973 resultados para visual literacy
Resumo:
Financial literacy may not be as effective as previously thought in protecting against fraud victimisation. It does not inoculate investors from persuasion or social engineering tactics used by offenders to secure investment in fraudulent schemes. In fact, recent research indicates that overconfidence in investment knowledge may make individuals more susceptible to fraud. Using boiler room fraud as a case study, this article introduces the PREY (Profiled, Relational, Exploitable and Yielding) model to capture the psychological tactics used by fraud perpetrators to influence the thoughts and decision-making processes of individuals. The PREY model operationalizes the tenets of social engineering and demonstrates how such tactics could be re-engineered to increase the effectiveness of fraud prevention within the financial literacy context.
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This paper introduces an improved line tracker using IMU and vision data for visual servoing tasks. We utilize an Image Jacobian which describes motion of a line feature to corresponding camera movements. These camera motions are estimated using an IMU. We demonstrate impacts of the proposed method in challenging environments: maximum angular rate ~160 0/s, acceleration ~6m /s2 and in cluttered outdoor scenes. Simulation and quantitative tracking performance comparison with the Visual Servoing Platform (ViSP) are also presented.
Resumo:
In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.
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"Food literacy" has emerged as a term to describe the everyday practicalities needed for healthy eating. It is increasingly used in policy, practice, research and in the public arena. This thesis empirically defined the term, identified its components, and developed models of its relationship to nutrition and health. Food literacy was examined from two perspectives; that of food experts and that of individuals using the case study of young people experiencing disadvantage. The research provides a common language and conceptualisation of food literacy which is being used by governments, policy-makers and practitioners to guide investment and practice.
Resumo:
Literacy in dance involves conscious awareness of cognitive, aesthetic and physical activity along with the skills to articulate these activities as required in any given context. Dance literacy, perhaps uniquely, also entails unconscious, tacit, embodied knowledge within the holistic body, a corporeality: knowledge which is physically experienced but only articulated in the dance. The essence of this corporeality has a transcendent quality which contributes to the universality of dance. The degrees to which a dancer’s awareness is refined, the physical activity articulated and the embodied knowledge universal, will define the level of development of the dancer’s literacy. This literacy can be learned, though not every body and mind has equal capacity for development. If we wish to develop dance literacy, qualitatively encompassing more than dance technique, the art of learning must be carefully cultivated to allow the art of dance to flourish. The pathways of learning dance are individuated; transcendence is realised through the common experience that what we are learning is coming from within.
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Ongoing innovation in digital animation and visual effects technologies has provided new opportunities for stories to be visually rendered in ways never before possible. Films featuring animation and visual effects continue to perform well at the box office, proving to be highly profitable projects. The Avengers (Whedon, 2012) holds the current record for opening weekend sales, accruing as much as $207,438,708 USD and $623,357,910 USD gross at time of writing. Life of Pi (Lee, 2012) at time of writing has grossed as much as $608,791,063 USD (Box Office Mojo, 2013). With so much creative potential and a demonstrable ability to generate a large amount of revenue, the animation and visual effects industry – otherwise known as the Post, Digital and Visual Effects (PDV) industry – has become significant to the future growth and stability of the Australian film industry as a whole.
Resumo:
Advocacy is integral to the work of many TESOL specialists. For several decades, ACTA and the state TESOL associations, along with other professional associations, and individual teachers, researchers and administrators have all engaged with conversations about EAL/D education in public forums. These advocates have drawn attention to implications of policy developments for EAL/D students; they have proffered alternative forms of curriculum, pedagogy and assessment to better account for the particularity of EAL/D learning pathways; they have argued the necessity of specialist EAL/D teaching. In response to the Australian Language and Literacy Policy of the early 1990s, for example, there was “a frenzy of writing responses… a conference… and attempts to publicise what was going on through the press and television” (Moore, 1995, p. 6). It is in this spirit that this double issue of TESOL in Context has been compiled...
Resumo:
Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.
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This work aims to contribute to the reliability and integrity of perceptual systems of unmanned ground vehicles (UGV). A method is proposed to evaluate the quality of sensor data prior to its use in a perception system by utilising a quality metric applied to heterogeneous sensor data such as visual and infrared camera images. The concept is illustrated specifically with sensor data that is evaluated prior to the use of the data in a standard SIFT feature extraction and matching technique. The method is then evaluated using various experimental data sets that were collected from a UGV in challenging environmental conditions, represented by the presence of airborne dust and smoke. In the first series of experiments, a motionless vehicle is observing a ’reference’ scene, then the method is extended to the case of a moving vehicle by compensating for its motion. This paper shows that it is possible to anticipate degradation of a perception algorithm by evaluating the input data prior to any actual execution of the algorithm.
Resumo:
This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke. An example of application is given with monocular SLAM estimating the pose of the UGV while smoke is present in the environment. It is shown that the proposed novel quality metric can be used to anticipate situations where the quality of the pose estimate will be significantly degraded due to the input image data. This leads to decisions of advantageously switching between data sources (e.g. using infrared images instead of visual images).
Resumo:
This paper proposes an experimental study of quality metrics that can be applied to visual and infrared images acquired from cameras onboard an unmanned ground vehicle (UGV). The relevance of existing metrics in this context is discussed and a novel metric is introduced. Selected metrics are evaluated on data collected by a UGV in clear and challenging environmental conditions, represented in this paper by the presence of airborne dust or smoke.
Resumo:
This work aims to contribute to reliability and integrity in perceptual systems of autonomous ground vehicles. Information theoretic based metrics to evaluate the quality of sensor data are proposed and applied to visual and infrared camera images. The contribution of the proposed metrics to the discrimination of challenging conditions is discussed and illustrated with the presence of airborne dust and smoke.
Resumo:
Objectives: To investigate the relationship between two assessments to quantify delayed onset muscle soreness [DOMS]: visual analog scale [VAS] and pressure pain threshold [PPT]. Methods: Thirty-one healthy young men [25.8 ± 5.5 years] performed 10 sets of six maximal eccentric contractions of the elbow flexors with their non-dominant arm. Before and one to four days after the exercise, muscle pain perceived upon palpation of the biceps brachii at three sites [5, 9 and 13 cm above the elbow crease] was assessed by VAS with a 100 mm line [0 = no pain, 100 = extremely painful], and PPT of the same sites was determined by an algometer. Changes in VAS and PPT over time were compared amongst three sites by a two-way repeated measures analysis of variance, and the relationship between VAS and PPT was analyzed using a Pearson product-moment correlation. Results: The VAS increased one to four days after exercise and peaked two days post-exercise, while the PPT decreased most one day post-exercise and remained below baseline for four days following exercise [p < 0.05]. No significant difference among the three sites was found for VAS [p = 0.62] or PPT [p = 0.45]. The magnitude of change in VAS did not significantly correlate with that of PPT [r = −0.20, p = 0.28]. Conclusion: These results suggest that the level of muscle pain is not region-specific, at least among the three sites investigated in the study, and VAS and PPT provide different information about DOMS, indicating that VAS and PPT represent different aspects of pain.
Resumo:
The integration of separate, yet complimentary, cortical pathways appears to play a role in visual perception and action when intercepting objects. The ventral system is responsible for object recognition and identification, while the dorsal system facilitates continuous regulation of action. This dual-system model implies that empirically manipulating different visual information sources during performance of an interceptive action might lead to the emergence of distinct gaze and movement pattern profiles. To test this idea, we recorded hand kinematics and eye movements of participants as they attempted to catch balls projected from a novel apparatus that synchronised or de-synchronised accompanying video images of a throwing action and ball trajectory. Results revealed that ball catching performance was less successful when patterns of hand movements and gaze behaviours were constrained by the absence of advanced perceptual information from the thrower's actions. Under these task constraints, participants began tracking the ball later, followed less of its trajectory, and adapted their actions by initiating movements later and moving the hand faster. There were no performance differences when the throwing action image and ball speed were synchronised or de-synchronised since hand movements were closely linked to information from ball trajectory. Results are interpreted relative to the two-visual system hypothesis, demonstrating that accurate interception requires integration of advanced visual information from kinematics of the throwing action and from ball flight trajectory.
Resumo:
Food literacy has emerged as a term to describe the everyday practicalities associated with healthy eating. The term is increasingly used in policy, practice, research and by the public; however, there is no shared understanding of its meaning. The purpose of this research was to develop a definition of food literacy which was informed by the identification of its components. This was considered from two perspectives: that of food experts which aimed to reflect the intention of existing policy and investment, and that of individuals, who could be considered experts in the everyday practicalities of food provisioning and consumption. Given that food literacy is likely to be highly contextual, this second study focused on disadvantaged young people living in an urban area who were responsible for feeding themselves. The Expert Study used a Delphi methodology (round one n = 43). The Young People’s Study used semi-structured, life-course interviews (n = 37). Constructivist Grounded Theory was used to analyse results. This included constant comparison of data within and between studies. From this, eleven components of food literacy were identified which fell into the domains of: planning and management; selection; preparation; and eating. These were used to develop a definition for the term “food literacy”.