88 resultados para Spatio-temporal dynamics
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This paper is directed towards providing an answer to the question, ”Can you control the trajectory of a Lagrangian float?” Being a float that has minimal actuation (only buoyancy control), their horizontal trajectory is dictated through drifting with ocean currents. However, with the appropriate vertical actuation and utilising spatio-temporal variations in water speed and direction, we show here that broad controllabilty results can be met such as waypoint following to keep a float inside of a bay or out of a designated region. This paper extends theory experimen- tally evaluted on horizontally actuated Autonomous Underwater Vehicles (AUVs) for trajectory control utilising ocean forecast models and presents an initial investi- gation into the controllability of these minimally actuated drifting AUVs. Simulated results for offshore coastal and within highly dynamic tidal bays illustrate two tech- niques with the promise for an affirmative answer to the posed question above.
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This work is an installation featuring three video projections, music and mirror balls. The three projections fill the walls with scrolling text borrowed from love song lyrics. Headphones in the gallery space allow you to hear a male voice sing the same words to an impromptu tune. Mirror balls send fragments of light spinning around the room while The Righteous Brothers’ Unchained Melody plays on repeat. This work emphasizes fragmentary, repetitious and spatio-temporal experiences of language in order to question the symbolic conventions of romance. By exaggerating and mixing hackneyed symbolic elements, this work extends on some of Nicolas Bourriaud’s theoretical insights into the creative and critical strategies of ‘postproduction’. In particular, it toys with the intersections between popular culture and inter-subjective experiences.
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The health effects of environmental hazards are often examined using time series of the association between a daily response variable (e.g., death) and a daily level of exposure (e.g., temperature). Exposures are usually the average from a network of stations. This gives each station equal importance, and negates the opportunity for some stations to be better measures of exposure. We used a Bayesian hierarchical model that weighted stations using random variables between zero and one. We compared the weighted estimates to the standard model using data on health outcomes (deaths and hospital admissions) and exposures (air pollution and temperature) in Brisbane, Australia. The improvements in model fit were relatively small, and the estimated health effects of pollution were similar using either the standard or weighted estimates. Spatial weighted exposures would be probably more worthwhile when there is either greater spatial detail in the health outcome, or a greater spatial variation in exposure.
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Problems involving the solution of advection-diffusion-reaction equations on domains and subdomains whose growth affects and is affected by these equations, commonly arise in developmental biology. Here, a mathematical framework for these situations, together with methods for obtaining spatio-temporal solutions and steady states of models built from this framework, is presented. The framework and methods are applied to a recently published model of epidermal skin substitutes. Despite the use of Eulerian schemes, excellent agreement is obtained between the numerical spatio-temporal, numerical steady state, and analytical solutions of the model.
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Quantifying spatial and/or temporal trends in environmental modelling data requires that measurements be taken at multiple sites. The number of sites and duration of measurement at each site must be balanced against costs of equipment and availability of trained staff. The split panel design comprises short measurement campaigns at multiple locations and continuous monitoring at reference sites [2]. Here we present a modelling approach for a spatio-temporal model of ultrafine particle number concentration (PNC) recorded according to a split panel design. The model describes the temporal trends and background levels at each site. The data were measured as part of the “Ultrafine Particles from Transport Emissions and Child Health” (UPTECH) project which aims to link air quality measurements, child health outcomes and a questionnaire on the child’s history and demographics. The UPTECH project involves measuring aerosol and particle counts and local meteorology at each of 25 primary schools for two weeks and at three long term monitoring stations, and health outcomes for a cohort of students at each school [3].
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Research on the aspirations of people with intellectual disabilities documents the importance of alternative zones of inclusion where they can assert their own definitions of ability and normality. This stands in contrast to assumptions concerning technology and disability that position technology as ‘normalising’ the disabled body. This paper reports on the role of a digital music jamming tool in providing access to creative practice by people with intellectual disabilities. The tool contributed to the development of a spatio-temporal zone to enable aesthetic agency within and beyond the contexts of deinstitutionalised care. The research identifies the interactions among tools, individuals and groups that facilitated participants’ agency in shaping the form of musical practice. Further, we document the properties of emergent interaction - supported by a tool oriented to enabling music improvisation - as potentially resisting assumptions regarding normalisation.
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Dengue fever is one of the world’s most important vector-borne diseases. The transmission area of this disease continues to expand due to many factors including urban sprawl, increased travel and global warming. Current preventative techniques are primarily based on controlling mosquito vectors as other prophylactic measures, such as a tetravalent vaccine are unlikely to be available in the foreseeable future. However, the continually increasing dengue incidence suggests that this strategy alone is not sufficient. Epidemiological models attempt to predict future outbreaks using information on the risk factors of the disease. Through a systematic literature review, this paper aims at analyzing the different modeling methods and their outputs in terms of accurately predicting disease outbreaks. We found that many previous studies have not sufficiently accounted for the spatio-temporal features of the disease in the modeling process. Yet with advances in technology, the ability to incorporate such information as well as the socio-environmental aspect allowed for its use as an early warning system, albeit limited geographically to a local scale.
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Cancer poses an undeniable burden to the health and wellbeing of the Australian community. In a recent report commissioned by the Australian Institute for Health and Welfare(AIHW, 2010), one in every two Australians on average will be diagnosed with cancer by the age of 85, making cancer the second leading cause of death in 2007, preceded only by cardiovascular disease. Despite modest decreases in standardised combined cancer mortality over the past few decades, in part due to increased funding and access to screening programs, cancer remains a significant economic burden. In 2010, all cancers accounted for an estimated 19% of the country's total burden of disease, equating to approximately $3:8 billion in direct health system costs (Cancer Council Australia, 2011). Furthermore, there remains established socio-economic and other demographic inequalities in cancer incidence and survival, for example, by indigenous status and rurality. Therefore, in the interests of the nation's health and economic management, there is an immediate need to devise data-driven strategies to not only understand the socio-economic drivers of cancer but also facilitate the implementation of cost-effective resource allocation for cancer management...
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Topic recommendation can help users deal with the information overload issue in micro-blogging communities. This paper proposes to use the implicit information network formed by the multiple relationships among users, topics and micro-blogs, and the temporal information of micro-blogs to find semantically and temporally relevant topics of each topic, and to profile users' time-drifting topic interests. The Content based, Nearest Neighborhood based and Matrix Factorization models are used to make personalized recommendations. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on a real world dataset that collected from Twitter.com.
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Real-world AI systems have been recently deployed which can automatically analyze the plan and tactics of tennis players. As the game-state is updated regularly at short intervals (i.e. point-level), a library of successful and unsuccessful plans of a player can be learnt over time. Given the relative strengths and weaknesses of a player’s plans, a set of proven plans or tactics from the library that characterize a player can be identified. For low-scoring, continuous team sports like soccer, such analysis for multi-agent teams does not exist as the game is not segmented into “discretized” plays (i.e. plans), making it difficult to obtain a library that characterizes a team’s behavior. Additionally, as player tracking data is costly and difficult to obtain, we only have partial team tracings in the form of ball actions which makes this problem even more difficult. In this paper, we propose a method to overcome these issues by representing team behavior via play-segments, which are spatio-temporal descriptions of ball movement over fixed windows of time. Using these representations we can characterize team behavior from entropy maps, which give a measure of predictability of team behaviors across the field. We show the efficacy and applicability of our method on the 2010-2011 English Premier League soccer data.
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Background Hallux valgus (HV) has been linked to functional disability and increased falls risk in older adults. However, specific gait alterations in individuals with HV are unclear. This systematic review investigated gait parameters associated with HV in otherwise healthy adults. Methods Electronic databases (Medline, Embase, CINAHL) were searched to October 2011, including cross-sectional studies with clearly defined HV and non-HV comparison groups. Two investigators independently rated studies for methodological quality. Effect sizes (95% confidence intervals (CI)) were calculated as standardized mean differences (SMD) for continuous data and risk ratios (RR) for dichotomous data. Results Nine studies included a total of 589 participants. Three plantar pressure studies reported increased hallux loading (SMD 0.56 to 1.78) and medial forefoot loading (SMD 0.62 to 1.21), while one study found reduced first metatarsal loading (SMD −0.61, CI −1.19 to −0.03) in HV participants. HV participants demonstrated less ankle and rearfoot motion during terminal stance (SMD −0.81 to −0.63) and increased intrinsic muscle activity (RR 1.6, 1.1 to 2.2). Most studies reported no differences in spatio-temporal parameters; however, one study found reduced speed (SMD −0.73, -1.25 to −0.20), step length (SMD −0.66 to −0.59) and less stable gait patterns (SMD −0.86 to −0.78) in older adults with HV. Conclusions HV impacts on particular gait parameters, and further understanding of potentially modifiable factors is important for prevention and management of HV. Cause and effect relationships cannot be inferred from cross-sectional studies, thus prospective studies are warranted to elucidate the relationship between HV and functional disability.
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Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.
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The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.
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A large number of methods have been published that aim to evaluate various components of multi-view geometry systems. Most of these have focused on the feature extraction, description and matching stages (the visual front end), since geometry computation can be evaluated through simulation. Many data sets are constrained to small scale scenes or planar scenes that are not challenging to new algorithms, or require special equipment. This paper presents a method for automatically generating geometry ground truth and challenging test cases from high spatio-temporal resolution video. The objective of the system is to enable data collection at any physical scale, in any location and in various parts of the electromagnetic spectrum. The data generation process consists of collecting high resolution video, computing accurate sparse 3D reconstruction, video frame culling and down sampling, and test case selection. The evaluation process consists of applying a test 2-view geometry method to every test case and comparing the results to the ground truth. This system facilitates the evaluation of the whole geometry computation process or any part thereof against data compatible with a realistic application. A collection of example data sets and evaluations is included to demonstrate the range of applications of the proposed system.
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Table of Contents “your darkness also/rich and beyond fear”: Community Performance, Somatic Poetics and the Vessels of Self and Other - Petra Kuppers. "So what will you do on the plinth?”: A Personal Experience of Disclosure during Antony Gormley’s "One & Other" Project - Jill Francesca Dowse. Food Confessions: Disclosing the Self through the Performance of Food - Jenny Lawson Participation Cartography: The Presentation of Self in Spatio-Temporal Terms - Luis Carlos Sotelo-Castro Disclosure in Biographically-Based Fiction: The Challenges of Writing Narratives Based on True Life Stories - Donna Lee Brien. Closure through Mock-Disclosure in Bret Easton Ellis’s Lunar Park - Jennifer Anne Phillips. Disclosing the Ethnographic Self - Christine Lohmeier Celebrity Twitter: Strategies of Intrusion and Disclosure in the Age of Technoculture - Nick Muntean, Anne Helen Petersen. “Just Emotional People”? Emo Culture and the Anxieties of Disclosure - Michelle Phillipov.