983 resultados para Multiple vehicle accidents.
Resumo:
OBJECTIVE: To study the effect of myopia and spectacle wear on bicycle-related injuries in rural Chinese students. Myopia is common among Chinese students but few studies have examined its effect on daily activities. METHODS: Data on visual acuity, refractive error, current spectacle wear, and history of bicycle use and accidents during the past 3 years were sought from 1891 students undergoing eye examinations in rural Guangdong province. RESULTS: Refractive and accident data were available for 1539 participants (81.3%), among whom the mean age was 14.6 years, 52.5% were girls, 26.8% wore glasses, and 12.9% had myopia of less than -4 diopters in both eyes. More than 90% relied on bicycles to get to school daily. A total of 2931 accidents were reported by 423 participants, with 68 requiring medical attention. Male sex (odds ratio, 1.55; P < .001) and spectacle wear (odds ratio, 1.38; P = .04) were associated with a higher risk of accident, but habitual visual acuity and myopia were unassociated with the crash risk, after adjusting for age, sex, time spent riding, and risky riding behaviors. CONCLUSION: These results may be consistent with data on motor vehicle accidents implicating peripheral vision (potentially compromised by spectacle wear) more strongly than central visual acuity in mediating crash risk.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
Lesões fatais em crianças causadas por acidentes de trânsito representam um problema em muitos países. Este estudo analisou a taxa de mortalidade em crianças passageiras de automóveis menores de 10 anos de idade no Brasil, entre 1997 e 2005. Para isso, o número de mortes foi obtido diretamente no banco de dados do Sistema de Informação sobre Mortalidade (SIM) e os dados da população são projeções intercensitárias a partir censo demográfico do Instituto Brasileiro de Geografia e Estatística (IBGE) disponíveis pelo site do DATASUS. Foram calculadas, para os triênios compreendidos no período em estudo, as taxas de mortalidade por acidente de trânsito entre crianças passageiras de automóveis segundo faixa etária (menor que 1 ano, 1 a 4 e 5 a 9) e região geográfica. Os resultados mostraram taxas de mortalidade de 5,68, 7,32 e 6,78 (por 1.000.000), respectivamente, para os períodos 1997-1999, 2000-2002 e 2003-2005 para todo o Brasil. Crianças menores de 1 ano de idade apresentam taxa de mortalidade de 10,18 (por 1,000,000), maior que as observadas para as outras faixas etárias. Para o período 1997-2005, as maiores taxas foram observadas nas regiões Centro-Oeste e Sul, representando, respectivamente, 13,88 e 11,47 (por 1.000.000). Tais resultados mostram a situação de risco da criança em relação a acidentes de trânsito como passageiras de automóveis e contribuem para a elaboração de campanhas educativas de prevenção de lesões.
Resumo:
The aim of this retrospective study was to clarify the occurrence and types of dental injuries in 389 patients who had been diagnosed with facial fractures, and to analyze whether the occurrence of dental injury correlates to gender, age, trauma mechanism and type of facial fracture. Dental injuries were observed in 62 patients (16%). The most common type of injury was a crown fracture (48%). Dental injuries were multiple in most patients (63%). Almost half (48%) of all injured teeth were severely injured. Most injured teeth (61%) were in the maxilla. The incisor region was the most prevalent site in both the mandible (45%) and the maxilla (56%). The occurrence of dental injury correlated significantly with trauma mechanism and fracture type: motor vehicle accidents and mandibular fracture were significant predictors for dental trauma. The notable rate of dental injury observed in the present study emphasizes the importance of a thorough examination of the oral cavity in all patients who have sustained facial fracture. Referral to a dental practice for further treatment and follow up as soon as possible after discharge from hospital is fundamental.
Resumo:
En esta tesis se aborda la detección y el seguimiento automático de vehículos mediante técnicas de visión artificial con una cámara monocular embarcada. Este problema ha suscitado un gran interés por parte de la industria automovilística y de la comunidad científica ya que supone el primer paso en aras de la ayuda a la conducción, la prevención de accidentes y, en última instancia, la conducción automática. A pesar de que se le ha dedicado mucho esfuerzo en los últimos años, de momento no se ha encontrado ninguna solución completamente satisfactoria y por lo tanto continúa siendo un tema de investigación abierto. Los principales problemas que plantean la detección y seguimiento mediante visión artificial son la gran variabilidad entre vehículos, un fondo que cambia dinámicamente debido al movimiento de la cámara, y la necesidad de operar en tiempo real. En este contexto, esta tesis propone un marco unificado para la detección y seguimiento de vehículos que afronta los problemas descritos mediante un enfoque estadístico. El marco se compone de tres grandes bloques, i.e., generación de hipótesis, verificación de hipótesis, y seguimiento de vehículos, que se llevan a cabo de manera secuencial. No obstante, se potencia el intercambio de información entre los diferentes bloques con objeto de obtener el máximo grado posible de adaptación a cambios en el entorno y de reducir el coste computacional. Para abordar la primera tarea de generación de hipótesis, se proponen dos métodos complementarios basados respectivamente en el análisis de la apariencia y la geometría de la escena. Para ello resulta especialmente interesante el uso de un dominio transformado en el que se elimina la perspectiva de la imagen original, puesto que este dominio permite una búsqueda rápida dentro de la imagen y por tanto una generación eficiente de hipótesis de localización de los vehículos. Los candidatos finales se obtienen por medio de un marco colaborativo entre el dominio original y el dominio transformado. Para la verificación de hipótesis se adopta un método de aprendizaje supervisado. Así, se evalúan algunos de los métodos de extracción de características más populares y se proponen nuevos descriptores con arreglo al conocimiento de la apariencia de los vehículos. Para evaluar la efectividad en la tarea de clasificación de estos descriptores, y dado que no existen bases de datos públicas que se adapten al problema descrito, se ha generado una nueva base de datos sobre la que se han realizado pruebas masivas. Finalmente, se presenta una metodología para la fusión de los diferentes clasificadores y se plantea una discusión sobre las combinaciones que ofrecen los mejores resultados. El núcleo del marco propuesto está constituido por un método Bayesiano de seguimiento basado en filtros de partículas. Se plantean contribuciones en los tres elementos fundamentales de estos filtros: el algoritmo de inferencia, el modelo dinámico y el modelo de observación. En concreto, se propone el uso de un método de muestreo basado en MCMC que evita el elevado coste computacional de los filtros de partículas tradicionales y por consiguiente permite que el modelado conjunto de múltiples vehículos sea computacionalmente viable. Por otra parte, el dominio transformado mencionado anteriormente permite la definición de un modelo dinámico de velocidad constante ya que se preserva el movimiento suave de los vehículos en autopistas. Por último, se propone un modelo de observación que integra diferentes características. En particular, además de la apariencia de los vehículos, el modelo tiene en cuenta también toda la información recibida de los bloques de procesamiento previos. El método propuesto se ejecuta en tiempo real en un ordenador de propósito general y da unos resultados sobresalientes en comparación con los métodos tradicionales. ABSTRACT This thesis addresses on-road vehicle detection and tracking with a monocular vision system. This problem has attracted the attention of the automotive industry and the research community as it is the first step for driver assistance and collision avoidance systems and for eventual autonomous driving. Although many effort has been devoted to address it in recent years, no satisfactory solution has yet been devised and thus it is an active research issue. The main challenges for vision-based vehicle detection and tracking are the high variability among vehicles, the dynamically changing background due to camera motion and the real-time processing requirement. In this thesis, a unified approach using statistical methods is presented for vehicle detection and tracking that tackles these issues. The approach is divided into three primary tasks, i.e., vehicle hypothesis generation, hypothesis verification, and vehicle tracking, which are performed sequentially. Nevertheless, the exchange of information between processing blocks is fostered so that the maximum degree of adaptation to changes in the environment can be achieved and the computational cost is alleviated. Two complementary strategies are proposed to address the first task, i.e., hypothesis generation, based respectively on appearance and geometry analysis. To this end, the use of a rectified domain in which the perspective is removed from the original image is especially interesting, as it allows for fast image scanning and coarse hypothesis generation. The final vehicle candidates are produced using a collaborative framework between the original and the rectified domains. A supervised classification strategy is adopted for the verification of the hypothesized vehicle locations. In particular, state-of-the-art methods for feature extraction are evaluated and new descriptors are proposed by exploiting the knowledge on vehicle appearance. Due to the lack of appropriate public databases, a new database is generated and the classification performance of the descriptors is extensively tested on it. Finally, a methodology for the fusion of the different classifiers is presented and the best combinations are discussed. The core of the proposed approach is a Bayesian tracking framework using particle filters. Contributions are made on its three key elements: the inference algorithm, the dynamic model and the observation model. In particular, the use of a Markov chain Monte Carlo method is proposed for sampling, which circumvents the exponential complexity increase of traditional particle filters thus making joint multiple vehicle tracking affordable. On the other hand, the aforementioned rectified domain allows for the definition of a constant-velocity dynamic model since it preserves the smooth motion of vehicles in highways. Finally, a multiple-cue observation model is proposed that not only accounts for vehicle appearance but also integrates the available information from the analysis in the previous blocks. The proposed approach is proven to run near real-time in a general purpose PC and to deliver outstanding results compared to traditional methods.
Resumo:
National Highway Traffic Safety Administration, Washington, D.C.
Resumo:
National Highway Traffic Safety Administration, Washington, D.C.
Resumo:
National Highway Traffic Safety Administration, Washington, D.C.
Resumo:
Mode of access: Internet.
Resumo:
National Highway Safety Bureau, Washington, D.C.
Resumo:
National Highway Traffic Safety Administration, Washington, D.C.
Acceptance of relapse fears in breast cancer patients: effects of an act-based abridged intervention
Resumo:
Objective: Relapse fear is a common psychological scar in cancer survivors. The aim of this study is to assess the effects of an abridged version of Acceptance and Commitment Therapy (ACT) in breast cancer patients.Method: An open trial was developed with 12 non-metastatic breast cancer patients assigned to 2 conditions, ACT and waiting list. Interventions were applied in just one session and focused on the acceptance of relapse fears through a ‘defusion’ exercise. Interference and intensity of fear measured through subjective scales were collected after each intervention and again 3 months later. Distress, hypochondria and ‘anxious preocupation’ were also evaluated through standardized questionnaires.Results: The analysis revealed that ‘defusion’ contributed to decrease the interference of the fear of recurrence, and these changes were maintained three months after intervention in most subjects. 87% of participants showed clinically significant decreases in interference at follow-up sessions whereas no patient in the waiting list showed such changes. Statistical analysis revealed that the changes in interference were significant when comparing pre, post and follow-up treatment, and also when comparing ACT and waiting list groups. Changes in intensity of fear, distress, anxious preoccupation and hypochondria were also observed.Conclusions: Exposure through ‘defusion’ techniques might be considered a useful option for treatment of persistent fears in cancer patients. This study provides evidence for therapies focusing on psychological acceptance in cancer patients through short, simple and feasible therapeutic methods.
Resumo:
The Inflatable Rescue Boat (IRB) is arguably the most effective rescue tool used by the Australian surf lifesavers. The exceptional features of high mobility and rapid response have enabled it to become an icon on Australia's popular beaches. However, the IRB's extensive use within an environment that is as rugged as it is spectacular, has led it to become a danger to those who risk their lives to save others. Epidemiological research revealed lower limb injuries to be predominant, particularly the right leg. The common types of injuries were fractures and dislocations, as well as muscle or ligament strains and tears. The concern expressed by Surf Life Saving Queensland (SLSQ) and Surf Life Saving Australia (SLSA) led to a biomechanical investigation into this unique and relatively unresearched field. The aim of the research was to identify the causes of injury and propose processes that may reduce the instances and severity of injury to surf lifesavers during IRB operation. Following a review of related research, a design analysis of the craft was undertaken as an introduction to the craft, its design and uses. The mechanical characteristics of the vessel were then evaluated and the accelerations applied to the crew in the IRB were established through field tests. The data were then combined and modelled in the 3-D mathematical modelling and simulation package, MADYMO. A tool was created to compare various scenarios of boat design and methods of operation to determine possible mechanisms to reduce injuries. The results of this study showed that under simulated wave loading the boats flex around a pivot point determined by the position of the hinge in the floorboard. It was also found that the accelerations experienced by the crew exhibited similar characteristics to road vehicle accidents. Staged simulations indicated the attributes of an optimum foam in terms of thickness and density. Likewise, modelling of the boat and crew produced simulations that predicted realistic crew response to tested variables. Unfortunately, the observed lack of adherence to the SLSA footstrap Standard has impeded successful epidemiological and modelling outcomes. If uniformity of boat setup can be assured then epidemiological studies will be able to highlight the influence of implementing changes to the boat design. In conclusion, the research provided a tool to successfully link the epidemiology and injury diagnosis to the mechanical engineering design through the use of biomechanics. This was a novel application of the mathematical modelling software MADYMO. Other craft can also be investigated in this manner to provide solutions to the problem identified and therefore reduce risk of injury for the operators.
Resumo:
Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes. Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.