929 resultados para pattern via food
Resumo:
The nonlinear interaction between light and atoms is an extensive field of study with a broad range of applications in quantum information science and condensed matter physics. Nonlinear optical phenomena occurring in cold atoms are particularly interesting because such slowly moving atoms can spatially organize into density gratings, which allows for studies involving optical interactions with structured materials. In this thesis, I describe a novel nonlinear optical effect that arises when cold atoms spatially bunch in an optical lattice. I show that employing this spatial atomic bunching provides access to a unique physical regime with reduced thresholds for nonlinear optical processes and enhanced material properties. Using this method, I observe the nonlinear optical phenomenon of transverse optical pattern formation at record-low powers. These transverse optical patterns are generated by a wave- mixing process that is mediated by the cold atomic vapor. The optical patterns are highly multimode and induce rich non-equilibrium atomic dynamics. In particular, I find that there exists a synergistic interplay between the generated optical pat- terns and the atoms, wherein the scattered fields help the atoms to self-organize into new, multimode structures that are not externally imposed on the atomic sample. These self-organized structures in turn enhance the power in the optical patterns. I provide the first detailed investigation of the motional dynamics of atoms that have self-organized in a multimode geometry. I also show that the transverse optical patterns induce Sisyphus cooling in all three spatial dimensions, which is the first observation of spontaneous three-dimensional cooling. My experiment represents a unique means by which to study nonlinear optics and non-equilibrium dynamics at ultra-low required powers.
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We have achieved highly localised control of pattern formation in two dimensional nanoparticle assemblies by direct modification of solvent dewetting dynamics. A striking dependence of nanoparticle organisation on the size of atomic force microscope-generated surface heterogeneities is observed and reproduced in numerical simulations. Nanoscale features induce rupture of the solvent-nanoparticle film, causing the local flow of solvent to carry nanoparticles into confinement. Microscale heterogeneities instead slow the evaporation of the solvent, producing a remarkably abrupt interface between different nanoparticle patterns.
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Background Primary prevention of childhood overweight is an international priority. In Australia 20-25% of 2-8 year olds are already overweight. These children are at substantially increased the risk of becoming overweight adults, with attendant increased risk of morbidity and mortality. Early feeding practices determine infant exposure to food (type, amount, frequency) and include responses (eg coercion) to infant feeding behaviour (eg. food refusal). There is correlational evidence linking parenting style and early feeding practices to child eating behaviour and weight status. A focus on early feeding is consistent with the national focus on early childhood as the foundation for life-long health and well being. The NOURISH trial aims to implement and evaluate a community-based intervention to promote early feeding practices that will foster healthy food preferences and intake and preserve the innate capacity to self-regulate food intake in young children. Methods/Design This randomised controlled trial (RCT) aims to recruit 820 first-time mothers and their healthy term infants. A consecutive sample of eligible mothers will be approached postnatally at major maternity hospitals in Brisbane and Adelaide. Initial consent will be for re-contact for full enrolment when the infants are 4-7 months old. Individual mother- infant dyads will be randomised to usual care or the intervention. The intervention will provide anticipatory guidance via two modules of six fortnightly parent education and peer support group sessions, each followed by six months of regular maintenance contact. The modules will commence when the infants are aged 4-7 and 13-16 months to coincide with establishment of solid feeding, and autonomy and independence, respectively. Outcome measures will be assessed at baseline, with follow up at nine and 18 months. These will include infant intake (type and amount of foods), food preferences, feeding behaviour and growth and self-reported maternal feeding practices and parenting practices and efficacy. Covariates will include sociodemographics, infant feeding mode and temperament, maternal weight status and weight concern and child care exposure. Discussion Despite the strong rationale to focus on parents’ early feeding practices as a key determinant of child food preferences, intake and self-regulatory capacity, prospective longitudinal and intervention studies are rare. This trial will be amongst to provide Level II evidence regarding the impact of an intervention (commencing prior to age 12 months) on children’s eating patterns and behaviours. Trial Registration: ACTRN12608000056392
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This workshop proposes to explore new approaches to cultivate and support sustainable food culture in urban environments via human computer interaction design and ubiquitous technologies. Food is a challenging issue in urban contexts: while food consumption decisions are made many times a day, most food interaction for urbanites occurs based on convenience and habitual practices. This situation is contrasting to the fact that food is at the centre of global environment, health, and social issues that are becoming increasingly immanent and imminent. As such, it is timely and crucial to ask: what are feasible, effective, and innovative ways to improve human-food-interaction through human-computer-interaction in order to contribute to environmental, health, and social sustainability in urban environments? This workshop brings together insights across disciplines to discuss this question, and plan and promote individual, local, and global change for sustainable food culture.
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As a result of the growing adoption of Business Process Management (BPM) technology different stakeholders need to understand and agree upon the process models that are used to configure BPM systems. However, BPM users have problems dealing with the complexity of such models. Therefore, the challenge is to improve the comprehension of process models. While a substantial amount of literature is devoted to this topic, there is no overview of the various mechanisms that exist to deal with managing complexity in (large) process models. It is thus hard to obtain comparative insight into the degree of support offered for various complexity reducing mechanisms by state-of-the-art languages and tools. This paper focuses on complexity reduction mechanisms that affect the abstract syntax of a process model, i.e. the structure of a process model. These mechanisms are captured as patterns, so that they can be described in their most general form and in a language- and tool-independent manner. The paper concludes with a comparative overview of the degree of support for these patterns offered by state-of-the-art languages and language implementations.
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This workshop explores innovative approaches to understanding and cultivating sustainable food culture in urban environments via human-computer-interaction (HCI) design and ubiquitous technologies. We perceive the city as an intersecting network of people, place, and technology in constant transformation. Our 2009 OZCHI workshop, Hungry 24/7? HCI Design for Sustainable Food Culture, opened a new space for discussion on this intersection amongst researchers and practitioners from diverse backgrounds including academia, government, industry, and non-for-profit organisations. Building on the past success, this new instalment of the workshop series takes a more refined view on mobile human-food interaction and the role of interactive media in engaging citizens to cultivate more sustainable everyday human-food interactions on the go. Interactive media in this sense is distributed, pervasive, and embedded in the city as a network. The workshop addresses environmental, health, and social domains of sustainability by bringing together insights across disciplines to discuss conceptual and design approaches in orchestrating mobility and interaction of people and food in the city as a network of people, place, technology, and food.
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The current food practices around the world raises concerns for food insecurity in the future. Urban / suburban / and peri-urban environments are particularly problematic in their segregation from rural areas where the natural food sources are grown and harvested. Soaring urban population growth only deteriorates the lack of understanding in and access to fresh produce for the people who live, work, and play in the city. This paper explores the role of Human-Computer Interaction (HCI) design in encouraging individual users to participate in creating sustainable food cultures in urban environments. The paper takes a disciplinary perspective of urban informatics and presents five core constituents of the HCI design framework to encourage sustainable food culture in the city via ubiquitous technologies: the perspective of transdisciplinarity; the domains of interest of people, place, and technology; and the perspective of design.
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While Business Process Management (BPM) is an established discipline, the increased adoption of BPM technology in recent years has introduced new challenges. One challenge concerns dealing with the ever-growing complexity of business process models. Mechanisms for dealing with this complexity can be classified into two categories: 1) those that are solely concerned with the visual representation of the model and 2) those that change its inner structure. While significant attention is paid to the latter category in the BPM literature, this paper focuses on the former category. It presents a collection of patterns that generalize and conceptualize various existing mechanisms to change the visual representation of a process model. Next, it provides a detailed analysis of the degree of support for these patterns in a number of state-of-the-art languages and tools. This paper concludes with the results of a usability evaluation of the patterns conducted with BPM practitioners.
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Objective To describe the impact of a parent-led, family focused child weight management program on the food intake and activity patterns of pre-pubertal children. Methods n assessor-blinded, randomized controlled trial involving 111 (64% female) overweight, pre-pubertal children 6 to 9 years of age randomly assigned to parenting-skills training plus intensive lifestyle education, parenting-skills training alone, or a 12-month wait-listed control. Study outcomes were assessed at baseline, 6 months, and 12 months. This paper presents data on food intake assessed via a validated 54-item parent completed dietary questionnaire and activity behaviours assessed via a parent-report 20-item activity questionnaire. Results Intake of energy-dense nutrient poor foods was lower in both intervention groups at 6 months (mean difference, P+DA -1.5 serves [CI -2.0;-1.0]; P -1.0 serves [-2.0;-0.5]) and 12 months (mean difference P+DA -1.0 serves [CI -2.0;-0.5]; P -1.0 serves [-1.5; 0.0]) compared to baseline. Intake of vegetables, fruit, breads and cereals, meat and alternatives and dairy foods remained unchanged. Regardless of study group there were significant reductions over time in the reported time spent engaged in small screen activities and an increase in the time reported spent in active play. Conclusion Child weight management intervention that promotes food intake in line with national dietary guidelines achieves a reduction in children’s intake of energy dense, nutrient poor foods. This was achieved without compromising intake of nutrient-rich food and changes in were maintained even once the intervention ceased.
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A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants
An approach to statistical lip modelling for speaker identification via chromatic feature extraction
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This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS1 database, show encouraging results
Resumo:
This workshop is a continuation and extension to the successful past workshops exploring the intersection of food, technology, place, and people, namely 2009 OZCHI workshop, Hungry 24/7? HCI Design for Sustainable Food Culture and Sustainable Interaction with Food, Technology, and the City [1] and 2010 CHI panel Making Food, Producing Sustainability [3]. The workshop aims to bring together experts from diverse backgrounds including academia, government, industry, and non-for-profit organisations. It specifically aims to create a space for discussion and design of innovative approaches to understanding and cultivating sustainable food practices via human-computer-interaction (HCI) as well as addressing the wider opportunities for the HCI community to engage with food as a key issue for sustainability The workshop addresses environmental, health, and social domains of sustainability in particular, by looking at various conceptual and design approaches in orchestrating sustainable interaction of people and food in and through dynamic techno-social networks.
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In the present paper, we introduce BioPatML.NET, an application library for the Microsoft Windows .NET framework [2] that implements the BioPatML pattern definition language and sequence search engine. BioPatML.NET is integrated with the Microsoft Biology Foundation (MBF) application library [3], unifying the parsers and annotation services supported or emerging through MBF with the language, search framework and pattern repository of BioPatML. End users who wish to exploit the BioPatML.NET engine and repository without engaging the services of a programmer may do so via the freely accessible web-based BioPatML Editor, which we describe below.
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Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.