997 resultados para Bootstrapping techniques
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Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.
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The mining environment presents a challenging prospect for stereo vision. Our objective is to produce a stereo vision sensor suited to close-range scenes consisting mostly of rocks. This sensor should produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this application. This paper compares a number of stereo matching algorithms in terms of robustness and suitability to fast implementation. These include traditional area-based algorithms, and algorithms based on non-parametric transforms, notably the rank and census transforms. Our experimental results show that the rank and census transforms are robust with respect to radiometric distortion and introduce less computational complexity than conventional area-based matching techniques.
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Purpose. To compare radiological records of 90 consecutive patients who underwent cemented total hip arthroplasty (THA) with or without use of the Rim Cutter to prepare the acetabulum. Methods. The acetabulum of 45 patients was prepared using the Rim Cutter, whereas the device was not used in the other 45 patients. Postoperative radiographs were evaluated using a digital templating system to measure (1) the positions of the operated hips with respect to the normal, contralateral hips (the centre of rotation of the socket, the height of the centre of rotation from the teardrop, and lateralisation of the centre of rotation from the teardrop) and (2) the uniformity and width of the cement mantle in the 3 DeLee Charnley acetabular zones, and the number of radiolucencies in these zones. Results. The study group showed improved radiological parameters and were closer to the anatomic centre of rotation both vertically (1.5 vs. 3.7 mm, p<0.001) and horizontally (1.8 vs. 4.4 mm, p<0.001) and had consistently thicker and more uniform cement mantles (p<0.001). There were 2 radiolucent lines in the control group but none in the study group. Conclusion. The Rim Cutter resulted in more accurate placement of the centre of rotation of a cemented prosthetic socket, and produced a thicker, more congruent cement mantle with fewer radiolucent lines.
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Sound tagging has been studied for years. Among all sound types, music, speech, and environmental sound are three hottest research areas. This survey aims to provide an overview about the state-of-the-art development in these areas.We discuss about the meaning of tagging in different sound areas at the beginning of the journey. Some examples of sound tagging applications are introduced in order to illustrate the significance of this research. Typical tagging techniques include manual, automatic, and semi-automatic approaches.After reviewing work in music, speech and environmental sound tagging, we compare them and state the research progress to date. Research gaps are identified for each research area and the common features and discriminations between three areas are discovered as well. Published datasets, tools used by researchers, and evaluation measures frequently applied in the analysis are listed. In the end, we summarise the worldwide distribution of countries dedicated to sound tagging research for years.
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This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.
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CTAC2012 was the 16th biennial Computational Techniques and Applications Conference, and took place at Queensland University of Technology from 23 - 26 September, 2012. The ANZIAM Special Interest Group in Computational Techniques and Applications is responsible for the CTAC meetings, the first of which was held in 1981.
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An optical system which performs the multiplication of binary numbers is described and proof-of-principle experiments are performed. The simultaneous generation of all partial products, optical regrouping of bit products, and optical carry look-ahead addition are novel features of the proposed scheme which takes advantage of the parallel operations capability of optical computers. The proposed processor uses liquid crystal light valves (LCLVs). By space-sharing the LCLVs one such system could function as an array of multipliers. Together with the optical carry look-ahead adders described, this would constitute an optical matrix-vector multiplier.
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Introduction: Undergraduate students studying the Bachelor of Radiation Therapy at Queensland University of Technology (QUT) attend clinical placements in a number of department sites across Queensland. To ensure that the curriculum prepares students for the most common treatments and current techniques in use in these departments, a curriculum matching exercise was performed. Methods: A cross-sectional census was performed on a pre-determined “Snapshot” date in 2012. This was undertaken by the clinical education staff in each department who used a standardized proforma to count the number of patients as well as prescription, equipment, and technique data for a list of tumour site categories. This information was combined into aggregate anonymized data. Results: All 12 Queensland radiation therapy clinical sites participated in the Snapshot data collection exercise to produce a comprehensive overview of clinical practice on the chosen day. A total of 59 different tumour sites were treated on the chosen day and as expected the most common treatment sites were prostate and breast, comprising 46% of patients treated. Data analysis also indicated that intensity-modulated radiotherapy (IMRT) use is relatively high with 19.6% of patients receiving IMRT treatment on the chosen day. Both IMRT and image-guided radiotherapy (IGRT) indications matched recommendations from the evidence. Conclusion: The Snapshot method proved to be a feasible and efficient method of gathering useful
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With the explosive growth of resources available through the Internet, information mismatching and overload have become a severe concern to users. Web users are commonly overwhelmed by huge volume of information and are faced with the challenge of finding the most relevant and reliable information in a timely manner. Personalised information gathering and recommender systems represent state-of-the-art tools for efficient selection of the most relevant and reliable information resources, and the interest in such systems has increased dramatically over the last few years. However, web personalization has not yet been well-exploited; difficulties arise while selecting resources through recommender systems from a technological and social perspective. Aiming to promote high quality research in order to overcome these challenges, this paper provides a comprehensive survey on the recent work and achievements in the areas of personalised web information gathering and recommender systems. The report covers concept-based techniques exploited in personalised information gathering and recommender systems.
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This paper investigates advanced channel compensation techniques for the purpose of improving i-vector speaker verification performance in the presence of high intersession variability using the NIST 2008 and 2010 SRE corpora. The performance of four channel compensation techniques: (a) weighted maximum margin criterion (WMMC), (b) source-normalized WMMC (SN-WMMC), (c) weighted linear discriminant analysis (WLDA), and; (d) source-normalized WLDA (SN-WLDA) have been investigated. We show that, by extracting the discriminatory information between pairs of speakers as well as capturing the source variation information in the development i-vector space, the SN-WLDA based cosine similarity scoring (CSS) i-vector system is shown to provide over 20% improvement in EER for NIST 2008 interview and microphone verification and over 10% improvement in EER for NIST 2008 telephone verification, when compared to SN-LDA based CSS i-vector system. Further, score-level fusion techniques are analyzed to combine the best channel compensation approaches, to provide over 8% improvement in DCF over the best single approach, (SN-WLDA), for NIST 2008 interview/ telephone enrolment-verification condition. Finally, we demonstrate that the improvements found in the context of CSS also generalize to state-of-the-art GPLDA with up to 14% relative improvement in EER for NIST SRE 2010 interview and microphone verification and over 7% relative improvement in EER for NIST SRE 2010 telephone verification.
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A number of mathematical models investigating certain aspects of the complicated process of wound healing are reported in the literature in recent years. However, effective numerical methods and supporting error analysis for the fractional equations which describe the process of wound healing are still limited. In this paper, we consider the numerical simulation of a fractional mathematical model of epidermal wound healing (FMM-EWH), which is based on the coupled advection-diffusion equations for cell and chemical concentration in a polar coordinate system. The space fractional derivatives are defined in the Left and Right Riemann-Liouville sense. Fractional orders in the advection and diffusion terms belong to the intervals (0, 1) or (1, 2], respectively. Some numerical techniques will be used. Firstly, the coupled advection-diffusion equations are decoupled to a single space fractional advection-diffusion equation in a polar coordinate system. Secondly, we propose a new implicit difference method for simulating this equation by using the equivalent of Riemann-Liouville and Grünwald-Letnikov fractional derivative definitions. Thirdly, its stability and convergence are discussed, respectively. Finally, some numerical results are given to demonstrate the theoretical analysis.
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This chapter provides researchers with a guide to some of the types of dating techniques that can be used in geomorpological investigations and issues that need to be addressed when using gechronological data, specifically issues relating to accuracy and precision. This chapter also introduces the 'types' of dating methods that are commonly used in geomorphological studies. This includes sidereal, isotopic, radiogenic, and chemical dating methods.