428 resultados para functional vision


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The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

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Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

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Introduction Single nucleotide polymorphisms in ERAP2 are strongly associated with ankylosing spondylitis (AS). One AS-associated single nucleotide polymorphism, rs2248374, causes a truncated ERAP2 protein that is degraded by nonsense-mediated decay. Approximately 25% of the populations of European ancestry are therefore natural ERAP2 knockouts. We investigated the effect of this associated variant on HLA class I allele presentation, surface heavy chains, endoplasmic reticulum (ER) stress markers and cytokine gene transcription in AS. Methods Patients with AS and healthy controls with either AA or GG homozygous status for rs2248374 were studied. Antibodies to CD14, CD19-ECD, HLA-A-B-C, Valpha7.2, CD161, anti-HC10 and anti-HLA-B27 were used to analyse peripheral blood mononuclear cells. Expression levels of ER stress markers (GRP78 and CHOP) and proinflammatory genes (tumour necrosis factor (TNF), IL6, IL17 and IL22) were assessed by qPCR. Results There was no significant difference in HLAclass I allele presentation or major histocompatibility class I heavy chains or ER stress markers GRP78 and CHOP or proinflammatory gene expression between genotypes for rs2248374 either between cases, between cases and controls, and between controls. Discussion Large differences were not seen in HLAB27 expression or cytokine levels between subjects with and without ERAP2 in AS cases and controls. This suggests that ERAP2 is more likely to influence AS risk through other mechanisms.

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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

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Functional Imagery Training (FIT) is a new theory-based, manualized intervention that trains positive goal imagery. Multisensory episodic imagery of proximal personal goals is elicited and practised, to sustain motivation and compete with less functional cravings. This study tested the impact of a single session of FIT plus a booster phone call on snacking. In a stepped-wedge design, 45 participants who wanted to lose weight or reduce snacking were randomly assigned to receive a session of FIT immediately or after a 2-week delay. High-sugar and high-fat snacks were recorded using timeline follow back for the previous 3 days, at baseline, 2 and 4 weeks. At 2 weeks, snacking was lower in the immediate group than in the delayed group, and the reduction after FIT was replicated in the delayed group between 2 and 4 weeks. Frequencies of motivational thoughts about snack reduction rose following FIT for both groups, and this change correlated with reductions in snacking and weight loss. By showing that FIT can support change in eating behaviours, these findings show its potential as a motivational intervention for weight management.

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Using density functional theory, we investigated the position preference and diffusion mechanisms of interstitial oxygen ions in lanthanum silicate La9.33Si6O26, which is an apatite-structured oxide and a promising candidate electrolyte material for solid oxide fuel cells. The reported lanthanum vacancies were explicitly taken into account by theoretically determining their arrangement with a supercell model. The most stable structures and the formation energies of oxygen interstitials were determined for each charged state. It was found that the double-negatively charged state is stable over a wide range of the Fermi level, and that the excess oxygen ions form split interstitials with the original oxygen ions, while the neutral and the single-negatively charged states preferably form molecular oxygen. These species were found near the lanthanum vacancy site. The theoretically determined migration pathway along the c-axis essentially follows an interstitialcy mechanism. The obtained migration barrier is sensitive to the charge state, and is also affected by the lanthanum vacancy. The barrier height of the double-negatively charged state was calculated to be 0.58 eV for the model structure, which is consistent with the measured activation energy.

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The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

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Exercise that targets ankle joint mobility may lead to improvement in calf muscle pump function and subsequent healing. The objectives of this research were to assess the impact of an exercise intervention in addition to routine evidence-based care on the healing rates, functional ability and health-related quality of life for adults with venous leg ulcers (VLUs). This study included 63 patients with VLUs. Patients were randomised to receive either a 12-week exercise intervention with a telephone coaching component or usual care plus telephone calls at the same timepoints. The primary outcome evaluated the effectiveness of the intervention in relation to wound healing. The secondary outcomes evaluated physical activity, functional ability and health-related quality of life measures between groups at the end of the 12 weeks. A per protocol analysis complemented the effectiveness (intention-to-treat) analysis to highlight the importance of adherence to an exercise intervention. Intention-to-treat analyses for the primary outcome showed 77% of those in the intervention group healed by 12 weeks compared to 53% of those in the usual care group. Although this difference was not statistically significant due to a smaller than expected sample size, a 24% difference in healing rates could be considered clinically significant. The per protocol analysis for wound healing, however, showed that those in the intervention group who adhered to the exercise protocol 75% or more of the time were significantly more likely to heal and showed higher rates for wound healing than the control group (P = 0·01), that is, 95% of those who adhered in the intervention group healed in 12 weeks. The secondary outcomes of physical activity, functional ability and health-related quality of life were not significantly altered by the intervention. Among the secondary outcomes (physical activity, functional ability and health-related quality of life), intention-to-treat analyses did not support the effectiveness of the intervention. However, per protocol analyses revealed encouraging results with those participants who adhered more than 75% of the time (n = 19) showing significantly improved Range of Ankle Motion from the self-management exercise programme (P = 0·045). This study has shown that those participants who adhere to the exercise programme as an adjunctive treatment to standard care are more likely to heal and have better functional outcomes than those who do not adhere to the exercises in conjunction with usual care.