Purpose: The aim of this study was to determine the incidence and pattern of injuries resulting from auto-tricycle crashes among patients in a tertiary referral centre in Ghana. Methods: Data were retrospectively extr...Purpose: The aim of this study was to determine the incidence and pattern of injuries resulting from auto-tricycle crashes among patients in a tertiary referral centre in Ghana. Methods: Data were retrospectively extracted from hospital records of patients who got involved in auto-tricycle crashes and presented to the Accident and Emergency Centre of the Komfo Anokye Teaching Hospital (KATH), over a one-year period using a structured questionnaire. The gathered data were then entered into an electronic database and then analysed with SPSS version 20.0. Results: The incidence of injury following auto-tricycle crashes over the one-year period was 5.9% (95% CI: 4.9% - 7.0%) with a case fatality rate (FR) of 3.8% (95% CI: 1.3% - 8.7%). All the mortalities resulted from head and neck injuries and none of the patients involved wore a crash helmet. Only 5% of those studied wore crash helmets and were all drivers. Closed fractures accounted for 58% of the injuries, followed by open fractures, 28%. The most commonly fractured bones were the tibia/fibula, followed by the femur and then radius/ulna. The most common mechanism of injury was auto-tricycle toppling over (29%). Passengers were the most injured (48%), followed by drivers (37%) and pedestrians (15%). Most (72%) injuries among participants involved a single body part. On the injury severity scale, most (61%) of patients had minor trauma and 38% had major trauma. Conclusion: Auto-tricycle crashes account for 5.9% of injuries at the study site with a case fatality rate of 3.8%. Passengers had a higher injury rate (48%) than drivers (37%). Fractures of the tibia/fibula were most commonly associated with auto-tricycle crashes. Injuries to the head and neck were responsible for the deaths in the study participants and non-use of a crash helmet was associated with mortalities.展开更多
This paper examines the relationship between fatal road traffic accidents and potential predictors using multilayer perceptron artificial neural network (MLANN) models. The initial analysis employed twelve potential p...This paper examines the relationship between fatal road traffic accidents and potential predictors using multilayer perceptron artificial neural network (MLANN) models. The initial analysis employed twelve potential predictors, including traffic volume, prevailing weather conditions, roadway characteristics and features, drivers’ age and gender, and number of lanes. Based on the output of the model and the variables’ importance factors, seven significant variables are identified and used for further analysis to improve the performance of models. The model is optimized by systematically changing the parameters, including the number of hidden layers and the activation function of both the hidden and output layers. The performances of the MLANN models are evaluated using the percentage of the achieved accuracy, R-squared, and Sum of Square Error (SSE) functions.展开更多
Although there has been a slight decrease in road traffic crashes, fatalities, and injuries in recent years, HCMC (Ho Chi Minh City) will continue to encounter challenges in mitigating and preventing road crashes. Thi...Although there has been a slight decrease in road traffic crashes, fatalities, and injuries in recent years, HCMC (Ho Chi Minh City) will continue to encounter challenges in mitigating and preventing road crashes. This study analyzes road crash data from the past five years, obtained from the Road-Railway Police Bureau (PC08) and TSB (Traffic Safety Board) in HCMC. This analysis gives us valuable insights into road crash patterns, characteristics, and underlying causes. This comprehensive understanding serves as a scientific foundation for developing cohesive strategies and implementing targeted solutions to address road traffic safety issues more effectively in the future.展开更多
In order to improve crash occurrence models to account for the influence of various contributing factors, a conditional autoregressive negative binomial （CAR-NB） model is employed to allow for overdispersion （tackl...In order to improve crash occurrence models to account for the influence of various contributing factors, a conditional autoregressive negative binomial （CAR-NB） model is employed to allow for overdispersion （tackled by the NB component）, unobserved heterogeneity and spatial autocorrelation （captured by the CAR process）, using Markov chain Monte Carlo methods and the Gibbs sampler. Statistical tests suggest that the CAR-NB model is preferred over the CAR-Poisson, NB, zero-inflated Poisson, zero-inflated NB models, due to its lower prediction errors and more robust parameter inference. The study results show that crash frequency and fatalities are positively associated with the number of lanes, curve length, annual average daily traffic （AADT） per lane, as well as rainfall. Speed limit and the distances to the nearest hospitals have negative associations with segment-based crash counts but positive associations with fatality counts, presumably as a result of worsened collision impacts at higher speed and time loss during transporting crash victims.展开更多
In order to improve the prediction precision of the safety performance function （SPF） of freeway basic segments, design and crash data of 640 segments are collected from different institutions. Three negative binomi...In order to improve the prediction precision of the safety performance function （SPF） of freeway basic segments, design and crash data of 640 segments are collected from different institutions. Three negative binomial （NB） regression models and three generalized negative binomial （GNB） regression models are built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The effective use of the GNB model in analyzing the interactive influence of explanatory variables and predicting freeway basic segments is demonstrated. Among six models, the two models （one is the NB model and the other is the GNB model. ） which consider the interactive influence of the annual average daily traffic （AADT） and length are more reasonable for predicting results. Furthermore, a comprehensive study is carried out to prove that when considering the interactive influence, the NB and GNB models have almost the same fitting performance in estimating the crashes, among which the GNB model is slightly better for prediction performance.展开更多
A hybrid conceptual design approach was introduced in this study to develop a conceptual design of oil palm polymer composite automotive crash box(ACB). A combination of theory of inventive problem solving(TRIZ), morp...A hybrid conceptual design approach was introduced in this study to develop a conceptual design of oil palm polymer composite automotive crash box(ACB). A combination of theory of inventive problem solving(TRIZ), morphological charts and biomimetics was applied where the foremost requirements in terms of the material characteristics, function specifications, force identification, root cause analysis, geometry profile and design selection criteria were considered. The strategy was to use creations of nature to inspire five innovative conceptual designs of the ACB structure and the AHP method was applied to perform the pairwise analysis of selecting the best ACB conceptual design. A new conceptual design for a composite ACB was conceived bearing in mind the properties of natural fibre, unlike those of conventional materials such as steel alloys and aluminium alloys. The design with the highest ranking(26.6 %) was chosen as the final conceptual design, which was the one with a honeycomb structure for the outermost profile, reinforced with a spider web structure inside the part, supported by fibre foam structure extracted from the woodpecker sponge tissue at the centre to maximize the energy absorption capability. The new design could solve the problem of bending collapse which is a major cause of failure to absorb maximum impact energy for ACB during collision. However, the final conceptual design will still need several modifications for production and assembly purposes, which will be completed in a further study.展开更多
This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using...This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using historical loop detector data from Interstate-894 in Milwaukee, Wisconsin, USA. The extracted loop detection data were aggregated over different stations and time intervals to produce explanatory features. A feature selection process, which addresses the interaction between SVM classifiers and explanatory features, was adopted to identify the features that significantly influence rear-end crashes. Afterwards, the identified significant explanatory features over three separate time levels were used to train three SVM models. In the end, the multi-layer perceptron(MLP) artificial neural network models were used as benchmarks to evaluate the performance of SVM models. The results show that the proposed feature selection procedure greatly enhances the accuracy and generalization capability of SVM models. Moreover, the optimal SVM classifier achieves 81.1% overall prediction precision rate. In comparison with MLP artificial neural networks, SVM models provide better results in terms of crash prediction accuracy and false positive rate, which confirms the superior performance of SVM technique in rear-end crash potential prediction analysis.展开更多
BACKGROUND: As the field of Emergency Medicine grows worldwide, the importance of an Emergency Department Crash Cart(EDCC) has long been recognized. Yet, there is paucity of relevant peer-reviewed literature specifica...BACKGROUND: As the field of Emergency Medicine grows worldwide, the importance of an Emergency Department Crash Cart(EDCC) has long been recognized. Yet, there is paucity of relevant peer-reviewed literature specifically discussing EDCCs or proposing detailed features for an EDCC suitable for both adult and pediatric patients. METHODS: The authors performed a systematic review of EDCC-specific literature indexed in Pubmed and Embase on December 20, 2016. In addition, the authors reviewed the 2015 American Heart Association(AHA) guidelines for cardiopulmonary resuscitation and emergency cardiovascular care, the 2015 European Resuscitation Council(ERC) guidelines for resuscitation, and the 2013 American College of Surgeons(ACS) Advanced Trauma Life Support(ATLS) 9 th edition.RESULTS: There were a total of 277 results, with 192 unique results and 85 duplicates. After careful review by two independent reviewers, all but four references were excluded. None of the four included articles described comprehensive contents of equipment and medications for both the adult and pediatric populations. This article describes in detail the final four articles specific to EDCC, and proposes a set of suggested contents for the EDCC. CONCLUSION: Our systematic review shows the striking paucity of such a high impact indispensable item in the ED. We hope that our EDCC content suggestions help enhance the level of response of EDs in the resuscitation of adult and pediatric populations, and encourage the implementation of and adherence to the latest evidence-based resuscitation guidelines.展开更多
文摘Purpose: The aim of this study was to determine the incidence and pattern of injuries resulting from auto-tricycle crashes among patients in a tertiary referral centre in Ghana. Methods: Data were retrospectively extracted from hospital records of patients who got involved in auto-tricycle crashes and presented to the Accident and Emergency Centre of the Komfo Anokye Teaching Hospital (KATH), over a one-year period using a structured questionnaire. The gathered data were then entered into an electronic database and then analysed with SPSS version 20.0. Results: The incidence of injury following auto-tricycle crashes over the one-year period was 5.9% (95% CI: 4.9% - 7.0%) with a case fatality rate (FR) of 3.8% (95% CI: 1.3% - 8.7%). All the mortalities resulted from head and neck injuries and none of the patients involved wore a crash helmet. Only 5% of those studied wore crash helmets and were all drivers. Closed fractures accounted for 58% of the injuries, followed by open fractures, 28%. The most commonly fractured bones were the tibia/fibula, followed by the femur and then radius/ulna. The most common mechanism of injury was auto-tricycle toppling over (29%). Passengers were the most injured (48%), followed by drivers (37%) and pedestrians (15%). Most (72%) injuries among participants involved a single body part. On the injury severity scale, most (61%) of patients had minor trauma and 38% had major trauma. Conclusion: Auto-tricycle crashes account for 5.9% of injuries at the study site with a case fatality rate of 3.8%. Passengers had a higher injury rate (48%) than drivers (37%). Fractures of the tibia/fibula were most commonly associated with auto-tricycle crashes. Injuries to the head and neck were responsible for the deaths in the study participants and non-use of a crash helmet was associated with mortalities.
文摘This paper examines the relationship between fatal road traffic accidents and potential predictors using multilayer perceptron artificial neural network (MLANN) models. The initial analysis employed twelve potential predictors, including traffic volume, prevailing weather conditions, roadway characteristics and features, drivers’ age and gender, and number of lanes. Based on the output of the model and the variables’ importance factors, seven significant variables are identified and used for further analysis to improve the performance of models. The model is optimized by systematically changing the parameters, including the number of hidden layers and the activation function of both the hidden and output layers. The performances of the MLANN models are evaluated using the percentage of the achieved accuracy, R-squared, and Sum of Square Error (SSE) functions.
文摘Although there has been a slight decrease in road traffic crashes, fatalities, and injuries in recent years, HCMC (Ho Chi Minh City) will continue to encounter challenges in mitigating and preventing road crashes. This study analyzes road crash data from the past five years, obtained from the Road-Railway Police Bureau (PC08) and TSB (Traffic Safety Board) in HCMC. This analysis gives us valuable insights into road crash patterns, characteristics, and underlying causes. This comprehensive understanding serves as a scientific foundation for developing cohesive strategies and implementing targeted solutions to address road traffic safety issues more effectively in the future.
基金The National Science Foundation by Changjiang Scholarship of Ministry of Education of China(No.BCS-0527508)the Joint Research Fund for Overseas Natural Science of China(No.51250110075)+1 种基金the Natural Science Foundation of Jiangsu Province(No.SBK200910046)the Postdoctoral Science Foundation of Jiangsu Province(No.0901005C)
文摘In order to improve crash occurrence models to account for the influence of various contributing factors, a conditional autoregressive negative binomial （CAR-NB） model is employed to allow for overdispersion （tackled by the NB component）, unobserved heterogeneity and spatial autocorrelation （captured by the CAR process）, using Markov chain Monte Carlo methods and the Gibbs sampler. Statistical tests suggest that the CAR-NB model is preferred over the CAR-Poisson, NB, zero-inflated Poisson, zero-inflated NB models, due to its lower prediction errors and more robust parameter inference. The study results show that crash frequency and fatalities are positively associated with the number of lanes, curve length, annual average daily traffic （AADT） per lane, as well as rainfall. Speed limit and the distances to the nearest hospitals have negative associations with segment-based crash counts but positive associations with fatality counts, presumably as a result of worsened collision impacts at higher speed and time loss during transporting crash victims.
基金The National Natural Science Foundation of China(No.51408229,51278202)the Program of the Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University(No.K201204)the Science and Technology Program of Guangdong Communication Department(No.2013-02-068)
文摘In order to improve the prediction precision of the safety performance function （SPF） of freeway basic segments, design and crash data of 640 segments are collected from different institutions. Three negative binomial （NB） regression models and three generalized negative binomial （GNB） regression models are built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The effective use of the GNB model in analyzing the interactive influence of explanatory variables and predicting freeway basic segments is demonstrated. Among six models, the two models （one is the NB model and the other is the GNB model. ） which consider the interactive influence of the annual average daily traffic （AADT） and length are more reasonable for predicting results. Furthermore, a comprehensive study is carried out to prove that when considering the interactive influence, the NB and GNB models have almost the same fitting performance in estimating the crashes, among which the GNB model is slightly better for prediction performance.
基金Project(6369107)supported by the Ministry of Higher Education,Malaysia
文摘A hybrid conceptual design approach was introduced in this study to develop a conceptual design of oil palm polymer composite automotive crash box(ACB). A combination of theory of inventive problem solving(TRIZ), morphological charts and biomimetics was applied where the foremost requirements in terms of the material characteristics, function specifications, force identification, root cause analysis, geometry profile and design selection criteria were considered. The strategy was to use creations of nature to inspire five innovative conceptual designs of the ACB structure and the AHP method was applied to perform the pairwise analysis of selecting the best ACB conceptual design. A new conceptual design for a composite ACB was conceived bearing in mind the properties of natural fibre, unlike those of conventional materials such as steel alloys and aluminium alloys. The design with the highest ranking(26.6 %) was chosen as the final conceptual design, which was the one with a honeycomb structure for the outermost profile, reinforced with a spider web structure inside the part, supported by fibre foam structure extracted from the woodpecker sponge tissue at the centre to maximize the energy absorption capability. The new design could solve the problem of bending collapse which is a major cause of failure to absorb maximum impact energy for ACB during collision. However, the final conceptual design will still need several modifications for production and assembly purposes, which will be completed in a further study.
基金Project(BK20160685)supported by the Science Foundation of Jiangsu Province,ChinaProject(61620106002)supported by the National Natural Science Foundation of China
文摘This study develops new real-time freeway rear-end crash potential predictors using support vector machine(SVM) technique. The relationship between rear-end crash occurrences and traffic conditions were explored using historical loop detector data from Interstate-894 in Milwaukee, Wisconsin, USA. The extracted loop detection data were aggregated over different stations and time intervals to produce explanatory features. A feature selection process, which addresses the interaction between SVM classifiers and explanatory features, was adopted to identify the features that significantly influence rear-end crashes. Afterwards, the identified significant explanatory features over three separate time levels were used to train three SVM models. In the end, the multi-layer perceptron(MLP) artificial neural network models were used as benchmarks to evaluate the performance of SVM models. The results show that the proposed feature selection procedure greatly enhances the accuracy and generalization capability of SVM models. Moreover, the optimal SVM classifier achieves 81.1% overall prediction precision rate. In comparison with MLP artificial neural networks, SVM models provide better results in terms of crash prediction accuracy and false positive rate, which confirms the superior performance of SVM technique in rear-end crash potential prediction analysis.
文摘BACKGROUND: As the field of Emergency Medicine grows worldwide, the importance of an Emergency Department Crash Cart(EDCC) has long been recognized. Yet, there is paucity of relevant peer-reviewed literature specifically discussing EDCCs or proposing detailed features for an EDCC suitable for both adult and pediatric patients. METHODS: The authors performed a systematic review of EDCC-specific literature indexed in Pubmed and Embase on December 20, 2016. In addition, the authors reviewed the 2015 American Heart Association(AHA) guidelines for cardiopulmonary resuscitation and emergency cardiovascular care, the 2015 European Resuscitation Council(ERC) guidelines for resuscitation, and the 2013 American College of Surgeons(ACS) Advanced Trauma Life Support(ATLS) 9 th edition.RESULTS: There were a total of 277 results, with 192 unique results and 85 duplicates. After careful review by two independent reviewers, all but four references were excluded. None of the four included articles described comprehensive contents of equipment and medications for both the adult and pediatric populations. This article describes in detail the final four articles specific to EDCC, and proposes a set of suggested contents for the EDCC. CONCLUSION: Our systematic review shows the striking paucity of such a high impact indispensable item in the ED. We hope that our EDCC content suggestions help enhance the level of response of EDs in the resuscitation of adult and pediatric populations, and encourage the implementation of and adherence to the latest evidence-based resuscitation guidelines.
