Visual assessment of pedestrian crashes

Of the numerous factors that play a role in fatal pedestrian collisions, the time of day, day of the week, and time of year can be significant determinants. More than 60% of all pedestrian collisions in 2007 occurred at night, despite the presumed decrease in both pedestrian and automobile exposure during the night. Although this trend is partially explained by factors such as fatigue and alcohol consumption, prior analysis of the Fatality Analysis Reporting System database suggests that pedestrian fatalities increase as light decreases after controlling for other factors. This study applies graphical cross-tabulation, a novel visual assessment approach, to explore the relationships among collision variables. The results reveal that twilight and the first hour of darkness typically observe the greatest frequency of pedestrian fatal collisions. These hours are not necessarily the most risky on a per mile travelled basis, however, because pedestrian volumes are often still high. Additional analysis is needed to quantify the extent to which pedestrian exposure (walking/crossing activity) in these time periods plays a role in pedestrian crash involvement. Weekly patterns of pedestrian fatal collisions vary by time of year due to the seasonal changes in sunset time. In December, collisions are concentrated around twilight and the first hour of darkness throughout the week while, in June, collisions are most heavily concentrated around twilight and the first hours of darkness on Friday and Saturday. Friday and Saturday nights in June may be the most dangerous times for pedestrians. Knowing when pedestrian risk is highest is critically important for formulating effective mitigation strategies and for efficiently investing safety funds. This applied visual approach is a helpful tool for researchers intending to communicate with policy-makers and to identify relationships that can then be tested with more sophisticated statistical tools.

Real Time Concrete Damage Visual Assessment for First Responders

First responders are in danger when they perform tasks in damaged buildings after earthquakes. Structural collapse due to the failure of critical load bearing structural members (e.g. columns) during a post-earthquake event such as an aftershock can make first responders victims, considering they are unable to assess the impact of the damage inflicted in load bearing members. The writers here propose a method that can provide first responders with a crude but quick estimate of the damage inflicted in load bearing members. Under the proposed method, critical structural members (reinforced concrete columns in this study) are identified from digital visual data and the damage superimposed on these structural members is detected with the help of Visual Pattern Recognition techniques. The correlation of the two (e.g. the position, orientation and size of a crack on the surface of a column) is used to query a case-based reasoning knowledge base, which contains apriori classified states of columns according to the damage inflicted on them. When query results indicate the column's damage state is severe, the method assumes that a structural collapse is likely and first responders are warned to evacuate.

Supporting visual assessment of food and nutrient intake in a clinical care setting

Monitoring nutritional intake is an important aspect of the care of older people, particularly for those at risk of malnutrition. Current practice for monitoring food intake relies on hand written food charts that have several inadequacies. We describe the design and validation of a tool for computer-assisted visual assessment of patient food and nutrient intake. To estimate food consumption, the application compares the pixels the user rubbed out against predefined graphical masks. Weight of food consumed is calculated as a percentage of pixels rubbed out against pixels in the mask. Results suggest that the application may be a useful tool for the conservative assessment of nutritional intake in hospitals.

Determinants of visual 2-D echo assessment of left ventricular wall motion: Comparison with myocardial thickening on cardiac magnetic resonance imaging

Background: left ventricular wall motion on 2d echo (2de) is usually scored visually. we sought to examine the determinants of visually assessed wall motion scoring on 2de by comparison with myocardial thickening quantified on MRI. Methods: using a 16 segment model, we studied 287 segments in 30 patients aged 61+/ -11 years (6 female), with ischaemic LV dysfunction (defined by at least 2 segments dysfunctional on 2de). 2de was performed in 5 views and wall motion scores (WMS) assigned: 1 (normal) 103 segments, 2 (hypokinetic) 93 segments, 3 (akinetic) 87 segments. MRI was used to measure end systolic wall thickness (ESWT), end diastolic wall thickness (EDWT) and percentage systolic wall thickening (SWT%) in the plane of the 2de and to assess WMS in the same planes visually. No patient had a clinical ischemic event between the tests. Results: visual assessment of wall motion by 2de and MRI showed moderate agreement (kappa = 0.425). Resting 2de wall motion correlated significantly (p

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

Generation and assessment of accuracy of Digital Elevation Model by using Pcigeomatica (10.3)

This study aims to assess the accuracy of Digital Elevation Model (DEM) which is generated by using Toutin’s model. Thus, Toutin’s model was run by using OrthoEngineSE of PCI Geomatics 10.3.Thealong-track stereoimages of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) sensor with 15 m resolution were used to produce DEM on an area with low and near Mean Sea Level (MSL) elevation in Johor Malaysia. Despite the satisfactory pre-processing results the visual assessment of the DEM generated from Toutin’s model showed that the DEM contained many outliers and incorrect values. The failure of Toutin’s model may mostly be due to the inaccuracy and insufficiency of ASTER ephemeris data for low terrains as well as huge water body in the stereo images.

An evaluation of genetic analyses, skull morphology and visual appearance for assessing dingo purity: implications for dingo conservation

The introgression of domestic dog genes into dingo populations threatens the genetic integrity of 'pure' dingoes. However, dingo conservation efforts are hampered by difficulties in distinguishing between dingoes and hybrids in the field. This study evaluates consistency in the status of hybridisation (i.e. dingo, hybrid or dog) assigned by genetic analyses, skull morphology and visual assessments. Of the 56 south-east Queensland animals sampled, 39 (69.6%) were assigned the same status by all three methods, 10 (17.9%) by genetic and skull methods, four (7.1%) by genetic and visual methods; and two (3.6%) by skull and visual methods. Pair-wise comparisons identified a significant relationship between genetic and skull methods, but not between either of these and visual methods. Results from surveying 13 experienced wild dog managers showed that hybrids were more easily identified by visual characters than were dingoes. A more reliable visual assessment can be developed through determining the relationship between (1) genetics and phenotype by sampling wild dog populations and (2) the expression of visual characteristics from different proportions and breeds of domestic dog genes by breeding trials. Culling obvious hybrids based on visual characteristics, such as sable and patchy coat colours, should slow the process of hybridisation.

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

Avaliação visual de sujeitos expostos de forma ocupacional a solventes orgânicos através de métodos psicofísicos

Os solventes orgânicos são substâncias neurotóxicas que podem causar efeitos danosos sobre as funções visuais. É comum a exposição ocupacional a esses tipos de substâncias, pois elas apresentam grande aplicabilidade em inúmeras atividades. Os efeitos podem ser quantificados por testes psicofísicos. Os testes mais usados nesse tipo de avaliação são de ordenamento de matizes, como o Teste D15 Dessaturado de Lanthony e o Teste dos 100 Matizes de Farnsworth-Munsell, e avaliação de sensibilidade ao contraste espacial de luminância, como MCT 8000 Vistech, VCTS 6500 Vistech e FACT 101. Em geral esses testes descrevem perda de discriminação de cores, afetando tanto o eixo azul-amarelo quanto o eixo verde-vermelho, e diminuição da sensibilidade ao contraste de luminância principalmente para as frequências espaciais mais baixas. Existe correlação positiva entre os resultados da avaliação psicofísica e vários marcadores biológicos e ambientais, mas essa correlação depende do marcador e do tipo de solvente ao qual os indivíduos são expostos. Fatores como alcoolismo crônico e tabagismo inveterado podem interferir no processo de correlacionar esses resultados.

Evaluation of perpendicular reflection intensity for assessment of caries lesion activity/inactivity

The aim of this study was to evaluate, using visual assessment, an experimental optical sensor measuring perpendicular reflection intensity (PRI) as an indicator of enamel caries lesion activity/inactivity. Forty teeth with either an active or an inactive enamel lesion were selected from a pool of extracted teeth. Each tooth was cut into halves, with a clinically sound half and a half with a non-cavitated enamel lesion. After gentle plaque removal, the teeth were kept moistened. The lesions were then photographed and a defined measuring site per lesion was chosen and indicated with an arrow on a printout. Independently, the chosen site was visually assessed for lesion activity, and its glossiness was measured with PRI assessment. Surface roughness (SR) was assessed with optical profilometry using a confocal microscope. Visual assessment and PRI were repeated after several weeks and a reliability analysis was performed. For enamel lesions visually scored as active versus inactive, significantly different values were obtained with both PRI and SR. PRI values of the clinically sound control surfaces were significantly different only from active lesions. Generally, inactive lesions had the same glossiness and the same roughness as the sound control surfaces. The reliabilities for visual assessment (? = 0.89) and for PRI (ICC = 0.86) were high. It is concluded that, within the limits of this study, PRI can be regarded as a promising tool for quantitative enamel lesion activity assessment. There is scope and potential for the PRI device to be considerably improved for in vivo use.