The sensitivity of the sensor is found to be 98 pm/cm of water, enhanced by more than a factor of 9 when compared to an equivalent sensor based on a silica fiber around 1550 nm. The temperature sensitivity is studied and a multi-sensor arrangement proposed, which has the potential to provide level readings independent of temperature and the liquid density.

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Adaptability for distributed object-oriented enterprise frameworks in multimedia technology is a critical mission for system evolution. Today, building adaptive services is a complex task due to lack of adequate framework support in the distributed computing systems. In this paper, we propose a Metalevel Component-Based Framework which uses distributed computing design patterns as components to develop an adaptable pattern-oriented framework for distributed computing applications. We describe our approach of combining a meta-architecture with a pattern-oriented framework, resulting in an adaptable framework which provides a mechanism to facilitate system evolution. This approach resolves the problem of dynamic adaptation in the framework, which is encountered in most distributed multimedia applications. The proposed architecture of the pattern-oriented framework has the abilities to dynamically adapt new design patterns to address issues in the domain of distributed computing and they can be woven together to shape the framework in future. © 2011 Springer Science+Business Media B.V.

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Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.