925 resultados para spatial activity recognition


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People interact with mobile computing devices everywhere, while sitting, walking, running or even driving. Adapting the interface to suit these contexts is important, thus this paper proposes a simple human activity classification system. Our approach uses a vector magnitude recognition technique to detect and classify when a person is stationary (or not walking), casually walking, or jogging, without any prior training. The user study has confirmed the accuracy.

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In Miller v Miller (2011) 85 ALJR 480; [2011] HCA 9 the High Court examined the complex issue of joint illegal activity. The issue before the court was whether a plaintiff who had engaged in an illegal activity with the defendant may claim damages in negligence. In its decision the court analysed the cases of Henwood v Municipal Tramways Trust (SA) (1938) 60 CLR 438, Smith v Jenkins (1970) 119 CLR 397, Jackson v Harrison (1978) 138 CLR 438 and Gala v Preston (1991) 172 CLR 243.

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This paper uses cultural-historical activity to examine the nature of learning assistance, provided in university settings, to assist learners in coping with academic study. Alternative rival constructions of learning assistance, either as part of an overall university activity system, or as an activity system overlapping with other separate activity systems (e.g. library and faculty) within the university, are outlined. Data from a research study at one university are used to describe the object, tools and tensions in learning assistance; and, together with the history of the service, these are used to suggest that the current situation is one where the objects of the Learning Assistance Unit, the faculty and the library have separated from the object of a university.

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Knowledge based urban development (KBUD) is a new paradigm in urban planning tailoring to the era of knowledge economy. It aims mainly to assist a contemporary city to promote a more sustainable socio-spatial order. The paper reports on the investigation of KBUD initiative in Malaysia which is manifested through the establishment of a project called Multimedia Super Corridor (MSC). MSC Malaysia aims to attract knowledge workers and industries to invest and operate within the area by creating a world class urban corridor with state-of-the-art multimedia infrastructure, efficient transportation system and an attractive living environment. Based on documents analysis and interviews, this paper analyses the strategies, implementations, and achievements of KBUD initiative in Cyberjaya, being the leading intelligent city of the unique Malaysia’s KBUD project-MSC Malaysia. A critical evaluation is made to assess the achievements of MSC, by looking at the physical changes after about ten years since its official launching. The findings recommend some valuable lessons for other cities that strive to develop KBUD strategies, strengthen their sustainable socio-spatial policies, and seek a global recognition.

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Objective: The aim of this study was to investigate the associations among measured physical fitness, perceived fitness, intention towards future physical activity and self-reported physical activity through junior high school years. Methods: Study participants included 122 Finnish students who were 13 years old during Grade 7. The sample was comprised of 80 girls and 42 boys from 3 junior high schools (Grades 7-9). During the autumn semester of Grade 7, students completed fitness tests and a questionnaire analyzing self-perception of their physical fitness. The questionnaire delivered at Grade 8 included intention towards future physical activity. At Grade 9 students’ self-reported physical activity levels. Results: Structural Equation Modeling revealed an indirect path from physical fitness to self-reported physical activity via perceived physical fitness and intention towards future physical activity. The model also demonstrated a correlation between perceived physical fitness and physical activity. Squared multiple correlations revealed that perceived physical fitness explained 33 % of the actual physical fitness. Conclusions: The results of this study highlight the role of physical and cognitive variables in the process of adoption of physical activity in adolescence.

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Many of the undergraduate and postgraduate programs of the former Faculty of Built Environment and Engineering PLUS Faculty of Sciences and Technology are changing as a result of merging these two large organisations, with some disciplines relocating to faculties of Creative Industries and Health respectively. The new STEM precinct under construction has begun rising from the proverbial hole-in-the-ground. Existing Surveying and Spatial Sciences programs, assets and staff are being repositioned with the newly formed School of Earth, Environment and Biological Sciences.2011. Golden graduates morning tea organised by QUT Alumni. Technology upgrades to the Mapping Sciences lab benefits 3-D learning experiences. Second and third-year students are undertaking Work Integrated Learning (WIL) over the summer vacation period. Final year students recently presented capstone project presentations at mini-conference in the Gibson Rooms overlooking a vibrant Southbank and sparkling Brisbane River. Discussion on end of year graduation ceremony held at QPAC.

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In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountainbiking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

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Significant research has demonstrated direct and indirect associations between substance use and sexual behaviour. Substance use is related to sexual risk-taking and HIV seroconversion among some substance-using MSM. It remains unclear what factors mediate or underlie this relationship, and which substances are associated with greater harm. Substance-related expectancies are hypothesised as potential mechanisms. A conceptual model based on social-cognitive theory was tested, which explores the role of demographic factors, substance use, substance-related expectancies and novelty-seeking personality characteristics in predicting unprotected anal intercourse (UAI) while under the influence, across four commonly used substance types. Phase 1, a qualitative study (N = 20), explored how MSM perceive the effects of substance use on their thoughts, feelings and behaviours, including sexual behaviours. Information was attained through discussion and interviews, resulting in the establishment of key themes. Results indicated MSM experience a wide range of reinforcing aspects associated with substance use. General and specific effects were evident across substance types, and were associated with sexual behaviour and sexual risk-taking. Phase 2 consisted of developing a comprehensive profile of substance-related expectancies for MSM (SEP-MSM) regarding alcohol, cannabis, amyl nitrite and stimulants that possessed sound psychometric properties and was appropriate for use among this group. A cross-sectional questionnaire with 249 participants recruited through gay community networks was used to validate these measures, and involved online data collection, participants rating expectancy items and subsequent factor analysis. Results indicated expectancies can be reliably assessed, and predicted substance use patterns. Phase 3 examined demographic factors, substance use, substance-related expectancies, and novelty-seeking traits among another community sample of MSM (N = 277) throughout Australia, in predicting UAI while under the influence. Using a cross-sectional design, participants were recruited through gay community networks and completed online questionnaires. The SEP-MSM, and associated substance use, predicted UAI. This research extends social-cognitive theory regarding sexual behaviour, and advances understanding of the role of expectancies associated with substance use and sexual risk-taking. Future applications of the SEP-MSM in health promotion, prevention, clinical interventions and research are likely to contribute to reducing harm associated with substance-using MSM (e.g., HIV transmission).

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Automatic species recognition plays an important role in assisting ecologists to monitor the environment. One critical issue in this research area is that software developers need prior knowledge of specific targets people are interested in to build templates for these targets. This paper proposes a novel approach for automatic species recognition based on generic knowledge about acoustic events to detect species. Acoustic component detection is the most critical and fundamental part of this proposed approach. This paper gives clear definitions of acoustic components and presents three clustering algorithms for detecting four acoustic components in sound recordings; whistles, clicks, slurs, and blocks. The experiment result demonstrates that these acoustic component recognisers have achieved high precision and recall rate.

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Secretory clusterin (sCLU) is a stress-activated, cytoprotective chaperone that confers broad-spectrum cancer treatment resistance, and its targeted inhibitor (OGX-011) is currently in phase II trials for prostate, lung, and breast cancer. However, the molecular mechanisms by which sCLU inhibits treatment-induced apoptosis in prostate cancer remain incompletely defined. We report that sCLU increases NF-κB nuclear translocation and transcriptional activity by serving as a ubiquitin-binding protein that enhances COMMD1 and I-κB proteasomal degradation by interacting with members of the SCF-βTrCP E3 ligase family. Knockdown of sCLU in prostate cancer cells stabilizes COMMD1 and I-κB, thereby sequestrating NF-κB in the cytoplasm and decreasing NF-κB transcriptional activity. Comparative microarray profiling of sCLU-overexpressing and sCLU-knockdown prostate cancer cells confirmed that the expression of many NF-κB–regulated genes positively correlates with sCLU levels. We propose that elevated levels of sCLU promote prostate cancer cell survival by facilitating degradation of COMMD1 and I-κB, thereby activating the canonical NF-κB pathway.

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The process of learning symbolic Arabic digits in early childhood requires that magnitude and spatial information integrates with the concept of symbolic digits. Previous research has separately investigated the development of automatic access to magnitude and spatial information from symbolic digits. However, developmental trajectories of symbolic number knowledge cannot be fully understood when considering components in isolation. In view of this, we have synthesized the existing lines of research and tested the use of both magnitude and spatial information with the same sample of British children in Years 1, 2 and 3 (6-8 years of age). The physical judgment task of the numerical Stroop paradigm (NSP) demonstrated that automatic access to magnitude was present from Year 1 and the distance effect signaled that a refined processing of numerical information had developed. Additionally, a parity judgment task showed that the onset of the Spatial-Numerical Association of Response Codes (SNARC) effect occurs in Year 2. These findings uncover the developmental timeline of how magnitude and spatial representations integrate with symbolic number knowledge during early learning of Arabic digits and resolve inconsistencies between previous developmental and experimental research lines.

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Rats are superior to the most advanced robots when it comes to creating and exploiting spatial representations. A wild rat can have a foraging range of hundreds of meters, possibly kilometers, and yet the rodent can unerringly return to its home after each foraging mission, and return to profitable foraging locations at a later date (Davis, et al., 1948). The rat runs through undergrowth and pipes with few distal landmarks, along paths where the visual, textural, and olfactory appearance constantly change (Hardy and Taylor, 1980; Recht, 1988). Despite these challenges the rat builds, maintains, and exploits internal representations of large areas of the real world throughout its two to three year lifetime. While algorithms exist that allow robots to build maps, the questions of how to maintain those maps and how to handle change in appearance over time remain open. The robotic approach to map building has been dominated by algorithms that optimise the geometry of the map based on measurements of distances to features. In a robotic approach, measurements of distance to features are taken with range-measuring devices such as laser range finders or ultrasound sensors, and in some cases estimates of depth from visual information. The features are incorporated into the map based on previous readings of other features in view and estimates of self-motion. The algorithms explicitly model the uncertainty in measurements of range and the measurement of self-motion, and use probability theory to find optimal solutions for the geometric configuration of the map features (Dissanayake, et al., 2001; Thrun and Leonard, 2008). Some of the results from the application of these algorithms have been impressive, ranging from three-dimensional maps of large urban strucutures (Thrun and Montemerlo, 2006) to natural environments (Montemerlo, et al., 2003).

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In this paper we present a novel algorithm for localization during navigation that performs matching over local image sequences. Instead of calculating the single location most likely to correspond to a current visual scene, the approach finds candidate matching locations within every section (subroute) of all learned routes. Through this approach, we reduce the demands upon the image processing front-end, requiring it to only be able to correctly pick the best matching image from within a short local image sequence, rather than globally. We applied this algorithm to a challenging downhill mountain biking visual dataset where there was significant perceptual or environment change between repeated traverses of the environment, and compared performance to applying the feature-based algorithm FAB-MAP. The results demonstrate the potential for localization using visual sequences, even when there are no visual features that can be reliably detected.

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The Lingodroids are a pair of mobile robots that evolve a language for places and relationships between places (based on distance and direction). Each robot in these studies has its own understanding of the layout of the world, based on its unique experiences and exploration of the environment. Despite having different internal representations of the world, the robots are able to develop a common lexicon for places, and then use simple sentences to explain and understand relationships between places even places that they could not physically experience, such as areas behind closed doors. By learning the language, the robots are able to develop representations for places that are inaccessible to them, and later, when the doors are opened, use those representations to perform goal-directed behavior.