816 resultados para Investigative tasks


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Purpose: To investigate the changes in axial length with the combined effect of accommodation and angle of gaze (convergence and downward gaze) over 5 minutes in groups of myopes and emmetropes. Methods: A total of 31 subjects (nine emmetropes, 10 low myopes, and 12 moderate to high myopes) aged from 18 to 31 years were recruited. To measure ocular biometrics in inferonasal gaze with accommodation, an optical biometer (Lenstar LS900) was inclined on a tilt and height adjustable stage, with the subject’s chinrest mounted on a rotary stage to induce various levels of convergence by rotation of the subject’s head in primary or downward gaze. Initially, the subjects performed a distance viewing task in primary gaze for 10 minutes to provide a ‘wash-out’ period for prior visual tasks, and then the subject’s axial length and ocular biometrics were measured in nine different combinations of gaze/accommodation over 5 minutes. These nine sessions for all gaze measurements (i.e. three levels of accommodation 9 three levels of convergence) were completed across 3 days of testing (one accommodation condition on each day).The nine combinations of gaze/accommodation were based on those required to view the centre, right and left edges of a distant TV at 6 m in primary gaze, an intermediate task (i.e. computer at 50 cm in 10° downward gaze) and a near task (i.e. reading A4 page at 20 cm in 20° downward gaze). Subjects were wearing a custom built three-axes head tracker throughout the experiment that monitored subjects’ relative head movements (roll, pitch and yaw) during measurements. Results: A significant increase in axial length occurred with the combined effect of accommodation, convergence and downward gaze (repeated measures ANOVA, p < 0.001), with the greatest axial elongation during the near task in downward gaze with convergence (i.e. downward 20°/inward 33°, with 5 D accommodation) (mean change 33 ± 13 lm, after 5 minutes task) followed by the intermediate task (i.e. downward 10°/inward 25°, with 2 D accommodation) (mean change 14 ± 11 lm, after 5 minutes task).Changes in axial length for the distance task (i.e. primary gaze/9° convergence, with 0.16 D accommodation) were not statistically significant (mean change 4 ± 8 lm, after 5 minutes task, p > 0.05). Moderate to high myopes had a greater change in the axial length (mean change 40 ± 11 lm after 5 minutes of near task) than that of emmetropes (mean change 29 ± 15 lm after 5 minutes of near task) and low myopes (mean change 29 ± 16 lm after 5 minutes of near task) associated with time (p = 0.02) and accommodation by time (p = 0.03). Conclusions: The combination of accommodation, convergence and downward angle has a significant short term effect on axial length over time. The near task in downward gaze with convergence caused a greater change in axial length than the intermediate and distant visual tasks. The greater axial elongation measured in the infero-nasal direction with accommodation is most likely associated with a combination of biomechanical factors such as, extraocular muscle forces and ciliary muscle contraction.

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Existing techniques for automated discovery of process models from event logs largely focus on extracting flat process models. In other words, they fail to exploit the notion of subprocess, as well as structured error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of BPMN models containing subprocesses, interrupting and non-interrupting boundary events, and loop and multi-instance markers. The technique analyzes dependencies between data attributes associated with events, in order to identify subprocesses and to extract their associated logs. Parent process and subprocess models are then discovered separately using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. A validation with one synthetic and two real-life logs shows that process models derived using the proposed technique are more accurate and less complex than those derived with flat process model discovery techniques.

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The primary aim of this paper was to investigate heterogeneity in language abilities of children with a confirmed diagnosis of an ASD (N = 20) and children with typical development (TD; N = 15). Group comparisons revealed no differences between ASD and TD participants on standard clinical assessments of language ability, reading ability or nonverbal intelligence. However, a hierarchical cluster analysis based on spoken nonword repetition and sentence repetition identified two clusters within the combined group of ASD and TD participants. The first cluster (N = 6) presented with significantly poorer performances than the second cluster (N = 29) on both of the clustering variables in addition to single word and nonword reading. The significant differences between the two clusters occur within a context of Cluster 1 having language impairment and a tendency towards more severe autistic symptomatology. Differences between the oral language abilities of the first and second clusters are considered in light of diagnosis, attention and verbal short term memory skills and reading impairment.

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Accurate process model elicitation continues to be a time consuming task, requiring skill on the part of the interviewer to extract explicit and tacit process information from the interviewee. Many errors occur in this elicitation stage that would be avoided by better activity recall, more consistent specification methods and greater engagement in the elicitation process by interviewees. Theories of situated cognition indicate that interactive 3D representations of real work environments engage and prime the cognitive state of the viewer. In this paper, our major contribution is to augment a previous process elicitation methodology with virtual world context metadata, drawn from a 3D simulation of the workplace. We present a conceptual and formal approach for representing this contextual metadata, integrated into a process similarity measure that provides hints for the business analyst to use in later modelling steps. Finally, we conclude with examples from two use cases to illustrate the potential abilities of this approach.

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The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

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Purpose To investigate the effect of different levels of refractive blur on real-world driving performance measured under day and nighttime conditions. Methods Participants included 12 visually normal, young adults (mean age = 25.8 ± 5.2 years) who drove an instrumented research vehicle around a 4 km closed road circuit with three different levels of binocular spherical refractive blur (+0.50 diopter sphere [DS], +1.00 DS, +2.00 DS) compared with a baseline condition. The subjects wore optimal spherocylinder correction and the additional blur lenses were mounted in modified full-field goggles; the order of testing of the blur conditions was randomized. Driving performance was assessed in two different sessions under day and nighttime conditions and included measures of road signs recognized, hazard detection and avoidance, gap detection, lane-keeping, sign recognition distance, speed, and time to complete the course. Results Refractive blur and time of day had significant effects on driving performance (P < 0.05), where increasing blur and nighttime driving reduced performance on all driving tasks except gap judgment and lane keeping. There was also a significant interaction between blur and time of day (P < 0.05), such that the effects of blur were exacerbated under nighttime driving conditions; performance differences were evident even for +0.50 DS blur relative to baseline for some measures. Conclusions The effects of blur were greatest under nighttime conditions, even for levels of binocular refractive blur as low as +0.50 DS. These results emphasize the importance of accurate and up-to-date refractive correction of even low levels of refractive error when driving at night.

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There have been different approaches to studying penalty-kick performance in association football. In this paper, the authors synthesize key findings within an ecological dynamics theoretical framework. According to this theoretical perspective, information is the cornerstone for understanding the dynamics of action regulation in penalty-kick performance. Research suggests that investigators need to identify the information sources that are most relevant to penalty-kick performance. An important task is to understand how constraints can channel (i.e. change, emphasize or mask) information sources used to regulate upcoming actions and how the influence of these constraints is expressed in players' behavioural dynamics. Due to the broad range of constraints influencing penalty-kick performance, it is recommended that future research adopts an interdisciplinary focus on performance assessment to overcome the current lack of representativeness in penalty-kick experimental designs. Such an approach would serve to capture the information-based control of action of both players as components of this dyadic system in competitive sport.

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Criminal profiling is one tool available to investigative agencies that may assist in narrowing suspect pools, linking crimes, providing relevant leads and new investigative strategies, and keeping the overall investigation on track (Turvey, 2008). However, like a flashlight in a darkened room, profiling may not always provide valuable assistance if it shines in the wrong direction or fails to shine at all. In a perfect world, profiles are intended to provide investigators with a set of refined characteristics of the offender for a crime or a crime series that will assist their efforts. In contrast, it could be argued that profiles are not intended to provide information that may be irrelevant, unclear, confusing, or distracting to these efforts. Any information provided within the profile that does not assist in narrowing suspect pools or providing new avenues of inquiry is left open to misinterpretation and is therefore potentially damaging (Turvey, 2008). The degree to which information provided in a profile can actually be utilized by investigators to meet their goals is known as investigative relevance...

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Background Physical conditions through gait and other functional task are parameters to consider for frailty detection. The aim of the present study is to measure and describe the variability of acceleration, angular velocity and trunk displacement in the ten meter Extended Timed Get-Up-and-Go test in two groups of frail and non-frail elderly people through instrumentation with the iPhone4® smartphone. Secondly, to analyze the differences and performance of the variance between the study groups (frail and non-frail). This is a cross-sectional study of 30 subjects aged over 65 years, 14 frail subjects and 16 non-frail subjects. Results The highest difference between groups in the Sit-to-Stand and Stand-to-Sit subphases was in the y axis (vertical vector). The minimum acceleration in the Stand-to-Sit phase was -2.69 (-4.17 / -0.96) m/s2 frail elderly versus -8.49 (-12.1 / -5.23) m/s2 non-frail elderly, p < 0.001. In the Gait Go and Gait Come subphases the biggest differences found between the groups were in the vertical axis: -2.45 (-2.77 /-1.89) m/s2 frail elderly versus -5.93 (-6.87 / -4.51) m/s2 non-frail elderly, p < 0.001. Finally, with regards to the turning subphase, the statistically significant differences found between the groups were greater in the data obtained from the gyroscope than from the accelerometer (the gyroscope data for the mean maximum peak value for Yaw movement angular velocity in the frail elderly was specifically 25.60°/s, compared to 112.8°/s for the non-frail elderly, p < 0.05). Conclusions The inertial sensor fitted in the iPhone4® is capable of studying and analyzing the kinematics of the different subphases of the Extended Timed Up and Go test in frail and non-frail elderly people. For the Extended Timed Up and Go test, this device allows more sensitive differentiation between population groups than the traditionally used variable, namely time.

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A 74 year old patient, EW, with dorsolateral frontal cortical compression due to hyperostosis frontalis interna, in the absence of the Morgagni or Stewart-Morel syndromes, is described. In addition to conventional neuropsychological measures EW was administered one nonspatial and two spatial self ordered working memory tasks, as well as a standard measure of fluid intelligence or g. She showed impaired performance on all three self ordered working memory tasks compared with a normal control group of 10 subjects matched for age, education, sex, and IQ. By contrast, her performance on the fluid intelligence test was comparable with that of the controls. It is concluded that the compression of dorsolateral frontal cortex accompanying hyperostosis frontalis interna may produce selective cognitive impairment.

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This research deals with the development of a Solar-Powered UAV designed for remote sensing, in particular to the development of the autopilot sub-system and path planning. The design of the Solar-Powered UAS followed a systems engineering methodology, by first defining system architecture, and selecting each subsystem. Validation tests and integration of autopilot is performed, in order to evaluate the performances of each subsystem and to obtain a global operational system for data collection missions. The flight tests planning and simulation results are also explored in order to verify the mission capabilities using an autopilot on a UAS. The important aspect of this research is to develop a Solar-Powered UAS for the purpose of data collection and video monitoring, especially data and images from the ground; transmit to the GS (Ground Station), segment the collected data, and afterwards analyze it with a Matlab code.