521 resultados para selection methods


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Speaker diarization is the process of annotating an input audio with information that attributes temporal regions of the audio signal to their respective sources, which may include both speech and non-speech events. For speech regions, the diarization system also specifies the locations of speaker boundaries and assign relative speaker labels to each homogeneous segment of speech. In short, speaker diarization systems effectively answer the question of ‘who spoke when’. There are several important applications for speaker diarization technology, such as facilitating speaker indexing systems to allow users to directly access the relevant segments of interest within a given audio, and assisting with other downstream processes such as summarizing and parsing. When combined with automatic speech recognition (ASR) systems, the metadata extracted from a speaker diarization system can provide complementary information for ASR transcripts including the location of speaker turns and relative speaker segment labels, making the transcripts more readable. Speaker diarization output can also be used to localize the instances of specific speakers to pool data for model adaptation, which in turn boosts transcription accuracies. Speaker diarization therefore plays an important role as a preliminary step in automatic transcription of audio data. The aim of this work is to improve the usefulness and practicality of speaker diarization technology, through the reduction of diarization error rates. In particular, this research is focused on the segmentation and clustering stages within a diarization system. Although particular emphasis is placed on the broadcast news audio domain and systems developed throughout this work are also trained and tested on broadcast news data, the techniques proposed in this dissertation are also applicable to other domains including telephone conversations and meetings audio. Three main research themes were pursued: heuristic rules for speaker segmentation, modelling uncertainty in speaker model estimates, and modelling uncertainty in eigenvoice speaker modelling. The use of heuristic approaches for the speaker segmentation task was first investigated, with emphasis placed on minimizing missed boundary detections. A set of heuristic rules was proposed, to govern the detection and heuristic selection of candidate speaker segment boundaries. A second pass, using the same heuristic algorithm with a smaller window, was also proposed with the aim of improving detection of boundaries around short speaker segments. Compared to single threshold based methods, the proposed heuristic approach was shown to provide improved segmentation performance, leading to a reduction in the overall diarization error rate. Methods to model the uncertainty in speaker model estimates were developed, to address the difficulties associated with making segmentation and clustering decisions with limited data in the speaker segments. The Bayes factor, derived specifically for multivariate Gaussian speaker modelling, was introduced to account for the uncertainty of the speaker model estimates. The use of the Bayes factor also enabled the incorporation of prior information regarding the audio to aid segmentation and clustering decisions. The idea of modelling uncertainty in speaker model estimates was also extended to the eigenvoice speaker modelling framework for the speaker clustering task. Building on the application of Bayesian approaches to the speaker diarization problem, the proposed approach takes into account the uncertainty associated with the explicit estimation of the speaker factors. The proposed decision criteria, based on Bayesian theory, was shown to generally outperform their non- Bayesian counterparts.

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This extended abstract summarizes the state-of-the-art solution to the structuring problem for models that describe existing real world or envisioned processes. Special attention is devoted to models that allow for the true concurrency semantics. Given a model of a process, the structuring problem deals with answering the question of whether there exists another model that describes the process and is solely composed of structured patterns, such as sequence, selection, option for simultaneous execution, and iteration. Methods and techniques for structuring developed by academia as well as products and standards proposed by industry are discussed. Expectations and recommendations on the future advancements of the structuring problem are suggested.

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Two approaches are described, which aid the selection of the most appropriate procurement arrangements for a building project. The first is a multi-attribute technique based on the National Economic Development Office procurement path decision chart. A small study is described in which the utility factors involved were weighted by averaging the scores of five 'experts' for three hypothetical building projects. A concordance analysis is used to provide some evidence of any abnormal data sources. When applied to the study data, one of the experts was seen to be atypical. The second approach is by means of discriminant analysis. This was found to provide reasonably consistent predictions through three discriminant functions. The analysis also showed the quality criteria to have no significant impact on the decision process. Both approaches provided identical and intuitively correct answers in the study described. Some concluding remarks are made on the potential of discriminant analysis for future research and development in procurement selection techniques.

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This paper explores what we are calling “Guerrilla Research Tactics” (GRT): research methods that exploit emerging mobile and cloud based digital technologies. We examine some case studies in the use of this technology to generate research data directly from the physical fabric and the people of the city. We argue that GRT is a new and novel way of engaging public participation in urban, place based research because it facilitates the co- creation of knowledge, with city inhabitants, ‘on the fly’. This paper discusses the potential of these new research techniques and what they have to offer researchers operating in the creative disciplines and beyond. This work builds on and extends Gauntlett’s “new creative methods” (2007) and contributes to the existing body of literature addressing creative and interactive approaches to data collection.

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Now as in earlier periods of acute change in the media environment, new disciplinary articulations are producing new methods for media and communication research. At the same time, established media and communication studies meth- ods are being recombined, reconfigured, and remediated alongside their objects of study. This special issue of JOBEM seeks to explore the conceptual, political, and practical aspects of emerging methods for digital media research. It does so at the conjuncture of a number of important contemporary trends: the rise of a ‘‘third wave’’ of the Digital Humanities and the ‘‘computational turn’’ (Berry, 2011) associated with natively digital objects and the methods for studying them; the apparently ubiquitous Big Data paradigm—with its various manifestations across academia, business, and government — that brings with it a rapidly increasing interest in social media communication and online ‘‘behavior’’ from the ‘‘hard’’ sciences; along with the multisited, embodied, and emplaced nature of everyday digital media practice.

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Fractional mathematical models represent a new approach to modelling complex spatial problems in which there is heterogeneity at many spatial and temporal scales. In this paper, a two-dimensional fractional Fitzhugh-Nagumo-monodomain model with zero Dirichlet boundary conditions is considered. The model consists of a coupled space fractional diffusion equation (SFDE) and an ordinary differential equation. For the SFDE, we first consider the numerical solution of the Riesz fractional nonlinear reaction-diffusion model and compare it to the solution of a fractional in space nonlinear reaction-diffusion model. We present two novel numerical methods for the two-dimensional fractional Fitzhugh-Nagumo-monodomain model using the shifted Grunwald-Letnikov method and the matrix transform method, respectively. Finally, some numerical examples are given to exhibit the consistency of our computational solution methodologies. The numerical results demonstrate the effectiveness of the methods.

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Transport processes within heterogeneous media may exhibit non-classical diffusion or dispersion; that is, not adequately described by the classical theory of Brownian motion and Fick's law. We consider a space fractional advection-dispersion equation based on a fractional Fick's law. The equation involves the Riemann-Liouville fractional derivative which arises from assuming that particles may make large jumps. Finite difference methods for solving this equation have been proposed by Meerschaert and Tadjeran. In the variable coefficient case, the product rule is first applied, and then the Riemann-Liouville fractional derivatives are discretised using standard and shifted Grunwald formulas, depending on the fractional order. In this work, we consider a finite volume method that deals directly with the equation in conservative form. Fractionally-shifted Grunwald formulas are used to discretise the fractional derivatives at control volume faces. We compare the two methods for several case studies from the literature, highlighting the convenience of the finite volume approach.

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Rayleigh–Stokes problems have in recent years received much attention due to their importance in physics. In this article, we focus on the variable-order Rayleigh–Stokes problem for a heated generalized second grade fluid with fractional derivative. Implicit and explicit numerical methods are developed to solve the problem. The convergence, stability of the numerical methods and solvability of the implicit numerical method are discussed via Fourier analysis. Moreover, a numerical example is given and the results support the effectiveness of the theoretical analysis.

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Spreadsheet for Creative City Index 2012

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Quantitative imaging methods to analyze cell migration assays are not standardized. Here we present a suite of two–dimensional barrier assays describing the collective spreading of an initially–confined population of 3T3 fibroblast cells. To quantify the motility rate we apply two different automatic image detection methods to locate the position of the leading edge of the spreading population after 24, 48 and 72 hours. These results are compared with a manual edge detection method where we systematically vary the detection threshold. Our results indicate that the observed spreading rates are very sensitive to the choice of image analysis tools and we show that a standard measure of cell migration can vary by as much as 25% for the same experimental images depending on the details of the image analysis tools. Our results imply that it is very difficult, if not impossible, to meaningfully compare previously published measures of cell migration since previous results have been obtained using different image analysis techniques and the details of these techniques are not always reported. Using a mathematical model, we provide a physical interpretation of our edge detection results. The physical interpretation is important since edge detection algorithms alone do not specify any physical measure, or physical definition, of the leading edge of the spreading population. Our modeling indicates that variations in the image threshold parameter correspond to a consistent variation in the local cell density. This means that varying the threshold parameter is equivalent to varying the location of the leading edge in the range of approximately 1–5% of the maximum cell density.

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Purpose: UC is a disease of the entire urothelium, characterized by multiplicity and multifocality. The clonal relationship among multiple UCs has implications regarding adjuvant chemotherapy. It has been investigated in studies of chromosomal alteration and single gene mutation. However, these genetic changes can occur in unrelated tumors under similar carcinogenic selection pressures. Tumors with high MSI have numerous DNA mutations, of which many provide no selection benefit. While these tumors represent an ideal model for studying UC clonality, their low frequency has prevented their previous investigation. Materials and Methods: We investigated 32 upper and lower urinary tract UCs with high MSI and 4 nonUC primary cancers in 9 patients. We used the high frequency and specificity of individual DNA mutations in these tumors (MSI at 17 loci) and the early timing of epigenetic events (methylation of 7 gene promoters) to investigate tumor clonality. Results: Molecular alterations varied among tumors from different primary organs but they appeared related in the UCs of all 9 patients. While 7 patients had a high degree of concordance among UCs, in 2 the UCs shared only a few similar alterations. Genetic and epigenetic abnormalities were frequently found in normal urothelial samples. Conclusions: Multiple UCs in each patient appeared to arise from a single clone. The molecular order of tumor development varied from the timing of clinical presentation and suggested that residual malignant cells persist in the urinary tract despite apparent curative surgery. These cells lead to subsequent tumor relapse and new methods are required to detect and eradicate them.

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Electronic word-of-mouth (eWOM) has gained significant attention from academics and practitioners since it has become an important source of consumers’ product information, which can influence consumer purchase intentions (Cheung & Lee, 2012). eWOM exchanges exist in two types of online communities: online communities of practice and online communities of interest. A few prior studies in online communities of interest have examined members’ motivations for product knowledge exchange (Hung & Li, 2007; Ma & Agarwal, 2007). However, there is a lack of understanding of member motivations for exchanging social bonds and enjoyment in addition to exchanging knowledge pertaining to products in the community. It is important to have an initial comprehension of motivation as an antecedent of these three eWOM exchanges so as to be able to determine the driving factors that lead members to generate eWOM communication. Thus, the research problem "What are the driving factors for members to exchange eWOM in an online community?" was justified for investigation. The purpose of this study was to examine different member motivations for exchanging three types of eWOM. Resource exchange theory and theory on consumer motivation and behavior were applied to develop a conceptual framework for this study. This study focused on an online beauty community since there is an increasing trend of consumers turning to online beauty resources so as to exchange useful beauty product information (SheSpot, 2011). As this study examined consumer motivation in an online beauty community, a web-based survey was the most effective and efficient way to gain responses from beauty community members and these members were appropriate samples from which to draw a conclusion about the whole population. Multiple regression analysis was used to test the relationships between member motivations and eWOM exchanges. It was found that members have different motivations for exchanging knowledge, social bonds, and enjoyment related to products: self-development, problem solving support, and relaxation, respectively. This study makes three theoretical contributions. First, this study identifies the influence of self-development motivation on knowledge exchange in an online community of interest, just as this motivation has previously been found in online communities of practice. This study highlights that members of the two different types of online communities share similar goals of knowledge exchange, despite the two communities evincing different attributes (e.g., member characteristics and tasks’ objectives). Further, this study will assist researchers to understand other motivations identified by prior research in online communities of practice since such motivations may be applicable to online communities of interest. Second, this study offers a new perspective on member motivation for social bonding. This study indicates that in addition to social support from friends and family, consumers are motivated to build social bonds with members in an online community of interest since they are an important source of problem solving support in regard to products. Finally, this study extends the body of knowledge pertaining to member motivation for enjoyment exchange. This study provides a basis for researchers to understand that members in an online community of interest value experiential aspects of enjoyable consumption activities, and thus based on group norms, members have a mutual desire for relaxation from enjoyment exchange. The major practical contribution is that this study provides an important guideline for marketing managers to develop different marketing strategies based on member motivations for exchanging three types of eWOM in an online community of interest, such as an online beauty community. This will potentially help marketing managers increase online traffic and revenue, and thus bring success to the community. Although, this study contributes to the literature by highlighting three distinctive member motivations for eWOM exchanges in an online community of interest, there are some possible research limitations. First, this study was conducted in an online beauty community in Australia. Hence, further research should replicate this study in other industries and nations so as to give the findings greater generalisability. Next, online beauty community members are female skewed. Thus, future research should examine whether similar patterns of motivations would emerge in other online communities that tend to be populated by males (e.g., communities focused on football). Further, a web-based survey has its limitations in terms of self-selection and self-reporting (Bhatnagar & Ghose, 2004). Therefore, further studies should test the framework by employing different research methods in order to overcome these weaknesses.

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Parametric and generative modelling methods are ways in which computer models are made more flexible, and of formalising domain-specific knowledge. At present, no open standard exists for the interchange of parametric and generative information. The Industry Foundation Classes (IFC) which are an open standard for interoperability in building information models is presented as the base for an open standard in parametric modelling. The advantage of allowing parametric and generative representations are that the early design process can allow for more iteration and changes can be implemented quicker than with traditional models. This paper begins with a formal definition of what constitutes to be parametric and generative modelling methods and then proceeds to describe an open standard in which the interchange of components could be implemented. As an illustrative example of generative design, Frazer’s ‘Reptiles’ project from 1968 is reinterpreted.

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Qualitative Health Psychology aims to contribute to the debate about the nature of psychology and of science through ‘an examination of the role of qualitative research within health psychology’ (p. 3). The editors, in bringing together contributors from the UK, Ireland, Canada, Brazil, New Zealand and Australia, have compiled a text that reflects different uses of qualitative health research in diverse social and cultural contexts. Structured into three parts, the book encompasses key theoretical and methodological issues in qualitative research in its attempt to encourage broad epistemological debate within health psychology.