134 resultados para class locations


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Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

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Background: Gestational diabetes mellitus (GDM) is increasing, along with obesity and type 2 diabetes (T2DM), with Aboriginal and Torres Strait Islander people* in Australia particularly affected. GDM causes serious complications in pregnancy, birth, and the longer term, for both women and their infants. Women diagnosed with GDM have an eightfold risk of developing T2DM after pregnancy, compared with women who have not had GDM. Indigenous women have an even higher risk, at a younger age, and progress more quickly from GDM to T2DM, compared to non-Indigenous women. If left undetected and untreated, T2DM can lead to heart disease, stroke, renal disease, kidney failure, amputations and blindness. A GDM diagnosis offers a ‘window of opportunity’ for diabetes health interventions and it is vital that acceptable and effective prevention, treatment, and post-pregnancy care are provided. Low rates of post-pregnancy screening for T2DM are reported among non-Aboriginal women in Australia and among Indigenous women in other countries, however data for Aboriginal women are scarce. Breastfeeding, a healthy diet, and exercise can also help to prevent T2DM, and together with T2DM screening are recommended elements of ‘post-pregnancy care’ for women with GDM, This paper describes methods for a data linkage study to investigate rates of post-pregnancy care among women with GDM. Methods/Design: This retrospective cohort includes all women who gave birth at Cairns Base Hospital in Far North Queensland, Australia, from 2004 to 2010, coded as having GDM in the Cairns Base Hospital Clinical Coding system. Data linkage is being conducted with the Queensland Perinatal Data Collection, and three laboratories. Hospital medical records are being reviewed to validate the accuracy of GDM case ascertainment, and gather information on breastfeeding and provision of dietary advice. Multiple logistic regression is being used to compare post-pregnancy care between Aboriginal and non-Aboriginal women, while adjusting for other factors may impact on post-pregnancy care. Survival analysis is being used to estimate the rates of progression from GDM to T2DM. Discussion: There are challenges to collecting post-pregnancy data for women with GDM. However, research is urgently needed to ensure adequate post-pregnancy care is provided for women with GDM in Australia.

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A switch-mode assisted linear amplifier (SMALA) combining a linear (Class B) and a switch-mode (Class D) amplifier is presented. The usual single hysteretic controlled half-bridge current dumping stage is replaced by two parallel buck converter stages, in a parallel voltage controlled topology. These operate independently: one buck converter sources current to assist the upper Class B output device, and a complementary converter sinks current to assist the lower device. This topology lends itself to a novel control approach of a dead-band at low power levels where neither class D amplifier assists, allowing the class B amplifier to supply the load without interference, ensuring high fidelity. A 20 W implementation demonstrates 85% efficiency, with distortion below 0.08% measured across the full audio bandwidth at 15 W. The class D amplifier begins assisting at 2 W, and below this value, the distortion was below 0.03%. Complete circuitry is given, showing the simplicity of the additional class D amplifier and its corresponding control circuitry.

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Class E Resonant Inverters are theoretically capable of delivering any power to a load and achieve 100% efficiency at any frequency of operation. In practice efficiency in the “high 90's” can be achieved into megahertz frequencies regardless of inverter output powers. The topology also allows the manipulation of output power through sub-optimal operation, with a negligible efficiency penalty. The 24W inverter discussed in this paper was specifically designed to harness the benefits, and discuss the shortcomings, of the Class E topology for use in the growing market for portable, battery powered lighting. It exhibits a peak recorded power efficiently of over 98%, and a conservatively measured efficiency of 95% across a range of dimming settings.

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The economics of supporting learning has seen institutional encouragement of a wide range of blended learning initiatives in face to face and online teaching and learning. This has become one of the key drivers for the adoption of technology in teaching, in a manner occassionally guilty of putting the cart before the horse. Learning spaces are increasingly equipped with a dizzying array of technological options testifying to institutional and governmental investment and commitment in supporting face to face blended learning (QUT, 2011, C/4.2). Yet innovation within traditional learning and teaching models faces a number of challenges both at an institutional level and at the teaching coal face. Web 2.0 technologies present a vast array of opportunities to harness and capture the attention of students in engaging learning opportunitites. This presentation will explore technologies supportive of active learning pedagogies.

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Purpose – This study aims to evaluate the usefulness of a university unit Facebook page, which was established to support a first-year university justice unit. The study pays particular regard to the Facebook page's impact on students learning outcomes and communications amongst students and between students and teaching staff. Design/methodology/approach – All students enrolled in the unit were asked to complete an online survey, which sought to determine whether they used the unit Facebook page and if so, the nature and extent of their use. Findings – The study found that the unit Facebook page was useful in achieving most learning objectives for the unit. This included enhancing students' knowledge and understanding of unit content, as well as their ability to critically analyse unit materials. Students also indicated that they found the Facebook page better than the university's central learning management system across a range of areas. It was particularly useful for facilitating unit-related discussions. Research limitations/implications – The survey results reported in this paper are based on a relatively small sample of students (n=67) from a first-year university justice unit. Future studies should seek to garner evidence from broader and larger samples that transcend specific unit populations. However, the findings of this study do indicate further support for the use of Facebook as a supplementary tool in university education. Originality/value – This study focuses on two aspects of social networking technologies that have not been previously researched and thus contributes to the growing literature on the uses and benefits of Facebook in tertiary education.

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Advancing the development of good practice around the teaching team has been the focus of a recently completed, nationally funded Australian grant entitled Coordinators Leading Advancement of Sessional Staff (CLASS). The project focused on developing leadership capacity of subject coordinators to provide supportive contexts for sessional staff to enhance their knowledge of teaching practice and contribute to subject improvement through a team approach. An action learning approach and notions of distributed leadership underpinned the activities of the teaching teams in the program. This paper provides an overview of a practical approach, led by the subject coordinator, to engaging sessional staff through the facilitation of a supportive network within the teaching team. It addresses some of the gaps identified in the recent literature which includes lack of role clarity for all members of the team and provides some examples of initiatives that teams engaged with to address some of the challenges identified. Resources to support this approach were developed and are shared through the project website. Recommendations for future direction include improved policy and practice at the institutional level, better recognition and reward for subject coordinators and resourcing to support the participation and professional development needs of sessional staff.

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Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

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Two poems in journal Axon. 2013 Issue 4.

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Attempts by universities to provide an improved learning environment to students have led to an increase in team-teaching approaches in higher education. While the definitions of team-teaching differ slightly, the benefits of team-teaching have been cited widely in the higher education literature. By tapping the specialist knowledge of a variety of staff members, students are exposed to current and emerging knowledge in different fields and topic areas; students are also able to understand concepts from a variety of viewpoints. However, while there is some evidence of the usefulness of team-teaching, there is patchy empirical support to underpin how well students appreciate and adapt to team-teaching approaches. This paper reports on the team-teaching approaches adopted in the delivery of an introductory journalism and communication course at the University of Queensland. The success of the approaches is examined against the background of quantitative and qualitative data. The study found that team-teaching is generally very well received by undergraduate students because they value the diverse expertise and teaching styles they are exposed to. Despite the positive feedback, students also complained about problems of continuity and cohesiveness.

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We introduce the notion of distributed password-based public-key cryptography, where a virtual high-entropy private key is implicitly defined as a concatenation of low-entropy passwords held in separate locations. The users can jointly perform private-key operations by exchanging messages over an arbitrary channel, based on their respective passwords, without ever sharing their passwords or reconstituting the key. Focusing on the case of ElGamal encryption as an example, we start by formally defining ideal functionalities for distributed public-key generation and virtual private-key computation in the UC model. We then construct efficient protocols that securely realize them in either the RO model (for efficiency) or the CRS model (for elegance). We conclude by showing that our distributed protocols generalize to a broad class of “discrete-log”-based public-key cryptosystems, which notably includes identity-based encryption. This opens the door to a powerful extension of IBE with a virtual PKG made of a group of people, each one memorizing a small portion of the master key.

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Sustainability has become one of the important research topics in the field of Human Computer Interaction (HCI). However, the majority of work has focused on the Western culture. In this paper, we explore sustainable household practices in the developing world. Our research draws on the results from an ethnographic field study of household women belonging to the so-called middle class in India. We analyze our results in the context of Blevis' [4] principles of sustainable interaction design (established within the Western culture), to extract the intercultural aspects that need to be considered for designing technologies. We present examples from the field that we term "domestic artefacts". Domestic artefacts represent creative and sustainable ways household women appropriate and adapt used objects to create more useful and enriching objects that support household members' everyday activities. Our results show that the rationale behind creating domestic artefacts is not limited to the practicality and usefulness, but it shows how religious beliefs, traditions, family intimacy, personal interests and health issues are incorporated into them.

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In this paper, we propose a new multi-class steganalysis for binary image. The proposed method can identify the type of steganographic technique used by examining on the given binary image. In addition, our proposed method is also capable of differentiating an image with hidden message from the one without hidden message. In order to do that, we will extract some features from the binary image. The feature extraction method used is a combination of the method extended from our previous work and some new methods proposed in this paper. Based on the extracted feature sets, we construct our multi-class steganalysis from the SVM classifier. We also present the empirical works to demonstrate that the proposed method can effectively identify five different types of steganography.

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This study presents an acoustic emission (AE) based fault diagnosis for low speed bearing using multi-class relevance vector machine (RVM). A low speed test rig was developed to simulate the various defects with shaft speeds as low as 10 rpm under several loading conditions. The data was acquired using anAEsensor with the test bearing operating at a constant loading (5 kN) andwith a speed range from20 to 80 rpm. This study is aimed at finding a reliable method/tool for low speed machines fault diagnosis based on AE signal. In the present study, component analysis was performed to extract the bearing feature and to reduce the dimensionality of original data feature. The result shows that multi-class RVM offers a promising approach for fault diagnosis of low speed machines.

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This paper proposes a method for designing set-point regulation controllers for a class of underactuated mechanical systems in Port-Hamiltonian System (PHS) form. A new set of potential shape variables in closed loop is proposed, which can replace the set of open loop shape variables-the configuration variables that appear in the kinetic energy. With this choice, the closed-loop potential energy contains free functions of the new variables. By expressing the regulation objective in terms of these new potential shape variables, the desired equilibrium can be assigned and there is freedom to reshape the potential energy to achieve performance whilst maintaining the PHS form in closed loop. This complements contemporary results in the literature, which preserve the open-loop shape variables. As a case study, we consider a robotic manipulator mounted on a flexible base and compensate for the motion of the base while positioning the end effector with respect to the ground reference. We compare the proposed control strategy with special cases that correspond to other energy shaping strategies previously proposed in the literature.