931 resultados para digital techniques


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The application of nanotechnology products has increased significantly in recent years. With their broad range of applications, including electronics, food and agriculture, power and energy, scientific instruments, clothing, cosmetics, buildings, biomedical and health, etc (Catanzariti, 2008), nanomaterials are an indispensible part of human life.

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How do you identify "good" teaching practice in the complexity of a real classroom? How do you know that beginning teachers can recognise effective digital pedagogy when they see it? How can teacher educators see through their students’ eyes? The study in this paper has arisen from our interest in what pre-service teachers “see” when observing effective classroom practice and how this might reveal their own technological, pedagogical and content knowledge. We asked 104 pre-service teachers from Early Years, Primary and Secondary cohorts to watch and comment upon selected exemplary videos of teachers using ICT (information and communication technologies) in Science. The pre-service teachers recorded their observations using a simple PMI (plus, minus, interesting) matrix which were then coded using the SOLO Taxonomy to look for evidence of their familiarity with and judgements of digital pedagogies. From this, we determined that the majority of preservice teachers we surveyed were using a descriptive rather than a reflective strategy, that is, not extending beyond what was demonstrated in the teaching exemplar or differentiating between action and purpose. We also determined that this method warrants wider trialling as a means of evaluating students’ understandings of the complexity of the digital classroom.

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Complex flow datasets are often difficult to represent in detail 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 (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

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This paper explores the process of introducing Digital Storytelling (DST) workshop practice to Turkey through a project called “Digital Stories from Amargi Women”, which was part of my Ph.D. research in the Creative Industries Faculty, Queensland University of Technology, Australia. In the resulting dissertation, I examined the potential of Digital Storytelling workshop practice as a means to promote agency and self-expression in a feminist activist organization (such as Amargi Women), focusing in particular on whether or not Digital Storytelling can be used as a change agent – as a tool for challenging the idea of a single public sphere in ways that make it more inclusive of women’s participation. In order to explore the issue in depth, my thesis engaged with feminist scholarship’s critiques of the public/private dichotomy, as well as the concept of gender. The conducted workshops, the resulting digital stories, and in-depth interviews were analyzed to seek connections between these topics and narrative identity. The results indicated that the participating women defined new activist usages for digital stories, as well as their overall activated networking habits in the DST workshop settings. Digital Stories from Amargi Women became the first Digital Storytelling project that aimed to enable women’s participation in Turkey through facilitating a co-creative environment where the participants could share their stories and learn digital skills that they could make use of after the workshops.

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The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

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The promotion of resilience (the capacity of an individual or community to bounce back and recover from adversity) has become an important area of public health. In recent years it has expanded into the digital domain, and many online applications have been developed to promote children's resilience. In this study, it is argued that the majority of existing applications are limited because they take a didactic approach, and conceive of interaction as providing navigational choices. Because they simply provide information about resilience or replicate offline, scenario-based strategies, the understanding of resilience they provide is confined to a few, predetermined factors. In this study I propose a new, experiential approach to promoting resilience digitally. I define resilience as an emergent, situated and context-specific phenomenon. Using a Participatory Design model in combination with a salutogenic (strength-based) health methodology, this project has involved approximately 50 children as co-designers and co-researchers over two years. The children have contributed to the design of a new set of interactive resilience tools, which facilitate resilience promotion through dialogic and experiential learning. The major outcomes of this study include a new methodology for developing digital resilience tools, a new set of tools that have been developed and evaluated in collaboration with children and a set of design principles to guide future development. Beyond these initial and tangible outcomes, this study has also established that the benefits of introducing Participatory Design into a health promoting model rests primarily in the change of the role of children from "users" of technology and education to co-designers, where they assume a leadership role in both designing the tools and in directing their resilience learning.

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A 1,000-word travel article about Ndola, Zambia.

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Prostate cancer (CaP) is the second leading cause of cancer-related deaths in North American males and the most common newly diagnosed cancer in men world wide. Biomarkers are widely used for both early detection and prognostic tests for cancer. The current, commonly used biomarker for CaP is serum prostate specific antigen (PSA). However, the specificity of this biomarker is low as its serum level is not only increased in CaP but also in various other diseases, with age and even body mass index. Human body fluids provide an excellent resource for the discovery of biomarkers, with the advantage over tissue/biopsy samples of their ease of access, due to the less invasive nature of collection. However, their analysis presents challenges in terms of variability and validation. Blood and urine are two human body fluids commonly used for CaP research, but their proteomic analyses are limited both by the large dynamic range of protein abundance making detection of low abundance proteins difficult and in the case of urine, by the high salt concentration. To overcome these challenges, different techniques for removal of high abundance proteins and enrichment of low abundance proteins are used. Their applications and limitations are discussed in this review. A number of innovative proteomic techniques have improved detection of biomarkers. They include two dimensional differential gel electrophoresis (2D-DIGE), quantitative mass spectrometry (MS) and functional proteomic studies, i.e., investigating the association of post translational modifications (PTMs) such as phosphorylation, glycosylation and protein degradation. The recent development of quantitative MS techniques such as stable isotope labeling with amino acids in cell culture (SILAC), isobaric tags for relative and absolute quantitation (iTRAQ) and multiple reaction monitoring (MRM) have allowed proteomic researchers to quantitatively compare data from different samples. 2D-DIGE has greatly improved the statistical power of classical 2D gel analysis by introducing an internal control. This chapter aims to review novel CaP biomarkers as well as to discuss current trends in biomarker research from two angles: the source of biomarkers (particularly human body fluids such as blood and urine), and emerging proteomic approaches for biomarker research.

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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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Psychosis is a mental disorder that affects 1-2% of the population at some point in their lives. One of the main causes of psychosis is the mental illness schizophrenia. Sufferers of this illness often have terrifying symptoms such as hallucinations, delusions, and thought disorder. This project aims to develop a virtual environment to simulate the experience of psychosis, focusing on re-creating auditory and visual hallucinations. A model of a psychiatric ward was created and the psychosis simulation software was written to re-create the auditory and visual hallucinations of one particular patient. The patient was very impressed with the simulation, and commented that it effectively re-created the same emotions that she experienced on a day-to-day basis during her psychotic episodes. It is hoped that this work will result in a useful educational tool about schizophrenia, leading to improved training of clinicians, and fostering improved understanding and empathy toward sufferers of schizophrenia in the community, ultimately improving the quality of life and chances of recovery of patients.

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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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The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

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An ambitious rendering of the digital future from a pioneer of media and cultural studies, a wise and witty take on a changing field, and our orientation to it Investigates the uses of multimedia by creative and productive citizen-consumers to provide new theories of communication that accommodate social media, participatory action, and user-creativity Leads the way for new interdisciplinary engagement with systems thinking, complexity and evolutionary sciences, and the convergence of cultural and economic values Analyzes the historical uses of multimedia from print, through broadcasting to the internet Combines conceptual innovation with historical erudition to present a high-level synthesis of ideas and detailed analysis of emergent forms and practices Features an international focus and global reach to provide a basis for students and researchers seeking broader perspectives

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Recent advancements in the capabilities of information and communication technologies (ICT) offer unique avenues to support the delivery of nutrition care. Despite ICTs being widely available, evidence on the practices and attitudes with regard to ICT use among dietitians is limited. A cross-sectional survey of Dietitians Association of Australia members was administered online in August 2011. All dietitians who responded (n=87) had access to a computer at work. Half reported providing non face-to-face consultations, with the telephone and email the most common modes of delivery. The use of smart phones was prevalent for 49% of practitioners, with 30% recommending nutrition-related applications and/or programs to clients. Benefits to technology use in practice most commonly reported included improvements in access to information/resources, time management, and workflow efficiency. Barriers identified related to cost and access to technology, and lack of suitable programs/applications. Technology was viewed as an important tool in practice among 93% of dietitians surveyed, however only 38% were satisfied with their current level of use. The majority (81%) believed more technology should be integrated within dietetics, while 85% indicated that the development of suitable and practical applications andprograms is necessary for future practice. Technology is regarded as an important tool by Australian dietitians, with an expressed need for theirinclusion to further facilitate nutrition care. Regular and ongoing evaluation of technology use among dietitians is vital to ensure thatapplications and use are evidence based and relevant to consumers in the digital world.