WorldWideScience

Sample records for crash prediction models

  1. Linear regression crash prediction models : issues and proposed solutions.

    Science.gov (United States)

    2010-05-01

    The paper develops a linear regression model approach that can be applied to : crash data to predict vehicle crashes. The proposed approach involves novice data aggregation : to satisfy linear regression assumptions; namely error structure normality ...

  2. Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models.

    Science.gov (United States)

    Cheng, Wen; Gill, Gurdiljot Singh; Sakrani, Taha; Dasu, Mohan; Zhou, Jiao

    2017-11-01

    Motorcycle crashes constitute a very high proportion of the overall motor vehicle fatalities in the United States, and many studies have examined the influential factors under various conditions. However, research on the impact of weather conditions on the motorcycle crash severity is not well documented. In this study, we examined the impact of weather conditions on motorcycle crash injuries at four different severity levels using San Francisco motorcycle crash injury data. Five models were developed using Full Bayesian formulation accounting for different correlations commonly seen in crash data and then compared for fitness and performance. Results indicate that the models with serial and severity variations of parameters had superior fit, and the capability of accurate crash prediction. The inferences from the parameter estimates from the five models were: an increase in the air temperature reduced the possibility of a fatal crash but had a reverse impact on crashes of other severity levels; humidity in air was not observed to have a predictable or strong impact on crashes; the occurrence of rainfall decreased the possibility of crashes for all severity levels. Transportation agencies might benefit from the research results to improve road safety by providing motorcyclists with information regarding the risk of certain crash severity levels for special weather conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. MOTORCYCLE CRASH PREDICTION MODEL FOR NON-SIGNALIZED INTERSECTIONS

    Directory of Open Access Journals (Sweden)

    S. HARNEN

    2003-01-01

    Full Text Available This paper attempts to develop a prediction model for motorcycle crashes at non-signalized intersections on urban roads in Malaysia. The Generalized Linear Modeling approach was used to develop the model. The final model revealed that an increase in motorcycle and non-motorcycle flows entering an intersection is associated with an increase in motorcycle crashes. Non-motorcycle flow on major road had the greatest effect on the probability of motorcycle crashes. Approach speed, lane width, number of lanes, shoulder width and land use were also found to be significant in explaining motorcycle crashes. The model should assist traffic engineers to decide the need for appropriate intersection treatment that specifically designed for non-exclusive motorcycle lane facilities.

  4. Robust human body model injury prediction in simulated side impact crashes.

    Science.gov (United States)

    Golman, Adam J; Danelson, Kerry A; Stitzel, Joel D

    2016-01-01

    This study developed a parametric methodology to robustly predict occupant injuries sustained in real-world crashes using a finite element (FE) human body model (HBM). One hundred and twenty near-side impact motor vehicle crashes were simulated over a range of parameters using a Toyota RAV4 (bullet vehicle), Ford Taurus (struck vehicle) FE models and a validated human body model (HBM) Total HUman Model for Safety (THUMS). Three bullet vehicle crash parameters (speed, location and angle) and two occupant parameters (seat position and age) were varied using a Latin hypercube design of Experiments. Four injury metrics (head injury criterion, half deflection, thoracic trauma index and pelvic force) were used to calculate injury risk. Rib fracture prediction and lung strain metrics were also analysed. As hypothesized, bullet speed had the greatest effect on each injury measure. Injury risk was reduced when bullet location was further from the B-pillar or when the bullet angle was more oblique. Age had strong correlation to rib fractures frequency and lung strain severity. The injuries from a real-world crash were predicted using two different methods by (1) subsampling the injury predictors from the 12 best crush profile matching simulations and (2) using regression models. Both injury prediction methods successfully predicted the case occupant's low risk for pelvic injury, high risk for thoracic injury, rib fractures and high lung strains with tight confidence intervals. This parametric methodology was successfully used to explore crash parameter interactions and to robustly predict real-world injuries.

  5. Predicting expressway crash frequency using a random effect negative binomial model: A case study in China.

    Science.gov (United States)

    Ma, Zhuanglin; Zhang, Honglu; Chien, Steven I-Jy; Wang, Jin; Dong, Chunjiao

    2017-01-01

    To investigate the relationship between crash frequency and potential influence factors, the accident data for events occurring on a 50km long expressway in China, including 567 crash records (2006-2008), were collected and analyzed. Both the fixed-length and the homogeneous longitudinal grade methods were applied to divide the study expressway section into segments. A negative binomial (NB) model and a random effect negative binomial (RENB) model were developed to predict crash frequency. The parameters of both models were determined using the maximum likelihood (ML) method, and the mixed stepwise procedure was applied to examine the significance of explanatory variables. Three explanatory variables, including longitudinal grade, road width, and ratio of longitudinal grade and curve radius (RGR), were found as significantly affecting crash frequency. The marginal effects of significant explanatory variables to the crash frequency were analyzed. The model performance was determined by the relative prediction error and the cumulative standardized residual. The results show that the RENB model outperforms the NB model. It was also found that the model performance with the fixed-length segment method is superior to that with the homogeneous longitudinal grade segment method. Copyright © 2016. Published by Elsevier Ltd.

  6. Crash prediction model for two-lane rural highways in the Ashanti region of Ghana

    Directory of Open Access Journals (Sweden)

    Williams Ackaah

    2011-07-01

    Full Text Available Crash Prediction Models (CPMs have been used elsewhere as a useful tool by road Engineers and Planners. There is however no study on the prediction of road traffic crashes on rural highways in Ghana. The main objective of the study was to develop a prediction model for road traffic crashes occurring on the rural sections of the highways in the Ashanti Region of Ghana. The model was developed for all injury crashes occurring on selected rural highways in the Region over the three (3 year period 2005–2007. Data was collected from 76 rural highway sections and each section varied between 0.8 km and 6.7 km. Data collected for each section comprised injury crash data, traffic flow and speed data, and roadway characteristics and road geometry data. The Generalised Linear Model (GLM with Negative Binomial (NB error structure was used to estimate the model parameters. Two types of models, the ‘core’ model which included key exposure variables only and the ‘full’ model which included a wider range of variables were developed. The results show that traffic flow, highway segment length, junction density, terrain type and presence of a village settlement within road segments were found to be statistically significant explanatory variables (p<0.05 for crash involvement. Adding one junction to a 1 km section of road segment was found to increase injury crashes by 32.0% and sections which had a village settlement within them were found to increase injury crashes by 60.3% compared with segments with no settlements. The model explained 61.2% of the systematic variation in the data. Road and Traffic Engineers and Planners can apply the crash prediction model as a tool in safety improvement works and in the design of safer roads. It is recommended that to improve safety, highways should be designed to by-pass village settlements and that the number of junctions on a highway should be limited to carefully designed ones.

  7. A real-time crash prediction model for the ramp vicinities of urban expressways

    Directory of Open Access Journals (Sweden)

    Moinul Hossain

    2013-07-01

    Full Text Available Ramp vicinities are arguably the known black-spots on urban expressways. There, while maintaining high speed, drivers need to respond to several complex events such as maneuvering, reading road signs, route planning and maintaining safe distance from other maneuvering vehicles simultaneously which demand higher level of cognitive response to ensure safety. Therefore, any additional discomfort caused by traffic dynamics may induce driving error resulting in a crash. This manuscript presents a methodology for identifying these dynamically forming hazardous traffic conditions near the ramp vicinities with high resolution real-time traffic flow data. It separates the ramp vicinities into four zones – upstream and downstream of entrance and exit ramps, and builds four separate real-time crash prediction models. Around two year (December 2007 to October 2009 crash data as well as their matching traffic sensor data from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited have been utilized for this research. Random multinomial logit, a forest of multinomial logit models, has been used to identify the most important variables. Finally, a real-time modeling method, Bayesian belief net (BBN, has been employed to build the four models using ramp flow, flow and congestion index in the upstream and flow and speed in the downstream of the ramp location as variables. The newly proposed models could predict 50%, 42%, 43% and 55% of the future crashes with around 10% false alarm for the downstream of entrance, downstream of exit, upstream of entrance and upstream of exit ramps respectively. The models can be utilized in combination with various traffic smoothing measures such as ramp metering, variable speed limit, warning messages through variable message signs, etc. to enhance safety near the ramp vicinities.

  8. Do calculated conflicts in microsimulation model predict number of crashes?

    NARCIS (Netherlands)

    Dijkstra, Atze; Marchesini, Paula; Bijleveld, Frits; Kars, Vincent; Drolenga, Hans; Maarseveen, Martin Van

    2010-01-01

    A microsimulation model and its calculations are described, and the results that are subsequently used to determine indicators for traffic safety are presented. The method demonstrates which changes occur at the level of traffic flow (number of vehicles per section of road) and at the vehicle level

  9. Predicting Free Flow Speed and Crash Risk of Bicycle Traffic Flow Using Artificial Neural Network Models

    Directory of Open Access Journals (Sweden)

    Cheng Xu

    2015-01-01

    Full Text Available Free flow speed is a fundamental measure of traffic performance and has been found to affect the severity of crash risk. However, the previous studies lack analysis and modelling of impact factors on bicycles’ free flow speed. The main focus of this study is to develop multilayer back propagation artificial neural network (BPANN models for the prediction of free flow speed and crash risk on the separated bicycle path. Four different models with considering different combinations of input variables (e.g., path width, traffic condition, bicycle type, and cyclists’ characteristics were developed. 459 field data samples were collected from eleven bicycle paths in Hangzhou, China, and 70% of total samples were used for training, 15% for validation, and 15% for testing. The results show that considering the input variables of bicycle types and characteristics of cyclists will effectively improve the accuracy of the prediction models. Meanwhile, the parameters of bicycle types have more significant effect on predicting free flow speed of bicycle compared to those of cyclists’ characteristics. The findings could contribute for evaluation, planning, and management of bicycle safety.

  10. Bayesian Poisson hierarchical models for crash data analysis: Investigating the impact of model choice on site-specific predictions.

    Science.gov (United States)

    Khazraee, S Hadi; Johnson, Valen; Lord, Dominique

    2018-08-01

    The Poisson-gamma (PG) and Poisson-lognormal (PLN) regression models are among the most popular means for motor vehicle crash data analysis. Both models belong to the Poisson-hierarchical family of models. While numerous studies have compared the overall performance of alternative Bayesian Poisson-hierarchical models, little research has addressed the impact of model choice on the expected crash frequency prediction at individual sites. This paper sought to examine whether there are any trends among candidate models predictions e.g., that an alternative model's prediction for sites with certain conditions tends to be higher (or lower) than that from another model. In addition to the PG and PLN models, this research formulated a new member of the Poisson-hierarchical family of models: the Poisson-inverse gamma (PIGam). Three field datasets (from Texas, Michigan and Indiana) covering a wide range of over-dispersion characteristics were selected for analysis. This study demonstrated that the model choice can be critical when the calibrated models are used for prediction at new sites, especially when the data are highly over-dispersed. For all three datasets, the PIGam model would predict higher expected crash frequencies than would the PLN and PG models, in order, indicating a clear link between the models predictions and the shape of their mixing distributions (i.e., gamma, lognormal, and inverse gamma, respectively). The thicker tail of the PIGam and PLN models (in order) may provide an advantage when the data are highly over-dispersed. The analysis results also illustrated a major deficiency of the Deviance Information Criterion (DIC) in comparing the goodness-of-fit of hierarchical models; models with drastically different set of coefficients (and thus predictions for new sites) may yield similar DIC values, because the DIC only accounts for the parameters in the lowest (observation) level of the hierarchy and ignores the higher levels (regression coefficients

  11. Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes.

    Science.gov (United States)

    Kononen, Douglas W; Flannagan, Carol A C; Wang, Stewart C

    2011-01-01

    A multivariate logistic regression model, based upon National Automotive Sampling System Crashworthiness Data System (NASS-CDS) data for calendar years 1999-2008, was developed to predict the probability that a crash-involved vehicle will contain one or more occupants with serious or incapacitating injuries. These vehicles were defined as containing at least one occupant coded with an Injury Severity Score (ISS) of greater than or equal to 15, in planar, non-rollover crash events involving Model Year 2000 and newer cars, light trucks, and vans. The target injury outcome measure was developed by the Centers for Disease Control and Prevention (CDC)-led National Expert Panel on Field Triage in their recent revision of the Field Triage Decision Scheme (American College of Surgeons, 2006). The parameters to be used for crash injury prediction were subsequently specified by the National Expert Panel. Model input parameters included: crash direction (front, left, right, and rear), change in velocity (delta-V), multiple vs. single impacts, belt use, presence of at least one older occupant (≥ 55 years old), presence of at least one female in the vehicle, and vehicle type (car, pickup truck, van, and sport utility). The model was developed using predictor variables that may be readily available, post-crash, from OnStar-like telematics systems. Model sensitivity and specificity were 40% and 98%, respectively, using a probability cutpoint of 0.20. The area under the receiver operator characteristic (ROC) curve for the final model was 0.84. Delta-V (mph), seat belt use and crash direction were the most important predictors of serious injury. Due to the complexity of factors associated with rollover-related injuries, a separate screening algorithm is needed to model injuries associated with this crash mode. Copyright © 2010 Elsevier Ltd. All rights reserved.

  12. Predictability and interpretability of hybrid link-level crash frequency models for urban arterials compared to cluster-based and general negative binomial regression models.

    Science.gov (United States)

    Najaf, Pooya; Duddu, Venkata R; Pulugurtha, Srinivas S

    2018-03-01

    Machine learning (ML) techniques have higher prediction accuracy compared to conventional statistical methods for crash frequency modelling. However, their black-box nature limits the interpretability. The objective of this research is to combine both ML and statistical methods to develop hybrid link-level crash frequency models with high predictability and interpretability. For this purpose, M5' model trees method (M5') is introduced and applied to classify the crash data and then calibrate a model for each homogenous class. The data for 1134 and 345 randomly selected links on urban arterials in the city of Charlotte, North Carolina was used to develop and validate models, respectively. The outputs from the hybrid approach are compared with the outputs from cluster-based negative binomial regression (NBR) and general NBR models. Findings indicate that M5' has high predictability and is very reliable to interpret the role of different attributes on crash frequency compared to other developed models.

  13. Development of a prediction model for crash occurrence by analyzing traffic crash and citation data : final report.

    Science.gov (United States)

    2017-04-30

    It is commonly acknowledged that factors such as human factors, vehicle characteristics, road design and environmental factors highly contribute to the occurrence of traffic crashes (WHO, 2004). Since human factors usually have the most significant i...

  14. Phantom crash confirms models

    International Nuclear Information System (INIS)

    Anon.

    1989-01-01

    To test computer models of how a nuclear reactor's containment building would fare if an airplane crashed into it, the Muto Institute in Tokyo sponsored a 3.2 million dollar project at Sandia National Laboratory to slam an F-4 Phantom jet into a 500 ton concrete wall. The results showed that the computer calculations were accurate

  15. Failed rib region prediction in a human body model during crash events with precrash braking.

    Science.gov (United States)

    Guleyupoglu, B; Koya, B; Barnard, R; Gayzik, F S

    2018-02-28

    The objective of this study is 2-fold. We used a validated human body finite element model to study the predicted chest injury (focusing on rib fracture as a function of element strain) based on varying levels of simulated precrash braking. Furthermore, we compare deterministic and probabilistic methods of rib injury prediction in the computational model. The Global Human Body Models Consortium (GHBMC) M50-O model was gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and airbag. Twelve cases were investigated with permutations for failure, precrash braking system, and crash severity. The severities used were median (17 kph), severe (34 kph), and New Car Assessment Program (NCAP; 56.4 kph). Cases with failure enabled removed rib cortical bone elements once 1.8% effective plastic strain was exceeded. Alternatively, a probabilistic framework found in the literature was used to predict rib failure. Both the probabilistic and deterministic methods take into consideration location (anterior, lateral, and posterior). The deterministic method is based on a rubric that defines failed rib regions dependent on a threshold for contiguous failed elements. The probabilistic method depends on age-based strain and failure functions. Kinematics between both methods were similar (peak max deviation: ΔX head = 17 mm; ΔZ head = 4 mm; ΔX thorax = 5 mm; ΔZ thorax = 1 mm). Seat belt forces at the time of probabilistic failed region initiation were lower than those at deterministic failed region initiation. The probabilistic method for rib fracture predicted more failed regions in the rib (an analog for fracture) than the deterministic method in all but 1 case where they were equal. The failed region patterns between models are similar; however, there are differences that arise due to stress reduced from element elimination that cause probabilistic failed regions to continue to rise after no deterministic failed region would be

  16. Crash data modeling with a generalized estimator.

    Science.gov (United States)

    Ye, Zhirui; Xu, Yueru; Lord, Dominique

    2018-05-11

    The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

  17. Prediction of vehicle crashes by drivers' characteristics and past traffic violations in Korea using a zero-inflated negative binomial model.

    Science.gov (United States)

    Kim, Dae-Hwan; Ramjan, Lucie M; Mak, Kwok-Kei

    2016-01-01

    Traffic safety is a significant public health challenge, and vehicle crashes account for the majority of injuries. This study aims to identify whether drivers' characteristics and past traffic violations may predict vehicle crashes in Korea. A total of 500,000 drivers were randomly selected from the 11.6 million driver records of the Ministry of Land, Transport and Maritime Affairs in Korea. Records of traffic crashes were obtained from the archives of the Korea Insurance Development Institute. After matching the past violation history for the period 2004-2005 with the number of crashes in year 2006, a total of 488,139 observations were used for the analysis. Zero-inflated negative binomial model was used to determine the incident risk ratio (IRR) of vehicle crashes by past violations of individual drivers. The included covariates were driver's age, gender, district of residence, vehicle choice, and driving experience. Drivers violating (1) a hit-and-run or drunk driving regulation at least once and (2) a signal, central line, or speed regulation more than once had a higher risk of a vehicle crash with respective IRRs of 1.06 and 1.15. Furthermore, female gender, a younger age, fewer years of driving experience, and middle-sized vehicles were all significantly associated with a higher likelihood of vehicle crashes. Drivers' demographic characteristics and past traffic violations could predict vehicle crashes in Korea. Greater resources should be assigned to the provision of traffic safety education programs for the high-risk driver groups.

  18. Comparison of four statistical and machine learning methods for crash severity prediction.

    Science.gov (United States)

    Iranitalab, Amirfarrokh; Khattak, Aemal

    2017-11-01

    Crash severity prediction models enable different agencies to predict the severity of a reported crash with unknown severity or the severity of crashes that may be expected to occur sometime in the future. This paper had three main objectives: comparison of the performance of four statistical and machine learning methods including Multinomial Logit (MNL), Nearest Neighbor Classification (NNC), Support Vector Machines (SVM) and Random Forests (RF), in predicting traffic crash severity; developing a crash costs-based approach for comparison of crash severity prediction methods; and investigating the effects of data clustering methods comprising K-means Clustering (KC) and Latent Class Clustering (LCC), on the performance of crash severity prediction models. The 2012-2015 reported crash data from Nebraska, United States was obtained and two-vehicle crashes were extracted as the analysis data. The dataset was split into training/estimation (2012-2014) and validation (2015) subsets. The four prediction methods were trained/estimated using the training/estimation dataset and the correct prediction rates for each crash severity level, overall correct prediction rate and a proposed crash costs-based accuracy measure were obtained for the validation dataset. The correct prediction rates and the proposed approach showed NNC had the best prediction performance in overall and in more severe crashes. RF and SVM had the next two sufficient performances and MNL was the weakest method. Data clustering did not affect the prediction results of SVM, but KC improved the prediction performance of MNL, NNC and RF, while LCC caused improvement in MNL and RF but weakened the performance of NNC. Overall correct prediction rate had almost the exact opposite results compared to the proposed approach, showing that neglecting the crash costs can lead to misjudgment in choosing the right prediction method. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Multivariate poisson lognormal modeling of crashes by type and severity on rural two lane highways.

    Science.gov (United States)

    Wang, Kai; Ivan, John N; Ravishanker, Nalini; Jackson, Eric

    2017-02-01

    In an effort to improve traffic safety, there has been considerable interest in estimating crash prediction models and identifying factors contributing to crashes. To account for crash frequency variations among crash types and severities, crash prediction models have been estimated by type and severity. The univariate crash count models have been used by researchers to estimate crashes by crash type or severity, in which the crash counts by type or severity are assumed to be independent of one another and modelled separately. When considering crash types and severities simultaneously, this may neglect the potential correlations between crash counts due to the presence of shared unobserved factors across crash types or severities for a specific roadway intersection or segment, and might lead to biased parameter estimation and reduce model accuracy. The focus on this study is to estimate crashes by both crash type and crash severity using the Integrated Nested Laplace Approximation (INLA) Multivariate Poisson Lognormal (MVPLN) model, and identify the different effects of contributing factors on different crash type and severity counts on rural two-lane highways. The INLA MVPLN model can simultaneously model crash counts by crash type and crash severity by accounting for the potential correlations among them and significantly decreases the computational time compared with a fully Bayesian fitting of the MVPLN model using Markov Chain Monte Carlo (MCMC) method. This paper describes estimation of MVPLN models for three-way stop controlled (3ST) intersections, four-way stop controlled (4ST) intersections, four-way signalized (4SG) intersections, and roadway segments on rural two-lane highways. Annual Average Daily traffic (AADT) and variables describing roadway conditions (including presence of lighting, presence of left-turn/right-turn lane, lane width and shoulder width) were used as predictors. A Univariate Poisson Lognormal (UPLN) was estimated by crash type and

  20. Modelling and mitigation of Flash Crashes

    OpenAIRE

    Fry, John; Serbera, Jean-Philippe

    2017-01-01

    The algorithmic trading revolution has had a dramatic effect upon markets. Trading has become faster, and in some ways more efficient, though potentially at the cost higher volatility and increased uncertainty. Stories of predatory trading and flash crashes constitute a new financial reality. Worryingly, highly capitalised stocks may be particularly vulnerable to flash crashes. Amid fears of high-risk technology failures in the global financial system we develop a model for flash crashes....

  1. How the choice of safety performance function affects the identification of important crash prediction variables.

    Science.gov (United States)

    Wang, Ketong; Simandl, Jenna K; Porter, Michael D; Graettinger, Andrew J; Smith, Randy K

    2016-03-01

    Across the nation, researchers and transportation engineers are developing safety performance functions (SPFs) to predict crash rates and develop crash modification factors to improve traffic safety at roadway segments and intersections. Generalized linear models (GLMs), such as Poisson or negative binomial regression, are most commonly used to develop SPFs with annual average daily traffic as the primary roadway characteristic to predict crashes. However, while more complex to interpret, data mining models such as boosted regression trees have improved upon GLMs crash prediction performance due to their ability to handle more data characteristics, accommodate non-linearities, and include interaction effects between the characteristics. An intersection data inventory of 36 safety relevant parameters for three- and four-legged non-signalized intersections along state routes in Alabama was used to study the importance of intersection characteristics on crash rate and the interaction effects between key characteristics. Four different SPFs were investigated and compared: Poisson regression, negative binomial regression, regularized generalized linear model, and boosted regression trees. The models did not agree on which intersection characteristics were most related to the crash rate. The boosted regression tree model significantly outperformed the other models and identified several intersection characteristics as having strong interaction effects. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Crash Prediction and Risk Evaluation Based on Traffic Analysis Zones

    Directory of Open Access Journals (Sweden)

    Cuiping Zhang

    2014-01-01

    Full Text Available Traffic safety evaluation for traffic analysis zones (TAZs plays an important role in transportation safety planning and long-range transportation plan development. This paper aims to present a comprehensive analysis of zonal safety evaluation. First, several criteria are proposed to measure the crash risk at zonal level. Then these criteria are integrated into one measure-average hazard index (AHI, which is used to identify unsafe zones. In addition, the study develops a negative binomial regression model to statistically estimate significant factors for the unsafe zones. The model results indicate that the zonal crash frequency can be associated with several social-economic, demographic, and transportation system factors. The impact of these significant factors on zonal crash is also discussed. The finding of this study suggests that safety evaluation and estimation might benefit engineers and decision makers in identifying high crash locations for potential safety improvements.

  3. Calibration of Airframe and Occupant Models for Two Full-Scale Rotorcraft Crash Tests

    Science.gov (United States)

    Annett, Martin S.; Horta, Lucas G.; Polanco, Michael A.

    2012-01-01

    Two full-scale crash tests of an MD-500 helicopter were conducted in 2009 and 2010 at NASA Langley's Landing and Impact Research Facility in support of NASA s Subsonic Rotary Wing Crashworthiness Project. The first crash test was conducted to evaluate the performance of an externally mounted composite deployable energy absorber under combined impact conditions. In the second crash test, the energy absorber was removed to establish baseline loads that are regarded as severe but survivable. Accelerations and kinematic data collected from the crash tests were compared to a system integrated finite element model of the test article. Results from 19 accelerometers placed throughout the airframe were compared to finite element model responses. The model developed for the purposes of predicting acceleration responses from the first crash test was inadequate when evaluating more severe conditions seen in the second crash test. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used to calibrate model results for the second full-scale crash test. This combination of heuristic and quantitative methods was used to identify modeling deficiencies, evaluate parameter importance, and propose required model changes. It is shown that the multi-dimensional calibration techniques presented here are particularly effective in identifying model adequacy. Acceleration results for the calibrated model were compared to test results and the original model results. There was a noticeable improvement in the pilot and co-pilot region, a slight improvement in the occupant model response, and an over-stiffening effect in the passenger region. This approach should be adopted early on, in combination with the building-block approaches that are customarily used, for model development and test planning guidance. Complete crash simulations with validated finite element models can be used

  4. Propensity scores-potential outcomes framework to incorporate severity probabilities in the highway safety manual crash prediction algorithm.

    Science.gov (United States)

    Sasidharan, Lekshmi; Donnell, Eric T

    2014-10-01

    Accurate estimation of the expected number of crashes at different severity levels for entities with and without countermeasures plays a vital role in selecting countermeasures in the framework of the safety management process. The current practice is to use the American Association of State Highway and Transportation Officials' Highway Safety Manual crash prediction algorithms, which combine safety performance functions and crash modification factors, to estimate the effects of safety countermeasures on different highway and street facility types. Many of these crash prediction algorithms are based solely on crash frequency, or assume that severity outcomes are unchanged when planning for, or implementing, safety countermeasures. Failing to account for the uncertainty associated with crash severity outcomes, and assuming crash severity distributions remain unchanged in safety performance evaluations, limits the utility of the Highway Safety Manual crash prediction algorithms in assessing the effect of safety countermeasures on crash severity. This study demonstrates the application of a propensity scores-potential outcomes framework to estimate the probability distribution for the occurrence of different crash severity levels by accounting for the uncertainties associated with them. The probability of fatal and severe injury crash occurrence at lighted and unlighted intersections is estimated in this paper using data from Minnesota. The results show that the expected probability of occurrence of fatal and severe injury crashes at a lighted intersection was 1 in 35 crashes and the estimated risk ratio indicates that the respective probabilities at an unlighted intersection was 1.14 times higher compared to lighted intersections. The results from the potential outcomes-propensity scores framework are compared to results obtained from traditional binary logit models, without application of propensity scores matching. Traditional binary logit analysis suggests that

  5. Estimating likelihood of future crashes for crash-prone drivers

    OpenAIRE

    Subasish Das; Xiaoduan Sun; Fan Wang; Charles Leboeuf

    2015-01-01

    At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the a...

  6. Modeling crash injury severity by road feature to improve safety.

    Science.gov (United States)

    Penmetsa, Praveena; Pulugurtha, Srinivas S

    2018-01-02

    The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.

  7. Prediction equation for vehicle-pedestrian crash and safety analysis ...

    African Journals Online (AJOL)

    The occurrences of vehicle-pedestrian crashes at signalized intersections were investigated using a 3 year (2004-2006) crash records of 82 signalized intersections in Accra, Kumasi, Tema, Sekondi-Takoradi and Tamale. The data were analyzed using Micro-computer Accident Analysis Package. Traffic flow characteristics ...

  8. A Bayesian network based framework for real-time crash prediction on the basic freeway segments of urban expressways.

    Science.gov (United States)

    Hossain, Moinul; Muromachi, Yasunori

    2012-03-01

    The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Statistical modeling of total crash frequency at highway intersections

    Directory of Open Access Journals (Sweden)

    Arash M. Roshandeh

    2016-04-01

    Full Text Available Intersection-related crashes are associated with high proportion of accidents involving drivers, occupants, pedestrians, and cyclists. In general, the purpose of intersection safety analysis is to determine the impact of safety-related variables on pedestrians, cyclists and vehicles, so as to facilitate the design of effective and efficient countermeasure strategies to improve safety at intersections. This study investigates the effects of traffic, environmental, intersection geometric and pavement-related characteristics on total crash frequencies at intersections. A random-parameter Poisson model was used with crash data from 357 signalized intersections in Chicago from 2004 to 2010. The results indicate that out of the identified factors, evening peak period traffic volume, pavement condition, and unlighted intersections have the greatest effects on crash frequencies. Overall, the results seek to suggest that, in order to improve effective highway-related safety countermeasures at intersections, significant attention must be focused on ensuring that pavements are adequately maintained and intersections should be well lighted. It needs to be mentioned that, projects could be implemented at and around the study intersections during the study period (7 years, which could affect the crash frequency over the time. This is an important variable which could be a part of the future studies to investigate the impacts of safety-related works at intersections and their marginal effects on crash frequency at signalized intersections.

  10. Estimating likelihood of future crashes for crash-prone drivers

    Directory of Open Access Journals (Sweden)

    Subasish Das

    2015-06-01

    Full Text Available At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the at-fault drivers. The logistic regression method is used by employing eight years' traffic crash data (2004–2011 in Louisiana. Crash predictors such as the driver's crash involvement, crash and road characteristics, human factors, collision type, and environmental factors are considered in the model. The at-fault and not-at-fault status of the crashes are used as the response variable. The developed model has identified a few important variables, and is used to correctly classify at-fault crashes up to 62.40% with a specificity of 77.25%. This model can identify as many as 62.40% of the crash incidence of at-fault drivers in the upcoming year. Traffic agencies can use the model for monitoring the performance of an at-fault crash-prone drivers and making roadway improvements meant to reduce crash proneness. From the findings, it is recommended that crash-prone drivers should be targeted for special safety programs regularly through education and regulations.

  11. Integrated traffic conflict model for estimating crash modification factors.

    Science.gov (United States)

    Shahdah, Usama; Saccomanno, Frank; Persaud, Bhagwant

    2014-10-01

    Crash modification factors (CMFs) for road safety treatments are usually obtained through observational models based on reported crashes. Observational Bayesian before-and-after methods have been applied to obtain more precise estimates of CMFs by accounting for the regression-to-the-mean bias inherent in naive methods. However, sufficient crash data reported over an extended period of time are needed to provide reliable estimates of treatment effects, a requirement that can be a challenge for certain types of treatment. In addition, these studies require that sites analyzed actually receive the treatment to which the CMF pertains. Another key issue with observational approaches is that they are not causal in nature, and as such, cannot provide a sound "behavioral" rationale for the treatment effect. Surrogate safety measures based on high risk vehicle interactions and traffic conflicts have been proposed to address this issue by providing a more "causal perspective" on lack of safety for different road and traffic conditions. The traffic conflict approach has been criticized, however, for lacking a formal link to observed and verified crashes, a difficulty that this paper attempts to resolve by presenting and investigating an alternative approach for estimating CMFs using simulated conflicts that are linked formally to observed crashes. The integrated CMF estimates are compared to estimates from an empirical Bayes (EB) crash-based before-and-after analysis for the same sample of treatment sites. The treatment considered involves changing left turn signal priority at Toronto signalized intersections from permissive to protected-permissive. The results are promising in that the proposed integrated method yields CMFs that closely match those obtained from the crash-based EB before-and-after analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

  12. Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

    Science.gov (United States)

    Chen, Feng; Chen, Suren; Ma, Xiaoxiang

    2018-06-01

    Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

  13. Crash simulation: an immersive learning model.

    Science.gov (United States)

    Wenham, John; Bennett, Paul; Gleeson, Wendy

    2017-12-26

    Far West New South Wales Local Emergency Management Committee runs an annual crash simulation exercise to assess the operational readiness of all local emergency services to coordinate and manage a multi-casualty exercise. Since 2009, the Broken Hill University Department of Rural Health (BHUDRH) has collaborated with the committee, enabling the inclusion of health students in this exercise. It is an immersive interprofessional learning experience that evaluates teamwork, communication and safe effective clinical trauma management outside the hospital setting. After 7 years of modifying and developing the exercise, we set out to evaluate its impact on the students' learning, and sought ethics approval from the University of Sydney for this study. At the start of this year's crash simulation, students were given information sheets and consent forms with regards to the research. Once formal debriefing had finished, the researchers conducted a semi-structured focus-group interview with the health students to gain insight into their experience and their perceived value of the training. Students also completed short-answer questionnaires, and the anonymised responses were analysed. Crash simulation … evaluates teamwork, communication and safe effective clinical trauma management IMPLICATIONS: Participants identified that this multidisciplinary learning opportunity in a pre-hospital mass casualty situation was of value to them. It has taken them outside of their usually protected hospital or primary care setting and tested their critical thinking and communication skills. We recommend this learning concept to other educational institutions. Further research will assess the learning value of the simulated event to the other agencies involved. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

  14. Bayesian log-periodic model for financial crashes

    DEFF Research Database (Denmark)

    Rodríguez-Caballero, Carlos Vladimir; Knapik, Oskar

    2014-01-01

    This paper introduces a Bayesian approach in econophysics literature about financial bubbles in order to estimate the most probable time for a financial crash to occur. To this end, we propose using noninformative prior distributions to obtain posterior distributions. Since these distributions...... cannot be performed analytically, we develop a Markov Chain Monte Carlo algorithm to draw from posterior distributions. We consider three Bayesian models that involve normal and Student’s t-distributions in the disturbances and an AR(1)-GARCH(1,1) structure only within the first case. In the empirical...... part of the study, we analyze a well-known example of financial bubble – the S&P 500 1987 crash – to show the usefulness of the three methods under consideration and crashes of Merval-94, Bovespa-97, IPCMX-94, Hang Seng-97 using the simplest method. The novelty of this research is that the Bayesian...

  15. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  16. Failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

    2013-08-01

    Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

  17. Lower extremity finite element model for crash simulation

    Energy Technology Data Exchange (ETDEWEB)

    Schauer, D.A.; Perfect, S.A.

    1996-03-01

    A lower extremity model has been developed to study occupant injury mechanisms of the major bones and ligamentous soft tissues resulting from vehicle collisions. The model is based on anatomically correct digitized bone surfaces of the pelvis, femur, patella and the tibia. Many muscles, tendons and ligaments were incrementally added to the basic bone model. We have simulated two types of occupant loading that occur in a crash environment using a non-linear large deformation finite element code. The modeling approach assumed that the leg was passive during its response to the excitation, that is, no active muscular contraction and therefore no active change in limb stiffness. The approach recognized that the most important contributions of the muscles to the lower extremity response are their ability to define and modify the impedance of the limb. When nonlinear material behavior in a component of the leg model was deemed important to response, a nonlinear constitutive model was incorporated. The accuracy of these assumptions can be verified only through a review of analysis results and careful comparison with test data. As currently defined, the model meets the objective for which it was created. Much work remains to be done, both from modeling and analysis perspectives, before the model can be considered complete. The model implements a modeling philosophy that can accurately capture both kinematic and kinetic response of the lower limb. We have demonstrated that the lower extremity model is a valuable tool for understanding the injury processes and mechanisms. We are now in a position to extend the computer simulation to investigate the clinical fracture patterns observed in actual crashes. Additional experience with this model will enable us to make a statement on what measures are needed to significantly reduce lower extremity injuries in vehicle crashes. 6 refs.

  18. Using cognitive status to predict crash risk: blazing new trails?

    Science.gov (United States)

    Staplin, Loren; Gish, Kenneth W; Sifrit, Kathy J

    2014-02-01

    A computer-based version of an established neuropsychological paper-and-pencil assessment tool, the Trail-Making Test, was applied with approximately 700 drivers aged 70 years and older in offices of the Maryland Motor Vehicle Administration. This was a volunteer sample that received a small compensation for study participation, with an assurance that their license status would not be affected by the results. Analyses revealed that the study sample was representative of Maryland older drivers with respect to age and indices of prior driving safety. The relationship between drivers' scores on the Trail-Making Test and prospective crash experience was analyzed using a new outcome measure that explicitly takes into account error responses as well as correct responses, the error-compensated completion time. For the only reliable predictor of crash risk, Trail-Making Test Part B, this measure demonstrated a modest gain in specificity and was a more significant predictor of future safety risk than the simple time-to-completion measure. Improved specificity and the potential for autonomous test administration are particular advantages of this measure for use with large populations, in settings such as health care or driver licensing. © 2013.

  19. Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

    Energy Technology Data Exchange (ETDEWEB)

    Coppola, Anthony [General Motors Company, Flint, MI (United States); Faruque, Omar [Ford Motor Company, Dearborn, MI (United States); Truskin, James F [FCA US LLC, Auburn Hills, MI (United States); Board, Derek [Ford Motor Company, Dearborn, MI (United States); Jones, Martin [Ford Motor Company, Dearborn, MI (United States); Tao, Jian [FCA US LLC, Auburn Hills, MI (United States); Chen, Yijung [Ford Motor Company, Dearborn, MI (United States); Mehta, Manish [M-Tech International LLC, Dubai (United Arab Emirates)

    2017-09-27

    As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared research project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing

  20. Analysing the Severity and Frequency of Traffic Crashes in Riyadh City Using Statistical Models

    Directory of Open Access Journals (Sweden)

    Saleh Altwaijri

    2012-12-01

    Full Text Available Traffic crashes in Riyadh city cause losses in the form of deaths, injuries and property damages, in addition to the pain and social tragedy affecting families of the victims. In 2005, there were a total of 47,341 injury traffic crashes occurred in Riyadh city (19% of the total KSA crashes and 9% of those crashes were severe. Road safety in Riyadh city may have been adversely affected by: high car ownership, migration of people to Riyadh city, high daily trips reached about 6 million, high rate of income, low-cost of petrol, drivers from different nationalities, young drivers and tremendous growth in population which creates a high level of mobility and transport activities in the city. The primary objective of this paper is therefore to explore factors affecting the severity and frequency of road crashes in Riyadh city using appropriate statistical models aiming to establish effective safety policies ready to be implemented to reduce the severity and frequency of road crashes in Riyadh city. Crash data for Riyadh city were collected from the Higher Commission for the Development of Riyadh (HCDR for a period of five years from 1425H to 1429H (roughly corresponding to 2004-2008. Crash data were classified into three categories: fatal, serious-injury and slight-injury. Two nominal response models have been developed: a standard multinomial logit model (MNL and a mixed logit model to injury-related crash data. Due to a severe underreporting problem on the slight injury crashes binary and mixed binary logistic regression models were also estimated for two categories of severity: fatal and serious crashes. For frequency, two count models such as Negative Binomial (NB models were employed and the unit of analysis was 168 HAIs (wards in Riyadh city. Ward-level crash data are disaggregated by severity of the crash (such as fatal and serious injury crashes. The results from both multinomial and binary response models are found to be fairly consistent but

  1. Investigation of time and weather effects on crash types using full Bayesian multivariate Poisson lognormal models.

    Science.gov (United States)

    El-Basyouny, Karim; Barua, Sudip; Islam, Md Tazul

    2014-12-01

    Previous research shows that various weather elements have significant effects on crash occurrence and risk; however, little is known about how these elements affect different crash types. Consequently, this study investigates the impact of weather elements and sudden extreme snow or rain weather changes on crash type. Multivariate models were used for seven crash types using five years of daily weather and crash data collected for the entire City of Edmonton. In addition, the yearly trend and random variation of parameters across the years were analyzed by using four different modeling formulations. The proposed models were estimated in a full Bayesian context via Markov Chain Monte Carlo simulation. The multivariate Poisson lognormal model with yearly varying coefficients provided the best fit for the data according to Deviance Information Criteria. Overall, results showed that temperature and snowfall were statistically significant with intuitive signs (crashes decrease with increasing temperature; crashes increase as snowfall intensity increases) for all crash types, while rainfall was mostly insignificant. Previous snow showed mixed results, being statistically significant and positively related to certain crash types, while negatively related or insignificant in other cases. Maximum wind gust speed was found mostly insignificant with a few exceptions that were positively related to crash type. Major snow or rain events following a dry weather condition were highly significant and positively related to three crash types: Follow-Too-Close, Stop-Sign-Violation, and Ran-Off-Road crashes. The day-of-the-week dummy variables were statistically significant, indicating a possible weekly variation in exposure. Transportation authorities might use the above results to improve road safety by providing drivers with information regarding the risk of certain crash types for a particular weather condition. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Meso-modeling of Carbon Fiber Composite for Crash Safety Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Shih-Po; Chen, Yijung; Zeng, Danielle; Su, Xuming

    2017-04-06

    In the conventional approach, the material properties for crash safety simulations are typically obtained from standard coupon tests, where the test results only provide single layer material properties used in crash simulations. However, the lay-up effects for the failure behaviors of the real structure were not considered in numerical simulations. Hence, there was discrepancy between the crash simulations and experimental tests. Consequently, an intermediate stage is required for accurate predictions. Some component tests are required to correlate the material models in the intermediate stage. In this paper, a Mazda Tube under high-impact velocity is chosen as an example for the crash safety analysis. The tube consists of 24 layers of uni-directional (UD) carbon fiber composite materials, in which 4 layers are perpendicular to, while the other layers are parallel to the impact direction. An LS-DYNA meso-model was constructed with orthotropic material models counting for the single-layer material behaviors. Between layers, a node-based tie-break contact was used for modeling the delamination of the composite material. Since fiber directions are not single-oriented, the lay-up effects could be an important effect. From the first numerical trial, premature material failure occurred due to the use of material parameters obtained directly from the coupon tests. Some parametric studies were conducted to identify the cause of the numerical instability. The finding is that the material failure strength used in the numerical model needs to be enlarged to stabilize the numerical model. Some hypothesis was made to provide the foundation for enlarging the failure strength and the corresponding experiments will be conducted to validate the hypothesis.

  3. A Partial Proportional Odds Model for Pedestrian Crashes at Mid-Blocks in Melbourne Metropolitan Area

    Directory of Open Access Journals (Sweden)

    Toran Pour Alireza

    2016-01-01

    Full Text Available Pedestrian crashes account for 11% of all reported traffic crashes in Melbourne metropolitan area between 2004 and 2013. There are very limited studies on pedestrian accidents at mid-blocks. Mid-block crashes account for about 46% of the total pedestrian crashes in Melbourne metropolitan area. Meanwhile, about 50% of all pedestrian fatalities occur at mid-blocks. In this research, Partial Proportional Odds (PPO model is applied to examine vehicle-pedestrian crash severity at mid-blocks in Melbourne metropolitan area. The PPO model is a logistic regression model that allows the covariates that meet the proportional odds assumption to affect different crash severity levels with the same magnitude; whereas the covariates that do not meet the proportional odds assumption can have different effects on different severity levels. In this research vehicle-pedestrian crashes at mid-blocks are analysed for first time. In addition, some factors such as distance of crashes to public transport stops, average road slope and some social characteristics are considered to develop the model in this research for first time. Results of PPO model show that speed limit, light condition, pedestrian age and gender, and vehicle type are the most significant factors that influence vehicle-pedestrian crash severity at mid-blocks.

  4. Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data

    Science.gov (United States)

    af Wåhlberg, Anders; Freeman, James; Watson, Barry; Watson, Angela

    2016-01-01

    Background Traffic offences have been considered an important predictor of crash involvement, and have often been used as a proxy safety variable for crashes. However the association between crashes and offences has never been meta-analysed and the population effect size never established. Research is yet to determine the extent to which this relationship may be spuriously inflated through systematic measurement error, with obvious implications for researchers endeavouring to accurately identify salient factors predictive of crashes. Methodology and Principal Findings Studies yielding a correlation between crashes and traffic offences were collated and a meta-analysis of 144 effects drawn from 99 road safety studies conducted. Potential impact of factors such as age, time period, crash and offence rates, crash severity and data type, sourced from either self-report surveys or archival records, were considered and discussed. After weighting for sample size, an average correlation of r = .18 was observed over the mean time period of 3.2 years. Evidence emerged suggesting the strength of this correlation is decreasing over time. Stronger correlations between crashes and offences were generally found in studies involving younger drivers. Consistent with common method variance effects, a within country analysis found stronger effect sizes in self-reported data even controlling for crash mean. Significance The effectiveness of traffic offences as a proxy for crashes may be limited. Inclusion of elements such as independently validated crash and offence histories or accurate measures of exposure to the road would facilitate a better understanding of the factors that influence crash involvement. PMID:27128093

  5. Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

    2015-07-01

    The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

  6. Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

    Science.gov (United States)

    Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

    2016-03-01

    Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

  7. Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach.

    Science.gov (United States)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that represents the selection among 5 emergency lateral and speed control maneuvers (i.e., "no avoidance maneuvers," "braking," "steering," "braking and steering," and "other maneuvers) while accommodating correlations across maneuvers and heteroscedasticity. Data for the analysis were retrieved from the General Estimates System (GES) crash database for the year 2009 by considering drivers for which crash avoidance maneuvers are known. The results show that (1) the nature of the critical event that made the crash imminent greatly influences the choice of crash avoidance maneuvers, (2) women and elderly have a relatively lower propensity to conduct crash avoidance maneuvers, (3) drowsiness and fatigue have a greater negative marginal effect on the tendency to engage in crash avoidance maneuvers than alcohol and drug consumption, (4) difficult road conditions increase the propensity to perform crash avoidance maneuvers, and (5) visual obstruction and artificial illumination decrease the probability to carry out crash avoidance maneuvers. The results emphasize the need for public awareness campaigns to promote safe driving style for senior drivers and warning about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing

  8. Bubbles, Post-Crash Dynamics, and the Housing Market

    OpenAIRE

    Crocker H. Liu; Adam Nowak; Stuart Rosenthal

    2014-01-01

    This paper documents and explains previously unrecognized post-crash dynamics following the collapse of a housing bubble. A simple model predicts that speculative developers ensure stable pre-crash relative prices between small and large homes while their post-crash exit allows small-home relative values to fall. Evidence from Phoenix supports the model. Although home prices doubled 2004-2006, relative prices of small-to-large homes remained nearly constant but then plummeted post-crash. As s...

  9. Critical market crashes

    Science.gov (United States)

    Sornette, D.

    2003-04-01

    This review presents a general theory of financial crashes and of stock market instabilities that his co-workers and the author have developed over the past seven years. We start by discussing the limitation of standard analyses for characterizing how crashes are special. The study of the frequency distribution of drawdowns, or runs of successive losses shows that large financial crashes are “outliers”: they form a class of their own as can be seen from their statistical signatures. If large financial crashes are “outliers”, they are special and thus require a special explanation, a specific model, a theory of their own. In addition, their special properties may perhaps be used for their prediction. The main mechanisms leading to positive feedbacks, i.e., self-reinforcement, such as imitative behavior and herding between investors are reviewed with many references provided to the relevant literature outside the narrow confine of Physics. Positive feedbacks provide the fuel for the development of speculative bubbles, preparing the instability for a major crash. We demonstrate several detailed mathematical models of speculative bubbles and crashes. A first model posits that the crash hazard drives the market price. The crash hazard may sky-rocket at some times due to the collective behavior of “noise traders”, those who act on little information, even if they think they “know”. A second version inverses the logic and posits that prices drive the crash hazard. Prices may skyrocket at some times again due to the speculative or imitative behavior of investors. According the rational expectation model, this entails automatically a corresponding increase of the probability for a crash. We also review two other models including the competition between imitation and contrarian behavior and between value investors and technical analysts. The most important message is the discovery of robust and universal signatures of the approach to crashes. These precursory

  10. Crash rates analysis in China using a spatial panel model

    Directory of Open Access Journals (Sweden)

    Wonmongo Lacina Soro

    2017-10-01

    Full Text Available The consideration of spatial externalities in traffic safety analysis is of paramount importance for the success of road safety policies. Yet, the quasi-totality of spatial dependence studies on crash rates is performed within the framework of single-equation spatial cross-sectional studies. The present study extends the spatial cross-sectional scheme to a spatial fixed-effects panel model estimated using the maximum likelihood method. The spatial units are the 31 administrative regions of mainland China over the period 2004–2013. The presence of neighborhood effects is evidenced through the Moran's I statistic. Consistent with previous studies, the analysis reveals that omitting the spatial effects in traffic safety analysis is likely to bias the estimation results. The spatial and error lags are all positive and statistically significant suggesting similarities of crash rates pattern in neighboring regions. Some other explanatory variables, such as freight traffic, the length of paved roads and the populations of age 65 and above are related to higher rates while the opposite trend is observed for the Gross Regional Product, the urban unemployment rate and passenger traffic.

  11. Crash-related mortality and model year: are newer vehicles safer?

    Science.gov (United States)

    Ryb, Gabriel E; Dischinger, Patricia C; McGwin, Gerald; Griffin, Russell L

    2011-01-01

    The objective of this study was to determine whether occupants of newer vehicles experience a lower risk of crash-related mortality. The occurrence of death was studied in relation to vehicle model year (MY) among front seat vehicular occupants, age ≥ 16 captured in the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) between 2000 and 2008. The associations between death and other occupant, vehicular and crash characteristics were also explored. Multiple logistic regression models for the prediction of death were built with model year as the independent variable and other characteristics linked to death as covariates. Imputation was used for missing data; weighted data was used. A total of 70,314 cases representing 30,514,372 weighted cases were available for analysis. Death occurred in 0.6% of the weighted population. Death was linked to age>60, male gender, higher BMI, near lateral direction of impact, high delta v, rollover, ejection and vehicle mismatch, and negatively associated with seatbelt use and rear and far lateral direction of impact. Mortality decreased with later model year groups (MY<94 0.78%, MY 94-97 0.53%, MY 98-04 0.51% and MY 05-08 0.38%, p=<0.0001). After adjustment for confounders, MY 94-97, MY 98-04 and MY 05-08 showed decreased odds of death [OR 0.80 (0.69-0.94), 0.82 (0.70-0.97), and 0.67 (0.47-0.96), respectively] when compared to MY <94. Newer vehicles are associated with lower crash-related mortality. Their introduction into the vehicle fleet may explain, at least in part, the decrease in mortality rates in the past two decades.

  12. Restraint status improves the predictive value of motor vehicle crash criteria for pediatric trauma team activation.

    Science.gov (United States)

    Bozeman, Andrew P; Dassinger, Melvin S; Recicar, John F; Smith, Samuel D; Rettiganti, Mallikarjuna R; Nick, Todd G; Maxson, Robert T

    2012-12-01

    Most trauma centers incorporate mechanistic criteria (MC) into their algorithm for trauma team activation (TTA). We hypothesized that characteristics of the crash are less reliable than restraint status in predicting significant injury and the need for TTA. We identified 271 patients (age, <15 y) admitted with a diagnosis of motor vehicle crash. Mechanistic criteria and restraint status of each patient were recorded. Both MC and MC plus restraint status were evaluated as separate measures for appropriately predicting TTA based on treatment outcomes and injury scores. Improper restraint alone predicted a need for TTA with an odds ratios of 2.69 (P = .002). MC plus improper restraint predicted the need for TTA with an odds ratio of 2.52 (P = .002). In contrast, the odds ratio when using MC alone was 1.65 (P = .16). When the 5 MC were evaluated individually as predictive of TTA, ejection, death of occupant, and intrusion more than 18 inches were statistically significant. Improper restraint is an independent predictor of necessitating TTA in this single-institution study. Copyright © 2012 Elsevier Inc. All rights reserved.

  13. Extension of the application of conway-maxwell-poisson models: analyzing traffic crash data exhibiting underdispersion.

    Science.gov (United States)

    Lord, Dominique; Geedipally, Srinivas Reddy; Guikema, Seth D

    2010-08-01

    The objective of this article is to evaluate the performance of the COM-Poisson GLM for analyzing crash data exhibiting underdispersion (when conditional on the mean). The COM-Poisson distribution, originally developed in 1962, has recently been reintroduced by statisticians for analyzing count data subjected to either over- or underdispersion. Over the last year, the COM-Poisson GLM has been evaluated in the context of crash data analysis and it has been shown that the model performs as well as the Poisson-gamma model for crash data exhibiting overdispersion. To accomplish the objective of this study, several COM-Poisson models were estimated using crash data collected at 162 railway-highway crossings in South Korea between 1998 and 2002. This data set has been shown to exhibit underdispersion when models linking crash data to various explanatory variables are estimated. The modeling results were compared to those produced from the Poisson and gamma probability models documented in a previous published study. The results of this research show that the COM-Poisson GLM can handle crash data when the modeling output shows signs of underdispersion. Finally, they also show that the model proposed in this study provides better statistical performance than the gamma probability and the traditional Poisson models, at least for this data set.

  14. The application of the random regret minimization model to drivers’ choice of crash avoidance maneuvers

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    This study explores the plausibility of regret minimization as behavioral paradigm underlying the choice of crash avoidance maneuvers. Alternatively to previous studies that considered utility maximization, this study applies the random regret minimization (RRM) model while assuming that drivers ...

  15. The application of the random regret minimization model to drivers’ choice of crash avoidance maneuvers

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    This study explores the plausibility of regret minimization as behavioral paradigm underlying the choice of crash avoidance maneuvers. Alternatively to previous studies that considered utility maximization, this study applies the random regret minimization (RRM) model while assuming that drivers ...

  16. An epidemiological survey on road traffic crashes in Iran: application of the two logistic regression models.

    Science.gov (United States)

    Bakhtiyari, Mahmood; Mehmandar, Mohammad Reza; Mirbagheri, Babak; Hariri, Gholam Reza; Delpisheh, Ali; Soori, Hamid

    2014-01-01

    Risk factors of human-related traffic crashes are the most important and preventable challenges for community health due to their noteworthy burden in developing countries in particular. The present study aims to investigate the role of human risk factors of road traffic crashes in Iran. Through a cross-sectional study using the COM 114 data collection forms, the police records of almost 600,000 crashes occurred in 2010 are investigated. The binary logistic regression and proportional odds regression models are used. The odds ratio for each risk factor is calculated. These models are adjusted for known confounding factors including age, sex and driving time. The traffic crash reports of 537,688 men (90.8%) and 54,480 women (9.2%) are analysed. The mean age is 34.1 ± 14 years. Not maintaining eyes on the road (53.7%) and losing control of the vehicle (21.4%) are the main causes of drivers' deaths in traffic crashes within cities. Not maintaining eyes on the road is also the most frequent human risk factor for road traffic crashes out of cities. Sudden lane excursion (OR = 9.9, 95% CI: 8.2-11.9) and seat belt non-compliance (OR = 8.7, CI: 6.7-10.1), exceeding authorised speed (OR = 17.9, CI: 12.7-25.1) and exceeding safe speed (OR = 9.7, CI: 7.2-13.2) are the most significant human risk factors for traffic crashes in Iran. The high mortality rate of 39 people for every 100,000 population emphasises on the importance of traffic crashes in Iran. Considering the important role of human risk factors in traffic crashes, struggling efforts are required to control dangerous driving behaviours such as exceeding speed, illegal overtaking and not maintaining eyes on the road.

  17. A comparative empirical analysis of statistical models for evaluating highway segment crash frequency

    Directory of Open Access Journals (Sweden)

    Bismark R.D.K. Agbelie

    2016-08-01

    Full Text Available The present study conducted an empirical highway segment crash frequency analysis on the basis of fixed-parameters negative binomial and random-parameters negative binomial models. Using a 4-year data from a total of 158 highway segments, with a total of 11,168 crashes, the results from both models were presented, discussed, and compared. About 58% of the selected variables produced normally distributed parameters across highway segments, while the remaining produced fixed parameters. The presence of a noise barrier along a highway segment would increase mean annual crash frequency by 0.492 for 88.21% of the highway segments, and would decrease crash frequency for 11.79% of the remaining highway segments. Besides, the number of vertical curves per mile along a segment would increase mean annual crash frequency by 0.006 for 84.13% of the highway segments, and would decrease crash frequency for 15.87% of the remaining highway segments. Thus, constraining the parameters to be fixed across all highway segments would lead to an inaccurate conclusion. Although, the estimated parameters from both models showed consistency in direction, the magnitudes were significantly different. Out of the two models, the random-parameters negative binomial model was found to be statistically superior in evaluating highway segment crashes compared with the fixed-parameters negative binomial model. On average, the marginal effects from the fixed-parameters negative binomial model were observed to be significantly overestimated compared with those from the random-parameters negative binomial model.

  18. A spatial generalized ordered response model to examine highway crash injury severity.

    Science.gov (United States)

    Castro, Marisol; Paleti, Rajesh; Bhat, Chandra R

    2013-03-01

    This paper proposes a flexible econometric structure for injury severity analysis at the level of individual crashes that recognizes the ordinal nature of injury severity categories, allows unobserved heterogeneity in the effects of contributing factors, as well as accommodates spatial dependencies in the injury severity levels experienced in crashes that occur close to one another in space. The modeling framework is applied to analyze the injury severity sustained in crashes occurring on highway road segments in Austin, Texas. The sample is drawn from the Texas Department of Transportation (TxDOT) crash incident files from 2009 and includes a variety of crash characteristics, highway design attributes, driver and vehicle characteristics, and environmental factors. The results from our analysis underscore the value of our proposed model for data fit purposes as well as to accurately estimate variable effects. The most important determinants of injury severity on highways, according to our results, are (1) whether any vehicle occupant is ejected, (2) whether collision type is head-on, (3) whether any vehicle involved in the crash overturned, (4) whether any vehicle occupant is unrestrained by a seat-belt, and (5) whether a commercial truck is involved. Copyright © 2012 Elsevier Ltd. All rights reserved.

  19. Can a stochastic cusp catastrophe model explain stock market crashes?

    Czech Academy of Sciences Publication Activity Database

    Baruník, Jozef; Vošvrda, Miloslav

    2009-01-01

    Roč. 33, č. 10 (2009), s. 1824-1836 ISSN 0165-1889 R&D Projects: GA ČR GD402/09/H045; GA ČR GA402/09/0965 Grant - others:GAUK(CZ) 46108 Institutional research plan: CEZ:AV0Z10750506 Keywords : Stochastic cusp catastrophe * Bifurcations * Singularity * Nonlinear dynamics * Stock market crash Subject RIV: AH - Economics Impact factor: 1.097, year: 2009

  20. Horizontal crash testing and analysis of model flatrols

    International Nuclear Information System (INIS)

    Dowler, H.J.; Soanes, T.P.T.

    1985-01-01

    To assess the behaviour of a full scale flask and flatrol during a proposed demonstration impact into a tunnel abutment, a mathematical modelling technique was developed and validated. The work was performed at quarter scale and comprised of both scale model tests and mathematical analysis in one and two dimensions. Good agreement between model test results of the 26.8m/s (60 mph) abutment impacts and the mathematical analysis, validated the modelling techniques. The modelling method may be used with confidence to predict the outcome of the proposed full scale demonstration. (author)

  1. Investigation of Influential Factors for Bicycle Crashes Using a Spatiotemporal Model

    Science.gov (United States)

    Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

    2017-09-01

    Despite the numerous potential advantages of indulging in bicycling, such as elevation of health and environment along with mitigation of congestion, the cyclists are a vulnerable group of commuters which is exposed to safety risks. This study aims to investigate the explanatory variables at transportation planning level which have a significant impact on the bicycle crashes. To account for the serial changes around the built environment, the linear time trend as well as time-varying coefficients are utilized for the covariates. These model modifications help account for the variations in the environment which may escape the incorporated variables due to lack of robustness in data. Also, to incorporate the interaction of roadway, demographic, and socioeconomic features within a Traffic Analysis Zone (TAZ), with the bicycle crashes of that area, a spatial correlation is integrated. This spatial correlation accounts for the spatially structured random effects which capture the unobserved heterogeneity and add towards building more comprehensive model with relatively precise estimates. Two different age groups, the student population in the TAZs, the presence of arterial roads and bike lanes, were observed to be statistically significant variables related with bicycle crashes. These observations will guide the transportation planning organizations which focus on the entity of TAZ while developing policies. The results of the current study establish a quantifies relationship between the significant factors and the crash count which will enable the planners to choose the most cost-efficient, yet most productive, factors which needs to be addressed for mitigation of crashes.

  2. Extended Traffic Crash Modelling through Precision and Response Time Using Fuzzy Clustering Algorithms Compared with Multi-layer Perceptron

    Directory of Open Access Journals (Sweden)

    Iman Aghayan

    2012-11-01

    Full Text Available This paper compares two fuzzy clustering algorithms – fuzzy subtractive clustering and fuzzy C-means clustering – to a multi-layer perceptron neural network for their ability to predict the severity of crash injuries and to estimate the response time on the traffic crash data. Four clustering algorithms – hierarchical, K-means, subtractive clustering, and fuzzy C-means clustering – were used to obtain the optimum number of clusters based on the mean silhouette coefficient and R-value before applying the fuzzy clustering algorithms. The best-fit algorithms were selected according to two criteria: precision (root mean square, R-value, mean absolute errors, and sum of square error and response time (t. The highest R-value was obtained for the multi-layer perceptron (0.89, demonstrating that the multi-layer perceptron had a high precision in traffic crash prediction among the prediction models, and that it was stable even in the presence of outliers and overlapping data. Meanwhile, in comparison with other prediction models, fuzzy subtractive clustering provided the lowest value for response time (0.284 second, 9.28 times faster than the time of multi-layer perceptron, meaning that it could lead to developing an on-line system for processing data from detectors and/or a real-time traffic database. The model can be extended through improvements based on additional data through induction procedure.

  3. INVESTIGATION OF ROADWAY GEOMETRIC AND TRAFFIC FLOW FACTORS FOR VEHICLE CRASHES USING SPATIOTEMPORAL INTERACTION

    Directory of Open Access Journals (Sweden)

    G. Gill

    2017-09-01

    Full Text Available Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.

  4. Investigation of Roadway Geometric and Traffic Flow Factors for Vehicle Crashes Using Spatiotemporal Interaction

    Science.gov (United States)

    Gill, G.; Sakrani, T.; Cheng, W.; Zhou, J.

    2017-09-01

    Traffic safety is a major concern in the transportation industry due to immense monetary and emotional burden caused by crashes of various severity levels, especially the injury and fatality ones. To reduce such crashes on all public roads, the safety management processes are commonly implemented which include network screening, problem diagnosis, countermeasure identification, and project prioritization. The selection of countermeasures for potential mitigation of crashes is governed by the influential factors which impact roadway crashes. Crash prediction model is the tool widely adopted by safety practitioners or researchers to link various influential factors to crash occurrences. Many different approaches have been used in the past studies to develop better fitting models which also exhibit prediction accuracy. In this study, a crash prediction model is developed to investigate the vehicular crashes occurring at roadway segments. The spatial and temporal nature of crash data is exploited to form a spatiotemporal model which accounts for the different types of heterogeneities among crash data and geometric or traffic flow variables. This study utilizes the Poisson lognormal model with random effects, which can accommodate the yearly variations in explanatory variables and the spatial correlations among segments. The dependency of different factors linked with roadway geometric, traffic flow, and road surface type on vehicular crashes occurring at segments was established as the width of lanes, posted speed limit, nature of pavement, and AADT were found to be correlated with vehicle crashes.

  5. Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.

    Science.gov (United States)

    Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique

    2015-05-01

    The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.

  6. A multinomial-logit ordered-probit model for jointly analyzing crash avoidance maneuvers and crash severity

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    ' propensity to engage in various corrective maneuvers in the case of the critical event of vehicle travelling. Five lateral and speed control maneuvers are considered: “braking”, “steering”, “braking & steering”, and “other maneuvers”, in addition to a “no action” option. The analyzed data are retrieved from...... the United States National Automotive Sampling System General Estimates System (GES) crash database for the years 2005-2009. Results show (i) the correlation between crash avoidance maneuvers and crash severity, and (ii) the link between drivers' attributes, risky driving behavior, road characteristics...

  7. A cross-comparison of different techniques for modeling macro-level cyclist crashes.

    Science.gov (United States)

    Guo, Yanyong; Osama, Ahmed; Sayed, Tarek

    2018-04-01

    Despite the recognized benefits of cycling as a sustainable mode of transportation, cyclists are considered vulnerable road users and there are concerns about their safety. Therefore, it is essential to investigate the factors affecting cyclist safety. The goal of this study is to evaluate and compare different approaches of modeling macro-level cyclist safety as well as investigating factors that contribute to cyclist crashes using a comprehensive list of covariates. Data from 134 traffic analysis zones (TAZs) in the City of Vancouver were used to develop macro-level crash models (CM) incorporating variables related to actual traffic exposure, socio-economics, land use, built environment, and bike network. Four types of CMs were developed under a full Bayesian framework: Poisson lognormal model (PLN), random intercepts PLN model (RIPLN), random parameters PLN model (RPPLN), and spatial PLN model (SPLN). The SPLN model had the best goodness of fit, and the results highlighted the significant effects of spatial correlation. The models showed that the cyclist crashes were positively associated with bike and vehicle exposure measures, households, commercial area density, and signal density. On the other hand, negative associations were found between cyclist crashes and some bike network indicators such as average edge length, average zonal slope, and off-street bike links. Copyright © 2018 Elsevier Ltd. All rights reserved.

  8. A probabilistic quantitative risk assessment model for the long-term work zone crashes.

    Science.gov (United States)

    Meng, Qiang; Weng, Jinxian; Qu, Xiaobo

    2010-11-01

    Work zones especially long-term work zones increase traffic conflicts and cause safety problems. Proper casualty risk assessment for a work zone is of importance for both traffic safety engineers and travelers. This paper develops a novel probabilistic quantitative risk assessment (QRA) model to evaluate the casualty risk combining frequency and consequence of all accident scenarios triggered by long-term work zone crashes. The casualty risk is measured by the individual risk and societal risk. The individual risk can be interpreted as the frequency of a driver/passenger being killed or injured, and the societal risk describes the relation between frequency and the number of casualties. The proposed probabilistic QRA model consists of the estimation of work zone crash frequency, an event tree and consequence estimation models. There are seven intermediate events--age (A), crash unit (CU), vehicle type (VT), alcohol (AL), light condition (LC), crash type (CT) and severity (S)--in the event tree. Since the estimated value of probability for some intermediate event may have large uncertainty, the uncertainty can thus be characterized by a random variable. The consequence estimation model takes into account the combination effects of speed and emergency medical service response time (ERT) on the consequence of work zone crash. Finally, a numerical example based on the Southeast Michigan work zone crash data is carried out. The numerical results show that there will be a 62% decrease of individual fatality risk and 44% reduction of individual injury risk if the mean travel speed is slowed down by 20%. In addition, there will be a 5% reduction of individual fatality risk and 0.05% reduction of individual injury risk if ERT is reduced by 20%. In other words, slowing down speed is more effective than reducing ERT in the casualty risk mitigation. 2010 Elsevier Ltd. All rights reserved.

  9. Macro-level vulnerable road users crash analysis: A Bayesian joint modeling approach of frequency and proportion.

    Science.gov (United States)

    Cai, Qing; Abdel-Aty, Mohamed; Lee, Jaeyoung

    2017-10-01

    This study aims at contributing to the literature on pedestrian and bicyclist safety by building on the conventional count regression models to explore exogenous factors affecting pedestrian and bicyclist crashes at the macroscopic level. In the traditional count models, effects of exogenous factors on non-motorist crashes were investigated directly. However, the vulnerable road users' crashes are collisions between vehicles and non-motorists. Thus, the exogenous factors can affect the non-motorist crashes through the non-motorists and vehicle drivers. To accommodate for the potentially different impact of exogenous factors we convert the non-motorist crash counts as the product of total crash counts and proportion of non-motorist crashes and formulate a joint model of the negative binomial (NB) model and the logit model to deal with the two parts, respectively. The formulated joint model is estimated using non-motorist crash data based on the Traffic Analysis Districts (TADs) in Florida. Meanwhile, the traditional NB model is also estimated and compared with the joint model. The result indicates that the joint model provides better data fit and can identify more significant variables. Subsequently, a novel joint screening method is suggested based on the proposed model to identify hot zones for non-motorist crashes. The hot zones of non-motorist crashes are identified and divided into three types: hot zones with more dangerous driving environment only, hot zones with more hazardous walking and cycling conditions only, and hot zones with both. It is expected that the joint model and screening method can help decision makers, transportation officials, and community planners to make more efficient treatments to proactively improve pedestrian and bicyclist safety. Published by Elsevier Ltd.

  10. Analysis of crashes using FE vehicle models. Relations between vehicle types and crash characteristics; Yugen yoso model wo mochiita sharyo no shototsu kaiseki. Sharyo type to shototsu tokusei

    Energy Technology Data Exchange (ETDEWEB)

    Takatori, O. [Japan Automobile Research Institute Inc., Tsukuba (Japan)

    2000-01-01

    The objective of this study is to analyze the crash characteristics of vehicles under the condition of real-world accidents. This paper pays attention to the differences in the crash characteristics of a vehicle colliding with a vehicle which is a different type. Vehicles on the market can be divided broadly into two vehicle structures, monocoque structure and frame structure. Monocoque structure is mainly used for passenger vehicles and frame structure is for recreational vehicles (RV). In recent years, RV has been a large seller on the market. So accidents between passenger vehicles and a RVs occur frequently. The analysis of experimental data and computer simulation, which is predicated on the experimental data, was carried out for this study. In the analysis of experimental data, barrier force data from the New Car Assessment Program (NCAP) were analyzed. The FE passenger vehicle model which is based on systematic validation tests was used for the computer simulation of car-to-car collisions. (author)

  11. Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system.

    Science.gov (United States)

    Scanlon, John M; Sherony, Rini; Gabler, Hampton C

    2016-09-01

    Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent. Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities. A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed

  12. Crash probability estimation via quantifying driver hazard perception.

    Science.gov (United States)

    Li, Yang; Zheng, Yang; Wang, Jianqiang; Kodaka, Kenji; Li, Keqiang

    2018-07-01

    Crash probability estimation is an important method to predict the potential reduction of crash probability contributed by forward collision avoidance technologies (FCATs). In this study, we propose a practical approach to estimate crash probability, which combines a field operational test and numerical simulations of a typical rear-end crash model. To consider driver hazard perception characteristics, we define a novel hazard perception measure, called as driver risk response time, by considering both time-to-collision (TTC) and driver braking response to impending collision risk in a near-crash scenario. Also, we establish a driving database under mixed Chinese traffic conditions based on a CMBS (Collision Mitigation Braking Systems)-equipped vehicle. Applying the crash probability estimation in this database, we estimate the potential decrease in crash probability owing to use of CMBS. A comparison of the results with CMBS on and off shows a 13.7% reduction of crash probability in a typical rear-end near-crash scenario with a one-second delay of driver's braking response. These results indicate that CMBS is positive in collision prevention, especially in the case of inattentive drivers or ole drivers. The proposed crash probability estimation offers a practical way for evaluating the safety benefits in the design and testing of FCATs. Copyright © 2017 Elsevier Ltd. All rights reserved.

  13. Modeling wrong-way crashes and fatalities on arterials and freeways

    Directory of Open Access Journals (Sweden)

    Raj V. Ponnaluri

    2018-04-01

    Full Text Available Wrong way driving (WWD research and mitigation measures have primarily focused on limited access facilities. This is most likely due to the higher incidence of fatal WWD crashes with dramatic consequences on freeways, media attention, and a call for innovative solutions to address the problem. While public agencies and published literature address WWD incidence on freeway systems, the crash analyses on non-limited access facilities, i.e., arterial corridors, remains untouched. This research extends previous works and attempts to provide many new perspectives on arterial WWD incidence. In particular, one work showed that while WWD fatalities are more likely to occur on freeways, the likelihood of these crashes is higher on arterials. Hence this work with univariate and multivariate analyses of WWD and non-WWD crashes, and fatal and non-fatal WWD incidents. Results show the impressive negative impacts of alcohol use, driver defect, nighttime and weekend incidence, poor street lighting, low traffic volumes, rural geography, and median and shoulder widths. The objective here is to highlight the need for paying greater attention to WWD crashes on arterial corridors as is done with fatal WWD incidents on freeway systems. It suffices to say that while engineering countermeasures should evolve from the traditional signing and pavement markings to connected vehicle technology applications, there is a clear and compelling need to focus on educational campaigns specifically targeting drunken driving, and enforcement initiatives with an objective to mitigate WWD in the most efficient manner possible. Keywords: Wrong-way driving, Modeling, Arterials and freeways, Logistic regression, Likelihood

  14. Realizing stock market crashes: stochastic cusp catastrophe model of returns under time-varying volatility

    Czech Academy of Sciences Publication Activity Database

    Baruník, Jozef; Kukačka, Jiří

    2015-01-01

    Roč. 15, č. 6 (2015), s. 959-973 ISSN 1469-7688 R&D Projects: GA ČR GA402/09/0965; GA ČR GA13-32263S EU Projects: European Commission 612955 - FINMAP Institutional support: RVO:67985556 Keywords : Stochastic cusp catastrophe model * Realized volatility * Bifurcations * Stock market crash Subject RIV: AH - Economics Impact factor: 0.794, year: 2015 http://library.utia.cas.cz/separaty/2014/E/barunik-0434202.pdf

  15. Crash sequence based risk matrix for motorcycle crashes.

    Science.gov (United States)

    Wu, Kun-Feng; Sasidharan, Lekshmi; Thor, Craig P; Chen, Sheng-Yin

    2018-04-05

    Considerable research has been conducted related to motorcycle and other powered-two-wheeler (PTW) crashes; however, it always has been controversial among practitioners concerning with types of crashes should be first targeted and how to prioritize resources for the implementation of mitigating actions. Therefore, there is a need to identify types of motorcycle crashes that constitute the greatest safety risk to riders - most frequent and most severe crashes. This pilot study seeks exhibit the efficacy of a new approach for prioritizing PTW crash causation sequences as they relate to injury severity to better inform the application of mitigating countermeasures. To accomplish this, the present study constructed a crash sequence-based risk matrix to identify most frequent and most severe motorcycle crashes in an attempt to better connect causes and countermeasures of PTW crashes. Although the frequency of each crash sequence can be computed from crash data, a crash severity model is needed to compare the levels of crash severity among different crash sequences, while controlling for other factors that also have effects on crash severity such drivers' age, use of helmet, etc. The construction of risk matrix based on crash sequences involve two tasks: formulation of crash sequence and the estimation of a mixed-effects (ME) model to adjust the levels of severities for each crash sequence to account for other crash contributing factors that would have an effect on the maximum level of crash severity in a crash. Three data elements from the National Automotive Sampling System - General Estimating System (NASS-GES) data were utilized to form a crash sequence: critical event, crash types, and sequence of events. A mixed-effects model was constructed to model the severity levels for each crash sequence while accounting for the effects of those crash contributing factors on crash severity. A total of 8039 crashes involving 8208 motorcycles occurred during 2011 and 2013 were

  16. Single-vehicle crashes along rural mountainous highways in Malaysia: An application of random parameters negative binomial model.

    Science.gov (United States)

    Rusli, Rusdi; Haque, Md Mazharul; King, Mark; Voon, Wong Shaw

    2017-05-01

    Mountainous highways generally associate with complex driving environment because of constrained road geometries, limited cross-section elements, inappropriate roadside features, and adverse weather conditions. As a result, single-vehicle (SV) crashes are overrepresented along mountainous roads, particularly in developing countries, but little attention is known about the roadway geometric, traffic and weather factors contributing to these SV crashes. As such, the main objective of the present study is to investigate SV crashes using detailed data obtained from a rigorous site survey and existing databases. The final dataset included a total of 56 variables representing road geometries including horizontal and vertical alignment, traffic characteristics, real-time weather condition, cross-sectional elements, roadside features, and spatial characteristics. To account for structured heterogeneities resulting from multiple observations within a site and other unobserved heterogeneities, the study applied a random parameters negative binomial model. Results suggest that rainfall during the crash is positively associated with SV crashes, but real-time visibility is negatively associated. The presence of a road shoulder, particularly a bitumen shoulder or wider shoulders, along mountainous highways is associated with less SV crashes. While speeding along downgrade slopes increases the likelihood of SV crashes, proper delineation decreases the likelihood. Findings of this study have significant implications for designing safer highways in mountainous areas, particularly in the context of a developing country. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Time-varying Crash Risk

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae

    We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on re...

  18. Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models

    Directory of Open Access Journals (Sweden)

    Yang beibei Ji

    2014-01-01

    Full Text Available Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

  19. COMPARISON OF SEVERITY AFFECTING FACTORS BETWEEN YOUNG AND OLDER DRIVERS INVOLVED IN SINGLE VEHICLE CRASHES

    Directory of Open Access Journals (Sweden)

    Sunanda DISSANAYAKE, Ph.D., P.E.

    2004-01-01

    Full Text Available Single vehicle crashes contribute to a significant amount of fatalities in the United States. At the same time, fatality crash involvement rates of young and older drivers are well above the average and both groups are identified as critical groups when it comes to highway safety. Therefore, the study described in this paper developed separate models to predict crash severity of single vehicle crashes by young and older drivers. By using the models, factors affecting towards increased crash severity were identified for each group and comparisons were made. Almost all the common identified factors influenced both driver groups in the same manner except in the case of alcohol and drug usage, which indicated an interesting finding in the case of crash severity of older drivers. Speeding and non-usage of a restraint device were the two most important factors affecting towards increased crash severity for both driver groups at all severity levels. Additionally, ejection and existence of curve/grade were determinants of higher young driver crash severity at all levels. For older drivers, having a frontal impact point was a severity determinant at all levels. County of residence and weather condition were not effective in making any changes with respect to crash severity at any level, while some other factors had a minimal affect. Findings of this study are beneficial in investigating the potential ways of reducing crash severity, which could also be influential in reducing the occurrence of crashes as well.

  20. A new fit-for-purpose model testing framework: Decision Crash Tests

    Science.gov (United States)

    Tolson, Bryan; Craig, James

    2016-04-01

    Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building

  1. Multinational Corporations and Stock Price Crash Risk

    Directory of Open Access Journals (Sweden)

    Anthony May

    2016-10-01

    interested in developing models that more accurately predict tail risk in the equity returns of individual firms.

  2. Construction and evaluation of thoracic injury risk curves for a finite element human body model in frontal car crashes.

    Science.gov (United States)

    Mendoza-Vazquez, Manuel; Davidsson, Johan; Brolin, Karin

    2015-12-01

    There is a need to improve the protection to the thorax of occupants in frontal car crashes. Finite element human body models are a more detailed representation of humans than anthropomorphic test devices (ATDs). On the other hand, there is no clear consensus on the injury criteria and the thresholds to use with finite element human body models to predict rib fractures. The objective of this study was to establish a set of injury risk curves to predict rib fractures using a modified Total HUman Model for Safety (THUMS). Injury criteria at the global, structural and material levels were computed with a modified THUMS in matched Post Mortem Human Subjects (PMHSs) tests. Finally, the quality of each injury risk curve was determined. For the included PMHS tests and the modified THUMS, DcTHOR and shear stress were the criteria at the global and material levels that reached an acceptable quality. The injury risk curves at the structural level did not reach an acceptable quality. Copyright © 2015 Elsevier Ltd. All rights reserved.

  3. "Crashing the gates" - selection criteria for television news reporting of traffic crashes.

    Science.gov (United States)

    De Ceunynck, Tim; De Smedt, Julie; Daniels, Stijn; Wouters, Ruud; Baets, Michèle

    2015-07-01

    This study investigates which crash characteristics influence the probability that the crash is reported in the television news. To this purpose, all news items from the period 2006-2012 about traffic crashes from the prime time news of two Belgian television channels are linked to the official injury crash database. Logistic regression models are built for the database of all injury crashes and for the subset of fatal crashes to identify crash characteristics that correlate with a lower or higher probability of being reported in the news. A number of significant biases in terms of crash severity, time, place, types of involved road users and victims' personal characteristics are found in the media reporting of crashes. More severe crashes are reported in the media more easily than less severe crashes. Significant fluctuations in media reporting probability through time are found in terms of the year and month in which the crash took place. Crashes during week days are generally less reported in the news. The geographical area (province) in which the crash takes place also has a significant impact on the probability of being reported in the news. Crashes on motorways are significantly more represented in the news. Regarding the age of the involved victims, a clear trend of higher media reporting rates of crashes involving young victims or young fatalities is observed. Crashes involving female fatalities are also more frequently reported in the news. Furthermore, crashes involving a bus have a significantly higher probability of being reported in the news, while crashes involving a motorcycle have a significantly lower probability. Some models also indicate a lower reporting rate of crashes involving a moped, and a higher reporting rate of crashes involving heavy goods vehicles. These biases in media reporting can create skewed perceptions in the general public about the prevalence of traffic crashes and eventually may influence people's behaviour. Copyright © 2015

  4. Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia.

    Science.gov (United States)

    Tulu, Getu Segni; Washington, Simon; Haque, Md Mazharul; King, Mark J

    2015-05-01

    Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements. Copyright © 2015. Published by Elsevier Ltd.

  5. Predictive modeling of complications.

    Science.gov (United States)

    Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

    2016-09-01

    Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

  6. A mathematical model for crashing projects by considering time, cost, quality and risk

    Directory of Open Access Journals (Sweden)

    Amin Mahmoudi

    2017-01-01

    Full Text Available Employers are looking for reducing execution time and maintaining the quality of the projects that are the main objective of the projects. In this article, we focus on crashing projects by con-sidering different factors such as cost, time, quality and risk. For the proposed integer linear model, cost of conformance and cost of non-conformance are considered as parts of the costs of quality of deliverables in projects. The cost of conformance consists of the costs of training the project team, inspection and test of deliverables. The cost of non-conformance also includes costs of rework and scrap. Project risk management is one of the important aspects of the pro-jects. The present study also considers the impact of risks, which is highly applicable in projects with a high level of uncertainty. Results are presented using integer programming approach with the aim of minimizing the costs of the project.

  7. Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

    Science.gov (United States)

    Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

    2016-05-18

    Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

  8. Alcohol-related predictors of adolescent driving: gender differences in crashes and offenses.

    Science.gov (United States)

    Shope, J T; Waller, P F; Lang, S W

    1996-11-01

    Demographic and alcohol-related data collected from eight-grade students (age 13 years) were used in logistic regression to predict subsequent first-year driving crashes and offenses (age 17 years). For young men's crashes and offenses, good-fitting models used living situation (both parents or not), parents' attitude about teen drinking (negative or neutral), and the interaction term. Young men who lived with both parents and reported negative parental attitudes regarding teen drinking were less likely to have crashes and offenses. For young women's crashes, a good-fitting model included friends' involvement with alcohol. Young women who reported that their friends were not involved with alcohol were least likely to have crashes. No model predicting young women's offenses emerged.

  9. Modeling the effect of operator and passenger characteristics on the fatality risk of motorcycle crashes.

    Science.gov (United States)

    Tavakoli Kashani, Ali; Rabieyan, Rahim; Besharati, Mohammad Mehdi

    2016-01-01

    In Iran more than 25% of crash fatalities belong to motorcycle operators and passengers in the recent years, from which about 20% are related to passenger fatalities. The aim of this study was to investigate the motorcycle operator and passenger characteristics as well as other contributory factors that may affect the fatality risk of motorcyclists involved in traffic crashes. To this end, motorcycle crash data between 2009 and 2012 was extracted from Iran traffic crash database and a logistic regression analysis was performed to obtain odds ratio estimates for each of the study variables. The fatality risk of motorcyclists has a direct relationship with the number of pillion passengers carried. Results also indicate that the amount of increase in the likelihood of having a fatality in a motorcycles crash is considerably higher when the operator is accompanied by a male passenger of the same age. Furthermore, results showed that if the crash is occurred in the darkness, on curves, in rural areas and on highways, then the crash would be more likely to be fatal. Moreover, the head-on collisions, older operators, unlicensed operators and not using a safety helmet were found to increase the likelihood of a fatality in a motorcycle crash. Preventative measures such as, imposing stricter rules regarding safety helmet usage and confining the number of pillion passengers to one, might be implemented to reduce the fatality risk in motorcycle crashes. In addition, more appropriate infrastructures for penalizing offending motorcyclists could also reduce the frequency of law violations such as not wearing helmet or riding without motorcycle license, which in turn, would result into a reduction in the fatality risk of motorcycle crashes. © 2016 KUMS, All rights reserved.

  10. A Poisson-lognormal conditional-autoregressive model for multivariate spatial analysis of pedestrian crash counts across neighborhoods.

    Science.gov (United States)

    Wang, Yiyi; Kockelman, Kara M

    2013-11-01

    This work examines the relationship between 3-year pedestrian crash counts across Census tracts in Austin, Texas, and various land use, network, and demographic attributes, such as land use balance, residents' access to commercial land uses, sidewalk density, lane-mile densities (by roadway class), and population and employment densities (by type). The model specification allows for region-specific heterogeneity, correlation across response types, and spatial autocorrelation via a Poisson-based multivariate conditional auto-regressive (CAR) framework and is estimated using Bayesian Markov chain Monte Carlo methods. Least-squares regression estimates of walk-miles traveled per zone serve as the exposure measure. Here, the Poisson-lognormal multivariate CAR model outperforms an aspatial Poisson-lognormal multivariate model and a spatial model (without cross-severity correlation), both in terms of fit and inference. Positive spatial autocorrelation emerges across neighborhoods, as expected (due to latent heterogeneity or missing variables that trend in space, resulting in spatial clustering of crash counts). In comparison, the positive aspatial, bivariate cross correlation of severe (fatal or incapacitating) and non-severe crash rates reflects latent covariates that have impacts across severity levels but are more local in nature (such as lighting conditions and local sight obstructions), along with spatially lagged cross correlation. Results also suggest greater mixing of residences and commercial land uses is associated with higher pedestrian crash risk across different severity levels, ceteris paribus, presumably since such access produces more potential conflicts between pedestrian and vehicle movements. Interestingly, network densities show variable effects, and sidewalk provision is associated with lower severe-crash rates. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. Improved process for calculating the probability of being hit by crashing aircraft by the Balfanz-model

    International Nuclear Information System (INIS)

    Hennings, W.

    1988-01-01

    For calculating the probability of being hit by crashing military aircraft on different buildings, a model was introduced, which has already been used in the conventional fields. In the context of converting the research reactor BER II, this model was also used in the nuclear field. The report introduces this model and shows the application to a vertical cylinder as an example. Compared to the previous model, an exact and also simpler solution of the model attempt for determining the shade surface for different shapes of buildings is derived. The problems of the distribution of crashes given by the previous model is treated via the vertical angle and an attempt to solve these problems is given. (orig./HP) [de

  12. Pedestrian Crashes

    Data.gov (United States)

    Town of Chapel Hill, North Carolina — This data set maps the locations of crashes involving pedestrians in the Chapel Hill Region of North Carolina.The data comes from police-reported bicycle-motor...

  13. Bicycle Crashes

    Data.gov (United States)

    Town of Chapel Hill, North Carolina — This data set maps the locations of crashes involving bicyclists in the Chapel Hill Region of North Carolina.The data comes from police-reported bicycle-motor...

  14. Airplane crash

    International Nuclear Information System (INIS)

    Brunner, P.

    1975-01-01

    In May, 1974, a severe airplane crash occurred near Springfield, llinois; the crew of three and a courier were killed. The plane was carrying a large container of controlled water with a slight amount of 60 Co. A survey of the crash site by Air Force detectives and the radiological assistance team from Wright--Patterson Air Force Base indicated no radioactivity. Experiences of the incident were used to develop guidelines for future emergency preparedness

  15. Archaeological predictive model set.

    Science.gov (United States)

    2015-03-01

    This report is the documentation for Task 7 of the Statewide Archaeological Predictive Model Set. The goal of this project is to : develop a set of statewide predictive models to assist the planning of transportation projects. PennDOT is developing t...

  16. Use of car crashes resulting in fatal and serious injuries to analyze a safe road transport system model and to identify system weaknesses.

    Science.gov (United States)

    Stigson, Helena; Hill, Julian

    2009-10-01

    The objective of this study was to evaluate a model for a safe road transport system, based on some safety performance indicators regarding the road user, the vehicle, and the road, by using crashes with fatally and seriously injured car occupants. The study also aimed to evaluate whether the model could be used to identify system weaknesses and components (road user, vehicles, and road) where improvements would yield the highest potential for further reductions in serious injuries. Real-life car crashes with serious injury outcomes (Maximum Abbreviated Injury Scale 2+) were classified according to the vehicle's safety rating by Euro NCAP (European New Car Assessment Programme) and whether the vehicle was fitted with ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol/drugs. Each crash was compared and classified according to the model criteria. Crashes where the safety criteria were not met in more than one of the 3 components were reclassified to identify whether all the components were correlated to the injury outcome. In-depth crash injury data collected by the UK On The Spot (OTS) accident investigation project was used in this study. All crashes in the OTS database occurring between 2000 and 2005 with a car occupant with injury rated MAIS2+ were included, for a total of 101 crashes with 120 occupants. It was possible to classify 90 percent of the crashes according to the model. Eighty-six percent of the occupants were injured when more than one of the 3 components were noncompliant with the safety criteria. These cases were reclassified to identify whether all of the components were correlated to the injury outcome. In 39 of the total 108 cases, at least two components were still seen to interact. The remaining cases were only related to one of the safety criteria

  17. Development and validation of a modified Hybrid-III six-year-old dummy model for simulating submarining in motor-vehicle crashes.

    Science.gov (United States)

    Hu, Jingwen; Klinich, Kathleen D; Reed, Matthew P; Kokkolaras, Michael; Rupp, Jonathan D

    2012-06-01

    In motor-vehicle crashes, young school-aged children restrained by vehicle seat belt systems often suffer from abdominal injuries due to submarining. However, the current anthropomorphic test device, so-called "crash dummy", is not adequate for proper simulation of submarining. In this study, a modified Hybrid-III six-year-old dummy model capable of simulating and predicting submarining was developed using MADYMO (TNO Automotive Safety Solutions). The model incorporated improved pelvis and abdomen geometry and properties previously tested in a modified physical dummy. The model was calibrated and validated against four sled tests under two test conditions with and without submarining using a multi-objective optimization method. A sensitivity analysis using this validated child dummy model showed that dummy knee excursion, torso rotation angle, and the difference between head and knee excursions were good predictors for submarining status. It was also shown that restraint system design variables, such as lap belt angle, D-ring height, and seat coefficient of friction (COF), may have opposite effects on head and abdomen injury risks; therefore child dummies and dummy models capable of simulating submarining are crucial for future restraint system design optimization for young school-aged children. Copyright © 2011 IPEM. Published by Elsevier Ltd. All rights reserved.

  18. Comparison of Test and Finite Element Analysis for Two Full-Scale Helicopter Crash Tests

    Science.gov (United States)

    Annett, Martin S.; Horta,Lucas G.

    2011-01-01

    Finite element analyses have been performed for two full-scale crash tests of an MD-500 helicopter. The first crash test was conducted to evaluate the performance of a composite deployable energy absorber under combined flight loads. In the second crash test, the energy absorber was removed to establish the baseline loads. The use of an energy absorbing device reduced the impact acceleration levels by a factor of three. Accelerations and kinematic data collected from the crash tests were compared to analytical results. Details of the full-scale crash tests and development of the system-integrated finite element model are briefly described along with direct comparisons of acceleration magnitudes and durations for the first full-scale crash test. Because load levels were significantly different between tests, models developed for the purposes of predicting the overall system response with external energy absorbers were not adequate under more severe conditions seen in the second crash test. Relative error comparisons were inadequate to guide model calibration. A newly developed model calibration approach that includes uncertainty estimation, parameter sensitivity, impact shape orthogonality, and numerical optimization was used for the second full-scale crash test. The calibrated parameter set reduced 2-norm prediction error by 51% but did not improve impact shape orthogonality.

  19. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  20. U08 : finite element analysis crash model of tractor-trailers (Phase B).

    Science.gov (United States)

    2009-08-01

    Improved understanding of truck-infrastructure crashes will enable the highway community to improve barrier design, to further reduce : the likelihood of vehicle-infrastructure fatalities and injuries, and to reduce highway congestion resulting from ...

  1. Demographic factors and traffic crashes. Part 1, descriptive statistics and models

    Science.gov (United States)

    1998-08-01

    This research analyzes the Department of Highway Safety and Motor Vehicle's (DHSMV) 1993 to 1995 crash data. There are four demographic variables investigated throughout the research, which are age, gender, race, and residency. To show general trends...

  2. Identification of a putative man-made object from an underwater crash site using CAD model superimposition.

    Science.gov (United States)

    Vincelli, Jay; Calakli, Fatih; Stone, Michael; Forrester, Graham; Mellon, Timothy; Jarrell, John

    2018-04-01

    In order to identify an object in video, a comparison with an exemplar object is typically needed. In this paper, we discuss the methodology used to identify an object detected in underwater video that was recorded during an investigation into Amelia Earhart's purported crash site. A computer aided design (CAD) model of the suspected aircraft component was created based on measurements made from orthogonally rectified images of a reference aircraft, and validated against historical photographs of the subject aircraft prior to the crash. The CAD model was then superimposed on the underwater video, and specific features on the object were geometrically compared between the CAD model and the video. This geometrical comparison was used to assess the goodness of fit between the purported object and the object identified in the underwater video. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Commercial truck crash injury severity analysis using gradient boosting data mining model.

    Science.gov (United States)

    Zheng, Zijian; Lu, Pan; Lantz, Brenda

    2018-06-01

    Truck crashes contribute to a large number of injuries and fatalities. This study seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 North Dakota and Colorado crash data provided by the Federal Motor Carrier Safety Administration. To fulfill a gap of previous studies, broad considerations of company and driver characteristics, such as company size and driver's license class, along with vehicle types and crash characteristics are researched. Gradient boosting, a data mining technique, is applied to comprehensively analyze the relationship between crash severities and a set of heterogeneous risk factors. Twenty five variables were tested and 22 of them are identified as significant variables contributing to injury severities, however, top 11 variables account for more than 80% of injury forecasting. The relative variable importance analysis is conducted and furthermore marginal effects of all contributing factors are also illustrated in this research. Several factors such as trucking company attributes (e.g., company size), safety inspection values, trucking company commerce status (e.g., interstate or intrastate), time of day, driver's age, first harmful events, and registration condition are found to be significantly associated with crash injury severity. Even though most of the identified contributing factors are significant for all four levels of crash severity, their relative importance and marginal effect are all different. For the first time, trucking company and driver characteristics are proved to have significant impact on truck crash injury severity. Some of the results in this study reinforce previous studies' conclusions. Findings in this study can be helpful for transportation agencies to reduce injury severity, and develop efficient strategies to improve safety. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

  4. Inverse and Predictive Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Syracuse, Ellen Marie [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2017-09-27

    The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an even greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.

  5. Bond graph modeling and simulation of impact dynamics of an automotive crash

    International Nuclear Information System (INIS)

    Khurshid, A.; Malik, M.A.

    2007-01-01

    With increase in the speeds of automotives, safety has become more and more important aspect of designers to care for. Thus, it is necessary to design the automobile body structure keeping in view all the safety requirements. As a result of the above-mentioned facts, in the recent years, the designers in making automotives more safe, more collision resistant and crash worthy have focused increased attention on designing automotives, which provides greater protection for the drivers and the passengers in case of an accident. Before a new model is launched into the market, a complete collision analysis is carried out to check the damage reduction capabilities and impact protection of automotives in case of an accident. Research in the field of automotive collision and impact analysis is a continuing activity and dedicated groups of engineers are devoting their full time and efforts for this. In this research work, the main attention is focused to provide a detailed knowledge about automotive collision analysis. The objective of this research paper is to develop an understanding of the automotive collision response. For this, we have done a simulation experiment in which, on a railroad, a train car is separated from a train and is moving towards two stationary train cars. By using a bond graph model of the system its state-space equations are found. Then by using software, the simulation is carried out. The bond graph method is a graphical presentation of the power flow using bonds. (author)

  6. Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

    Directory of Open Access Journals (Sweden)

    Yanyong Guo

    2017-01-01

    Full Text Available The primary objective of this study is to evaluate factors affecting e-bike involved crash and license plate use in China. E-bike crashes data were collected from police database and completed through a telephone interview. Noncrash samples were collected by a questionnaire survey. A bivariate probit (BP model was developed to simultaneously examine the significant factors associated with e-bike involved crash and e-bike license plate and to account for the correlations between them. Marginal effects for contributory factors were calculated to quantify their impacts on the outcomes. The results show that several contributory factors, including gender, age, education level, driver license, car in household, experiences in using e-bike, law compliance, and aggressive driving behaviors, are found to have significant impacts on both e-bike involved crash and license plate use. Moreover, type of e-bike, frequency of using e-bike, impulse behavior, degree of riding experience, and risk perception scale are found to be associated with e-bike involved crash. It is also found that e-bike involved crash and e-bike license plate use are strongly correlated and are negative in direction. The result enhanced our comprehension of the factors related to e-bike involved crash and e-bike license plate use.

  7. Crash Models for Advanced Automotive Batteries: A Review of the Current State of the Art

    Energy Technology Data Exchange (ETDEWEB)

    Turner, John A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Allu, Srikanth [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Gorti, Sarma B. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kalnaus, Sergiy [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kumar, Abhishek [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Lebrun-Grandie, Damien T. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pannala, Sreekanth [Saudi Arabia Basic Industries Corporation (SABIC), Houston, TX (United States); Simunovic, Srdjan [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Slattery, Stuart R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Hsin [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2015-02-01

    Safety is a critical aspect of lithium-ion (Li-ion) battery design. Impact/crash conditions can trigger a complex interplay of mechanical contact, heat generation and electrical discharge, which can result in adverse thermal events. The cause of these thermal events has been linked to internal contact between the opposite electrodes, i.e. internal short circuit. The severity of the outcome is influenced by the configuration of the internal short circuit and the battery state. Different loading conditions and battery states may lead to micro (soft) shorts where material burnout due to generated heat eliminates contact between the electrodes, or persistent (hard) shorts which can lead to more significant thermal events and potentially damage the entire battery system and beyond. Experimental characterization of individual battery components for the onset of internal shorts is limited, since it is impractical to canvas all possible variations in battery state of charge, operating conditions, and impact loading in a timely manner. This report provides a survey of modeling and simulation approaches and documents a project initiated and funded by DOT/NHTSA to improve modeling and simulation capabilities in order to design tests that provide leading indicators of failure in batteries. In this project, ORNL has demonstrated a computational infrastructure to conduct impact simulations of Li-ion batteries using models that resolve internal structures and electro-thermo-chemical and mechanical conditions. Initial comparisons to abuse experiments on cells and cell strings conducted at ORNL and Naval Surface Warfare Center (NSWC) at Carderock MD for parameter estimation and model validation have been performed. This research has provided insight into the mechanisms of deformation in batteries (both at cell and electrode level) and their relationship to the safety of batteries.

  8. Use of fatal real-life crashes to analyze a safe road transport system model, including the road user, the vehicle, and the road.

    Science.gov (United States)

    Stigson, Helena; Krafft, Maria; Tingvall, Claes

    2008-10-01

    To evaluate if the Swedish Road Administration (SRA) model for a safe road transport system, which includes the interaction between the road user, the vehicle, and the road, could be used to classify fatal car crashes according to some safety indicators. Also, to present a development of the model to better identify system weakness. Real-life crashes with a fatal outcome were classified according to the vehicle's safety rating by Euro NCAP (European Road Assessment Programme) and fitment of ESC (Electronic Stability Control). For each crash, the road was also classified according to EuroRAP (European Road Assessment Programme) criteria, and human behavior in terms of speeding, seat belt use, and driving under the influence of alcohol. Each crash was compared with the model criteria, to identify components that might have contributed to fatal outcome. All fatal crashes where a car occupant was killed that occurred in Sweden during 2004 were included: in all, 215 crashes with 248 fatalities. The data were collected from the in-depth fatal crash data of the Swedish Road Administration (SRA). It was possible to classify 93% of the fatal car crashes according to the SRA model. A number of shortcomings in the criteria were identified since the model did not address rear-end or animal collisions or collisions with stationary/parked vehicles or trailers (18 out of 248 cases). Using the further developed model, it was possible to identify that most of the crashes occurred when two or all three components interacted (in 85 of the total 230 cases). Noncompliance with safety criteria for the road user, the vehicle, and the road led to fatal outcome in 43, 27, and 75 cases, respectively. The SRA model was found to be useful for classifying fatal crashes but needs to be further developed to identify how the components interact and thereby identify weaknesses in the road traffic system. This developed model might be a tool to systematically identify which of the components are

  9. Influence of horizontally curved roadway section characteristics on motorcycle-to-barrier crash frequency.

    Science.gov (United States)

    Gabauer, Douglas J; Li, Xiaolong

    2015-04-01

    The purpose of this study was to investigate motorcycle-to-barrier crash frequency on horizontally curved roadway sections in Washington State using police-reported crash data linked with roadway data and augmented with barrier presence information. Data included 4915 horizontal curved roadway sections with 252 of these sections experiencing 329 motorcycle-to-barrier crashes between 2002 and 2011. Negative binomial regression was used to predict motorcycle-to-barrier crash frequency using horizontal curvature and other roadway characteristics. Based on the model results, the strongest predictor of crash frequency was found to be curve radius. This supports a motorcycle-to-barrier crash countermeasure placement criterion based, at the very least, on horizontal curve radius. With respect to the existing horizontal curve criterion of 820 feet or less, curves meeting this criterion were found to increase motorcycle-to-barrier crash frequency rate by a factor of 10 compared to curves not meeting this criterion. Other statistically significant predictors were curve length, traffic volume and the location of adjacent curves. Assuming curves of identical radius, the model results suggest that longer curves, those with higher traffic volume, and those that have no adjacent curved sections within 300 feet of either curve end would likely be better candidates for a motorcycle-to-barrier crash countermeasure. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Quantifying reflexivity in financial markets: Toward a prediction of flash crashes

    Science.gov (United States)

    Filimonov, Vladimir; Sornette, Didier

    2012-05-01

    We introduce a measure of activity of financial markets that provides a direct access to their level of endogeneity. This measure quantifies how much of price changes is due to endogenous feedback processes, as opposed to exogenous news. For this, we calibrate the self-excited conditional Poisson Hawkes model, which combines in a natural and parsimonious way exogenous influences with self-excited dynamics, to the E-mini S&P 500 futures contracts traded in the Chicago Mercantile Exchange from 1998 to 2010. We find that the level of endogeneity has increased significantly from 1998 to 2010, with only 70% in 1998 to less than 30% since 2007 of the price changes resulting from some revealed exogenous information. Analogous to nuclear plant safety measures concerned with avoiding “criticality,” our measure provides a direct quantification of the distance of the financial market from a critical state defined precisely as the limit of diverging trading activity in the absence of any external driving.

  11. Application of a random effects negative binomial model to examine tram-involved crash frequency on route sections in Melbourne, Australia.

    Science.gov (United States)

    Naznin, Farhana; Currie, Graham; Logan, David; Sarvi, Majid

    2016-07-01

    Safety is a key concern in the design, operation and development of light rail systems including trams or streetcars as they impose crash risks on road users in terms of crash frequency and severity. The aim of this study is to identify key traffic, transit and route factors that influence tram-involved crash frequencies along tram route sections in Melbourne. A random effects negative binomial (RENB) regression model was developed to analyze crash frequency data obtained from Yarra Trams, the tram operator in Melbourne. The RENB modelling approach can account for spatial and temporal variations within observation groups in panel count data structures by assuming that group specific effects are randomly distributed across locations. The results identify many significant factors effecting tram-involved crash frequency including tram service frequency (2.71), tram stop spacing (-0.42), tram route section length (0.31), tram signal priority (-0.25), general traffic volume (0.18), tram lane priority (-0.15) and ratio of platform tram stops (-0.09). Findings provide useful insights on route section level tram-involved crashes in an urban tram or streetcar operating environment. The method described represents a useful planning tool for transit agencies hoping to improve safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Vehicular crash data used to rank intersections by injury crash frequency and severity

    OpenAIRE

    Liu, Yi; Li, Zongzhi; Liu, Jingxian; Patel, Harshingar

    2016-01-01

    This article contains data on research conducted in “A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability” (Liu et al., 2016) [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, modera...

  13. Effect of Accounting for Crash Severity on the Relationship between Mass Reduction and Crash Frequency and Risk per Crash

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Tom P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Building Technology and Urban Systems Division. Energy Technologies Area

    2016-05-20

    Previous analyses have indicated that mass reduction is associated with an increase in crash frequency (crashes per VMT), but a decrease in fatality or casualty risk once a crash has occurred, across all types of light-duty vehicles. These results are counter-intuitive: one would expect that lighter, and perhaps smaller, vehicles have better handling and shorter braking distances, and thus should be able to avoid crashes that heavier vehicles cannot. And one would expect that heavier vehicles would have lower risk once a crash has occurred than lighter vehicles. However, these trends occur under several alternative regression model specifications. This report tests whether these results continue to hold after accounting for crash severity, by excluding crashes that result in relatively minor damage to the vehicle(s) involved in the crash. Excluding non-severe crashes from the initial LBNL Phase 2 and simultaneous two-stage regression models for the most part has little effect on the unexpected relationships observed in the baseline regression models. This finding suggests that other subtle differences in vehicles and/or their drivers, or perhaps biases in the data reported in state crash databases, are causing the unexpected results from the regression models.

  14. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

  15. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  16. Associating crash avoidance maneuvers with driver attributes and accident characteristics: a mixed logit model approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    from the key role of proactive and state-aware road users within the concept of sustainable safety systems, as well as from the key role of effective corrective maneuvers in the success of automated in-vehicle warning and driver assistance systems. Methods: The analysis is conducted by means of a mixed...... about the risks of driving under fatigue and distraction being comparable to the risks of driving under the influence of alcohol and drugs. Moreover, the results suggest the need to educate drivers about hazard perception, designing a forgiving infrastructure within a sustainable safety systems......Objective: The current study focuses on the propensity of drivers to engage in crash avoidance maneuvers in relation to driver attributes, critical events, crash characteristics, vehicles involved, road characteristics, and environmental conditions. The importance of avoidance maneuvers derives...

  17. Measuring a conceptual model of the relationship between compulsive cell phone use, in-vehicle cell phone use, and motor vehicle crash.

    Science.gov (United States)

    O'Connor, Stephen S; Shain, Lindsey M; Whitehill, Jennifer M; Ebel, Beth E

    2017-02-01

    Previous research suggests that anticipation of incoming phone calls or messages and impulsivity are significantly associated with motor vehicle crash. We took a more explanative approach to investigate a conceptual model regarding the direct and indirect effect of compulsive cell phone use and impulsive personality traits on crash risk. We recruited a sample of 307 undergraduate college students to complete an online survey that included measures of cell phone use, impulsivity, and history of motor vehicle crash. Using a structural equation model, we examined the direct and indirect relationships between factors of the Cell Phone Overuse Scale-II (CPOS-II), impulsivity, in-vehicle phone use, and severity and frequency of previous motor vehicle crash. Self-reported miles driven per week and year in college were included as covariates in the model. Our findings suggest that anticipation of incoming communication has a direct association with greater in-vehicle phone use, but was not directly or indirectly associated with increasing risk of previous motor vehicle crash. Of the three latent factors comprising the CPOS-II, only anticipation was significantly associated with elevated cell phone use while driving. Greater impulsivity and use of in-vehicle cell phone use while driving were directly and significantly associated with greater risk of motor vehicle crash. Anticipation of incoming cellular contacts (calls or texts) is associated with greater in-vehicle phone use, while greater in-vehicle cell phone use and impulsive traits are associated with elevated risk of motor vehicle crashes. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Predictive Surface Complexation Modeling

    Energy Technology Data Exchange (ETDEWEB)

    Sverjensky, Dimitri A. [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Earth and Planetary Sciences

    2016-11-29

    Surface complexation plays an important role in the equilibria and kinetics of processes controlling the compositions of soilwaters and groundwaters, the fate of contaminants in groundwaters, and the subsurface storage of CO2 and nuclear waste. Over the last several decades, many dozens of individual experimental studies have addressed aspects of surface complexation that have contributed to an increased understanding of its role in natural systems. However, there has been no previous attempt to develop a model of surface complexation that can be used to link all the experimental studies in order to place them on a predictive basis. Overall, my research has successfully integrated the results of the work of many experimentalists published over several decades. For the first time in studies of the geochemistry of the mineral-water interface, a practical predictive capability for modeling has become available. The predictive correlations developed in my research now enable extrapolations of experimental studies to provide estimates of surface chemistry for systems not yet studied experimentally and for natural and anthropogenically perturbed systems.

  19. Comparison of moped, scooter and motorcycle crash risk and crash severity.

    Science.gov (United States)

    Blackman, Ross A; Haworth, Narelle L

    2013-08-01

    The increased popularity of mopeds and motor scooters in Australia and elsewhere in the last decade has contributed substantially to the greater use of powered two-wheelers (PTWs) as a whole. As the exposure of mopeds and scooters has increased, so too has the number of reported crashes involving those PTW types, but there is currently little research comparing the safety of mopeds and, particularly, larger scooters with motorcycles. This study compared the crash risk and crash severity of motorcycles, mopeds and larger scooters in Queensland, Australia. Comprehensive data cleansing was undertaken to separate motorcycles, mopeds and larger scooters in police-reported crash data covering the five years to 30 June 2008. The crash rates of motorcycles (including larger scooters) and mopeds in terms of registered vehicles were similar over this period, although the moped crash rate showed a stronger downward trend. However, the crash rates in terms of distance travelled were nearly four times higher for mopeds than for motorcycles (including larger scooters). More comprehensive distance travelled data is needed to confirm these findings. The overall severity of moped and scooter crashes was significantly lower than motorcycle crashes but an ordered probit regression model showed that crash severity outcomes related to differences in crash characteristics and circumstances, rather than differences between PTW types per se. Greater motorcycle crash severity was associated with higher (>80km/h) speed zones, horizontal curves, weekend, single vehicle and nighttime crashes. Moped crashes were more severe at night and in speed zones of 90km/h or more. Larger scooter crashes were more severe in 70km/h zones (than 60km/h zones) but not in higher speed zones, and less severe on weekends than on weekdays. The findings can be used to inform potential crash and injury countermeasures tailored to users of different PTW types. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. Evaluation of Vehicle-Based Crash Severity Metrics.

    Science.gov (United States)

    Tsoi, Ada H; Gabler, Hampton C

    2015-01-01

    estimate to be a significant predictor in the model (p feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.

  1. Counterfactual simulations applied to SHRP2 crashes: The effect of driver behavior models on safety benefit estimations of intelligent safety systems.

    Science.gov (United States)

    Bärgman, Jonas; Boda, Christian-Nils; Dozza, Marco

    2017-05-01

    As the development and deployment of in-vehicle intelligent safety systems (ISS) for crash avoidance and mitigation have rapidly increased in the last decades, the need to evaluate their prospective safety benefits before introduction has never been higher. Counterfactual simulations using relevant mathematical models (for vehicle dynamics, sensors, the environment, ISS algorithms, and models of driver behavior) have been identified as having high potential. However, although most of these models are relatively mature, models of driver behavior in the critical seconds before a crash are still relatively immature. There are also large conceptual differences between different driver models. The objective of this paper is, firstly, to demonstrate the importance of the choice of driver model when counterfactual simulations are used to evaluate two ISS: Forward collision warning (FCW), and autonomous emergency braking (AEB). Secondly, the paper demonstrates how counterfactual simulations can be used to perform sensitivity analyses on parameter settings, both for driver behavior and ISS algorithms. Finally, the paper evaluates the effect of the choice of glance distribution in the driver behavior model on the safety benefit estimation. The paper uses pre-crash kinematics and driver behavior from 34 rear-end crashes from the SHRP2 naturalistic driving study for the demonstrations. The results for FCW show a large difference in the percent of avoided crashes between conceptually different models of driver behavior, while differences were small for conceptually similar models. As expected, the choice of model of driver behavior did not affect AEB benefit much. Based on our results, researchers and others who aim to evaluate ISS with the driver in the loop through counterfactual simulations should be sure to make deliberate and well-grounded choices of driver models: the choice of model matters. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Differences in passenger car and large truck involved crash frequencies at urban signalized intersections: an exploratory analysis.

    Science.gov (United States)

    Dong, Chunjiao; Clarke, David B; Richards, Stephen H; Huang, Baoshan

    2014-01-01

    The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car-truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Contributory factors to traffic crashes at signalized intersections in Hong Kong.

    Science.gov (United States)

    Wong, S C; Sze, N N; Li, Y C

    2007-11-01

    Efficient geometric design and signal timing not only improve operational performance at signalized intersections by expanding capacity and reducing traffic delays, but also result in an appreciable reduction in traffic conflicts, and thus better road safety. Information on the incidence of crashes, traffic flow, geometric design, road environment, and traffic control at 262 signalized intersections in Hong Kong during 2002 and 2003 are incorporated into a crash prediction model. Poisson regression and negative binomial regression are used to quantify the influence of possible contributory factors on the incidence of killed and severe injury (KSI) crashes and slight injury crashes, respectively, while possible interventions by traffic flow are controlled. The results for the incidence of slight injury crashes reveal that the road environment, degree of curvature, and presence of tram stops are significant factors, and that traffic volume has a diminishing effect on the crash risk. The presence of tram stops, number of pedestrian streams, road environment, proportion of commercial vehicles, average lane width, and degree of curvature increase the risk of KSI crashes, but the effect of traffic volume is negligible.

  4. Confidence scores for prediction models

    DEFF Research Database (Denmark)

    Gerds, Thomas Alexander; van de Wiel, MA

    2011-01-01

    In medical statistics, many alternative strategies are available for building a prediction model based on training data. Prediction models are routinely compared by means of their prediction performance in independent validation data. If only one data set is available for training and validation,...

  5. Peer Review of “LDT Weight Reduction Study with Crash Model, Feasibility and Detailed Cost Analyses – Chevrolet Silverado 1500 Pickup”

    Science.gov (United States)

    The contractor will conduct an independent peer review of FEV’s light-duty truck (LDT) mass safety study, “Light-Duty Vehicle Weight Reduction Study with Crash Model, Feasibility and Detailed Cost Analysis – Silverado 1500”, and its corresponding computer-aided engineering (CAE) ...

  6. A novel approach to modeling and predicting crash frequency at rural intersections by crash type and injury severity level.

    Science.gov (United States)

    2015-04-01

    Safety at intersections is of significant interest to transportation professionals due to the large number of : possible conflicts that occur at those locations. In particular, rural intersections have been recognized as : one of the most hazardous l...

  7. Motor Carrier Crash Data -

    Data.gov (United States)

    Department of Transportation — Contains data on large trucks and buses involved in Federally reportable crashes as per Title 49 U.S.C. Part 390.5 (crashes involving a commercial motor vehicle, and...

  8. PREDICTED PERCENTAGE DISSATISFIED (PPD) MODEL ...

    African Journals Online (AJOL)

    HOD

    their low power requirements, are relatively cheap and are environment friendly. ... PREDICTED PERCENTAGE DISSATISFIED MODEL EVALUATION OF EVAPORATIVE COOLING ... The performance of direct evaporative coolers is a.

  9. Crash test rating and likelihood of major thoracoabdominal injury in motor vehicle crashes: the new car assessment program side-impact crash test, 1998-2010.

    Science.gov (United States)

    Figler, Bradley D; Mack, Christopher D; Kaufman, Robert; Wessells, Hunter; Bulger, Eileen; Smith, Thomas G; Voelzke, Bryan

    2014-03-01

    The National Highway Traffic Safety Administration's New Car Assessment Program (NCAP) implemented side-impact crash testing on all new vehicles since 1998 to assess the likelihood of major thoracoabdominal injuries during a side-impact crash. Higher crash test rating is intended to indicate a safer car, but the real-world applicability of these ratings is unknown. Our objective was to determine the relationship between a vehicle's NCAP side-impact crash test rating and the risk of major thoracoabdominal injury among the vehicle's occupants in real-world side-impact motor vehicle crashes. The National Automotive Sampling System Crashworthiness Data System contains detailed crash and injury data in a sample of major crashes in the United States. For model years 1998 to 2010 and crash years 1999 to 2010, 68,124 occupants were identified in the Crashworthiness Data System database. Because 47% of cases were missing crash severity (ΔV), multiple imputation was used to estimate the missing values. The primary predictor of interest was the occupant vehicle's NCAP side-impact crash test rating, and the outcome of interest was the presence of major (Abbreviated Injury Scale [AIS] score ≥ 3) thoracoabdominal injury. In multivariate analysis, increasing NCAP crash test rating was associated with lower likelihood of major thoracoabdominal injury at high (odds ratio [OR], 0.8; 95% confidence interval [CI], 0.7-0.9; p NCAP side-impact crash test rating is associated with a lower likelihood of major thoracoabdominal trauma. Epidemiologic study, level III.

  10. System crash as dynamics of complex networks.

    Science.gov (United States)

    Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

    2016-10-18

    Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

  11. EMPLOYMENT OF ATMS TRAFFIC CONTROL DEVICE DATA TO ASSIST IN IDENTIFICATION OF CRASH-PRONE INTERSECTIONS

    Directory of Open Access Journals (Sweden)

    Kevin P. HWANG

    2008-01-01

    Full Text Available This paper employs information from the advanced traffic management system (ATMS of Kaohsiung, Taiwan to help differentiate those crash-prone intersections by discriminant analysis. From the 25,604 records of 2005, 1977 crashes that occurred at 119 intersections with traffic exposure data were compiled to calibrate and validate the model. The road attributes of crash records, traffic control devices and movement exposure are the three types of data used as predicting variables. The correct ratios for model calibration and validation range from 78.33% to 67.80%. if traffic movements are removed, the correct ratios become slightly lowered to 76.67% to 66.10%. Research findings reveal that with or without inclusion of exposure data in identifying high crash-prone intersections for an urban environment does not make a significant difference. in addition, layout and traffic control devices could possibly explain about 66.10 ∼ 78.33% of the possibility that an intersection will become a high crash intersection. it suggests that the developed approach could be a countermeasure for budget constraints and difficulties in continuation of exposure data collection, and the information of ATMS could help identify crash-prone urban intersections.

  12. Report 6: Guidance document. Man-made hazards and Accidental Aircraft Crash hazards modelling and implementation in extended PSA

    International Nuclear Information System (INIS)

    Kahia, S.; Brinkman, H.; Bareith, A.; Siklossy, T.; Vinot, T.; Mateescu, T.; Espargilliere, J.; Burgazzi, L.; Ivanov, I.; Bogdanov, D.; Groudev, P.; Ostapchuk, S.; Zhabin, O.; Stojka, T.; Alzbutas, R.; Kumar, M.; Nitoi, M.; Farcasiu, M.; Borysiewicz, M.; Kowal, K.; Potempski, S.

    2016-01-01

    The goal of this report is to provide guidance on practices to model man-made hazards (mainly external fires and explosions) and accidental aircraft crash hazards and implement them in extended Level 1 PSA. This report is a joint deliverable of work package 21 (WP21) and work package 22 (WP22). The general objective of WP21 is to provide guidance on all of the individual hazards selected at the first ASAMPSA-E End Users Workshop (May 2014, Uppsala, Sweden). The objective of WP22 is to provide the solutions for purposes of different parts of man-made hazards Level 1 PSA fulfilment. This guidance is focusing on man-made hazards, namely: external fires and explosions, and accidental aircraft crash hazards. Guidance developed refers to existing guidance whenever possible. The initial part of guidance (WP21 part) reflects current practices to assess the frequencies for each type of hazards or combination of hazards (including correlated hazards) as initiating event for PSAs. The sources and quality of hazard data, the elements of hazard assessment methodologies and relevant examples are discussed. Classification and criteria to properly assess hazard combinations as well as examples and methods for assessment of these combinations are included in this guidance. In appendixes additional material is presented with the examples of practical approaches to aircraft crash and man-made hazard. The following issues are addressed: 1) Hazard assessment methodologies, including issues related to hazard combinations. 2) Modelling equipment of safety related SSC, 3) HRA, 4) Emergency response, 5) Multi-unit issues. Recommendations and also limitations, gaps identified in the existing methodologies and a list of open issues are included. At all stages of this guidance and especially from an industrial end-user perspective, one must keep in mind that the development of man-made hazards probabilistic analysis must be conditioned to the ability to ultimately obtain a representative risk

  13. Bootstrap prediction and Bayesian prediction under misspecified models

    OpenAIRE

    Fushiki, Tadayoshi

    2005-01-01

    We consider a statistical prediction problem under misspecified models. In a sense, Bayesian prediction is an optimal prediction method when an assumed model is true. Bootstrap prediction is obtained by applying Breiman's `bagging' method to a plug-in prediction. Bootstrap prediction can be considered to be an approximation to the Bayesian prediction under the assumption that the model is true. However, in applications, there are frequently deviations from the assumed model. In this paper, bo...

  14. Advances in crash dynamics for aircraft safety

    Science.gov (United States)

    Guida, M.; Marulo, F.; Abrate, S.

    2018-04-01

    This paper studies the ability of the fuselage's lower lobe to absorb the energy during a crash landing, where the introduction of the composite materials can improve the crash survivability thanks to the crushing capability of structural parts to limit the effects of deceleration on the occupants. Providing a protective shell around the occupants and minimizing the risks of injuries during and immediately after the crash in the post-crash regime is a safety requirement. This study consists of: (1) numerical and experimental investigations on small components to verify design concepts using high performance composite materials; (2) analyses of full scale crashes of fuselage lower lobes. This paper outlines an approach for demonstrating the crashworthiness characteristics of the airframe performing a drop test at low velocity impact to validate a numerical model obtained by assembling structural components and materials' properties previously obtained by testing coupons and sub-elements.

  15. MODEL PREDICTIVE CONTROL FUNDAMENTALS

    African Journals Online (AJOL)

    2012-07-02

    Jul 2, 2012 ... signal based on a process model, coping with constraints on inputs and ... paper, we will present an introduction to the theory and application of MPC with Matlab codes ... section 5 presents the simulation results and section 6.

  16. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. A semiparametric negative binomial generalized linear model for modeling over-dispersed count data with a heavy tail: Characteristics and applications to crash data.

    Science.gov (United States)

    Shirazi, Mohammadali; Lord, Dominique; Dhavala, Soma Sekhar; Geedipally, Srinivas Reddy

    2016-06-01

    Crash data can often be characterized by over-dispersion, heavy (long) tail and many observations with the value zero. Over the last few years, a small number of researchers have started developing and applying novel and innovative multi-parameter models to analyze such data. These multi-parameter models have been proposed for overcoming the limitations of the traditional negative binomial (NB) model, which cannot handle this kind of data efficiently. The research documented in this paper continues the work related to multi-parameter models. The objective of this paper is to document the development and application of a flexible NB generalized linear model with randomly distributed mixed effects characterized by the Dirichlet process (NB-DP) to model crash data. The objective of the study was accomplished using two datasets. The new model was compared to the NB and the recently introduced model based on the mixture of the NB and Lindley (NB-L) distributions. Overall, the research study shows that the NB-DP model offers a better performance than the NB model once data are over-dispersed and have a heavy tail. The NB-DP performed better than the NB-L when the dataset has a heavy tail, but a smaller percentage of zeros. However, both models performed similarly when the dataset contained a large amount of zeros. In addition to a greater flexibility, the NB-DP provides a clustering by-product that allows the safety analyst to better understand the characteristics of the data, such as the identification of outliers and sources of dispersion. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Modelling bankruptcy prediction models in Slovak companies

    Directory of Open Access Journals (Sweden)

    Kovacova Maria

    2017-01-01

    Full Text Available An intensive research from academics and practitioners has been provided regarding models for bankruptcy prediction and credit risk management. In spite of numerous researches focusing on forecasting bankruptcy using traditional statistics techniques (e.g. discriminant analysis and logistic regression and early artificial intelligence models (e.g. artificial neural networks, there is a trend for transition to machine learning models (support vector machines, bagging, boosting, and random forest to predict bankruptcy one year prior to the event. Comparing the performance of this with unconventional approach with results obtained by discriminant analysis, logistic regression, and neural networks application, it has been found that bagging, boosting, and random forest models outperform the others techniques, and that all prediction accuracy in the testing sample improves when the additional variables are included. On the other side the prediction accuracy of old and well known bankruptcy prediction models is quiet high. Therefore, we aim to analyse these in some way old models on the dataset of Slovak companies to validate their prediction ability in specific conditions. Furthermore, these models will be modelled according to new trends by calculating the influence of elimination of selected variables on the overall prediction ability of these models.

  19. Predictive models of moth development

    Science.gov (United States)

    Degree-day models link ambient temperature to insect life-stages, making such models valuable tools in integrated pest management. These models increase management efficacy by predicting pest phenology. In Wisconsin, the top insect pest of cranberry production is the cranberry fruitworm, Acrobasis v...

  20. Predictive Models and Computational Embryology

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  1. Predictive Modeling in Race Walking

    Directory of Open Access Journals (Sweden)

    Krzysztof Wiktorowicz

    2015-01-01

    Full Text Available This paper presents the use of linear and nonlinear multivariable models as tools to support training process of race walkers. These models are calculated using data collected from race walkers’ training events and they are used to predict the result over a 3 km race based on training loads. The material consists of 122 training plans for 21 athletes. In order to choose the best model leave-one-out cross-validation method is used. The main contribution of the paper is to propose the nonlinear modifications for linear models in order to achieve smaller prediction error. It is shown that the best model is a modified LASSO regression with quadratic terms in the nonlinear part. This model has the smallest prediction error and simplified structure by eliminating some of the predictors.

  2. AP statistics crash course

    CERN Document Server

    D'Alessio, Michael

    2012-01-01

    AP Statistics Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP Statistics Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP Statistics course description outline and actual Advanced Placement test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Our easy-to-read format covers: exploring da

  3. Distracted Driving Raises Crash Risk

    Science.gov (United States)

    ... this issue Health Capsule Distracted Driving Raises Crash Risk En español Send us your comments Video technology ... distracted driving, especially among new drivers, raises the risk for car crashes and near crashes. The study ...

  4. Analysis of the injury severity of crashes by considering different lighting conditions on two-lane rural roads.

    Science.gov (United States)

    Jafari Anarkooli, A; Hadji Hosseinlou, M

    2016-02-01

    Many studies have examined different factors contributing to the injury severity of crashes; however, relatively few studies have focused on the crashes by considering the specific effects of lighting conditions. This research investigates lighting condition differences in the injury severity of crashes using 3-year (2009-2011) crash data of two-lane rural roads of the state of Washington. Separate ordered-probit models were developed to predict the effects of a set of factors expected to influence injury severity in three lighting conditions; daylight, dark, and dark with street lights. A series of likelihood ratio tests were conducted to determine if these lighting condition models were justified. The modeling results suggest that injury severity in specific lighting conditions are associated with contributing factors in different ways, and that such differences cannot be uncovered by focusing merely on one aggregate model. Key differences include crash location, speed limit, shoulder width, driver action, and three collision types (head-on, rear-end, and right-side impact collisions). This paper highlights the importance of deploying street lights at and near intersections (or access points) on two-lane rural roads because injury severity highly increases when crashes occur at these points in dark conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

  5. Road crash costs.

    NARCIS (Netherlands)

    2010-01-01

    Road crashes result in all kinds of social costs, such as medical costs, production loss, human losses, property damage, settlement costs and costs due to congestion. Studies into road crash costs and their trends are carried out quite regularly. In 2009, the costs amounted to € 12.5 billion, or

  6. Vehicular crash data used to rank intersections by injury crash frequency and severity

    Directory of Open Access Journals (Sweden)

    Yi Liu

    2016-09-01

    Full Text Available This article contains data on research conducted in “A double standard model for allocating limited emergency medical service vehicle resources ensuring service reliability” (Liu et al., 2016 [1]. The crash counts were sorted out from comprehensive crash records of over one thousand major signalized intersections in the city of Chicago from 2004 to 2010. For each intersection, vehicular crashes were counted by crash severity levels, including fatal, injury Types A, B, and C for major, moderate, and minor injury levels, property damage only (PDO, and unknown. The crash data was further used to rank intersections by equivalent injury crash frequency. The top 200 intersections with the highest number of crash occurrences identified based on crash frequency- and severity-based scenarios are shared in this brief. The provided data would be a valuable source for research in urban traffic safety analysis and could also be utilized to examine the effectiveness of traffic safety improvement planning and programming, intersection design enhancement, incident and emergency management, and law enforcement strategies.

  7. Modeling Vehicle Collision Angle in Traffic Crashes Based on Three-Dimensional Laser Scanning Data

    Directory of Open Access Journals (Sweden)

    Nengchao Lyu

    2017-02-01

    Full Text Available In road traffic accidents, the analysis of a vehicle’s collision angle plays a key role in identifying a traffic accident’s form and cause. However, because accurate estimation of vehicle collision angle involves many factors, it is difficult to accurately determine it in cases in which less physical evidence is available and there is a lack of monitoring. This paper establishes the mathematical relation model between collision angle, deformation, and normal vector in the collision region according to the equations of particle deformation and force in Hooke’s law of classical mechanics. At the same time, the surface reconstruction method suitable for a normal vector solution is studied. Finally, the estimation model of vehicle collision angle is presented. In order to verify the correctness of the model, verification of multi-angle collision experiments and sensitivity analysis of laser scanning precision for the angle have been carried out using three-dimensional (3D data obtained by a 3D laser scanner in the collision deformation zone. Under the conditions with which the model has been defined, validation results show that the collision angle is a result of the weighted synthesis of the normal vector of the collision point and the weight value is the deformation of the collision point corresponding to normal vectors. These conclusions prove the applicability of the model. The collision angle model proposed in this paper can be used as the theoretical basis for traffic accident identification and cause analysis. It can also be used as a theoretical reference for the study of the impact deformation of elastic materials.

  8. Associating Crash Avoidance Maneuvers with Driver Attributes and Accident Characteristics: A Mixed Logit Model Approach

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    as from the key role of the ability of drivers to perform effective corrective maneuvers for the success of automated in-vehicle warning and driver assistance systems. The analysis is conducted by means of a mixed logit model that accommodates correlations across alternatives and heteroscedasticity. Data...

  9. Investigation of dynamics of ELM crashes and their mitigation techniques

    Energy Technology Data Exchange (ETDEWEB)

    Pankin, Alexei Y. [Tech-X Corporation, Boulder, CO (United States)

    2015-08-14

    The accurate prediction of H-mode pedestal dynamics is critical for planning experiments in existing tokamaks and in the design of future tokamaks such as ITER and DEMO. The main objective of the proposed research is to advance the understanding of the physics of H-mode pedestal. Through advances in coupled kinetic-MHD simulations, a new model for H-mode pedestal and ELM crashes as well as an improved model for the bootstrap current will be developed. ELMmitigation techniques will also be investigated. The proposed research will help design efficient confinement scenarios and reduce transient heat loads on the divertor and plasma facing components. During the last two years, the principal investigator (PI) of this proposal actively participated in physics studies related to the DOE Joint Research Targets. These studies include the modeling of divertor heat load in the DIII-D, Alcator C-Mod, and NSTX tokamaks in 2010, and the modeling of H-mode pedestal structure in the DIII-D tokamak in 2011. It is proposed that this close collaboration with experimentalists from major US tokamaks continue during the next funding period. Verification and validation will be a strong component of the proposed research. During the course of the project, advances will be made in the following areas; Dynamics of the H-mode pedestal buildup and recovery after ELM crashes – The effects of neutral fueling, particle and thermal pinches will be explored; Dynamics of ELM crashes in realistic tokamak geometries – Heat loads associated with ELM crashes will be validated against experimental measurements. An improved model for ELM crashes will be developed; ELM mitigation – The effect of resonant magnetic perturbations on ELMs stability and their evolution will be investigated; Development of a new bootstrap current model – A reduced model for will be developed through careful verification of existing models for bootstrap current against first-principle kinetic neoclassical simulations

  10. Neighborhood Influences on Vehicle-Pedestrian Crash Severity.

    Science.gov (United States)

    Toran Pour, Alireza; Moridpour, Sara; Tay, Richard; Rajabifard, Abbas

    2017-12-01

    Socioeconomic factors are known to be contributing factors for vehicle-pedestrian crashes. Although several studies have examined the socioeconomic factors related to the location of the crashes, limited studies have considered the socioeconomic factors of the neighborhood where the road users live in vehicle-pedestrian crash modelling. This research aims to identify the socioeconomic factors related to both the neighborhoods where the road users live and where crashes occur that have an influence on vehicle-pedestrian crash severity. Data on vehicle-pedestrian crashes that occurred at mid-blocks in Melbourne, Australia, was analyzed. Neighborhood factors associated with road users' residents and location of crash were investigated using boosted regression tree (BRT). Furthermore, partial dependence plots were applied to illustrate the interactions between these factors. We found that socioeconomic factors accounted for 60% of the 20 top contributing factors to vehicle-pedestrian crashes. This research reveals that socioeconomic factors of the neighborhoods where the road users live and where the crashes occur are important in determining the severity of the crashes, with the former having a greater influence. Hence, road safety countermeasures, especially those focussing on the road users, should be targeted at these high-risk neighborhoods.

  11. Plasticity and fracture modeling of three-layer steel composite Tribond® 1200 for crash simulation

    NARCIS (Netherlands)

    Eller, Tom; Ramaker, Kenny; Greve, Lars; Andres, M.T.; Hazrati Marangalou, Javad; van den Boogaard, Antonius H.

    2017-01-01

    A constitutive model is presented for the three-layer steel composite Tribond® 1200. Tribond® is a hot forming steel which consists of three layers: a high strength steel core between two outer layers of ductile low strength steel. The model is designed to provide an accurate prediction of the

  12. Geospatial and machine learning techniques for wicked social science problems: analysis of crash severity on a regional highway corridor

    Science.gov (United States)

    Effati, Meysam; Thill, Jean-Claude; Shabani, Shahin

    2015-04-01

    The contention of this paper is that many social science research problems are too "wicked" to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is well suited to this purpose. Recognizing the intrinsic wickedness of traffic safety issues, such approach is used to unravel the complexity of traffic crash severity on highway corridors as an example of such problems. The support vector machine (SVM) and coactive neuro-fuzzy inference system (CANFIS) algorithms are tested as inferential engines to predict crash severity and uncover spatial and non-spatial factors that systematically relate to crash severity, while a sensitivity analysis is conducted to determine the relative influence of crash severity factors. Different specifications of the two methods are implemented, trained, and evaluated against crash events recorded over a 4-year period on a regional highway corridor in Northern Iran. Overall, the SVM model outperforms CANFIS by a notable margin. The combined use of spatial analysis and artificial intelligence is effective at identifying leading factors of crash severity, while explicitly accounting for spatial dependence and spatial heterogeneity effects. Thanks to the demonstrated effectiveness of a sensitivity analysis, this approach produces comprehensive results that are consistent with existing traffic safety theories and supports the prioritization of effective safety measures that are geographically targeted and behaviorally sound on regional highway corridors.

  13. New evidence concerning fatal crashes of passenger vehicles before and after adding antilock braking systems.

    Science.gov (United States)

    Farmer, C M

    2001-05-01

    Fatal crash rates for passenger cars and vans were compared for the last model year before four-wheel antilock brakes were introduced and the first model year for which antilock brakes were standard equipment. A prior study, based on fatal crash experience through 1995, reported that vehicle models with antilock brakes were more likely than identical but 1-year-earlier models to be involved in crashes fatal to their own occupants, but were less likely to be involved in crashes fatal to occupants of other vehicles. Overall, there was no significant effect of antilocks on the likelihood of fatal crashes. Similar analyses, based on fatal crash experience during 1996-98, yielded very different results. During 1996-98, vehicles with antilock brakes were again less likely than earlier models to be involved in crashes fatal to occupants of other vehicles, but they were no longer overinvolved in crashes fatal to their own occupants.

  14. Allegheny County Crash Data

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Contains locations and information about every crash incident reported to the police in Allegheny County from 2004 to 2016. Fields include injury severity,...

  15. Allegheny County Crash Data

    Data.gov (United States)

    Allegheny County / City of Pittsburgh / Western PA Regional Data Center — Contains locations and information about every crash incident reported to the police in Allegheny County from 2004 to 2017. Fields include injury severity,...

  16. Aircraft crash upon outer containment of nuclear power plant

    International Nuclear Information System (INIS)

    Abbas, H.; Paul, D.K.; Godbole, P.N.; Nayak, G.C.

    1996-01-01

    In this paper, analysis of an aircraft crash upon an outer containment of a nuclear power plant is presented. The effect of target yielding is considered simultaneously by calculating the reaction time in a time marching scheme. The concrete model employed is capable of predicting the cracking and yielding. The response for different cracking strains and different locations of aircraft strike for different aircraft has been studied. Critical location of aircraft strike for the containment has been investigated. The analytical procedure and the material model used are found to be capable of representing the aircraft impact response of the containment structure. (orig.)

  17. Crash Lethality Model

    Science.gov (United States)

    2012-06-06

    of Death from Burn Injuries, New England Journal of Medicine. Massachusetts, Feb 1998. 11. Crull, Michelle. Tatom, John. Conway, Robert . SPIDER 2... Raymer , Daniel P. Aircraft Design: A Conceptual Approach. Washington DC: American Institute of Aeronautics and Astronautics, Inc., 1992. ISBN 0-930403...Patuxent River, MD 20670 NAVAIRSYSCOM (AIR-5.1G - Roberts ), Bldg. 8010 (1) 47320 Priests Point Loop, St. Inigoes, MD 20684-4017 NAVAIRSYSCOM (UASTD

  18. An investigation of the speeding-related crash designation through crash narrative reviews sampled via logistic regression.

    Science.gov (United States)

    Fitzpatrick, Cole D; Rakasi, Saritha; Knodler, Michael A

    2017-01-01

    Speed is one of the most important factors in traffic safety as higher speeds are linked to increased crash risk and higher injury severities. Nearly a third of fatal crashes in the United States are designated as "speeding-related", which is defined as either "the driver behavior of exceeding the posted speed limit or driving too fast for conditions." While many studies have utilized the speeding-related designation in safety analyses, no studies have examined the underlying accuracy of this designation. Herein, we investigate the speeding-related crash designation through the development of a series of logistic regression models that were derived from the established speeding-related crash typologies and validated using a blind review, by multiple researchers, of 604 crash narratives. The developed logistic regression model accurately identified crashes which were not originally designated as speeding-related but had crash narratives that suggested speeding as a causative factor. Only 53.4% of crashes designated as speeding-related contained narratives which described speeding as a causative factor. Further investigation of these crashes revealed that the driver contributing code (DCC) of "driving too fast for conditions" was being used in three separate situations. Additionally, this DCC was also incorrectly used when "exceeding the posted speed limit" would likely have been a more appropriate designation. Finally, it was determined that the responding officer only utilized one DCC in 82% of crashes not designated as speeding-related but contained a narrative indicating speed as a contributing causal factor. The use of logistic regression models based upon speeding-related crash typologies offers a promising method by which all possible speeding-related crashes could be identified. Published by Elsevier Ltd.

  19. Model predictive control using fuzzy decision functions

    NARCIS (Netherlands)

    Kaymak, U.; Costa Sousa, da J.M.

    2001-01-01

    Fuzzy predictive control integrates conventional model predictive control with techniques from fuzzy multicriteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the (fuzzy) goals and the (fuzzy) constraints of the

  20. Driver Injury Risk Variability in Finite Element Reconstructions of Crash Injury Research and Engineering Network (CIREN) Frontal Motor Vehicle Crashes.

    Science.gov (United States)

    Gaewsky, James P; Weaver, Ashley A; Koya, Bharath; Stitzel, Joel D

    2015-01-01

    A 3-phase real-world motor vehicle crash (MVC) reconstruction method was developed to analyze injury variability as a function of precrash occupant position for 2 full-frontal Crash Injury Research and Engineering Network (CIREN) cases. Phase I: A finite element (FE) simplified vehicle model (SVM) was developed and tuned to mimic the frontal crash characteristics of the CIREN case vehicle (Camry or Cobalt) using frontal New Car Assessment Program (NCAP) crash test data. Phase II: The Toyota HUman Model for Safety (THUMS) v4.01 was positioned in 120 precrash configurations per case within the SVM. Five occupant positioning variables were varied using a Latin hypercube design of experiments: seat track position, seat back angle, D-ring height, steering column angle, and steering column telescoping position. An additional baseline simulation was performed that aimed to match the precrash occupant position documented in CIREN for each case. Phase III: FE simulations were then performed using kinematic boundary conditions from each vehicle's event data recorder (EDR). HIC15, combined thoracic index (CTI), femur forces, and strain-based injury metrics in the lung and lumbar vertebrae were evaluated to predict injury. Tuning the SVM to specific vehicle models resulted in close matches between simulated and test injury metric data, allowing the tuned SVM to be used in each case reconstruction with EDR-derived boundary conditions. Simulations with the most rearward seats and reclined seat backs had the greatest HIC15, head injury risk, CTI, and chest injury risk. Calculated injury risks for the head, chest, and femur closely correlated to the CIREN occupant injury patterns. CTI in the Camry case yielded a 54% probability of Abbreviated Injury Scale (AIS) 2+ chest injury in the baseline case simulation and ranged from 34 to 88% (mean = 61%) risk in the least and most dangerous occupant positions. The greater than 50% probability was consistent with the case occupant's AIS 2

  1. Analysis of factors associated with injury severity in crashes involving young New Zealand drivers

    DEFF Research Database (Denmark)

    Weiss, Harold B.; Kaplan, Sigal; Prato, Carlo Giacomo

    2014-01-01

    measures within youth-oriented road safety programs. The current study estimates discrete choice models of injury severity of crashes involving young drivers conditional on these crashes having occurred. The analysis examined a comprehensive set of single-vehicle and two-vehicle crashes involving at least...

  2. The October 2014 United States Treasury bond flash crash and the contributory effect of mini flash crashes.

    Directory of Open Access Journals (Sweden)

    Zachary S Levine

    Full Text Available We investigate the causal uncertainty surrounding the flash crash in the U.S. Treasury bond market on October 15, 2014, and the unresolved concern that no clear link has been identified between the start of the flash crash at 9:33 and the opening of the U.S. equity market at 9:30. We consider the contributory effect of mini flash crashes in equity markets, and find that the number of equity mini flash crashes in the three-minute window between market open and the Treasury Flash Crash was 2.6 times larger than the number experienced in any other three-minute window in the prior ten weekdays. We argue that (a this statistically significant finding suggests that mini flash crashes in equity markets both predicted and contributed to the October 2014 U.S. Treasury Bond Flash Crash, and (b mini-flash crashes are important phenomena with negative externalities that deserve much greater scholarly attention.

  3. The October 2014 United States Treasury bond flash crash and the contributory effect of mini flash crashes.

    Science.gov (United States)

    Levine, Zachary S; Hale, Scott A; Floridi, Luciano

    2017-01-01

    We investigate the causal uncertainty surrounding the flash crash in the U.S. Treasury bond market on October 15, 2014, and the unresolved concern that no clear link has been identified between the start of the flash crash at 9:33 and the opening of the U.S. equity market at 9:30. We consider the contributory effect of mini flash crashes in equity markets, and find that the number of equity mini flash crashes in the three-minute window between market open and the Treasury Flash Crash was 2.6 times larger than the number experienced in any other three-minute window in the prior ten weekdays. We argue that (a) this statistically significant finding suggests that mini flash crashes in equity markets both predicted and contributed to the October 2014 U.S. Treasury Bond Flash Crash, and (b) mini-flash crashes are important phenomena with negative externalities that deserve much greater scholarly attention.

  4. Patterns of severe injury in pediatric car crash victims: Crash Injury Research Engineering Network database.

    Science.gov (United States)

    Brown, J Kristine; Jing, Yuezhou; Wang, Stewart; Ehrlich, Peter F

    2006-02-01

    Motor vehicle crashes (MVCs) account for 50% of pediatric trauma. Safety improvements are typically tested with child crash dummies using an in vitro model. The Crash Injury Research Engineering Network (CIREN) provides an in vivo validation process. Previous research suggest that children in lateral crashes or front-seat locations have higher Injury Severity Scale scores and lower Glasgow Coma Scale scores than those in frontal-impact crashes. However, specific injury patterns and crash characteristics have not been characterized. Data were collected from the CIREN multidisciplinary crash reconstruction network (10 pediatric trauma centers). Injuries were examined with regard to crash direction (frontal/lateral), restraint use, seat location, and change in velocity at impact (DeltaV). Injuries were limited to Abbreviated Injury Scale (AIS) scores of 3 or higher and included head, thoracic, abdominal, pelvic, spine, and long bone (orthopedic) injuries. Standard age groupings (0-4, 5-9, 10-14, and 15-18 years) were used. Statistical analyses used Fisher's Exact test and multiple logistic regressions. Four hundred seventeen MVCs with 2500 injuries were analyzed (males = 219, females = 198). Controlling for DeltaV and age, children in lateral-impact crashes (n = 232) were significantly more likely to suffer severe injuries to the head and thorax as compared with children in frontal crashes (n = 185), who were more likely to suffer severe spine and orthopedic injuries. Children in a front-seat (n = 236) vs those in a back-seat (n = 169) position had more injuries to the thoracic (27% vs 17%), abdominal (21% vs 13%), pelvic (11% vs 1%), and orthopedic (28% vs 10%) regions (P < .05 for all). Seat belts were protective for pelvic (5% vs 12% unbelted) and orthopedic (15% vs 40%) injuries (odds ratio = 3, P < .01 for both). A reproducible pattern of injury is noted for children involved in lateral-impact crashes characterized by head and chest injuries. The Injury Severity

  5. Impact of connected vehicles on mitigating secondary crash risk

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2017-09-01

    Full Text Available Reducing the risk of secondary crashes is a key goal for effective traffic incident management. However, only few countermeasures have been established in practices to achieve the goal. This is mainly due to the stochastic nature of both primary and secondary crashes. Given the emerging connected vehicle (CV technologies, it is highly likely that CVs will soon be able to communicate with each other through the ad-hoc wireless vehicular network. Information sharing among vehicles is deemed to change traffic operations and allow motorists for more proactive actions. Motorists who receive safety messages can be motivated to approach queues and incident sites with more caution. As a result of the improved situational awareness, the risk of secondary crashes is expected to be reduced. To examine whether this expectation is achievable or not, this study aims to assess the impact of connectivity on the risk of secondary crashes. A simulation-based modeling framework that enables vehicle-to-vehicle communication module was developed. Since crashes cannot be directly simulated in micro-simulation, the use of surrogate safety measures was proposed to capture vehicular conflicts as a proxy for secondary crash risk upstream of a primary crash site. An experimental study was conducted based on the developed simulation modeling framework. The results show that the use of connected vehicles can be a viable way to reduce the risk of secondary crashes. Their impact is expected to change with an increasing market penetration of connected vehicles.

  6. Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

    NARCIS (Netherlands)

    Tian, X.; Negenborn, R.R.; Van Overloop, P.J.A.T.M.; Mostert, E.

    2014-01-01

    In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for

  7. Good Models Gone Bad: Quantifying and Predicting Parameter-Induced Climate Model Simulation Failures

    Science.gov (United States)

    Lucas, D. D.; Klein, R.; Tannahill, J.; Brandon, S.; Covey, C. C.; Domyancic, D.; Ivanova, D. P.

    2012-12-01

    Simulations using IPCC-class climate models are subject to fail or crash for a variety of reasons. Statistical analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation failures of the Parallel Ocean Program (POP2). About 8.5% of our POP2 runs failed for numerical reasons at certain combinations of parameter values. We apply support vector machine (SVM) classification from the fields of pattern recognition and machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. The SVM classifiers readily predict POP2 failures in an independent validation ensemble, and are subsequently used to determine the causes of the failures via a global sensitivity analysis. Four parameters related to ocean mixing and viscosity are identified as the major sources of POP2 failures. Our method can be used to improve the robustness of complex scientific models to parameter perturbations and to better steer UQ ensembles. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and was funded by the Uncertainty Quantification Strategic Initiative Laboratory Directed Research and Development Project at LLNL under project tracking code 10-SI-013 (UCRL LLNL-ABS-569112).

  8. Load event: Aircraft crash

    International Nuclear Information System (INIS)

    Fritsch, H.

    1985-01-01

    The bibliography includes 48 quotations, up to the year 1983, on the following issues: Experiments and computational methods. Design load for the dimensioning of reinforced concrete buildings and components with respect to the dynamic load in the event of an aircraft crash. (orig./HP) [de

  9. Advances in Crash Response

    Centers for Disease Control (CDC) Podcasts

    In this podcast, Dr. Richard C. Hunt, Director of CDC's Division of Injury Response, provides an overview on the benefits of using an Advanced Automatic Collision Notification system, or AACN, to help with emergency triage of people injured in vehicle crashes.

  10. Crash testing of nuclear fuel shipping containers

    International Nuclear Information System (INIS)

    Jefferson, R.M.; Yoshimura, H.R.

    1977-08-01

    In an attempt to understand the dynamics of extra severe transportation accidents and to evaluate state-of-the-art computational techniques for predicting the dynamic response of shipping casks involved in vehicular system crashes, the Environmental Control Technology Division of ERDA undertook a program with Sandia to investigate these areas. The program encompasses the following distinct major efforts. The first of these utilizes computational methods for predicting the effects of the accident environment and, subsequently, to calculate the damage incurred by a container as the result of such an accident. The second phase involves the testing of 1 / 8 -scale models of transportation systems. Through the use of instrumentation and high-speed motion photography the accident environments and physical damage mechanisms are studied in detail. After correlating the results of these first two phases, a full scale event involving representative hardware is conducted. To date two of the three selected test scenarios have been completed. Results of the program to this point indicate that both computational techniques and scale modeling are viable engineering approaches to studying accident environments and physical damage to shipping casks

  11. Crash testing of nuclear fuel shipping containers

    International Nuclear Information System (INIS)

    Jefferson, R.M.; Yoshimura, H.R.

    1977-12-01

    In an attempt to understand the dynamics of extra severe transportation accidents and to evaluate state-of-the-art computational techniques for predicting the dynamic response of shipping casks involved in vehicular system crashes, the Environmental Control Technology Division of ERDA undertook a program with Sandia to investigate these areas. This program, which began in 1975, encompasses the following distinct major efforts. The first of these utilizes computational methods for predicting the effects of the accident environment and, subsequently, to calculate the damage incurred by a container as the result of such an accident. The second phase involves the testing of 1 / 8 -scale models of transportation systems. Through the use of instrumentation and high-speed motion photography, the accident environments and physical damage mechanisms are studied in detail. After correlating the results of these first two phases, a full scale event involving representative hardware is conducted. To date two of the three selected test scenarios have been completed. Results of the program to this point indicate that both computational techniques and scale modeling are viable engineering approaches to studying accident environments and physical damage to shipping casks

  12. Iowa calibration of MEPDG performance prediction models.

    Science.gov (United States)

    2013-06-01

    This study aims to improve the accuracy of AASHTO Mechanistic-Empirical Pavement Design Guide (MEPDG) pavement : performance predictions for Iowa pavement systems through local calibration of MEPDG prediction models. A total of 130 : representative p...

  13. Model complexity control for hydrologic prediction

    NARCIS (Netherlands)

    Schoups, G.; Van de Giesen, N.C.; Savenije, H.H.G.

    2008-01-01

    A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore

  14. Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems.

    Science.gov (United States)

    Kusano, Kristofer D; Gabler, Hampton C

    2015-01-01

    The U.S. New Car Assessment Program (NCAP) now tests for forward collision warning (FCW) and lane departure warning (LDW). The design of these warnings differs greatly between vehicles and can result in different real-world field performance in preventing or mitigating the effects of collisions. The objective of this study was to compare the expected number of crashes and injured drivers that could be prevented if all vehicles in the fleet were equipped with the FCW and LDW systems tested under the U.S. NCAP. To predict the potential crashes and serious injury that could be prevented, our approach was to computationally model the U.S. crash population. The models simulated all rear-end and single-vehicle road departure collisions that occurred in a nationally representative crash database (NASS-CDS). A sample of 478 single-vehicle crashes from NASS-CDS 2012 was the basis for 24,822 simulations for LDW. A sample of 1,042 rear-end collisions from NASS-CDS years 1997-2013 was the basis for 7,616 simulations for FCW. For each crash, 2 simulations were performed: (1) without the system present and (2) with the system present. Models of each production safety system were based on 54 model year 2010-2014 vehicles that were evaluated under the NCAP confirmation procedure for LDW and/or FCW. NCAP performed 40 LDW and 45 FCW tests of these vehicles. The design of the FCW systems had a dramatic impact on their potential to prevent crashes and injuries. Between 0 and 67% of crashes and 2 and 69% of moderately to fatally injured drivers in rear-end impacts could have been prevented if all vehicles were equipped with the FCW systems. Earlier warning times resulted in increased benefits. The largest effect on benefits, however, was the lower operating speed threshold of the systems. Systems that only operated at speeds above 20 mph were less than half as effective as those that operated above 5 mph with similar warning times. The production LDW systems could have prevented

  15. Crashes and near-crashes on horizontal curves along rural two-lane highways: Analysis of naturalistic driving data.

    Science.gov (United States)

    Wang, Bo; Hallmark, Shauna; Savolainen, Peter; Dong, Jing

    2017-12-01

    Prior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves. The second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions. Logistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions. This paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data. This paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit

  16. Hotspots and causes of motor vehicle crashes in Baltimore, Maryland: A geospatial analysis of five years of police crash and census data.

    Science.gov (United States)

    Dezman, Zachary; de Andrade, Luciano; Vissoci, Joao Ricardo; El-Gabri, Deena; Johnson, Abree; Hirshon, Jon Mark; Staton, Catherine A

    2016-11-01

    Road traffic injuries are a leading killer of youth (aged 15-29) and are projected to be the 7th leading cause of death by 2030. To better understand road traffic crash locations and characteristics in the city of Baltimore, we used police and census data, to describe the epidemiology, hotspots, and modifiable risk factors involved to guide further interventions. Data on all crashes in Baltimore City from 2009 to 2013 were made available from the Maryland Automated Accident Reporting System. Socioeconomic data collected by the US CENSUS 2010 were obtained. A time series analysis was conducted using an ARIMA model. We analyzed the geographical distribution of traffic crashes and hotspots using exploratory spatial data analysis and spatial autocorrelation. Spatial regression was performed to evaluate the impact of socioeconomic indicators on hotspots. In Baltimore City, between 2009 and 2013, there were a total of 100,110 crashes reported, with 1% of crashes considered severe. Of all crashes, 7% involved vulnerable road users and 12% had elderly or youth involvement. Reasons for crashes included: distracted driving (31%), speeding (6%), and alcohol or drug use (5%). After 2010, we observed an increasing trend in all crashes especially from March to June. Distracted driving then youth and elderly drivers were consistently the highest risk factors over time. Multivariate spatial regression model including socioeconomic indicators and controlling for age, gender and population size did not show a distinct predictor of crashes explaining only 20% of the road crash variability, indicating crashes are not geographically explained by socioeconomic indicators alone. In Baltimore City, road traffic crashes occurred predominantly in the high density center of the city, involved distracted driving and extremes of age with an increase in crashes from March to June. There was no association between socioeconomic variables where crashes occurred and hotspots. In depth analysis of

  17. Nonlinear chaotic model for predicting storm surges

    Directory of Open Access Journals (Sweden)

    M. Siek

    2010-09-01

    Full Text Available This paper addresses the use of the methods of nonlinear dynamics and chaos theory for building a predictive chaotic model from time series. The chaotic model predictions are made by the adaptive local models based on the dynamical neighbors found in the reconstructed phase space of the observables. We implemented the univariate and multivariate chaotic models with direct and multi-steps prediction techniques and optimized these models using an exhaustive search method. The built models were tested for predicting storm surge dynamics for different stormy conditions in the North Sea, and are compared to neural network models. The results show that the chaotic models can generally provide reliable and accurate short-term storm surge predictions.

  18. Staying Power of Churn Prediction Models

    NARCIS (Netherlands)

    Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

    In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

  19. Predictive user modeling with actionable attributes

    NARCIS (Netherlands)

    Zliobaite, I.; Pechenizkiy, M.

    2013-01-01

    Different machine learning techniques have been proposed and used for modeling individual and group user needs, interests and preferences. In the traditional predictive modeling instances are described by observable variables, called attributes. The goal is to learn a model for predicting the target

  20. Conscientious personality and young drivers’ crash risk

    Science.gov (United States)

    Ehsani, Johnathon P.; Li, Kaigang; Simons-Morton, Bruce; Tree-McGrath, Cheyenne Fox; Perlus, Jessamyn; O’Brien, Fearghal; Klauer, Sheila G.

    2015-01-01

    Introduction Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior and crashes and near-crashes, using naturalistic driving research methods. Method Participants’ driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants’ KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results Conscientiousness was marginally negatively associated with CNC (path c = −0.034, p = .09) and both potential mediators KRD (path a = −0.040, p = .09) and secondary task engagement while driving (path a = −0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c’ = −0.025, p = .20). Conclusions Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, suffered fewer CNC. Practical Applications Part of the variability in crash-risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage

  1. Conscientious personality and young drivers' crash risk.

    Science.gov (United States)

    Ehsani, Johnathon P; Li, Kaigang; Simons-Morton, Bruce G; Fox Tree-McGrath, Cheyenne; Perlus, Jessamyn G; O'Brien, Fearghal; Klauer, Sheila G

    2015-09-01

    Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Conscientiousness was marginally negatively associated with CNC (path c=-0.034, p=.09) and both potential mediators KRD (path a=-0.040, p=.09) and secondary task engagement while driving (path a=-0.053, p=.03). KRD, but not secondary task engagement, was found to mediate (path b=0.376, p=.02) the relationship between conscientiousness and CNC (path c'=-0.025, p=.20). Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and

  2. EFFICIENT PREDICTIVE MODELLING FOR ARCHAEOLOGICAL RESEARCH

    OpenAIRE

    Balla, A.; Pavlogeorgatos, G.; Tsiafakis, D.; Pavlidis, G.

    2014-01-01

    The study presents a general methodology for designing, developing and implementing predictive modelling for identifying areas of archaeological interest. The methodology is based on documented archaeological data and geographical factors, geospatial analysis and predictive modelling, and has been applied to the identification of possible Macedonian tombs’ locations in Northern Greece. The model was tested extensively and the results were validated using a commonly used predictive gain, which...

  3. Classification of soft and hard impacts-Application to aircraft crash

    International Nuclear Information System (INIS)

    Koechlin, Pierre; Potapov, Serguei

    2009-01-01

    Before modeling an aircraft crash on a shield building of a nuclear power plant, it is very important to understand the physical phenomena and the structural behavior associated with this kind of impact. In the scientific literature, aircraft crash is classified as a soft impact, or as an impact of deformable missile. Nevertheless the existing classifications are not precise enough to be able to predict 'a priori' the structural response mode. The aim of this paper is to characterize very precisely what is a soft and a hard impact in the frame of aircraft crash on nuclear power plant. First the existing qualitative definition of soft and hard impact is quickly reviewed in order to introduce a new criterion to make a quantitative distinction between soft and hard impact. Then the experimental tests carried out during the last thirty years in the research field of aircraft crash are presented in the light of the new classification. The authors show that this characterization of soft and hard impacts has a real physical interest because it is linked to the failure mode for perforation: for soft impacts, perforation is the consequence of a shear plug breaking away and for hard impact it comes from local failure and projectile penetration. Moreover the boundary between soft and hard impact is the limit for the use of an impact force in an uncoupled computation of the impact

  4. Robust predictions of the interacting boson model

    International Nuclear Information System (INIS)

    Casten, R.F.; Koeln Univ.

    1994-01-01

    While most recognized for its symmetries and algebraic structure, the IBA model has other less-well-known but equally intrinsic properties which give unavoidable, parameter-free predictions. These predictions concern central aspects of low-energy nuclear collective structure. This paper outlines these ''robust'' predictions and compares them with the data

  5. Comparison of Prediction-Error-Modelling Criteria

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    Single and multi-step prediction-error-methods based on the maximum likelihood and least squares criteria are compared. The prediction-error methods studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model, which is a r...

  6. Gasoline prices and traffic crashes in Alabama, 1999-2009.

    Science.gov (United States)

    Chi, Guangqing; McClure, Timothy E; Brown, David B

    2012-09-01

    The price of gasoline has been found to be negatively associated with traffic crashes in a limited number of studies. However, most of the studies have focused either on fatal crashes only or on all crashes but measured over a very short time period. In this study, we examine gasoline price effects on all traffic crashes by demographic groups in the state of Alabama from 1999 to 2009. Using negative binomial regression techniques to examine monthly data from 1999 to 2009 in the state of Alabama, we estimate the effects of changes in gasoline price on changes in automobile crashes. We also examine how these effects differ by age group (16-20, 21-25, 26-30, 31-64, and 65+), gender (male and female), and race/ethnicity (non-Hispanic white, non-Hispanic black, and Hispanic). The results show that gasoline prices have both short-term and long-term effects on reducing total traffic crashes and crashes of each age, gender, and race/ethnicity group (except Hispanic due to data limitations). The short-term and long-term effects are not statistically different for each individual demographic group. Gasoline prices have a stronger effect in reducing crashes involving drivers aged 16 to 20 than crashes involving drivers aged 31 to 64 and 65+ in the short term; the effects, however, are not statistically different across other demographic groups. Although gasoline price increases are not favored, our findings show that gasoline price increases (or decreases) are associated with reductions (or increases) in the incidence of traffic crashes. If gasoline prices had remained at the 1999 level of $1.41 from 1999 to 2009, applying the estimated elasticities would result in a predicted increase in total crashes of 169,492 (or 11.3%) from the actual number of crashes. If decision makers wish to reduce traffic crashes, increasing gasoline taxes is a possible option-however, doing so would increase travel costs and lead to equity concerns. These findings may help to shape transportation

  7. A nested mechanistic sub-study into the effect of tranexamic acid versus placebo on intracranial haemorrhage and cerebral ischaemia in isolated traumatic brain injury: study protocol for a randomised controlled trial (CRASH-3 Trial Intracranial Bleeding Mechanistic Sub-Study [CRASH-3 IBMS]).

    Science.gov (United States)

    Mahmood, Abda; Roberts, Ian; Shakur, Haleema

    2017-07-17

    Tranexamic acid prevents blood clots from breaking down and reduces bleeding. However, it is uncertain whether tranexamic acid is effective in traumatic brain injury. The CRASH-3 trial is a randomised controlled trial that will examine the effect of tranexamic acid (versus placebo) on death and disability in 13,000 patients with traumatic brain injury. The CRASH-3 trial hypothesizes that tranexamic acid will reduce intracranial haemorrhage, which will reduce the risk of death. Although it is possible that tranexamic acid will reduce intracranial bleeding, there is also a potential for harm. In particular, tranexamic acid may increase the risk of cerebral thrombosis and ischaemia. The protocol detailed here is for a mechanistic sub-study nested within the CRASH-3 trial. This mechanistic sub-study aims to examine the effect of tranexamic acid (versus placebo) on intracranial bleeding and cerebral ischaemia. The CRASH-3 Intracranial Bleeding Mechanistic Sub-Study (CRASH-3 IBMS) is nested within a prospective, double-blind, multi-centre, parallel-arm randomised trial called the CRASH-3 trial. The CRASH-3 IBMS will be conducted in a cohort of approximately 1000 isolated traumatic brain injury patients enrolled in the CRASH-3 trial. In the CRASH-3 IBMS, brain scans acquired before and after randomisation are examined, using validated methods, for evidence of intracranial bleeding and cerebral ischaemia. The primary outcome is the total volume of intracranial bleeding measured on computed tomography after randomisation, adjusting for baseline bleeding volume. Secondary outcomes include progression of intracranial haemorrhage (from pre- to post-randomisation scans), new intracranial haemorrhage (seen on post- but not pre-randomisation scans), intracranial haemorrhage following neurosurgery, and new focal ischaemic lesions (seen on post-but not pre-randomisation scans). A linear regression model will examine whether receipt of the trial treatment can predict haemorrhage

  8. Perbandingan Stock Market Crash 1987 : Dan Stock Market Crash 1997

    OpenAIRE

    Indridewi Atmadjaja, Yovita Vivianty

    1999-01-01

    Stock market crash refers to the condition, which is marked with the large dropping of stock Market price index. Historically, stock market crash has happened three times, namely in 1929, 1987 and 1997. This paper will discuss the causes of 1987's and 1997's stock market Crash and the similarities and the differences between 1987's and 1997's stock market crash. The structure of the paper is as follows. The paper starts with the introduction. The second Section briefly explains the causes of ...

  9. Advances in Crash Response

    Centers for Disease Control (CDC) Podcasts

    2009-06-29

    In this podcast, Dr. Richard C. Hunt, Director of CDC's Division of Injury Response, provides an overview on the benefits of using an Advanced Automatic Collision Notification system, or AACN, to help with emergency triage of people injured in vehicle crashes.  Created: 6/29/2009 by National Center for Injury Prevention and Control (NCIPC), Division of Injury Response (DIR).   Date Released: 6/29/2009.

  10. Injury mitigation estimates for an intersection driver assistance system in straight crossing path crashes in the United States.

    Science.gov (United States)

    Scanlon, John M; Sherony, Rini; Gabler, Hampton C

    2017-05-29

    Accounting for one fifth of all crashes and one sixth of all fatal crashes in the United States, intersection crashes are among the most frequent and fatal crash modes. Intersection advanced driver assistance systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (Maximum Abbreviated Injury Scale [MAIS] 3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS. This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of 5 separate activation timing thresholds, 3 separate computational latency times, and 2 different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-V. The results were then compiled across all crashes in order to estimate system effectiveness. The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 to 0.5 s was found to reduce crash and injury prevention estimates by approximately one third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to

  11. Extracting falsifiable predictions from sloppy models.

    Science.gov (United States)

    Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

    2007-12-01

    Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

  12. The prediction of epidemics through mathematical modeling.

    Science.gov (United States)

    Schaus, Catherine

    2014-01-01

    Mathematical models may be resorted to in an endeavor to predict the development of epidemics. The SIR model is one of the applications. Still too approximate, the use of statistics awaits more data in order to come closer to reality.

  13. Calibration of PMIS pavement performance prediction models.

    Science.gov (United States)

    2012-02-01

    Improve the accuracy of TxDOTs existing pavement performance prediction models through calibrating these models using actual field data obtained from the Pavement Management Information System (PMIS). : Ensure logical performance superiority patte...

  14. Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling

    Science.gov (United States)

    Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.

    2017-12-01

    Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model

  15. U.S. Civil Air Show Crashes, 1993 to 2013: Burden, Fatal Risk Factors, and Evaluation of a Risk Index for Aviation Crashes.

    Science.gov (United States)

    Ballard, Sarah-Blythe; Osorio, Victor B

    2015-01-01

    This study provides new public health data about U.S. civil air shows. Risk factors for fatalities in civil air show crashes were analyzed. The value of the FIA score in predicting fatal outcomes was evaluated. With the use of the FAA's General Aviation and Air Taxi Survey and the National Transportation Safety Board's data, the incidence of civil air show crashes from 1993 to 2013 was calculated. Fatality risk factors for crashes were analyzed by means of regression methods. The FIA index was validated to predict fatal outcomes by using the factors of fire, instrument conditions, and away-from-airport location, and was evaluated through receiver operating characteristic (ROC) curves. The civil air show crash rate was 31 crashes per 1,000 civil air events. Of the 174 civil air show crashes that occurred during the study period, 91 (52%) involved at least one fatality; on average, 1.1 people died per fatal crash. Fatalities were associated with four major risk factors: fire [adjusted odds ratio (AOR) = 7.1, 95% confidence interval (CI) = 2.4 to 20.6, P Civil air show crashes were marked by a high risk of fatal outcomes to pilots in aerobatic performances but rare mass casualties. The FIA score was not a valid measurement of fatal risk in civil air show crashes.

  16. Case studies in archaeological predictive modelling

    NARCIS (Netherlands)

    Verhagen, Jacobus Wilhelmus Hermanus Philippus

    2007-01-01

    In this thesis, a collection of papers is put together dealing with various quantitative aspects of predictive modelling and archaeological prospection. Among the issues covered are the effects of survey bias on the archaeological data used for predictive modelling, and the complexities of testing

  17. Clinical Prediction Models for Cardiovascular Disease: Tufts Predictive Analytics and Comparative Effectiveness Clinical Prediction Model Database.

    Science.gov (United States)

    Wessler, Benjamin S; Lai Yh, Lana; Kramer, Whitney; Cangelosi, Michael; Raman, Gowri; Lutz, Jennifer S; Kent, David M

    2015-07-01

    Clinical prediction models (CPMs) estimate the probability of clinical outcomes and hold the potential to improve decision making and individualize care. For patients with cardiovascular disease, there are numerous CPMs available although the extent of this literature is not well described. We conducted a systematic review for articles containing CPMs for cardiovascular disease published between January 1990 and May 2012. Cardiovascular disease includes coronary heart disease, heart failure, arrhythmias, stroke, venous thromboembolism, and peripheral vascular disease. We created a novel database and characterized CPMs based on the stage of development, population under study, performance, covariates, and predicted outcomes. There are 796 models included in this database. The number of CPMs published each year is increasing steadily over time. Seven hundred seventeen (90%) are de novo CPMs, 21 (3%) are CPM recalibrations, and 58 (7%) are CPM adaptations. This database contains CPMs for 31 index conditions, including 215 CPMs for patients with coronary artery disease, 168 CPMs for population samples, and 79 models for patients with heart failure. There are 77 distinct index/outcome pairings. Of the de novo models in this database, 450 (63%) report a c-statistic and 259 (36%) report some information on calibration. There is an abundance of CPMs available for a wide assortment of cardiovascular disease conditions, with substantial redundancy in the literature. The comparative performance of these models, the consistency of effects and risk estimates across models and the actual and potential clinical impact of this body of literature is poorly understood. © 2015 American Heart Association, Inc.

  18. Large truck and bus crash facts, 2010.

    Science.gov (United States)

    2012-09-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and : property damage only crashes involving large trucks and buses in 2010. Selected crash statistics on passenger : vehicles are also presen...

  19. Large truck and bus crash facts, 2012.

    Science.gov (United States)

    2014-06-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and property damage only crashes involving large trucks and buses in 2012. Selected crash statistics on passenger vehicles are also presented ...

  20. Large truck and bus crash facts, 2013.

    Science.gov (United States)

    2015-04-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and property damage only crashes involving large trucks and buses in 2013. Selected crash statistics on passenger vehicles are also presented ...

  1. Large truck and bus crash facts, 2009.

    Science.gov (United States)

    2011-10-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and : property damage only crashes involving large trucks and buses in 2009. Selected crash statistics on passenger : vehicles are also presen...

  2. Large truck and bus crash facts, 2011.

    Science.gov (United States)

    2013-10-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and : property damage only crashes involving large trucks and buses in 2011. Selected crash statistics on passenger : vehicles are also presen...

  3. Omitted variable bias in crash reduction factors.

    Science.gov (United States)

    2015-09-01

    Transportation planners and traffic engineers are increasingly turning to crash reduction factors to evaluate changes in road : geometric and design features in order to reduce crashes. Crash reduction factors are typically estimated based on segment...

  4. An Analysis of the Relationship between Casualty Risk Per Crash and Vehicle Mass and Footprint for Model Year 2000-2007 Light-Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Tom [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Building Technology and Urban Systems Dept.

    2012-08-01

    NHTSA recently completed a logistic regression analysis (Kahane 2012) updating its 2003 and 2010 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT). The new study updates the previous analyses in several ways: updated FARS data for 2002 to 2008 involving MY00 to MY07 vehicles are used; induced exposure data from police reported crashes in several additional states are added; a new vehicle category for car-based crossover utility vehicles (CUVs) and minivans is created; crashes with other light-duty vehicles are divided into two groups based on the crash partner vehicle’s weight, and a category for all other fatal crashes is added; and new control variables for new safety technologies and designs, such as electronic stability controls (ESC), side airbags, and methods to meet voluntary agreement to improve light truck compatibility with cars, are included.

  5. Incorporating uncertainty in predictive species distribution modelling.

    Science.gov (United States)

    Beale, Colin M; Lennon, Jack J

    2012-01-19

    Motivated by the need to solve ecological problems (climate change, habitat fragmentation and biological invasions), there has been increasing interest in species distribution models (SDMs). Predictions from these models inform conservation policy, invasive species management and disease-control measures. However, predictions are subject to uncertainty, the degree and source of which is often unrecognized. Here, we review the SDM literature in the context of uncertainty, focusing on three main classes of SDM: niche-based models, demographic models and process-based models. We identify sources of uncertainty for each class and discuss how uncertainty can be minimized or included in the modelling process to give realistic measures of confidence around predictions. Because this has typically not been performed, we conclude that uncertainty in SDMs has often been underestimated and a false precision assigned to predictions of geographical distribution. We identify areas where development of new statistical tools will improve predictions from distribution models, notably the development of hierarchical models that link different types of distribution model and their attendant uncertainties across spatial scales. Finally, we discuss the need to develop more defensible methods for assessing predictive performance, quantifying model goodness-of-fit and for assessing the significance of model covariates.

  6. Model Predictive Control for Smart Energy Systems

    DEFF Research Database (Denmark)

    Halvgaard, Rasmus

    pumps, heat tanks, electrical vehicle battery charging/discharging, wind farms, power plants). 2.Embed forecasting methodologies for the weather (e.g. temperature, solar radiation), the electricity consumption, and the electricity price in a predictive control system. 3.Develop optimization algorithms....... Chapter 3 introduces Model Predictive Control (MPC) including state estimation, filtering and prediction for linear models. Chapter 4 simulates the models from Chapter 2 with the certainty equivalent MPC from Chapter 3. An economic MPC minimizes the costs of consumption based on real electricity prices...... that determined the flexibility of the units. A predictive control system easily handles constraints, e.g. limitations in power consumption, and predicts the future behavior of a unit by integrating predictions of electricity prices, consumption, and weather variables. The simulations demonstrate the expected...

  7. Evaluating the Predictive Value of Growth Prediction Models

    Science.gov (United States)

    Murphy, Daniel L.; Gaertner, Matthew N.

    2014-01-01

    This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high…

  8. a Geographic Weighted Regression for Rural Highways Crashes Modelling Using the Gaussian and Tricube Kernels: a Case Study of USA Rural Highways

    Science.gov (United States)

    Aghayari, M.; Pahlavani, P.; Bigdeli, B.

    2017-09-01

    Based on world health organization (WHO) report, driving incidents are counted as one of the eight initial reasons for death in the world. The purpose of this paper is to develop a method for regression on effective parameters of highway crashes. In the traditional methods, it was assumed that the data are completely independent and environment is homogenous while the crashes are spatial events which are occurring in geographic space and crashes have spatial data. Spatial data have spatial features such as spatial autocorrelation and spatial non-stationarity in a way working with them is going to be a bit difficult. The proposed method has implemented on a set of records of fatal crashes that have been occurred in highways connecting eight east states of US. This data have been recorded between the years 2007 and 2009. In this study, we have used GWR method with two Gaussian and Tricube kernels. The Number of casualties has been considered as dependent variable and number of persons in crash, road alignment, number of lanes, pavement type, surface condition, road fence, light condition, vehicle type, weather, drunk driver, speed limitation, harmful event, road profile, and junction type have been considered as explanatory variables according to previous studies in using GWR method. We have compered the results of implementation with OLS method. Results showed that R2 for OLS method is 0.0654 and for the proposed method is 0.9196 that implies the proposed GWR is better method for regression in rural highway crashes.

  9. M5 model tree based predictive modeling of road accidents on non-urban sections of highways in India.

    Science.gov (United States)

    Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh

    2016-11-01

    This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Model predictive control classical, robust and stochastic

    CERN Document Server

    Kouvaritakis, Basil

    2016-01-01

    For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplic...

  11. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  12. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  13. Increased inequality in mortality from road crashes among Arabs and Jews in Israel.

    Science.gov (United States)

    Magid, Avi; Leibovitch-Zur, Shalhevet; Baron-Epel, Orna

    2015-01-01

    Previous studies in several countries have shown that the economically disadvantaged seem to have a greater risk of being involved in a car crash. The aim of the present study was to compare rates and trends in mortality and injury from road crashes by age among the Arab and Jewish populations in Israel. Data on road crashes with casualties (2003-2011) from the Israeli Central Bureau of Statistics were analyzed. Age-adjusted road crash injury rates and mortality rates for 2003 to 2011 were calculated and time trends for each age group and population group are presented. Time trend significance was evaluated by linear regression models. Arabs in Israel are at increased risk of injury and mortality from road crashes compared to Jews. Road crash injury rates have significantly decreased in both populations over the last decade, although the rates have been persistently higher among Arabs. Road crash mortality rates have also decreased significantly in the Jewish population but not in the Arab population. This implies an increase in the disparity in mortality between Jews and Arabs. The most prominent differences in road crash injury and mortality rates between Arabs and Jews can be observed in young adults and young children. The reduction in road crashes in the last decade is a positive achievement. However, the reductions are not equal among Arabs and Jews in Israel. Therefore, an increase in the disparities in mortality from road crashes is apparent. Public health efforts need to focus specifically on decreasing road crashes in the Arab community.

  14. Numerical simulation of aircraft crash on nuclear containment structure

    Energy Technology Data Exchange (ETDEWEB)

    Iqbal, M.A., E-mail: iqbalfce@iitr.ernet.in [Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247667 (India); Rai, S.; Sadique, M.R.; Bhargava, P. [Department of Civil Engineering, Indian Institute of Technology Roorkee, Roorkee 247667 (India)

    2012-02-15

    Highlights: Black-Right-Pointing-Pointer The deformation was more localised at the center of cylindrical portion. Black-Right-Pointing-Pointer The peak deflection at the junction of dome and cylinder was found to be 67 mm. Black-Right-Pointing-Pointer The peak deflection at midpoint of the cylindrical portion was found to be 88.9 mm. Black-Right-Pointing-Pointer The strain rate was found to be an important parameter to effect the deformation. Black-Right-Pointing-Pointer The model without strain rate and 290 s{sup -1} strain rate predicted very high deformations. - Abstract: Numerical simulations were carried with ABAQUS/Explicit finite element code in order to predict the response of BWR Mark III type nuclear containment against Boeing 707-320 aircraft crash. The load of the aircraft was applied using and force history curve. The damaged plasticity model was used to predict the behavior of concrete while the Johnson-Cook elasto-viscoplastic material model was used to incorporate the behavior of steel reinforcement. The crash was considered to occur at two different locations i.e., the midpoint of the cylindrical portion and the junction of dome and cylinder. The midpoint of the cylindrical portion experienced more deformation. The strain rate in the material model was varied and found to have a significant effect on the response of containment. The results of the present investigation were compared with those of the studies available in literature and a close agreement with the previous results was found in terms of maximum target deformation.

  15. Fatal crashes of passenger vehicles before and after adding antilock braking systems.

    Science.gov (United States)

    Farmer, C M; Lund, A K; Trempel, R E; Braver, E R

    1997-11-01

    Fatal crash rates of passenger cars and vans were compared for the last model year before four-wheel antilock brakes were introduced and the first model year for which antilock brakes were standard equipment. Vehicles selected for analysis had no other significant design changes between the model years being compared, and the model years with and without antilocks were no more than two years apart. The overall fatal crash rates were similar for the two model years. However, the vehicles with antilocks were significantly more likely to be involved in crashes fatal to their own occupants, particularly single-vehicle crashes. Conversely, antilock vehicles were less likely to be involved in crashes fatal to occupants of other vehicles or nonoccupants (pedestrians, bicyclists). Overall, antilock brakes appear to have had little effect on fatal crash involvement. Further study is needed to better understand why fatality risk has increased for occupants of antilock vehicles.

  16. Unreachable Setpoints in Model Predictive Control

    DEFF Research Database (Denmark)

    Rawlings, James B.; Bonné, Dennis; Jørgensen, John Bagterp

    2008-01-01

    In this work, a new model predictive controller is developed that handles unreachable setpoints better than traditional model predictive control methods. The new controller induces an interesting fast/slow asymmetry in the tracking response of the system. Nominal asymptotic stability of the optimal...... steady state is established for terminal constraint model predictive control (MPC). The region of attraction is the steerable set. Existing analysis methods for closed-loop properties of MPC are not applicable to this new formulation, and a new analysis method is developed. It is shown how to extend...

  17. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

  18. Predictive Modelling and Time: An Experiment in Temporal Archaeological Predictive Models

    OpenAIRE

    David Ebert

    2006-01-01

    One of the most common criticisms of archaeological predictive modelling is that it fails to account for temporal or functional differences in sites. However, a practical solution to temporal or functional predictive modelling has proven to be elusive. This article discusses temporal predictive modelling, focusing on the difficulties of employing temporal variables, then introduces and tests a simple methodology for the implementation of temporal modelling. The temporal models thus created ar...

  19. Fingerprint verification prediction model in hand dermatitis.

    Science.gov (United States)

    Lee, Chew K; Chang, Choong C; Johor, Asmah; Othman, Puwira; Baba, Roshidah

    2015-07-01

    Hand dermatitis associated fingerprint changes is a significant problem and affects fingerprint verification processes. This study was done to develop a clinically useful prediction model for fingerprint verification in patients with hand dermatitis. A case-control study involving 100 patients with hand dermatitis. All patients verified their thumbprints against their identity card. Registered fingerprints were randomized into a model derivation and model validation group. Predictive model was derived using multiple logistic regression. Validation was done using the goodness-of-fit test. The fingerprint verification prediction model consists of a major criterion (fingerprint dystrophy area of ≥ 25%) and two minor criteria (long horizontal lines and long vertical lines). The presence of the major criterion predicts it will almost always fail verification, while presence of both minor criteria and presence of one minor criterion predict high and low risk of fingerprint verification failure, respectively. When none of the criteria are met, the fingerprint almost always passes the verification. The area under the receiver operating characteristic curve was 0.937, and the goodness-of-fit test showed agreement between the observed and expected number (P = 0.26). The derived fingerprint verification failure prediction model is validated and highly discriminatory in predicting risk of fingerprint verification in patients with hand dermatitis. © 2014 The International Society of Dermatology.

  20. Massive Predictive Modeling using Oracle R Enterprise

    CERN Multimedia

    CERN. Geneva

    2014-01-01

    R is fast becoming the lingua franca for analyzing data via statistics, visualization, and predictive analytics. For enterprise-scale data, R users have three main concerns: scalability, performance, and production deployment. Oracle's R-based technologies - Oracle R Distribution, Oracle R Enterprise, Oracle R Connector for Hadoop, and the R package ROracle - address these concerns. In this talk, we introduce Oracle's R technologies, highlighting how each enables R users to achieve scalability and performance while making production deployment of R results a natural outcome of the data analyst/scientist efforts. The focus then turns to Oracle R Enterprise with code examples using the transparency layer and embedded R execution, targeting massive predictive modeling. One goal behind massive predictive modeling is to build models per entity, such as customers, zip codes, simulations, in an effort to understand behavior and tailor predictions at the entity level. Predictions...

  1. Connected motorcycle crash warning interfaces.

    Science.gov (United States)

    2016-01-15

    Crash warning systems have been deployed in the high-end vehicle market segment for some time and are trickling down to additional motor vehicle industry segments each year. The motorcycle segment, however, has no deployed crash warning system to dat...

  2. Resisting "Crash Diet" Staff Development

    Science.gov (United States)

    Dana, Nancy Fichtman; Yendol-Hoppey, Diane

    2008-01-01

    People often respond to the pressure of attending a high school reunion or their child's wedding by going on a crash diet to get quick results. In response, friends may marvel about how good they look on the outside. But what folks don't acknowledge is that, in the name of getting results, crash dieters have done some very unhealthy things to…

  3. Mitigating Wind Induced Truck Crashes

    Science.gov (United States)

    2009-12-25

    Dangerous weather and high wind in particular, is a common contributing factor in truck crashes. High wind speeds have been documented as a perennial cause of truck crashes in Kansas and other Great Plains states. The possibility of reducing such cra...

  4. Multi-model analysis in hydrological prediction

    Science.gov (United States)

    Lanthier, M.; Arsenault, R.; Brissette, F.

    2017-12-01

    Hydrologic modelling, by nature, is a simplification of the real-world hydrologic system. Therefore ensemble hydrological predictions thus obtained do not present the full range of possible streamflow outcomes, thereby producing ensembles which demonstrate errors in variance such as under-dispersion. Past studies show that lumped models used in prediction mode can return satisfactory results, especially when there is not enough information available on the watershed to run a distributed model. But all lumped models greatly simplify the complex processes of the hydrologic cycle. To generate more spread in the hydrologic ensemble predictions, multi-model ensembles have been considered. In this study, the aim is to propose and analyse a method that gives an ensemble streamflow prediction that properly represents the forecast probabilities and reduced ensemble bias. To achieve this, three simple lumped models are used to generate an ensemble. These will also be combined using multi-model averaging techniques, which generally generate a more accurate hydrogram than the best of the individual models in simulation mode. This new predictive combined hydrogram is added to the ensemble, thus creating a large ensemble which may improve the variability while also improving the ensemble mean bias. The quality of the predictions is then assessed on different periods: 2 weeks, 1 month, 3 months and 6 months using a PIT Histogram of the percentiles of the real observation volumes with respect to the volumes of the ensemble members. Initially, the models were run using historical weather data to generate synthetic flows. This worked for individual models, but not for the multi-model and for the large ensemble. Consequently, by performing data assimilation at each prediction period and thus adjusting the initial states of the models, the PIT Histogram could be constructed using the observed flows while allowing the use of the multi-model predictions. The under-dispersion has been

  5. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  6. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  7. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  8. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  9. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  11. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  12. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  13. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  14. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Modeling and Prediction Using Stochastic Differential Equations

    DEFF Research Database (Denmark)

    Juhl, Rune; Møller, Jan Kloppenborg; Jørgensen, John Bagterp

    2016-01-01

    Pharmacokinetic/pharmakodynamic (PK/PD) modeling for a single subject is most often performed using nonlinear models based on deterministic ordinary differential equations (ODEs), and the variation between subjects in a population of subjects is described using a population (mixed effects) setup...... deterministic and can predict the future perfectly. A more realistic approach would be to allow for randomness in the model due to e.g., the model be too simple or errors in input. We describe a modeling and prediction setup which better reflects reality and suggests stochastic differential equations (SDEs...

  17. Multi-level Bayesian analyses for single- and multi-vehicle freeway crashes.

    Science.gov (United States)

    Yu, Rongjie; Abdel-Aty, Mohamed

    2013-09-01

    This study presents multi-level analyses for single- and multi-vehicle crashes on a mountainous freeway. Data from a 15-mile mountainous freeway section on I-70 were investigated. Both aggregate and disaggregate models for the two crash conditions were developed. Five years of crash data were used in the aggregate investigation, while the disaggregate models utilized one year of crash data along with real-time traffic and weather data. For the aggregate analyses, safety performance functions were developed for the purpose of revealing the contributing factors for each crash type. Two methodologies, a Bayesian bivariate Poisson-lognormal model and a Bayesian hierarchical Poisson model with correlated random effects, were estimated to simultaneously analyze the two crash conditions with consideration of possible correlations. Except for the factors related to geometric characteristics, two exposure parameters (annual average daily traffic and segment length) were included. Two different sets of significant explanatory and exposure variables were identified for the single-vehicle (SV) and multi-vehicle (MV) crashes. It was found that the Bayesian bivariate Poisson-lognormal model is superior to the Bayesian hierarchical Poisson model, the former with a substantially lower DIC and more significant variables. In addition to the aggregate analyses, microscopic real-time crash risk evaluation models were developed for the two crash conditions. Multi-level Bayesian logistic regression models were estimated with the random parameters accounting for seasonal variations, crash-unit-level diversity and segment-level random effects capturing unobserved heterogeneity caused by the geometric characteristics. The model results indicate that the effects of the selected variables on crash occurrence vary across seasons and crash units; and that geometric characteristic variables contribute to the segment variations: the more unobserved heterogeneity have been accounted, the better

  18. Predictive Model of Systemic Toxicity (SOT)

    Science.gov (United States)

    In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

  19. The effects of age, gender, and crash types on drivers' injury-related health care costs.

    Science.gov (United States)

    Shen, Sijun; Neyens, David M

    2015-04-01

    There are many studies that evaluate the effects of age, gender, and crash types on crash related injury severity. However, few studies investigate the effects of those crash factors on the crash related health care costs for drivers that are transported to hospital. The purpose of this study is to examine the relationships between drivers' age, gender, and the crash types, as well as other crash characteristics (e.g., not wearing a seatbelt, weather condition, and fatigued driving), on the crash related health care costs. The South Carolina Crash Outcome Data Evaluation System (SC CODES) from 2005 to 2007 was used to construct six separate hierarchical linear regression models based on drivers' age and gender. The results suggest that older drivers have higher health care costs than younger drivers and male drivers tend to have higher health care costs than female drivers in the same age group. Overall, single vehicle crashes had the highest health care costs for all drivers. For males older than 64-years old sideswipe crashes are as costly as single vehicle crashes. In general, not wearing a seatbelt, airbag deployment, and speeding were found to be associated with higher health care costs. Distraction-related crashes are more likely to be associated with lower health care costs in most cases. Furthermore this study highlights the value of considering drivers in subgroups, as some factors have different effects on health care costs in different driver groups. Developing an understanding of longer term outcomes of crashes and their characteristics can lead to improvements in vehicle technology, educational materials, and interventions to reduce crash-related health care costs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Spent fuel: prediction model development

    International Nuclear Information System (INIS)

    Almassy, M.Y.; Bosi, D.M.; Cantley, D.A.

    1979-07-01

    The need for spent fuel disposal performance modeling stems from a requirement to assess the risks involved with deep geologic disposal of spent fuel, and to support licensing and public acceptance of spent fuel repositories. Through the balanced program of analysis, diagnostic testing, and disposal demonstration tests, highlighted in this presentation, the goal of defining risks and of quantifying fuel performance during long-term disposal can be attained

  1. Navy Recruit Attrition Prediction Modeling

    Science.gov (United States)

    2014-09-01

    have high correlation with attrition, such as age, job characteristics, command climate, marital status, behavior issues prior to recruitment, and the...the additive model. glm(formula = Outcome ~ Age + Gender + Marital + AFQTCat + Pay + Ed + Dep, family = binomial, data = ltraining) Deviance ...0.1 ‘ ‘ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance : 105441 on 85221 degrees of freedom Residual deviance

  2. Predicting and Modeling RNA Architecture

    Science.gov (United States)

    Westhof, Eric; Masquida, Benoît; Jossinet, Fabrice

    2011-01-01

    SUMMARY A general approach for modeling the architecture of large and structured RNA molecules is described. The method exploits the modularity and the hierarchical folding of RNA architecture that is viewed as the assembly of preformed double-stranded helices defined by Watson-Crick base pairs and RNA modules maintained by non-Watson-Crick base pairs. Despite the extensive molecular neutrality observed in RNA structures, specificity in RNA folding is achieved through global constraints like lengths of helices, coaxiality of helical stacks, and structures adopted at the junctions of helices. The Assemble integrated suite of computer tools allows for sequence and structure analysis as well as interactive modeling by homology or ab initio assembly with possibilities for fitting within electronic density maps. The local key role of non-Watson-Crick pairs guides RNA architecture formation and offers metrics for assessing the accuracy of three-dimensional models in a more useful way than usual root mean square deviation (RMSD) values. PMID:20504963

  3. An examination of the environmental, driver and vehicle factors associated with the serious and fatal crashes of older rural drivers.

    Science.gov (United States)

    Thompson, J P; Baldock, M R J; Mathias, J L; Wundersitz, L N

    2013-01-01

    Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004-2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances. Copyright © 2012 Elsevier Ltd. All rights reserved.

  4. Predictive Models and Computational Toxicology (II IBAMTOX)

    Science.gov (United States)

    EPA’s ‘virtual embryo’ project is building an integrative systems biology framework for predictive models of developmental toxicity. One schema involves a knowledge-driven adverse outcome pathway (AOP) framework utilizing information from public databases, standardized ontologies...

  5. Finding furfural hydrogenation catalysts via predictive modelling

    NARCIS (Netherlands)

    Strassberger, Z.; Mooijman, M.; Ruijter, E.; Alberts, A.H.; Maldonado, A.G.; Orru, R.V.A.; Rothenberg, G.

    2010-01-01

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes

  6. FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL ...

    African Journals Online (AJOL)

    FINITE ELEMENT MODEL FOR PREDICTING RESIDUAL STRESSES IN ... the transverse residual stress in the x-direction (σx) had a maximum value of 375MPa ... the finite element method are in fair agreement with the experimental results.

  7. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico; Kryshtafovych, Andriy; Tramontano, Anna

    2009-01-01

    established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic

  8. Mental models accurately predict emotion transitions.

    Science.gov (United States)

    Thornton, Mark A; Tamir, Diana I

    2017-06-06

    Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

  9. Mental models accurately predict emotion transitions

    Science.gov (United States)

    Thornton, Mark A.; Tamir, Diana I.

    2017-01-01

    Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

  10. Return Predictability, Model Uncertainty, and Robust Investment

    DEFF Research Database (Denmark)

    Lukas, Manuel

    Stock return predictability is subject to great uncertainty. In this paper we use the model confidence set approach to quantify uncertainty about expected utility from investment, accounting for potential return predictability. For monthly US data and six representative return prediction models, we...... find that confidence sets are very wide, change significantly with the predictor variables, and frequently include expected utilities for which the investor prefers not to invest. The latter motivates a robust investment strategy maximizing the minimal element of the confidence set. The robust investor...... allocates a much lower share of wealth to stocks compared to a standard investor....

  11. Model predictive Controller for Mobile Robot

    OpenAIRE

    Alireza Rezaee

    2017-01-01

    This paper proposes a Model Predictive Controller (MPC) for control of a P2AT mobile robot. MPC refers to a group of controllers that employ a distinctly identical model of process to predict its future behavior over an extended prediction horizon. The design of a MPC is formulated as an optimal control problem. Then this problem is considered as linear quadratic equation (LQR) and is solved by making use of Ricatti equation. To show the effectiveness of the proposed method this controller is...

  12. Spatial Economics Model Predicting Transport Volume

    Directory of Open Access Journals (Sweden)

    Lu Bo

    2016-10-01

    Full Text Available It is extremely important to predict the logistics requirements in a scientific and rational way. However, in recent years, the improvement effect on the prediction method is not very significant and the traditional statistical prediction method has the defects of low precision and poor interpretation of the prediction model, which cannot only guarantee the generalization ability of the prediction model theoretically, but also cannot explain the models effectively. Therefore, in combination with the theories of the spatial economics, industrial economics, and neo-classical economics, taking city of Zhuanghe as the research object, the study identifies the leading industry that can produce a large number of cargoes, and further predicts the static logistics generation of the Zhuanghe and hinterlands. By integrating various factors that can affect the regional logistics requirements, this study established a logistics requirements potential model from the aspect of spatial economic principles, and expanded the way of logistics requirements prediction from the single statistical principles to an new area of special and regional economics.

  13. Accuracy assessment of landslide prediction models

    International Nuclear Information System (INIS)

    Othman, A N; Mohd, W M N W; Noraini, S

    2014-01-01

    The increasing population and expansion of settlements over hilly areas has greatly increased the impact of natural disasters such as landslide. Therefore, it is important to developed models which could accurately predict landslide hazard zones. Over the years, various techniques and models have been developed to predict landslide hazard zones. The aim of this paper is to access the accuracy of landslide prediction models developed by the authors. The methodology involved the selection of study area, data acquisition, data processing and model development and also data analysis. The development of these models are based on nine different landslide inducing parameters i.e. slope, land use, lithology, soil properties, geomorphology, flow accumulation, aspect, proximity to river and proximity to road. Rank sum, rating, pairwise comparison and AHP techniques are used to determine the weights for each of the parameters used. Four (4) different models which consider different parameter combinations are developed by the authors. Results obtained are compared to landslide history and accuracies for Model 1, Model 2, Model 3 and Model 4 are 66.7, 66.7%, 60% and 22.9% respectively. From the results, rank sum, rating and pairwise comparison can be useful techniques to predict landslide hazard zones

  14. Application of Extreme Value Theory to Crash Data Analysis.

    Science.gov (United States)

    Xu, Lan; Nusholtz, Guy

    2017-11-01

    A parametric model obtained by fitting a set of data to a function generally uses a procedure such as maximum likelihood or least squares. In general this will generate the best estimate for the distribution of the data overall but will not necessarily generate a reasonable estimation for the tail of the distribution unless the function fitted resembles the underlying distribution function. A distribution function can represent an estimate that is significantly different from the actual tail data, while the bulk of the data is reasonably represented by the central part of the fitted distribution. Extreme value theory can be used to improve the predictive capabilities of the fitted function in the tail region. In this study the peak-over-threshold approach from the extreme value theory was utilized to show that it is possible to obtain a better fit of the tail of a distribution than the procedures that use the entire distribution only. Additional constraints, on the current use of the extreme value approach with respect to the selection of the threshold (an estimate of the beginning of the tail region) that minimize the sensitivity to individual data samples associated with the tail section as well as contamination from the central distribution are used. Once the threshold is determined, the maximum likelihood method was used to fit the exceedances with the Generalized Pareto Distribution to obtain the tail distribution. The approach was then used in the analysis of airbag inflator pressure data from tank tests, crash velocity distribution and mass distribution from the field crash data (NASS). From the examples, the extreme (tail) distributions were better estimated with the Generalized Pareto Distribution, than a single overall distribution, along with the probability of the occurrence for a given extreme value, or a rare observation such as a high speed crash. It was concluded that the peak-over-threshold approach from extreme value theory can be a useful tool in

  15. Braking news: link between crash severity and crash avoidance maneuvers

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2012-01-01

    across severity levels were estimated to accommodate the ordered-response nature of severity. The sample used for estimation consisted of data for single-vehicle crashes extracted from the General Estimates System crash database for the period from 2005 to 2009. Results showed the correlation between...... of lower crash severity. These trends suggest that efforts to understand the mechanisms of reactions to different critical events should be made to improve in-vehicle warning systems, promote responsible driving behavior, and design forgiving infrastructures....

  16. Predictive validation of an influenza spread model.

    Directory of Open Access Journals (Sweden)

    Ayaz Hyder

    Full Text Available BACKGROUND: Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. METHODS AND FINDINGS: We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998-1999. Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type. Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. CONCLUSIONS: Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve

  17. Predictive Validation of an Influenza Spread Model

    Science.gov (United States)

    Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

    2013-01-01

    Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive

  18. A GEOGRAPHIC WEIGHTED REGRESSION FOR RURAL HIGHWAYS CRASHES MODELLING USING THE GAUSSIAN AND TRICUBE KERNELS: A CASE STUDY OF USA RURAL HIGHWAYS

    Directory of Open Access Journals (Sweden)

    M. Aghayari

    2017-09-01

    Full Text Available Based on world health organization (WHO report, driving incidents are counted as one of the eight initial reasons for death in the world. The purpose of this paper is to develop a method for regression on effective parameters of highway crashes. In the traditional methods, it was assumed that the data are completely independent and environment is homogenous while the crashes are spatial events which are occurring in geographic space and crashes have spatial data. Spatial data have spatial features such as spatial autocorrelation and spatial non-stationarity in a way working with them is going to be a bit difficult. The proposed method has implemented on a set of records of fatal crashes that have been occurred in highways connecting eight east states of US. This data have been recorded between the years 2007 and 2009. In this study, we have used GWR method with two Gaussian and Tricube kernels. The Number of casualties has been considered as dependent variable and number of persons in crash, road alignment, number of lanes, pavement type, surface condition, road fence, light condition, vehicle type, weather, drunk driver, speed limitation, harmful event, road profile, and junction type have been considered as explanatory variables according to previous studies in using GWR method. We have compered the results of implementation with OLS method. Results showed that R2 for OLS method is 0.0654 and for the proposed method is 0.9196 that implies the proposed GWR is better method for regression in rural highway crashes.

  19. Finding Furfural Hydrogenation Catalysts via Predictive Modelling.

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-09-10

    We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (k(H):k(D)=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R(2)=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model's predictions, demonstrating the validity and value of predictive modelling in catalyst optimization.

  20. Factors influencing pediatric Injury Severity Score and Glasgow Coma Scale in pediatric automobile crashes: results from the Crash Injury Research Engineering Network.

    Science.gov (United States)

    Ehrlich, Peter F; Brown, J Kristine; Sochor, Mark R; Wang, Stewart C; Eichelberger, Martin E

    2006-11-01

    Motor vehicle crashes account for more than 50% of pediatric injuries. Triage of pediatric patients to appropriate centers can be based on the crash/injury characteristics. Pediatric motor vehicle crash/injury characteristics can be determined from an in vitro laboratory using child crash dummies. However, to date, no detailed data with respect to outcomes and crash mechanism have been presented with a pediatric in vivo model. The Crash Injury Research Engineering Network is comprised of 10 level 1 trauma centers. Crashes were examined with regard to age, crash severity (DeltaV), crash direction, restraint use, and airbag deployment. Multiple logistic regression analysis was performed with Injury Severity Score (ISS) and Glasgow Coma Scale (GCS) as outcomes. Standard age groupings (0-4, 5-9, 10-14, and 15-18) were used. The database is biases toward a survivor population with few fatalities. Four hundred sixty-one motor vehicle crashes with 2500 injuries were analyzed (242 boys, 219 girls). Irrespective of age, DeltaV > 30 mph resulted in increased ISS and decreased GCS (eg, for 0-4 years, DeltaV 30: ISS = 19.5, GCS = 10.6; P 15) injuries than did backseat passengers (odds ratio, 1.7; 95% confidence interval, 0.7-3.4). A trend was noted for children younger than 12 years sitting in the front seat to have increased ISS and decreased GCS with airbag deployment but was limited by case number. A reproducible pattern of increased ISS and lower GCS characterized by high severity, lateral crashes in children was noted. Further analysis of the specific injuries as a function and the crash characteristic can help guide management and prevention strategies.

  1. Corporate prediction models, ratios or regression analysis?

    NARCIS (Netherlands)

    Bijnen, E.J.; Wijn, M.F.C.M.

    1994-01-01

    The models developed in the literature with respect to the prediction of a company s failure are based on ratios. It has been shown before that these models should be rejected on theoretical grounds. Our study of industrial companies in the Netherlands shows that the ratios which are used in

  2. Predicting Protein Secondary Structure with Markov Models

    DEFF Research Database (Denmark)

    Fischer, Paul; Larsen, Simon; Thomsen, Claus

    2004-01-01

    we are considering here, is to predict the secondary structure from the primary one. To this end we train a Markov model on training data and then use it to classify parts of unknown protein sequences as sheets, helices or coils. We show how to exploit the directional information contained...... in the Markov model for this task. Classifications that are purely based on statistical models might not always be biologically meaningful. We present combinatorial methods to incorporate biological background knowledge to enhance the prediction performance....

  3. How does Euro NCAP results correlate to real life injury risks - a paired comparison study of car-to-car crashes in Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Lie, A. [Swedish National Road Administration, Borlaenge (Sweden)]|[ Karolinska Institutet (Sweden); Tingvall, C. [Monash University, Accident Research Centre (Australia)

    2001-07-01

    Euro NCAP is a resource for consumers regarding vehicle crash safety. The program also promotes safety developments, and credits car manufacturers focussing on safety. This study, based on real life car to car crashes, shows that the overall indication of the safety level, provided by the crash testing, is a valid prediction, at least when looking at the star rating and severe to fatal injuries. For minor injuries no significant injury risk differences are seen. The cars with three or four stars are approximately 30% safer, compared to two star cars or cars without an Euro NCAP score, in car to car collisions. The good general correlation between injury risk, and Euro NCAP scores is not necessarily similarly good for individual car models. Pedestrian safety and child occupant protection was not studied. (orig.)

  4. Energy based prediction models for building acoustics

    DEFF Research Database (Denmark)

    Brunskog, Jonas

    2012-01-01

    In order to reach robust and simplified yet accurate prediction models, energy based principle are commonly used in many fields of acoustics, especially in building acoustics. This includes simple energy flow models, the framework of statistical energy analysis (SEA) as well as more elaborated...... principles as, e.g., wave intensity analysis (WIA). The European standards for building acoustic predictions, the EN 12354 series, are based on energy flow and SEA principles. In the present paper, different energy based prediction models are discussed and critically reviewed. Special attention is placed...... on underlying basic assumptions, such as diffuse fields, high modal overlap, resonant field being dominant, etc., and the consequences of these in terms of limitations in the theory and in the practical use of the models....

  5. Comparative Study of Bancruptcy Prediction Models

    Directory of Open Access Journals (Sweden)

    Isye Arieshanti

    2013-09-01

    Full Text Available Early indication of bancruptcy is important for a company. If companies aware of  potency of their bancruptcy, they can take a preventive action to anticipate the bancruptcy. In order to detect the potency of a bancruptcy, a company can utilize a a model of bancruptcy prediction. The prediction model can be built using a machine learning methods. However, the choice of machine learning methods should be performed carefully. Because the suitability of a model depends on the problem specifically. Therefore, in this paper we perform a comparative study of several machine leaning methods for bancruptcy prediction. According to the comparative study, the performance of several models that based on machine learning methods (k-NN, fuzzy k-NN, SVM, Bagging Nearest Neighbour SVM, Multilayer Perceptron(MLP, Hybrid of MLP + Multiple Linear Regression, it can be showed that fuzzy k-NN method achieve the best performance with accuracy 77.5%

  6. Prediction Models for Dynamic Demand Response

    Energy Technology Data Exchange (ETDEWEB)

    Aman, Saima; Frincu, Marc; Chelmis, Charalampos; Noor, Muhammad; Simmhan, Yogesh; Prasanna, Viktor K.

    2015-11-02

    As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D2R, which we address in this paper. Our first contribution is the formal definition of D2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D2R. Also, prediction models require just few days’ worth of data indicating that small amounts of

  7. Evaluation of CASP8 model quality predictions

    KAUST Repository

    Cozzetto, Domenico

    2009-01-01

    The model quality assessment problem consists in the a priori estimation of the overall and per-residue accuracy of protein structure predictions. Over the past years, a number of methods have been developed to address this issue and CASP established a prediction category to evaluate their performance in 2006. In 2008 the experiment was repeated and its results are reported here. Participants were invited to infer the correctness of the protein models submitted by the registered automatic servers. Estimates could apply to both whole models and individual amino acids. Groups involved in the tertiary structure prediction categories were also asked to assign local error estimates to each predicted residue in their own models and their results are also discussed here. The correlation between the predicted and observed correctness measures was the basis of the assessment of the results. We observe that consensus-based methods still perform significantly better than those accepting single models, similarly to what was concluded in the previous edition of the experiment. © 2009 WILEY-LISS, INC.

  8. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    Science.gov (United States)

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre throughout the reaction. Deuterium-labelling studies showed a secondary isotope effect (kH:kD=1.5). Further mechanistic studies showed that this transfer hydrogenation follows the so-called monohydride pathway. Using these data, we built a predictive model for 13 of the catalysts, based on 2D and 3D molecular descriptors. We tested and validated the model using the remaining five catalysts (cross-validation, R2=0.913). Then, with this model, the conversion and selectivity were predicted for four completely new ruthenium-carbene complexes. These four catalysts were then synthesized and tested. The results were within 3% of the model’s predictions, demonstrating the validity and value of predictive modelling in catalyst optimization. PMID:23193388

  9. Wind farm production prediction - The Zephyr model

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Giebel, G. [Risoe National Lab., Wind Energy Dept., Roskilde (Denmark); Madsen, H. [IMM (DTU), Kgs. Lyngby (Denmark); Nielsen, T.S. [IMM (DTU), Kgs. Lyngby (Denmark); Joergensen, J.U. [Danish Meteorologisk Inst., Copenhagen (Denmark); Lauersen, L. [Danish Meteorologisk Inst., Copenhagen (Denmark); Toefting, J. [Elsam, Fredericia (DK); Christensen, H.S. [Eltra, Fredericia (Denmark); Bjerge, C. [SEAS, Haslev (Denmark)

    2002-06-01

    This report describes a project - funded by the Danish Ministry of Energy and the Environment - which developed a next generation prediction system called Zephyr. The Zephyr system is a merging between two state-of-the-art prediction systems: Prediktor of Risoe National Laboratory and WPPT of IMM at the Danish Technical University. The numerical weather predictions were generated by DMI's HIRLAM model. Due to technical difficulties programming the system, only the computational core and a very simple version of the originally very complex system were developed. The project partners were: Risoe, DMU, DMI, Elsam, Eltra, Elkraft System, SEAS and E2. (au)

  10. Model predictive controller design of hydrocracker reactors

    OpenAIRE

    GÖKÇE, Dila

    2011-01-01

    This study summarizes the design of a Model Predictive Controller (MPC) in Tüpraş, İzmit Refinery Hydrocracker Unit Reactors. Hydrocracking process, in which heavy vacuum gasoil is converted into lighter and valuable products at high temperature and pressure is described briefly. Controller design description, identification and modeling studies are examined and the model variables are presented. WABT (Weighted Average Bed Temperature) equalization and conversion increase are simulate...

  11. Statistical analysis of vehicle crashes in Mississippi based on crash data from 2010 to 2014.

    Science.gov (United States)

    2017-08-15

    Traffic crash data from 2010 to 2014 were collected by Mississippi Department of Transportation (MDOT) and extracted for the study. Three tasks were conducted in this study: (1) geographic distribution of crashes; (2) descriptive statistics of crash ...

  12. Intelligent geocoding system to locate traffic crashes.

    Science.gov (United States)

    Qin, Xiao; Parker, Steven; Liu, Yi; Graettinger, Andrew J; Forde, Susie

    2013-01-01

    State agencies continue to face many challenges associated with new federal crash safety and highway performance monitoring requirements that use data from multiple and disparate systems across different platforms and locations. On a national level, the federal government has a long-term vision for State Departments of Transportation (DOTs) to report state route and off-state route crash data in a single network. In general, crashes occurring on state-owned or state maintained highways are a priority at the Federal and State level; therefore, state-route crashes are being geocoded by state DOTs. On the other hand, crashes occurring on off-state highway system do not always get geocoded due to limited resources and techniques. Creating and maintaining a statewide crash geographic information systems (GIS) map with state route and non-state route crashes is a complicated and expensive task. This study introduces an automatic crash mapping process, Crash-Mapping Automation Tool (C-MAT), where an algorithm translates location information from a police report crash record to a geospatial map and creates a pinpoint map for all crashes. The algorithm has approximate 83 percent mapping rate. An important application of this work is the ability to associate the mapped crash records to underlying business data, such as roadway inventory and traffic volumes. The integrated crash map is the foundation for effective and efficient crash analyzes to prevent highway crashes. Published by Elsevier Ltd.

  13. Correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists in single-vehicle crashes.

    Science.gov (United States)

    Wang, Chen; Lu, Linjun; Lu, Jian; Wang, Tao

    2016-01-01

    In order to improve motorcycle safety, this article examines the correlation between crash avoidance maneuvers and injury severity sustained by motorcyclists, under multiple precrash conditions. Ten-year crash data for single-vehicle motorcycle crashes from the General Estimates Systems (GES) were analyzed, using partial proportional odds models (i.e., generalized ordered logit models). The modeling results show that "braking (no lock-up)" is associated with a higher probability of increased severity, whereas "braking (lock-up)" is associated with a higher probability of decreased severity, under all precrash conditions. "Steering" is associated with a higher probability of reduced injury severity when other vehicles are encroaching, whereas it is correlated with high injury severity under other conditions. "Braking and steering" is significantly associated with a higher probability of low severity under "animal encounter and object presence," whereas it is surprisingly correlated with high injury severity when motorcycles are traveling off the edge of the road. The results also show that a large number of motorcyclists did not perform any crash avoidance maneuvers or conducted crash avoidance maneuvers that are significantly associated with high injury severity. In general, this study suggests that precrash maneuvers are an important factor associated with motorcyclists' injury severity. To improve motorcycle safety, training/educational programs should be considered to improve safety awareness and adjust driving habits of motorcyclists. Antilock brakes and such systems are also promising, because they could effectively prevent brake lock-up and assist motorcyclists in maneuvering during critical conditions. This study also provides valuable information for the design of motorcycle training curriculum.

  14. Minor Crashes and ‘Whiplash’ in the United States

    Science.gov (United States)

    Bartsch, Adam J.; Gilbertson, Lars G.; Prakash, Vikas; Morr, Douglas R.; Wiechel, John F.

    2008-01-01

    In the United States there is currently a paucity of available real world minor rear crash data with struck vehicle delta-V, or speed change, less than or equal to 15 kilometers per hour. These data are essential as researchers attempt to define ‘whiplash’ injury risk potential in these minor crashes. This study analyzed a new set of 105 U.S. minor rear aligned crashes between passenger vehicles. Mean struck vehicle delta-V and acceleration were 6.3 km/h (s.d. = 2.1 km/h) and 1.4g (s.d. = 0.5g), respectively. A total of 113 struck vehicle occupants were diagnosed within five weeks post-crash with 761 ICD-9-CM complaints and 427 AIS injuries (99.5% AIS1) attributed to the crashes. No striking vehicle occupants reported complaints. The main ICD-9-CM diagnoses were 40.6% cervical, 22.5% lumbar/sacral and 10.2% thoracic and the main AIS1 diagnoses were 29.7% cervical, 23.2% lumbar/sacral and 14.3% thoracic. The diagnosis disparity was mainly due to coding for pre-existing degenerative diagnosis in ICD-9-CM. Degenerative spine conditions were not significant for increased AIS1 injury risk. Surprisingly, many non-‘whiplash’ diagnoses were found. The AIS injury diagnosis distribution and frequency in these minor delta-V crashes did not correspond with previous minor rear crash studies. A prospectively collected and unbiased minor rear crash databank in the model of CIREN or NASS is highly desirable to verify or refute these results for the U.S. population since the current study cohort may have been influenced by litigation. PMID:19026229

  15. Minor crashes and 'whiplash' in the United States.

    Science.gov (United States)

    Bartsch, Adam J; Gilbertson, Lars G; Prakash, Vikas; Morr, Douglas R; Wiechel, John F

    2008-10-01

    In the United States there is currently a paucity of available real world minor rear crash data with struck vehicle delta-V, or speed change, less than or equal to 15 kilometers per hour. These data are essential as researchers attempt to define 'whiplash' injury risk potential in these minor crashes. This study analyzed a new set of 105 U.S. minor rear aligned crashes between passenger vehicles. Mean struck vehicle delta-V and acceleration were 6.3 km/h (s.d. = 2.1 km/h) and 1.4 g (s.d. = 0.5 g), respectively. A total of 113 struck vehicle occupants were diagnosed within five weeks post-crash with 761 ICD-9-CM complaints and 427 AIS injuries (99.5% AIS1) attributed to the crashes. No striking vehicle occupants reported complaints. The main ICD-9-CM diagnoses were 40.6% cervical, 22.5% lumbar/sacral and 10.2% thoracic and the main AIS1 diagnoses were 29.7% cervical, 23.2% lumbar/sacral and 14.3% thoracic. The diagnosis disparity was mainly due to coding for pre-existing degenerative diagnosis in ICD-9-CM. Degenerative spine conditions were not significant for increased AIS1 injury risk. Surprisingly, many non-'whiplash' diagnoses were found. The AIS injury diagnosis distribution and frequency in these minor delta-V crashes did not correspond with previous minor rear crash studies. A prospectively collected and unbiased minor rear crash databank in the model of CIREN or NASS is highly desirable to verify or refute these results for the U.S. population since the current study cohort may have been influenced by litigation.

  16. Alternative states and population crashes in a resource-susceptible-infected model for planktonic parasites and hosts

    NARCIS (Netherlands)

    Gerla, D.J.; Gsell, A.S.; Kooi, B.W.; Ibelings, B.W.; Van Donk, E.; Mooij, W.M.

    2013-01-01

    1. Despite the strong impact parasites can have, only few models of phytoplankton ecology or aquatic food webs have specifically included parasitism. 2. Here, we provide a susceptible-infected model for a diatom-chytrid host–parasite system that explicitly includes nutrients, infected and uninfected

  17. Alternative states and population crashes in a resource-susceptible-infected model for planktonic parasites and hosts

    NARCIS (Netherlands)

    Gerla, D.J.; Gsell, A.S.; Kooi, B.W.; Ibelings, B.W.; Donk, van E.; Mooij, W.M.

    2013-01-01

    1. Despite the strong impact parasites can have, only few models of phytoplankton ecology or aquatic food webs have specifically included parasitism. 2. Here, we provide a susceptible-infected model for a diatom-chytrid hostparasite system that explicitly includes nutrients, infected and uninfected

  18. Multi-Model Ensemble Wake Vortex Prediction

    Science.gov (United States)

    Koerner, Stephan; Holzaepfel, Frank; Ahmad, Nash'at N.

    2015-01-01

    Several multi-model ensemble methods are investigated for predicting wake vortex transport and decay. This study is a joint effort between National Aeronautics and Space Administration and Deutsches Zentrum fuer Luft- und Raumfahrt to develop a multi-model ensemble capability using their wake models. An overview of different multi-model ensemble methods and their feasibility for wake applications is presented. The methods include Reliability Ensemble Averaging, Bayesian Model Averaging, and Monte Carlo Simulations. The methodologies are evaluated using data from wake vortex field experiments.

  19. Structural Integrity Assessment of Reactor Containment Subjected to Aircraft Crash

    International Nuclear Information System (INIS)

    Kim, Junyong; Chang, Yoonsuk

    2013-01-01

    When an accident occurs at the NPP, containment building which acts as the last barrier should be assessed and analyzed structural integrity by internal loading or external loading. On many occasions that can occur in the containment internal such as LOCA(Loss Of Coolant Accident) are already reflected to design. Likewise, there are several kinds of accidents that may occur from the outside of containment such as earthquakes, hurricanes and strong wind. However, aircraft crash that at outside of containment is not reflected yet in domestic because NPP sites have been selected based on the probabilistic method. After intentional aircraft crash such as World Trade Center and Pentagon accident in US, social awareness for safety of infrastructure like NPP was raised world widely and it is time for assessment of aircraft crash in domestic. The object of this paper is assessment of reactor containment subjected to aircraft crash by FEM(Finite Element Method). In this paper, assessment of structural integrity of containment building subjected to certain aircraft crash was carried out. Verification of structure integrity of containment by intentional severe accident. Maximum stress 61.21MPa of horizontal shell crash does not penetrate containment. Research for more realistic results needed by steel reinforced concrete model

  20. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  1. Alcohol and older drivers' crashes.

    Science.gov (United States)

    2014-09-01

    Researchers have examined the effects of alcohol consumption : on older adults functioning, and some have : addressed alcohols effects on older drivers crash risk. : Generally, the findings have shown that alcohol is less : likely to be a fa...

  2. Improving freight crash incident management.

    Science.gov (United States)

    2015-06-01

    The objective of this study was to determine the most effective way to mitigate the effect of freight : crash incidents on Louisiana freeways. Candidate incident management strategies were reviewed from : practice in other states and from those publi...

  3. Crash course in readers' advisory

    CERN Document Server

    Orr, Cynthia

    2014-01-01

    One of the key services librarians provide is helping readers find books they'll enjoy. This ""crash course"" will furnish you with the basic, practical information you need to excel at readers' advisory (RA) for adults and teens.

  4. An Analysis of the Relationship between Casualty Risk Per Crash and Vehicle Mass and Footprint for Model Year 2003-2010 Light-Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Tom P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2018-01-05

    The Department of Energy’s (DOE) Vehicle Technologies Office funds research on development of technologies to improve the fuel economy of both light- and heavy-duty vehicles, including advanced combustion systems, improved batteries and electric drive systems, and new lightweight materials. Of these approaches to increase fuel economy and reduce fuel consumption, reducing vehicle mass through more extensive use of strong lightweight materials is perhaps the easiest and least expensive method; however, there is a concern that reducing vehicle mass may lead to more fatalities. Lawrence Berkeley National Laboratory (LBNL) has conducted several analyses to better understand the relationship between vehicle mass, size and safety, in order to ameliorate concerns that down-weighting vehicles will inherently lead to more fatalities. These analyses include recreating the regression analyses conducted by the National Highway Traffic Safety Administration (NHTSA) that estimate the relationship between mass reduction and U.S. societal fatality risk per vehicle mile of travel (VMT), while holding vehicle size (i.e. footprint, wheelbase times track width) constant; these analyses are referred to as LBNL Phase 1 analysis. In addition, LBNL has conducted additional analysis of the relationship between mass and the two components of risk per VMT, crash frequency (crashes per VMT) and risk once a crash has occurred (risk per crash); these analyses are referred to as LBNL Phase 2 analysis.

  5. PREDICTIVE CAPACITY OF ARCH FAMILY MODELS

    Directory of Open Access Journals (Sweden)

    Raphael Silveira Amaro

    2016-03-01

    Full Text Available In the last decades, a remarkable number of models, variants from the Autoregressive Conditional Heteroscedastic family, have been developed and empirically tested, making extremely complex the process of choosing a particular model. This research aim to compare the predictive capacity, using the Model Confidence Set procedure, than five conditional heteroskedasticity models, considering eight different statistical probability distributions. The financial series which were used refers to the log-return series of the Bovespa index and the Dow Jones Industrial Index in the period between 27 October 2008 and 30 December 2014. The empirical evidences showed that, in general, competing models have a great homogeneity to make predictions, either for a stock market of a developed country or for a stock market of a developing country. An equivalent result can be inferred for the statistical probability distributions that were used.

  6. Alcator C-Mod predictive modeling

    International Nuclear Information System (INIS)

    Pankin, Alexei; Bateman, Glenn; Kritz, Arnold; Greenwald, Martin; Snipes, Joseph; Fredian, Thomas

    2001-01-01

    Predictive simulations for the Alcator C-mod tokamak [I. Hutchinson et al., Phys. Plasmas 1, 1511 (1994)] are carried out using the BALDUR integrated modeling code [C. E. Singer et al., Comput. Phys. Commun. 49, 275 (1988)]. The results are obtained for temperature and density profiles using the Multi-Mode transport model [G. Bateman et al., Phys. Plasmas 5, 1793 (1998)] as well as the mixed-Bohm/gyro-Bohm transport model [M. Erba et al., Plasma Phys. Controlled Fusion 39, 261 (1997)]. The simulated discharges are characterized by very high plasma density in both low and high modes of confinement. The predicted profiles for each of the transport models match the experimental data about equally well in spite of the fact that the two models have different dimensionless scalings. Average relative rms deviations are less than 8% for the electron density profiles and 16% for the electron and ion temperature profiles

  7. Motorcycle crashes potentially preventable by three crash avoidance technologies on passenger vehicles.

    Science.gov (United States)

    Teoh, Eric R

    2018-07-04

    The objective of this study was to identify and quantify the motorcycle crash population that would be potential beneficiaries of 3 crash avoidance technologies recently available on passenger vehicles. Two-vehicle crashes between a motorcycle and a passenger vehicle that occurred in the United States during 2011-2015 were classified by type, with consideration of the functionality of 3 classes of passenger vehicle crash avoidance technologies: frontal crash prevention, lane maintenance, and blind spot detection. Results were expressed as the percentage of crashes potentially preventable by each type of technology, based on all known types of 2-vehicle crashes and based on all crashes involving motorcycles. Frontal crash prevention had the largest potential to prevent 2-vehicle motorcycle crashes with passenger vehicles. The 3 technologies in sum had the potential to prevent 10% of fatal 2-vehicle crashes and 23% of police-reported crashes. However, because 2-vehicle crashes with a passenger vehicle represent fewer than half of all motorcycle crashes, these technologies represent a potential to avoid 4% of all fatal motorcycle crashes and 10% of all police-reported motorcycle crashes. Refining the ability of passenger vehicle crash avoidance systems to detect motorcycles represents an opportunity to improve motorcycle safety. Expanding the capabilities of these technologies represents an even greater opportunity. However, even fully realizing these opportunities can affect only a minority of motorcycle crashes and does not change the need for other motorcycle safety countermeasures such as helmets, universal helmet laws, and antilock braking systems.

  8. Modelling the predictive performance of credit scoring

    Directory of Open Access Journals (Sweden)

    Shi-Wei Shen

    2013-07-01

    Research purpose: The purpose of this empirical paper was to examine the predictive performance of credit scoring systems in Taiwan. Motivation for the study: Corporate lending remains a major business line for financial institutions. However, in light of the recent global financial crises, it has become extremely important for financial institutions to implement rigorous means of assessing clients seeking access to credit facilities. Research design, approach and method: Using a data sample of 10 349 observations drawn between 1992 and 2010, logistic regression models were utilised to examine the predictive performance of credit scoring systems. Main findings: A test of Goodness of fit demonstrated that credit scoring models that incorporated the Taiwan Corporate Credit Risk Index (TCRI, micro- and also macroeconomic variables possessed greater predictive power. This suggests that macroeconomic variables do have explanatory power for default credit risk. Practical/managerial implications: The originality in the study was that three models were developed to predict corporate firms’ defaults based on different microeconomic and macroeconomic factors such as the TCRI, asset growth rates, stock index and gross domestic product. Contribution/value-add: The study utilises different goodness of fits and receiver operator characteristics during the examination of the robustness of the predictive power of these factors.

  9. Comparison of two ordinal prediction models

    DEFF Research Database (Denmark)

    Kattan, Michael W; Gerds, Thomas A

    2015-01-01

    system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared...... on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. RESULTS: We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We...... demonstrate our algorithm with a prostate cancer staging system example. CONCLUSION: We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models....

  10. Analysis of delta velocity and PDOF by means of collision partner and structural involvement in real-life crash pulses with modern passenger cars.

    Science.gov (United States)

    Iraeus, Johan; Lindquist, Mats

    2014-01-01

    In the widely used National Automotive Sampling System (NASS)-Crashworthiness Data System (CDS) database, summary metrics that describe crashes are available. Crash angle or principal direction of force (PDOF) is estimated by the crash examiner and velocity changes (ΔV) in the x- and y-directions are calculated by the WinSMASH computer program using PDOF and results from rigid barrier crash testing combined with deformations of the crashed car. In recent years, results from event data recorders (EDRs) have been added to the database. The aim of this study is to compare both PDOF and ΔV between EDR measurements and WinSMASH calculations. NASS-CDS inclusion criteria were model-year 2000 through 2010 automobiles, frontal crashes with ΔV higher than 16 km/h, and the pulse entirely recorded in the EDR module. This resulted in 649 cases. The subject vehicles were further examined and characterized with regard to frontal structure engagement (large or small overlap) as well as collision properties of the partner (impact location; front, side, or back) or object. The EDR crash angle was calculated as the angle between the lateral and longitudinal ΔV at the time of peak longitudinal ΔV. This angle was compared to the NASS-CDS investigator's estimated PDOF with regard to structural engagement and the collision partner or object. Multiple linear regression was used to establish adjustment factors on ΔV and crash angle between the results calculated based on EDR recorded data and that estimated in NASS-CDS. According to this study, simulation in the newest WinSMASH version (2008) underestimates EDR ΔV by 11 percent for large overlap crashes and 17 percent for small overlap impacts. The older WinSMASH version, used prior to 2008, underestimated each one of these two groups by an additional 7 percentage points. Another significant variable to enhance the prediction was whether the crash examiner had reported the WinSMASH estimated ΔV as low or high. In this study, none

  11. A market systems analysis of the U.S. Sport Utility Vehicle market considering frontal crash safety technology and policy.

    Science.gov (United States)

    Hoffenson, Steven; Frischknecht, Bart D; Papalambros, Panos Y

    2013-01-01

    Active safety features and adjustments to the New Car Assessment Program (NCAP) consumer-information crash tests have the potential to decrease the number of serious traffic injuries each year, according to previous studies. However, literature suggests that risk reductions, particularly in the automotive market, are often accompanied by adjusted consumer risk tolerance, and so these potential safety benefits may not be fully realized due to changes in consumer purchasing or driving behavior. This article approaches safety in the new vehicle market, particularly in the Sport Utility Vehicle and Crossover Utility Vehicle segments, from a market systems perspective. Crash statistics and simulations are used to predict the effects of design and policy changes on occupant crash safety, and discrete choice experiments are conducted to estimate the values consumers place on vehicle attributes. These models are combined in a market simulation that forecasts how consumers respond to the available vehicle alternatives, resulting in predictions of the market share of each vehicle and how the change in fleet mixture influences societal outcomes including injuries, fuel consumption, and firm profits. The model is tested for a scenario where active safety features are implemented across the new vehicle fleet and a scenario where the U.S. frontal NCAP test speed is modified. While results exhibit evidence of consumer risk adjustment, they support adding active safety features and lowering the NCAP frontal test speed, as these changes are predicted to improve the welfare of both firms and society. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Predictive analytics can support the ACO model.

    Science.gov (United States)

    Bradley, Paul

    2012-04-01

    Predictive analytics can be used to rapidly spot hard-to-identify opportunities to better manage care--a key tool in accountable care. When considering analytics models, healthcare providers should: Make value-based care a priority and act on information from analytics models. Create a road map that includes achievable steps, rather than major endeavors. Set long-term expectations and recognize that the effectiveness of an analytics program takes time, unlike revenue cycle initiatives that may show a quick return.

  13. Predictive performance models and multiple task performance

    Science.gov (United States)

    Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

    1989-01-01

    Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

  14. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  15. Distributed Model Predictive Control via Dual Decomposition

    DEFF Research Database (Denmark)

    Biegel, Benjamin; Stoustrup, Jakob; Andersen, Palle

    2014-01-01

    This chapter presents dual decomposition as a means to coordinate a number of subsystems coupled by state and input constraints. Each subsystem is equipped with a local model predictive controller while a centralized entity manages the subsystems via prices associated with the coupling constraints...

  16. Validation of a method to evaluate future impact of road safety interventions, a comparison between fatal passenger car crashes in Sweden 2000 and 2010.

    Science.gov (United States)

    Strandroth, Johan

    2015-03-01

    When targeting a society free from serious and fatal road-traffic injuries, it has been a common practice in many countries and organizations to set up time-limited and quantified targets for the reduction of fatalities and injuries. In setting these targets EU and other organizations have recognized the importance to monitor and predict the development toward the target as well as the efficiency of road safety policies and interventions. This study aims to validate a method to forecast future road safety challenges by applying it to the fatal crashes in Sweden in 2000 and using the method to explain the change in fatalities based on the road safety interventions made until 2010. The estimation of the method is then compared to the true outcome in 2010. The aim of this study was to investigate if a residual of crashes produced by a partial analysis could constitute a sufficient base to describe the characteristics of future crashes. show that out of the 332 car occupants killed in 2000, 197 were estimated to constitute the residual in 2010. Consequently, 135 fatalities from 2000 were estimated by the model to be prevented by 2010. That is a predicted reduction of 41% compared to the reduction in the real outcome of 53%, from 332 in 2000 to 156 in 2010. The method was found able to generate a residual of crashes in 2010 from the crashes in 2000 that had a very similar nature, with regards to crash type, as the true outcome of 2010. It was also found suitable to handle double counting and system effects. However, future research is needed in order to investigate how external factors as well as random and systematic variation should be taken into account in a reliable manner. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. A stepwise model to predict monthly streamflow

    Science.gov (United States)

    Mahmood Al-Juboori, Anas; Guven, Aytac

    2016-12-01

    In this study, a stepwise model empowered with genetic programming is developed to predict the monthly flows of Hurman River in Turkey and Diyalah and Lesser Zab Rivers in Iraq. The model divides the monthly flow data to twelve intervals representing the number of months in a year. The flow of a month, t is considered as a function of the antecedent month's flow (t - 1) and it is predicted by multiplying the antecedent monthly flow by a constant value called K. The optimum value of K is obtained by a stepwise procedure which employs Gene Expression Programming (GEP) and Nonlinear Generalized Reduced Gradient Optimization (NGRGO) as alternative to traditional nonlinear regression technique. The degree of determination and root mean squared error are used to evaluate the performance of the proposed models. The results of the proposed model are compared with the conventional Markovian and Auto Regressive Integrated Moving Average (ARIMA) models based on observed monthly flow data. The comparison results based on five different statistic measures show that the proposed stepwise model performed better than Markovian model and ARIMA model. The R2 values of the proposed model range between 0.81 and 0.92 for the three rivers in this study.

  18. The Asian Correction Can Be Quantitatively Forecasted Using a Statistical Model of Fusion-Fission Processes.

    Science.gov (United States)

    Teh, Boon Kin; Cheong, Siew Ann

    2016-01-01

    The Global Financial Crisis of 2007-2008 wiped out US$37 trillions across global financial markets, this value is equivalent to the combined GDPs of the United States and the European Union in 2014. The defining moment of this crisis was the failure of Lehman Brothers, which precipitated the October 2008 crash and the Asian Correction (March 2009). Had the Federal Reserve seen these crashes coming, they might have bailed out Lehman Brothers, and prevented the crashes altogether. In this paper, we show that some of these market crashes (like the Asian Correction) can be predicted, if we assume that a large number of adaptive traders employing competing trading strategies. As the number of adherents for some strategies grow, others decline in the constantly changing strategy space. When a strategy group grows into a giant component, trader actions become increasingly correlated and this is reflected in the stock price. The fragmentation of this giant component will leads to a market crash. In this paper, we also derived the mean-field market crash forecast equation based on a model of fusions and fissions in the trading strategy space. By fitting the continuous returns of 20 stocks traded in Singapore Exchange to the market crash forecast equation, we obtain crash predictions ranging from end October 2008 to mid-February 2009, with early warning four to six months prior to the crashes.

  19. The Asian Correction Can Be Quantitatively Forecasted Using a Statistical Model of Fusion-Fission Processes.

    Directory of Open Access Journals (Sweden)

    Boon Kin Teh

    Full Text Available The Global Financial Crisis of 2007-2008 wiped out US$37 trillions across global financial markets, this value is equivalent to the combined GDPs of the United States and the European Union in 2014. The defining moment of this crisis was the failure of Lehman Brothers, which precipitated the October 2008 crash and the Asian Correction (March 2009. Had the Federal Reserve seen these crashes coming, they might have bailed out Lehman Brothers, and prevented the crashes altogether. In this paper, we show that some of these market crashes (like the Asian Correction can be predicted, if we assume that a large number of adaptive traders employing competing trading strategies. As the number of adherents for some strategies grow, others decline in the constantly changing strategy space. When a strategy group grows into a giant component, trader actions become increasingly correlated and this is reflected in the stock price. The fragmentation of this giant component will leads to a market crash. In this paper, we also derived the mean-field market crash forecast equation based on a model of fusions and fissions in the trading strategy space. By fitting the continuous returns of 20 stocks traded in Singapore Exchange to the market crash forecast equation, we obtain crash predictions ranging from end October 2008 to mid-February 2009, with early warning four to six months prior to the crashes.

  20. A data mining approach to investigate the factors influencing the crash severity of motorcycle pillion passengers.

    Science.gov (United States)

    Tavakoli Kashani, Ali; Rabieyan, Rahim; Besharati, Mohammad Mehdi

    2014-12-01

    Motorcycle passengers comprise a considerable proportion of traffic crash victims. During a 5 year period (2006-2010) in Iran, an average of 3.4 pillion passengers are killed daily due to motorcycle crashes. This study investigated the main factors influencing crash severity of this group of road users. The Classification and Regression Trees (CART) method was employed to analyze the injury severity of pillion passengers in Iran over a 4 y ear period (2009-2012). The predictive accuracy of the model built with a total of 16 variables was 74%, which showed a considerable improvement compared to previous studies. The results indicate that area type, land use, and injured part of the body (head, neck, etc.) are the most influential factors affecting the fatality of motorcycle passengers. Results also show that helmet usage could reduce the fatality risk among motorcycle passengers by 28%. The findings of this study might help develop more targeted countermeasures to reduce the death rate of motorcycle pillion passengers. Copyright © 2014 Elsevier Ltd. All rights reserved.

  1. The non-resonant kink modes triggering strong sawtooth-like crashes in the EAST tokamak

    Science.gov (United States)

    Li, Erzhong; Igochine, V.; Dumbrajs, O.; Xu, L.; Chen, K.; Shi, T.; Hu, L.

    2014-12-01

    Evolution of the safety factor (q) profile during L-H transitions in the Experimental Advanced Superconducting Tokamak (EAST) was accompanied by strong core crashes prior to regular sawtooth behavior. These crashes appeared in the absence of q = 1 (q is the safety factor) rational surface inside the plasma. Analysis indicates that the m/n = 2/1 tearing mode is destabilized and phase-locked with the m/n = 1/1 non-resonant kink mode (the q = 1 rational surface is absent) due to the self-consistent evolution of plasma profiles as the L-H transition occurs (m and n are the poloidal and toroidal mode numbers, respectively). The growing m/n = 1/1 mode destabilizes the m/n = 2/2 kink mode which eventually triggers the strong crash due to an anomalous heat conductivity, as predicted by the transport model of stochastic magnetic fields using experimental parameters. It is also shown that the magnetic topology changes with the amplitude of m/n = 2/2 mode and the value of center safety factor in a reasonable range.

  2. [The significance of the results of crash-tests with the use of the models of the pedestrians' lower extremities for the prevention of the traffic road accidents].

    Science.gov (United States)

    Smirenin, S A; Fetisov, V A; Grigoryan, V G; Gusarov, A A; Kucheryavets, Yu O

    The disabling injuries inflicted during road traffic accidents (RTA) create a serious challenge for the public health services and are at the same time a major socio-economic problem in the majority of the countries throughout the world. The injuries to the lower extremities of the pedestrians make up the largest fraction of the total number of the non-lethal RTA injuries. Most of them are responsible for the considerable deterioration of the quality of life for the participants in the accidents during the subsequent period. The objective of the present study was to summarize the currently available results of experimental testing of the biomechanical models of the pedestrians' lower extremities in the framework of the program for the prevention of the road traffic accidents as proposed by the World Health Organization (WHO, 2004). The European Enhanced Safety Vehicle Committee (EEVC) has developed a series of crash-tests with the use of the models of the pedestrians' lower extremities simulating the vehicle bumper-pedestrian impact. The models are intended for the assessment of the risk of the tibia fractures and the injuries to the knee joint ligaments. The experts of EEVC proposed the biomechanical criteria for the acceleration of the knee and talocrural parts of the lower limbs as well as for the shear displacement of the knee and knee-bending angle. The engineering solution of this problem is based on numerous innovation proposals being implemented in the machine-building industry with the purpose of reducing the stiffness of structural elements of the bumper and other front components of a modern vehicle designed to protect the pedestrians from severe injuries that can be inflicted in the road traffic accidents. The activities of the public health authorities (in the first place, bureaus of forensic medical expertise and analogous facilities) have a direct bearing on the solution of the problem of control of road traffic injuries because they are possessed of

  3. Crash protectiveness to occupant injury and vehicle damage: An investigation on major car brands.

    Science.gov (United States)

    Huang, Helai; Li, Chunyang; Zeng, Qiang

    2016-01-01

    This study sets out to investigate vehicles' crash protectiveness on occupant injury and vehicle damage, which can be deemed as an extension of the traditional crash worthiness. A Bayesian bivariate hierarchical ordered logistic (BVHOL) model is developed to estimate the occupant protectiveness (OP) and vehicle protectiveness (VP) of 23 major car brands in Florida, with considering vehicles' crash aggressivity and controlling external factors. The proposed model not only takes over the strength of the existing hierarchical ordered logistic (HOL) model, i.e. specifying the order characteristics of crash outcomes and cross-crash heterogeneities, but also accounts for the correlation between the two crash responses, driver injury and vehicle damage. A total of 7335 two-vehicle-crash records with 14,670 cars involved in Florida are used for the investigation. From the estimation results, it's found that most of the luxury cars such as Cadillac, Volvo and Lexus possess excellent OP and VP while some brands such as KIA and Saturn perform very badly in both aspects. The ranks of the estimated safety performance indices are even compared to the counterparts in Huang et al. study [Huang, H., Hu, S., Abdel-Aty, M., 2014. Indexing crash worthiness and crash aggressivity by major car brands. Safety Science 62, 339-347]. The results show that the rank of occupant protectiveness index (OPI) is relatively coherent with that of crash worthiness index, but the ranks of crash aggressivity index in both studies is more different from each other. Meanwhile, a great discrepancy between the OPI rank and that of vehicle protectiveness index is found. What's more, the results of control variables and hyper-parameters estimation as well as comparison to HOL models with separate or identical threshold errors, demonstrate the validity and advancement of the proposed model and the robustness of the estimated OP and VP. Copyright © 2015 Elsevier Ltd. All rights reserved.

  4. Electrostatic ion thrusters - towards predictive modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kalentev, O.; Matyash, K.; Duras, J.; Lueskow, K.F.; Schneider, R. [Ernst-Moritz-Arndt Universitaet Greifswald, D-17489 (Germany); Koch, N. [Technische Hochschule Nuernberg Georg Simon Ohm, Kesslerplatz 12, D-90489 Nuernberg (Germany); Schirra, M. [Thales Electronic Systems GmbH, Soeflinger Strasse 100, D-89077 Ulm (Germany)

    2014-02-15

    The development of electrostatic ion thrusters so far has mainly been based on empirical and qualitative know-how, and on evolutionary iteration steps. This resulted in considerable effort regarding prototype design, construction and testing and therefore in significant development and qualification costs and high time demands. For future developments it is anticipated to implement simulation tools which allow for quantitative prediction of ion thruster performance, long-term behavior and space craft interaction prior to hardware design and construction. Based on integrated numerical models combining self-consistent kinetic plasma models with plasma-wall interaction modules a new quality in the description of electrostatic thrusters can be reached. These open the perspective for predictive modeling in this field. This paper reviews the application of a set of predictive numerical modeling tools on an ion thruster model of the HEMP-T (High Efficiency Multi-stage Plasma Thruster) type patented by Thales Electron Devices GmbH. (copyright 2014 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  5. An Intelligent Model for Stock Market Prediction

    Directory of Open Access Journals (Sweden)

    IbrahimM. Hamed

    2012-08-01

    Full Text Available This paper presents an intelligent model for stock market signal prediction using Multi-Layer Perceptron (MLP Artificial Neural Networks (ANN. Blind source separation technique, from signal processing, is integrated with the learning phase of the constructed baseline MLP ANN to overcome the problems of prediction accuracy and lack of generalization. Kullback Leibler Divergence (KLD is used, as a learning algorithm, because it converges fast and provides generalization in the learning mechanism. Both accuracy and efficiency of the proposed model were confirmed through the Microsoft stock, from wall-street market, and various data sets, from different sectors of the Egyptian stock market. In addition, sensitivity analysis was conducted on the various parameters of the model to ensure the coverage of the generalization issue. Finally, statistical significance was examined using ANOVA test.

  6. Predictive Models, How good are they?

    DEFF Research Database (Denmark)

    Kasch, Helge

    The WAD grading system has been used for more than 20 years by now. It has shown long-term viability, but with strengths and limitations. New bio-psychosocial assessment of the acute whiplash injured subject may provide better prediction of long-term disability and pain. Furthermore, the emerging......-up. It is important to obtain prospective identification of the relevant risk underreported disability could, if we were able to expose these hidden “risk-factors” during our consultations, provide us with better predictive models. New data from large clinical studies will present exciting new genetic risk markers...

  7. Human fatigue and the crash of the airship Italia

    Directory of Open Access Journals (Sweden)

    Gregg A. Bendrick

    2016-07-01

    Full Text Available The airship Italia, commanded by General Umberto Nobile, crashed during its return flight from the North Pole in 1928. The cause of the accident was never satisfactorily explained. We present evidence that the crash may have been fatigue-related. Nobile's memoirs indicate that at the time of the crash he had been awake for at least 72 h. Sleep deprivation impairs multiple aspects of cognitive functioning necessary for exploration missions. Just prior to the crash, Nobile made three command errors, all of which are of types associated with inadequate sleep. First, he ordered a release of lift gas when he should have restarted engines (an example of incorrect data synthesis, with deterioration of divergent thinking; second, he inappropriately ordered the ship above the cloud layer (a deficiency in the assessment of relative risks; and third, he remained above the cloud layer for a prolonged period of time (examples of attention to secondary problems, and calculation problems. We argue that as a result of these three errors, which would not be expected from such an experienced commander, there was no longer enough static lift to maintain level flight when the ship went below the cloud layer. Applying Circadian Performance Simulation Software to the sleep–wake patterns described by Nobile in his memoirs, we found that the predicted performance for someone awake as long as he had been is extremely low. This supports the historical evidence that human fatigue contributed to the crash of the Italia.

  8. NONLINEAR MODEL PREDICTIVE CONTROL OF CHEMICAL PROCESSES

    Directory of Open Access Journals (Sweden)

    SILVA R. G.

    1999-01-01

    Full Text Available A new algorithm for model predictive control is presented. The algorithm utilizes a simultaneous solution and optimization strategy to solve the model's differential equations. The equations are discretized by equidistant collocation, and along with the algebraic model equations are included as constraints in a nonlinear programming (NLP problem. This algorithm is compared with the algorithm that uses orthogonal collocation on finite elements. The equidistant collocation algorithm results in simpler equations, providing a decrease in computation time for the control moves. Simulation results are presented and show a satisfactory performance of this algorithm.

  9. A statistical model for predicting muscle performance

    Science.gov (United States)

    Byerly, Diane Leslie De Caix

    The objective of these studies was to develop a capability for predicting muscle performance and fatigue to be utilized for both space- and ground-based applications. To develop this predictive model, healthy test subjects performed a defined, repetitive dynamic exercise to failure using a Lordex spinal machine. Throughout the exercise, surface electromyography (SEMG) data were collected from the erector spinae using a Mega Electronics ME3000 muscle tester and surface electrodes placed on both sides of the back muscle. These data were analyzed using a 5th order Autoregressive (AR) model and statistical regression analysis. It was determined that an AR derived parameter, the mean average magnitude of AR poles, significantly correlated with the maximum number of repetitions (designated Rmax) that a test subject was able to perform. Using the mean average magnitude of AR poles, a test subject's performance to failure could be predicted as early as the sixth repetition of the exercise. This predictive model has the potential to provide a basis for improving post-space flight recovery, monitoring muscle atrophy in astronauts and assessing the effectiveness of countermeasures, monitoring astronaut performance and fatigue during Extravehicular Activity (EVA) operations, providing pre-flight assessment of the ability of an EVA crewmember to perform a given task, improving the design of training protocols and simulations for strenuous International Space Station assembly EVA, and enabling EVA work task sequences to be planned enhancing astronaut performance and safety. Potential ground-based, medical applications of the predictive model include monitoring muscle deterioration and performance resulting from illness, establishing safety guidelines in the industry for repetitive tasks, monitoring the stages of rehabilitation for muscle-related injuries sustained in sports and accidents, and enhancing athletic performance through improved training protocols while reducing

  10. Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

    Directory of Open Access Journals (Sweden)

    Cecilie Røe

    2015-01-01

    Full Text Available The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury model based prediction, from the Medical Research Council (MRC. Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic (age, GCS score, and pupil reactivity to light, as well as with additional CT findings (CRASH CT. Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7 years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR for mortality was 2.65. Unfavorable outcome (GOSE < 5 was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI.

  11. Mortality and One-Year Functional Outcome in Elderly and Very Old Patients with Severe Traumatic Brain Injuries: Observed and Predicted

    Science.gov (United States)

    Røe, Cecilie; Skandsen, Toril; Manskow, Unn; Ader, Tiina; Anke, Audny

    2015-01-01

    The aim of the present study was to evaluate mortality and functional outcome in old and very old patients with severe traumatic brain injury (TBI) and compare to the predicted outcome according to the internet based CRASH (Corticosteroid Randomization After Significant Head injury) model based prediction, from the Medical Research Council (MRC). Methods. Prospective, national multicenter study including patients with severe TBI ≥65 years. Predicted mortality and outcome were calculated based on clinical information (CRASH basic) (age, GCS score, and pupil reactivity to light), as well as with additional CT findings (CRASH CT). Observed 14-day mortality and favorable/unfavorable outcome according to the Glasgow Outcome Scale at one year was compared to the predicted outcome according to the CRASH models. Results. 97 patients, mean age 75 (SD 7) years, 64% men, were included. Two patients were lost to follow-up; 48 died within 14 days. The predicted versus the observed odds ratio (OR) for mortality was 2.65. Unfavorable outcome (GOSE < 5) was observed at one year follow-up in 72% of patients. The CRASH models predicted unfavorable outcome in all patients. Conclusion. The CRASH model overestimated mortality and unfavorable outcome in old and very old Norwegian patients with severe TBI. PMID:26688614

  12. Compulsive Cell Phone Use and History of Motor Vehicle Crash

    Science.gov (United States)

    O’Connor, Stephen S.; Whitehill, Jennifer M.; King, Kevin M.; Kernic, Mary A.; Boyle, Linda Ng; Bresnahan, Brian; Mack, Christopher D.; Ebel, Beth E.

    2013-01-01

    Introduction Few studies have examined the psychological factors underlying the association between cell phone use and motor vehicle crash. We sought to examine the factor structure and convergent validity of a measure of problematic cell phone use and explore whether compulsive cell phone use is associated with a history of motor vehicle crash. Methods We recruited a sample of 383 undergraduate college students to complete an on-line assessment that included cell phone use and driving history. We explored the dimensionality of the Cell Phone Overuse Scale (CPOS) using factor analytic methods. Ordinary least squares regression models were used to examine associations between identified subscales and measures of impulsivity, alcohol use, and anxious relationship style to establish convergent validity. We used negative binomial regression models to investigate associations between the CPOS and motor vehicle crash incidence. Results We found the CPOS to be comprised of four subscales: anticipation, activity interfering, emotional reaction, and problem recognition. Each displayed significant associations with aspects of impulsivity, problematic alcohol use, and anxious relationship style characteristics. Only the anticipation subscale demonstrated statistically significant associations with reported motor vehicle crash incidence, controlling for clinical and demographic characteristics (RR 1.13, CI 1.01 to 1.26). For each one-point increase on the 6-point anticipation subscale, risk for previous motor vehicle crash increased by 13%. Conclusions Crash risk is strongly associated with heightened anticipation about incoming phone calls or messages. The mean score on the CPOS is associated with increased risk of motor vehicle crash but does not reach statistical significance. PMID:23910571

  13. Compulsive cell phone use and history of motor vehicle crash.

    Science.gov (United States)

    O'Connor, Stephen S; Whitehill, Jennifer M; King, Kevin M; Kernic, Mary A; Boyle, Linda Ng; Bresnahan, Brian W; Mack, Christopher D; Ebel, Beth E

    2013-10-01

    Few studies have examined the psychological factors underlying the association between cell phone use and motor vehicle crash. We sought to examine the factor structure and convergent validity of a measure of problematic cell phone use, and to explore whether compulsive cell phone use is associated with a history of motor vehicle crash. We recruited a sample of 383 undergraduate college students to complete an online assessment that included cell phone use and driving history. We explored the dimensionality of the Cell Phone Overuse Scale (CPOS) using factor analytic methods. Ordinary least-squares regression models were used to examine associations between identified subscales and measures of impulsivity, alcohol use, and anxious relationship style, to establish convergent validity. We used negative binomial regression models to investigate associations between the CPOS and motor vehicle crash incidence. We found the CPOS to be composed of four subscales: anticipation, activity interfering, emotional reaction, and problem recognition. Each displayed significant associations with aspects of impulsivity, problematic alcohol use, and anxious relationship style characteristics. Only the anticipation subscale demonstrated statistically significant associations with reported motor vehicle crash incidence, controlling for clinical and demographic characteristics (relative ratio, 1.13; confidence interval, 1.01-1.26). For each 1-point increase on the 6-point anticipation subscale, risk for previous motor vehicle crash increased by 13%. Crash risk is strongly associated with heightened anticipation about incoming phone calls or messages. The mean score on the CPOS is associated with increased risk of motor vehicle crash but does not reach statistical significance. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  14. General aviation crash safety program at Langley Research Center

    Science.gov (United States)

    Thomson, R. G.

    1976-01-01

    The purpose of the crash safety program is to support development of the technology to define and demonstrate new structural concepts for improved crash safety and occupant survivability in general aviation aircraft. The program involves three basic areas of research: full-scale crash simulation testing, nonlinear structural analyses necessary to predict failure modes and collapse mechanisms of the vehicle, and evaluation of energy absorption concepts for specific component design. Both analytical and experimental methods are being used to develop expertise in these areas. Analyses include both simplified procedures for estimating energy absorption capabilities and more complex computer programs for analysis of general airframe response. Full-scale tests of typical structures as well as tests on structural components are being used to verify the analyses and to demonstrate improved design concepts.

  15. Creating pedestrian crash scenarios in a driving simulator environment.

    Science.gov (United States)

    Chrysler, Susan T; Ahmad, Omar; Schwarz, Chris W

    2015-01-01

    In 2012 in the United States, pedestrian injuries accounted for 3.3% of all traffic injuries but, disproportionately, pedestrian fatalities accounted for roughly 14% of traffic-related deaths (NHTSA 2014 ). In many other countries, pedestrians make up more than 50% of those injured and killed in crashes. This research project examined driver response to crash-imminent situations involving pedestrians in a high-fidelity, full-motion driving simulator. This article presents a scenario development method and discusses experimental design and control issues in conducting pedestrian crash research in a simulation environment. Driving simulators offer a safe environment in which to test driver response and offer the advantage of having virtual pedestrian models that move realistically, unlike test track studies, which by nature must use pedestrian dummies on some moving track. An analysis of pedestrian crash trajectories, speeds, roadside features, and pedestrian behavior was used to create 18 unique crash scenarios representative of the most frequent and most costly crash types. For the study reported here, we only considered scenarios where the car is traveling straight because these represent the majority of fatalities. We manipulated driver expectation of a pedestrian both by presenting intersection and mid-block crossing as well as by using features in the scene to direct the driver's visual attention toward or away from the crossing pedestrian. Three visual environments for the scenarios were used to provide a variety of roadside environments and speed: a 20-30 mph residential area, a 55 mph rural undivided highway, and a 40 mph urban area. Many variables of crash situations were considered in selecting and developing the scenarios, including vehicle and pedestrian movements; roadway and roadside features; environmental conditions; and characteristics of the pedestrian, driver, and vehicle. The driving simulator scenarios were subjected to iterative testing to

  16. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to

  17. Neuro-fuzzy modeling in bankruptcy prediction

    Directory of Open Access Journals (Sweden)

    Vlachos D.

    2003-01-01

    Full Text Available For the past 30 years the problem of bankruptcy prediction had been thoroughly studied. From the paper of Altman in 1968 to the recent papers in the '90s, the progress of prediction accuracy was not satisfactory. This paper investigates an alternative modeling of the system (firm, combining neural networks and fuzzy controllers, i.e. using neuro-fuzzy models. Classical modeling is based on mathematical models that describe the behavior of the firm under consideration. The main idea of fuzzy control, on the other hand, is to build a model of a human control expert who is capable of controlling the process without thinking in a mathematical model. This control expert specifies his control action in the form of linguistic rules. These control rules are translated into the framework of fuzzy set theory providing a calculus, which can stimulate the behavior of the control expert and enhance its performance. The accuracy of the model is studied using datasets from previous research papers.

  18. Predictive Models for Carcinogenicity and Mutagenicity ...

    Science.gov (United States)

    Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

  19. Validated predictive modelling of the environmental resistome.

    Science.gov (United States)

    Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

    2015-06-01

    Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

  20. Nonlinear model predictive control theory and algorithms

    CERN Document Server

    Grüne, Lars

    2017-01-01

    This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. T...

  1. Baryogenesis model predicting antimatter in the Universe

    International Nuclear Information System (INIS)

    Kirilova, D.

    2003-01-01

    Cosmic ray and gamma-ray data do not rule out antimatter domains in the Universe, separated at distances bigger than 10 Mpc from us. Hence, it is interesting to analyze the possible generation of vast antimatter structures during the early Universe evolution. We discuss a SUSY-condensate baryogenesis model, predicting large separated regions of matter and antimatter. The model provides generation of the small locally observed baryon asymmetry for a natural initial conditions, it predicts vast antimatter domains, separated from the matter ones by baryonically empty voids. The characteristic scale of antimatter regions and their distance from the matter ones is in accordance with observational constraints from cosmic ray, gamma-ray and cosmic microwave background anisotropy data

  2. Influence of Different Yield Loci on Failure Prediction with Damage Models

    Science.gov (United States)

    Heibel, S.; Nester, W.; Clausmeyer, T.; Tekkaya, A. E.

    2017-09-01

    Advanced high strength steels are widely used in the automotive industry to simultaneously improve crash performance and reduce the car body weight. A drawback of these multiphase steels is their sensitivity to damage effects and thus the reduction of ductility. For that reason the Forming Limit Curve is only partially suitable for this class of steels. An improvement in failure prediction can be obtained by using damage mechanics. The objective of this paper is to comparatively review the phenomenological damage model GISSMO and the Enhanced Lemaitre Damage Model. GISSMO is combined with three different yield loci, namely von Mises, Hill48 and Barlat2000 to investigate the influence of the choice of the plasticity description on damage modelling. The Enhanced Lemaitre Model is used with Hill48. An inverse parameter identification strategy for a DP1000 based on stress-strain curves and optical strain measurements of shear, uniaxial, notch and (equi-)biaxial tension tests is applied to calibrate the models. A strong dependency of fracture strains on the choice of yield locus can be observed. The identified models are validated on a cross-die cup showing ductile fracture with slight necking.

  3. Statewide analysis of bicycle crashes : [project summary].

    Science.gov (United States)

    2017-06-01

    An extensive literature review was conducted to locate existing studies in four areas: (1) risk factors that affect the frequency and severity of bicycle crashes; (2) bicycle crash causes, patterns, and contributing factors; (3) network screening met...

  4. Alcohol-crash problem in Canada, 2007

    Science.gov (United States)

    2010-03-01

    This report examines: data on alcohol in fatally injured drivers and pedestrians; the number and : percent of people who died in alcohol-related crashes; and alcohol involvement in those crashes : in which someone was seriously injured but not killed...

  5. Alcohol-crash problem in Canada, 2006

    Science.gov (United States)

    2009-01-01

    This report examines: data on alcohol in fatally injured drivers and pedestrians; the number and : percent of people who died in alcohol-related crashes; and alcohol involvement in those crashes : in which someone was seriously injured but not killed...

  6. Alcohol-crash problem in Canada, 2008

    Science.gov (United States)

    2010-12-01

    This report examines: data on alcohol in fatally injured drivers and pedestrians; the number and : percent of people who died in alcohol-related crashes; and alcohol involvement in those crashes : in which someone was seriously injured but not killed...

  7. National Motor Vehicle Crash Causation Survey (NMVCCS)

    Data.gov (United States)

    Department of Transportation — The National Motor Vehicle Crash Causation Survey (NMVVCS) was a nationwide survey of crashes involving light passenger vehicles, with a focus on the factors related...

  8. Teen driver crashes : a report to Congress

    Science.gov (United States)

    2008-07-01

    This report summarizes what is known about the teen driver crash problem and reviews the research on the major contributing factors to the high teen crash rate. Dispositional factors, such as immaturity, inexperience, faulty judgment, and a higher pr...

  9. 2004 road traffic crashes in Queensland

    Science.gov (United States)

    2009-05-01

    This report presents an overview of reported road traffic crashes in Queensland during : 2004 in the context of the previous five years based on data contained in the Queensland : Road Crash Information System maintained by the Department of Transpor...

  10. Finding Furfural Hydrogenation Catalysts via Predictive Modelling

    OpenAIRE

    Strassberger, Zea; Mooijman, Maurice; Ruijter, Eelco; Alberts, Albert H; Maldonado, Ana G; Orru, Romano V A; Rothenberg, Gadi

    2010-01-01

    Abstract We combine multicomponent reactions, catalytic performance studies and predictive modelling to find transfer hydrogenation catalysts. An initial set of 18 ruthenium-carbene complexes were synthesized and screened in the transfer hydrogenation of furfural to furfurol with isopropyl alcohol complexes gave varied yields, from 62% up to >99.9%, with no obvious structure/activity correlations. Control experiments proved that the carbene ligand remains coordinated to the ruthenium centre t...

  11. Predictive Modeling in Actinide Chemistry and Catalysis

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ping [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-05-16

    These are slides from a presentation on predictive modeling in actinide chemistry and catalysis. The following topics are covered in these slides: Structures, bonding, and reactivity (bonding can be quantified by optical probes and theory, and electronic structures and reaction mechanisms of actinide complexes); Magnetic resonance properties (transition metal catalysts with multi-nuclear centers, and NMR/EPR parameters); Moving to more complex systems (surface chemistry of nanomaterials, and interactions of ligands with nanoparticles); Path forward and conclusions.

  12. Piercing of the containment shell of a reactor building in case of airplane crash

    International Nuclear Information System (INIS)

    Herzog, M.

    1978-01-01

    The author presents a simple calculation model for a realistic check of the piercing safety of containments of reactor buildings in case of airplane crash. Its application is illustrated by a numerical example (Starfighter crash on the Unterweser nuclear power plant). (orig.) [de

  13. Tectonic predictions with mantle convection models

    Science.gov (United States)

    Coltice, Nicolas; Shephard, Grace E.

    2018-04-01

    Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough

  14. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  15. A predictive model for dimensional errors in fused deposition modeling

    DEFF Research Database (Denmark)

    Stolfi, A.

    2015-01-01

    This work concerns the effect of deposition angle (a) and layer thickness (L) on the dimensional performance of FDM parts using a predictive model based on the geometrical description of the FDM filament profile. An experimental validation over the whole a range from 0° to 177° at 3° steps and two...... values of L (0.254 mm, 0.330 mm) was produced by comparing predicted values with external face-to-face measurements. After removing outliers, the results show that the developed two-parameter model can serve as tool for modeling the FDM dimensional behavior in a wide range of deposition angles....

  16. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Effectiveness of antilock braking systems in reducing motorcycle fatal crash rates.

    Science.gov (United States)

    Teoh, Eric R

    2011-04-01

    Overbraking and underbraking have been shown to be common factors in motorcycle crashes. Antilock braking systems (ABS) prevent wheels from locking during braking and may make riders less reluctant to apply full braking force. The objective of this study was to evaluate the effect of ABS in fatal motorcycle crashes. Motorcycle drivers involved in fatal crashes per 10,000 registered vehicle years were compared for 13 motorcycle models with optional ABS and those same models without the option during 2003-2008. Motorcycles with optional ABS were included only if the presence of the option could be identified from the vehicle identification number. The rate of fatal motorcycle crashes per 10,000 registered vehicle years was 37 percent lower for ABS models than for their non-ABS versions. ABS appears to be highly effective in preventing fatal motorcycle crashes based on some early adopters of motorcycle ABS technology.

  18. Predicting extinction rates in stochastic epidemic models

    International Nuclear Information System (INIS)

    Schwartz, Ira B; Billings, Lora; Dykman, Mark; Landsman, Alexandra

    2009-01-01

    We investigate the stochastic extinction processes in a class of epidemic models. Motivated by the process of natural disease extinction in epidemics, we examine the rate of extinction as a function of disease spread. We show that the effective entropic barrier for extinction in a susceptible–infected–susceptible epidemic model displays scaling with the distance to the bifurcation point, with an unusual critical exponent. We make a direct comparison between predictions and numerical simulations. We also consider the effect of non-Gaussian vaccine schedules, and show numerically how the extinction process may be enhanced when the vaccine schedules are Poisson distributed

  19. Predictive Modeling of the CDRA 4BMS

    Science.gov (United States)

    Coker, Robert F.; Knox, James C.

    2016-01-01

    As part of NASA's Advanced Exploration Systems (AES) program and the Life Support Systems Project (LSSP), fully predictive models of the Four Bed Molecular Sieve (4BMS) of the Carbon Dioxide Removal Assembly (CDRA) on the International Space Station (ISS) are being developed. This virtual laboratory will be used to help reduce mass, power, and volume requirements for future missions. In this paper we describe current and planned modeling developments in the area of carbon dioxide removal to support future crewed Mars missions as well as the resolution of anomalies observed in the ISS CDRA.

  20. The effects of roadway characteristics on farm equipment crashes: A GIS approach

    Science.gov (United States)

    Greenan, Mitchell Joseph

    for every 5 foot increase in shoulder width, the odds of a crash decreased by 8 percent. (CI: 0.86-0.98). Although not statically significant, unpaved roads increased the odds of a crash by 17 percent. (CI: 0.91-1.50) Lastly, it was found that Farm to Market routes increased the odds of a crash by two fold compared to local roads (which make up roughly 67 percent of Iowa public roads). (CI: 1.72-2.43) When the same model was stratified by rurality (urban/rural), it was found that high traffic density leads to a higher risk of a crash in rural areas. Iowa routes and Farm to Market routes had a greater odds of a crash in urban than rural areas, and road and shoulder width were more protective in rural than urban areas. When only using roads with a crash involving an injury versus all other roads as the outcome, Iowa routes and roads with increased speed limits had higher odds for an injury-involved crash, while increased road width were more protective against crashes involving injuries. Findings from the study suggest that several roadway characteristics were associated with farm-equipment crashes. Through administrative and engineering controls, the six static explanatory variables used in this study may be modified to decrease the risk of a farm equipment crash. Speed limit can be modified through administrative controls while traffic density, road and shoulder width, road type, and surface type can be modified through engineering controls. Results from this study provide information that will aid policy-makers in developing safer roads for farm equipment.

  1. Conscientious personality and young drivers’ crash risk

    OpenAIRE

    Ehsani, Johnathon P.; Li, Kaigang; Simons-Morton, Bruce; Tree-McGrath, Cheyenne Fox; Perlus, Jessamyn; O’Brien, Fearghal; Klauer, Sheila G.

    2015-01-01

    Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Method: Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes...

  2. Building concepts against airplane crash

    International Nuclear Information System (INIS)

    Henkel, F.O.; Woelfel, H.

    1984-01-01

    In Germany safety related buildings of nuclear facilities as well as their equipment are to be designed against airplane crash. While the safety of the structure itself can always be guaranteed by structural means, the induced vibrations may cause severe problems for the equipment. Considerable effort was expended in recent years to comprehend the load case airplane crash in a more exact manner and to evaluate reasonable floor response spectra. Besides this analytical effort, investigations are cited to minimize the induced vibrations by new structural concepts. The present paper gives a survey concerning the development of structural concepts, culminating in the double shell structures that are state of the art today. Then the idea of spring supports, as it is known for the aseismic foundation of buildings, is further developed to a new spring concept which reduces the induced vibrations in an optimum way in the load case airplane crash and which additionally isolates earthquake vibrations. (orig.)

  3. Data Driven Economic Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Masoud Kheradmandi

    2018-04-01

    Full Text Available This manuscript addresses the problem of data driven model based economic model predictive control (MPC design. To this end, first, a data-driven Lyapunov-based MPC is designed, and shown to be capable of stabilizing a system at an unstable equilibrium point. The data driven Lyapunov-based MPC utilizes a linear time invariant (LTI model cognizant of the fact that the training data, owing to the unstable nature of the equilibrium point, has to be obtained from closed-loop operation or experiments. Simulation results are first presented demonstrating closed-loop stability under the proposed data-driven Lyapunov-based MPC. The underlying data-driven model is then utilized as the basis to design an economic MPC. The economic improvements yielded by the proposed method are illustrated through simulations on a nonlinear chemical process system example.

  4. Plant control using embedded predictive models

    International Nuclear Information System (INIS)

    Godbole, S.S.; Gabler, W.E.; Eschbach, S.L.

    1990-01-01

    B and W recently undertook the design of an advanced light water reactor control system. A concept new to nuclear steam system (NSS) control was developed. The concept, which is called the Predictor-Corrector, uses mathematical models of portions of the controlled NSS to calculate, at various levels within the system, demand and control element position signals necessary to satisfy electrical demand. The models give the control system the ability to reduce overcooling and undercooling of the reactor coolant system during transients and upsets. Two types of mathematical models were developed for use in designing and testing the control system. One model was a conventional, comprehensive NSS model that responds to control system outputs and calculates the resultant changes in plant variables that are then used as inputs to the control system. Two other models, embedded in the control system, were less conventional, inverse models. These models accept as inputs plant variables, equipment states, and demand signals and predict plant operating conditions and control element states that will satisfy the demands. This paper reports preliminary results of closed-loop Reactor Coolant (RC) pump trip and normal load reduction testing of the advanced concept. Results of additional transient testing, and of open and closed loop stability analyses will be reported as they are available

  5. Ground Motion Prediction Models for Caucasus Region

    Science.gov (United States)

    Jorjiashvili, Nato; Godoladze, Tea; Tvaradze, Nino; Tumanova, Nino

    2016-04-01

    Ground motion prediction models (GMPMs) relate ground motion intensity measures to variables describing earthquake source, path, and site effects. Estimation of expected ground motion is a fundamental earthquake hazard assessment. The most commonly used parameter for attenuation relation is peak ground acceleration or spectral acceleration because this parameter gives useful information for Seismic Hazard Assessment. Since 2003 development of Georgian Digital Seismic Network has started. In this study new GMP models are obtained based on new data from Georgian seismic network and also from neighboring countries. Estimation of models is obtained by classical, statistical way, regression analysis. In this study site ground conditions are additionally considered because the same earthquake recorded at the same distance may cause different damage according to ground conditions. Empirical ground-motion prediction models (GMPMs) require adjustment to make them appropriate for site-specific scenarios. However, the process of making such adjustments remains a challenge. This work presents a holistic framework for the development of a peak ground acceleration (PGA) or spectral acceleration (SA) GMPE that is easily adjustable to different seismological conditions and does not suffer from the practical problems associated with adjustments in the response spectral domain.

  6. Modeling and Prediction of Krueger Device Noise

    Science.gov (United States)

    Guo, Yueping; Burley, Casey L.; Thomas, Russell H.

    2016-01-01

    This paper presents the development of a noise prediction model for aircraft Krueger flap devices that are considered as alternatives to leading edge slotted slats. The prediction model decomposes the total Krueger noise into four components, generated by the unsteady flows, respectively, in the cove under the pressure side surface of the Krueger, in the gap between the Krueger trailing edge and the main wing, around the brackets supporting the Krueger device, and around the cavity on the lower side of the main wing. For each noise component, the modeling follows a physics-based approach that aims at capturing the dominant noise-generating features in the flow and developing correlations between the noise and the flow parameters that control the noise generation processes. The far field noise is modeled using each of the four noise component's respective spectral functions, far field directivities, Mach number dependencies, component amplitudes, and other parametric trends. Preliminary validations are carried out by using small scale experimental data, and two applications are discussed; one for conventional aircraft and the other for advanced configurations. The former focuses on the parametric trends of Krueger noise on design parameters, while the latter reveals its importance in relation to other airframe noise components.

  7. Prediction of Chemical Function: Model Development and ...

    Science.gov (United States)

    The United States Environmental Protection Agency’s Exposure Forecaster (ExpoCast) project is developing both statistical and mechanism-based computational models for predicting exposures to thousands of chemicals, including those in consumer products. The high-throughput (HT) screening-level exposures developed under ExpoCast can be combined with HT screening (HTS) bioactivity data for the risk-based prioritization of chemicals for further evaluation. The functional role (e.g. solvent, plasticizer, fragrance) that a chemical performs can drive both the types of products in which it is found and the concentration in which it is present and therefore impacting exposure potential. However, critical chemical use information (including functional role) is lacking for the majority of commercial chemicals for which exposure estimates are needed. A suite of machine-learning based models for classifying chemicals in terms of their likely functional roles in products based on structure were developed. This effort required collection, curation, and harmonization of publically-available data sources of chemical functional use information from government and industry bodies. Physicochemical and structure descriptor data were generated for chemicals with function data. Machine-learning classifier models for function were then built in a cross-validated manner from the descriptor/function data using the method of random forests. The models were applied to: 1) predict chemi

  8. Evaluating Predictive Models of Software Quality

    Science.gov (United States)

    Ciaschini, V.; Canaparo, M.; Ronchieri, E.; Salomoni, D.

    2014-06-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  9. Predicting FLDs Using a Multiscale Modeling Scheme

    Science.gov (United States)

    Wu, Z.; Loy, C.; Wang, E.; Hegadekatte, V.

    2017-09-01

    The measurement of a single forming limit diagram (FLD) requires significant resources and is time consuming. We have developed a multiscale modeling scheme to predict FLDs using a combination of limited laboratory testing, crystal plasticity (VPSC) modeling, and dual sequential-stage finite element (ABAQUS/Explicit) modeling with the Marciniak-Kuczynski (M-K) criterion to determine the limit strain. We have established a means to work around existing limitations in ABAQUS/Explicit by using an anisotropic yield locus (e.g., BBC2008) in combination with the M-K criterion. We further apply a VPSC model to reduce the number of laboratory tests required to characterize the anisotropic yield locus. In the present work, we show that the predicted FLD is in excellent agreement with the measured FLD for AA5182 in the O temper. Instead of 13 different tests as for a traditional FLD determination within Novelis, our technique uses just four measurements: tensile properties in three orientations; plane strain tension; biaxial bulge; and the sheet crystallographic texture. The turnaround time is consequently far less than for the traditional laboratory measurement of the FLD.

  10. PREDICTION MODELS OF GRAIN YIELD AND CHARACTERIZATION

    Directory of Open Access Journals (Sweden)

    Narciso Ysac Avila Serrano

    2009-06-01

    Full Text Available With the objective to characterize the grain yield of five cowpea cultivars and to find linear regression models to predict it, a study was developed in La Paz, Baja California Sur, Mexico. A complete randomized blocks design was used. Simple and multivariate analyses of variance were carried out using the canonical variables to characterize the cultivars. The variables cluster per plant, pods per plant, pods per cluster, seeds weight per plant, seeds hectoliter weight, 100-seed weight, seeds length, seeds wide, seeds thickness, pods length, pods wide, pods weight, seeds per pods, and seeds weight per pods, showed significant differences (P≤ 0.05 among cultivars. Paceño and IT90K-277-2 cultivars showed the higher seeds weight per plant. The linear regression models showed correlation coefficients ≥0.92. In these models, the seeds weight per plant, pods per cluster, pods per plant, cluster per plant and pods length showed significant correlations (P≤ 0.05. In conclusion, the results showed that grain yield differ among cultivars and for its estimation, the prediction models showed determination coefficients highly dependable.

  11. Evaluating predictive models of software quality

    International Nuclear Information System (INIS)

    Ciaschini, V; Canaparo, M; Ronchieri, E; Salomoni, D

    2014-01-01

    Applications from High Energy Physics scientific community are constantly growing and implemented by a large number of developers. This implies a strong churn on the code and an associated risk of faults, which is unavoidable as long as the software undergoes active evolution. However, the necessities of production systems run counter to this. Stability and predictability are of paramount importance; in addition, a short turn-around time for the defect discovery-correction-deployment cycle is required. A way to reconcile these opposite foci is to use a software quality model to obtain an approximation of the risk before releasing a program to only deliver software with a risk lower than an agreed threshold. In this article we evaluated two quality predictive models to identify the operational risk and the quality of some software products. We applied these models to the development history of several EMI packages with intent to discover the risk factor of each product and compare it with its real history. We attempted to determine if the models reasonably maps reality for the applications under evaluation, and finally we concluded suggesting directions for further studies.

  12. Gamma-Ray Pulsars Models and Predictions

    CERN Document Server

    Harding, A K

    2001-01-01

    Pulsed emission from gamma-ray pulsars originates inside the magnetosphere, from radiation by charged particles accelerated near the magnetic poles or in the outer gaps. In polar cap models, the high energy spectrum is cut off by magnetic pair production above an energy that is dependent on the local magnetic field strength. While most young pulsars with surface fields in the range B = 10^{12} - 10^{13} G are expected to have high energy cutoffs around several GeV, the gamma-ray spectra of old pulsars having lower surface fields may extend to 50 GeV. Although the gamma-ray emission of older pulsars is weaker, detecting pulsed emission at high energies from nearby sources would be an important confirmation of polar cap models. Outer gap models predict more gradual high-energy turnovers at around 10 GeV, but also predict an inverse Compton component extending to TeV energies. Detection of pulsed TeV emission, which would not survive attenuation at the polar caps, is thus an important test of outer gap models. N...

  13. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  14. Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

    Science.gov (United States)

    Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

    2015-01-01

    Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

  15. Urban sprawl as a risk factor in motor vehicle crashes

    Science.gov (United States)

    Ewing, Reid; Hamidi, Shima; Grace, James B.

    2016-01-01

    A decade ago, compactness/sprawl indices were developed for metropolitan areas and counties which have been widely used in health and other research. In this study, we first update the original county index to 2010, then develop a refined index that accounts for more relevant factors, and finally seek to test the relationship between sprawl and traffic crash rates using structural equation modelling. Controlling for covariates, we find that sprawl is associated with significantly higher direct and indirect effects on fatal crash rates. The direct effect is likely due to the higher traffic speeds in sprawling areas, and the indirect effect is due to greater vehicle miles driven in such areas. Conversely, sprawl has negative direct relationships with total crashes and non-fatal injury crashes, and these offset (and sometimes overwhelm) the positive indirect effects of sprawl on both types of crashes through the mediating effect of increased vehicle miles driven. The most likely explanation is the greater prevalence of fender benders and other minor accidents in the low speed, high conflict traffic environments of compact areas, negating the lower vehicle miles travelled per capita in such areas.

  16. Sawtooth crashes at high beta on JET

    Energy Technology Data Exchange (ETDEWEB)

    Alper, B; Huysmans, G T.A.; Sips, A C.C. [Commission of the European Communities, Abingdon (United Kingdom). JET Joint Undertaking; Nave, M F.F. [Universidade Tecnica, Lisbon (Portugal). Inst. Superior Tecnico

    1994-07-01

    The sawtooth crashes on JET display features which depend on beta. The main observation is a transient bulging of flux surfaces (duration inferior to 30 microsec.), which is predominantly on the low field side and extends to larger radii as beta increases. This phenomenon reaches the plasma boundary when beta{sub N} exceeds 0.5 and in these cases is followed by an ELM within 50 microsec. These sawtooth/ELM events limit plasma performance. Modelling of mode coupling shows qualitative agreement between observations of the structure of the sawtooth precursor and the calculated internal kink mode at high beta. (authors). 6 refs., 5 figs.

  17. An analytical model for climatic predictions

    International Nuclear Information System (INIS)

    Njau, E.C.

    1990-12-01

    A climatic model based upon analytical expressions is presented. This model is capable of making long-range predictions of heat energy variations on regional or global scales. These variations can then be transformed into corresponding variations of some other key climatic parameters since weather and climatic changes are basically driven by differential heating and cooling around the earth. On the basis of the mathematical expressions upon which the model is based, it is shown that the global heat energy structure (and hence the associated climatic system) are characterized by zonally as well as latitudinally propagating fluctuations at frequencies downward of 0.5 day -1 . We have calculated the propagation speeds for those particular frequencies that are well documented in the literature. The calculated speeds are in excellent agreement with the measured speeds. (author). 13 refs

  18. An Anisotropic Hardening Model for Springback Prediction

    Science.gov (United States)

    Zeng, Danielle; Xia, Z. Cedric

    2005-08-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test.

  19. An Anisotropic Hardening Model for Springback Prediction

    International Nuclear Information System (INIS)

    Zeng, Danielle; Xia, Z. Cedric

    2005-01-01

    As more Advanced High-Strength Steels (AHSS) are heavily used for automotive body structures and closures panels, accurate springback prediction for these components becomes more challenging because of their rapid hardening characteristics and ability to sustain even higher stresses. In this paper, a modified Mroz hardening model is proposed to capture realistic Bauschinger effect at reverse loading, such as when material passes through die radii or drawbead during sheet metal forming process. This model accounts for material anisotropic yield surface and nonlinear isotropic/kinematic hardening behavior. Material tension/compression test data are used to accurately represent Bauschinger effect. The effectiveness of the model is demonstrated by comparison of numerical and experimental springback results for a DP600 straight U-channel test

  20. From “Crash!” to Crash: Adapting the Adaptation

    Directory of Open Access Journals (Sweden)

    Ljubica Matek

    2017-12-01

    Full Text Available The paper focuses on J.G. Ballard’s various adaptations of his own material related to the issue of the sexual and sensual nature of an automobile crash, and suggests that adaptation is one of the key methods in art and literature which can be used as a means of contemplating and developing various aesthetic and political ideas. Ballard’s short story “Crash!” was first published in the ICA’s (Institute of Contemporary Arts Eventsheet in February 1969, and later became a chapter of his experimental novel The Atrocity Exhibition (1970. At the same time, Ballard adapts the idea into the “Crashed Cars” exhibition (1970 in London. The short story was then adapted into a short film, Crash!, directed by Harley Cokeliss (1971 and starring Ballard himself, to be finally adapted into the novel Crash (1973. Ballard’s adaptation of his initial ideas across literary forms and media testifies to the importance of adaptation as a process and method of creating art. Thus, rather than suggesting that adaptations merely “breathe life” into the written word, the paper points to the conclusion that the form and content are mutually influential and that, in this case, the novel itself is an adaptation, rather than a hypotext (which it becomes in 1996 to David Cronenberg as he adapts it to film. The complexity of the relationship between the source text and its many adaptations has already contributed to the deconstruction, in Derrida’s terms, of the hierarchy (opposition between the original and the copy. Rather, Ballard’s crossmedial and transmedial adaptations of his own ideas show how, as Ray would suggest, an adaptation cites the source and grafts it into a new context, giving it a new function, both aesthetic and political.

  1. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  2. Predictions of models for environmental radiological assessment

    International Nuclear Information System (INIS)

    Peres, Sueli da Silva; Lauria, Dejanira da Costa; Mahler, Claudio Fernando

    2011-01-01

    In the field of environmental impact assessment, models are used for estimating source term, environmental dispersion and transfer of radionuclides, exposure pathway, radiation dose and the risk for human beings Although it is recognized that the specific information of local data are important to improve the quality of the dose assessment results, in fact obtaining it can be very difficult and expensive. Sources of uncertainties are numerous, among which we can cite: the subjectivity of modelers, exposure scenarios and pathways, used codes and general parameters. The various models available utilize different mathematical approaches with different complexities that can result in different predictions. Thus, for the same inputs different models can produce very different outputs. This paper presents briefly the main advances in the field of environmental radiological assessment that aim to improve the reliability of the models used in the assessment of environmental radiological impact. The intercomparison exercise of model supplied incompatible results for 137 Cs and 60 Co, enhancing the need for developing reference methodologies for environmental radiological assessment that allow to confront dose estimations in a common comparison base. The results of the intercomparison exercise are present briefly. (author)

  3. A comprehensive analysis of factors influencing the injury severity of large-truck crashes.

    Science.gov (United States)

    Zhu, Xiaoyu; Srinivasan, Sivaramakrishnan

    2011-01-01

    Given the importance of trucking to the economic well being of a country and the safety concerns posed by the trucks, a study of large-truck crashes is critical. This paper contributes by undertaking an extensive analysis of the empirical factors affecting injury severity of large-truck crashes. Data from a recent, nationally representative sample of large-truck crashes are examined to determine the factors affecting the overall injury severity of these crashes. The explanatory factors include the characteristics of the crash, vehicle(s), and the driver(s). The injury severity was modeled using two measures. Several similarities and some differences were observed across the two models which underscore the need for improved accuracy in the assessment of injury severity of crashes. The estimated models capture the marginal effects of a variety of explanatory factors simultaneously. In particular, the models indicate the impacts of several driver behavior variables on the severity of the crashes, after controlling for a variety of other factors. For example, driver distraction (truck drivers), alcohol use (car drivers), and emotional factors (car drivers) are found to be associated with higher severity crashes. A further interesting finding is the strong statistical significance of several dummy variables that indicate missing data - these reflect how the nature of the crash itself could affect the completeness of the data. Future efforts should seek to collect such data more comprehensively so that the true effects of these aspects on the crash severity can be determined. Copyright © 2010 Elsevier Ltd. All rights reserved.

  4. A Predictive Maintenance Model for Railway Tracks

    DEFF Research Database (Denmark)

    Li, Rui; Wen, Min; Salling, Kim Bang

    2015-01-01

    presents a mathematical model based on Mixed Integer Programming (MIP) which is designed to optimize the predictive railway tamping activities for ballasted track for the time horizon up to four years. The objective function is setup to minimize the actual costs for the tamping machine (measured by time......). Five technical and economic aspects are taken into account to schedule tamping: (1) track degradation of the standard deviation of the longitudinal level over time; (2) track geometrical alignment; (3) track quality thresholds based on the train speed limits; (4) the dependency of the track quality...

  5. Validation of a finite element human model for prediction of rib fractures

    NARCIS (Netherlands)

    Mordaka, J.K.; Meijer, R.; Rooij, L. van; Zmijewska, A.

    2007-01-01

    In the past, several crash test dummies were developed in order to measure forces acting on the human body during different loading conditions. However, they are limited in their biofidelity and their application type (frontal, lateral etc.). Recently, several numerical human models were developed.

  6. Predictive Capability Maturity Model for computational modeling and simulation.

    Energy Technology Data Exchange (ETDEWEB)

    Oberkampf, William Louis; Trucano, Timothy Guy; Pilch, Martin M.

    2007-10-01

    The Predictive Capability Maturity Model (PCMM) is a new model that can be used to assess the level of maturity of computational modeling and simulation (M&S) efforts. The development of the model is based on both the authors experience and their analysis of similar investigations in the past. The perspective taken in this report is one of judging the usefulness of a predictive capability that relies on the numerical solution to partial differential equations to better inform and improve decision making. The review of past investigations, such as the Software Engineering Institute's Capability Maturity Model Integration and the National Aeronautics and Space Administration and Department of Defense Technology Readiness Levels, indicates that a more restricted, more interpretable method is needed to assess the maturity of an M&S effort. The PCMM addresses six contributing elements to M&S: (1) representation and geometric fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) model validation, and (6) uncertainty quantification and sensitivity analysis. For each of these elements, attributes are identified that characterize four increasing levels of maturity. Importantly, the PCMM is a structured method for assessing the maturity of an M&S effort that is directed toward an engineering application of interest. The PCMM does not assess whether the M&S effort, the accuracy of the predictions, or the performance of the engineering system satisfies or does not satisfy specified application requirements.

  7. Effective modelling for predictive analytics in data science ...

    African Journals Online (AJOL)

    Effective modelling for predictive analytics in data science. ... the nearabsence of empirical or factual predictive analytics in the mainstream research going on ... Keywords: Predictive Analytics, Big Data, Business Intelligence, Project Planning.

  8. Technostress: Surviving a Database Crash.

    Science.gov (United States)

    Dobb, Linda S.

    1990-01-01

    Discussion of technostress in libraries focuses on a database crash at California Polytechnic State University, San Luis Obispo. Steps taken to restore the data are explained, strategies for handling technological accidents are suggested, the impact on library staff is discussed, and a 10-item annotated bibliography on technostress is provided.…

  9. Crash simulations for interior design

    NARCIS (Netherlands)

    Poeze, E.; Slaats, P.M.A.

    1996-01-01

    With the increasing number of compact cars, safety aspects becomes increasingly important for interior designs. The smaller dimensions of these cars do not only decrease the car mass, but also the energy absorption length, resulting in a more severe crash pulse. As a consequence, the inertia loading

  10. 2008 Michigan traffic crash facts

    Science.gov (United States)

    2009-03-18

    In keeping with recent trends, traffic fatalities in 2008 were down to 980, a 9.6 : percent decrease from last year. The total number of persons injured also declined : 7.5 percent to 74,568 and total crashes dropped 2.5 percent to 316,057. Most : no...

  11. 2009 Michigan traffic crash facts

    Science.gov (United States)

    2010-01-01

    In keeping with recent trends, traffic fatalities in 2009 were down to 871, a 11.1 : percent decrease from last year. The total number of persons injured also declined : 4.9 percent to 70,931 and total crashes dropped 7.9 percent to 290,978. Most : n...

  12. The risk of PTSD and depression after an airplane crash and its potential association with physical injury: A longitudinal study

    NARCIS (Netherlands)

    Gouweloos, Juul; Postma, Ingri L. E.; Te Brake, Hans; Sijbrandij, Marit; Kleber, Rolf J.; Goslings, J. Carel

    2016-01-01

    In 2009, a commercial airplane crashed near Amsterdam. This longitudinal study aims to investigate (1) the proportion of survivors of the airplane crash showing a probable posttraumatic stress disorders (PTSD) or depressive disorder, and (2) whether symptoms of PTSD and depression were predicted by

  13. The risk of PTSD and depression after an airplane crash and its potential association with physical injury : A longitudinal study

    NARCIS (Netherlands)

    Gouweloos, J.; Postma, Ingri L.E.; Te Brake, Hans; Sijbrandij, E.M.; Kleber, R.J.; Goslings, J. Carel

    In 2009, a commercial airplane crashed near Amsterdam. This longitudinal study aims to investigate (1) the proportion of survivors of the airplane crash showing a probable posttraumatic stress disorders (PTSD) or depressive disorder, and (2) whether symptoms of PTSD and depression were predicted by

  14. The risk of PTSD and depression after an airplane crash and its potential association with physical injury: A longitudinal study.

    NARCIS (Netherlands)

    Gouweloos, J.; Postma, I.L.; te Brake, H.; Sijbrandij, M.; Kleber, R.; Goslings, J.C.

    2016-01-01

    In 2009, a commercial airplane crashed near Amsterdam. This longitudinal study aims to investigate (1) the proportion of survivors of the airplane crash showing a probable posttraumatic stress disorders (PTSD) or depressive disorder, and (2) whether symptoms of PTSD and depression were predicted by

  15. Impact of pavement conditions on crash severity.

    Science.gov (United States)

    Li, Yingfeng; Liu, Chunxiao; Ding, Liang

    2013-10-01

    Pavement condition has been known as a key factor related to ride quality, but it is less clear how exactly pavement conditions are related to traffic crashes. The researchers used Geographic Information System (GIS) to link Texas Department of Transportation (TxDOT) Crash Record Information System (CRIS) data and Pavement Management Information System (PMIS) data, which provided an opportunity to examine the impact of pavement conditions on traffic crashes in depth. The study analyzed the correlation between several key pavement condition ratings or scores and crash severity based on a large number of crashes in Texas between 2008 and 2009. The results in general suggested that poor pavement condition scores and ratings were associated with proportionally more severe crashes, but very poor pavement conditions were actually associated with less severe crashes. Very good pavement conditions might induce speeding behaviors and therefore could have caused more severe crashes, especially on non-freeway arterials and during favorable driving conditions. In addition, the results showed that the effects of pavement conditions on crash severity were more evident for passenger vehicles than for commercial vehicles. These results provide insights on how pavement conditions may have contributed to crashes, which may be valuable for safety improvement during pavement design and maintenance. Readers should notice that, although the study found statistically significant effects of pavement variables on crash severity, the effects were rather minor in reality as suggested by frequency analyses. Copyright © 2013 Elsevier Ltd. All rights reserved.

  16. Reporting on cyclist crashes in Australian newspapers.

    Science.gov (United States)

    Boufous, Soufiane; Aboss, Ahmad; Montgomery, Victoria

    2016-10-01

    To assess information on cyclist crashes reported in Australian newspapers. The Factiva news archive was searched for articles on cyclist crashes published in major Australian newspapers between 2010 and 2013. Information on the circumstances of cyclist crashes were extracted and coded. A total of 160 cyclist crashes were covered by 198 newspaper articles, with 44% of crashes resulting in cyclist fatalities. Crashes reported by more than one newspaper were more likely to involve public figures or protracted court cases. Individual characteristics of cyclists as well as the location of the crash were reported for more than 80% of crashes. The road user at fault was reported for more than half of crashes. In contrast, information on helmet use, alcohol and cycling lanes was mentioned for only about 10% of crashes. Fewer than one in five articles mentioned prevention strategies including education campaigns, legislative and infrastructure changes. Australian newspapers tend to focus on the most dramatic and more 'newsworthy' aspects of cyclist crashes. Cycling advocates need to work with journalists to improve the quality of this coverage. Better communication between cycling advocates and journalists is likely to have a positive impact on the safety and the uptake of cycling in the community. © 2016 Public Health Association of Australia.

  17. Combining GPS measurements and IRI model predictions

    International Nuclear Information System (INIS)

    Hernandez-Pajares, M.; Juan, J.M.; Sanz, J.; Bilitza, D.

    2002-01-01

    The free electrons distributed in the ionosphere (between one hundred and thousands of km in height) produce a frequency-dependent effect on Global Positioning System (GPS) signals: a delay in the pseudo-orange and an advance in the carrier phase. These effects are proportional to the columnar electron density between the satellite and receiver, i.e. the integrated electron density along the ray path. Global ionospheric TEC (total electron content) maps can be obtained with GPS data from a network of ground IGS (international GPS service) reference stations with an accuracy of few TEC units. The comparison with the TOPEX TEC, mainly measured over the oceans far from the IGS stations, shows a mean bias and standard deviation of about 2 and 5 TECUs respectively. The discrepancies between the STEC predictions and the observed values show an RMS typically below 5 TECUs (which also includes the alignment code noise). he existence of a growing database 2-hourly global TEC maps and with resolution of 5x2.5 degrees in longitude and latitude can be used to improve the IRI prediction capability of the TEC. When the IRI predictions and the GPS estimations are compared for a three month period around the Solar Maximum, they are in good agreement for middle latitudes. An over-determination of IRI TEC has been found at the extreme latitudes, the IRI predictions being, typically two times higher than the GPS estimations. Finally, local fits of the IRI model can be done by tuning the SSN from STEC GPS observations

  18. Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.

    Science.gov (United States)

    Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F

    2013-04-01

    In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.

  19. Mathematical models for indoor radon prediction

    International Nuclear Information System (INIS)

    Malanca, A.; Pessina, V.; Dallara, G.

    1995-01-01

    It is known that the indoor radon (Rn) concentration can be predicted by means of mathematical models. The simplest model relies on two variables only: the Rn source strength and the air exchange rate. In the Lawrence Berkeley Laboratory (LBL) model several environmental parameters are combined into a complex equation; besides, a correlation between the ventilation rate and the Rn entry rate from the soil is admitted. The measurements were carried out using activated carbon canisters. Seventy-five measurements of Rn concentrations were made inside two rooms placed on the second floor of a building block. One of the rooms had a single-glazed window whereas the other room had a double pane window. During three different experimental protocols, the mean Rn concentration was always higher into the room with a double-glazed window. That behavior can be accounted for by the simplest model. A further set of 450 Rn measurements was collected inside a ground-floor room with a grounding well in it. This trend maybe accounted for by the LBL model

  20. Towards predictive models for transitionally rough surfaces

    Science.gov (United States)

    Abderrahaman-Elena, Nabil; Garcia-Mayoral, Ricardo

    2017-11-01

    We analyze and model the previously presented decomposition for flow variables in DNS of turbulence over transitionally rough surfaces. The flow is decomposed into two contributions: one produced by the overlying turbulence, which has no footprint of the surface texture, and one induced by the roughness, which is essentially the time-averaged flow around the surface obstacles, but modulated in amplitude by the first component. The roughness-induced component closely resembles the laminar steady flow around the roughness elements at the same non-dimensional roughness size. For small - yet transitionally rough - textures, the roughness-free component is essentially the same as over a smooth wall. Based on these findings, we propose predictive models for the onset of the transitionally rough regime. Project supported by the Engineering and Physical Sciences Research Council (EPSRC).

  1. Resource-estimation models and predicted discovery

    International Nuclear Information System (INIS)

    Hill, G.W.

    1982-01-01

    Resources have been estimated by predictive extrapolation from past discovery experience, by analogy with better explored regions, or by inference from evidence of depletion of targets for exploration. Changes in technology and new insights into geological mechanisms have occurred sufficiently often in the long run to form part of the pattern of mature discovery experience. The criterion, that a meaningful resource estimate needs an objective measure of its precision or degree of uncertainty, excludes 'estimates' based solely on expert opinion. This is illustrated by development of error measures for several persuasive models of discovery and production of oil and gas in USA, both annually and in terms of increasing exploration effort. Appropriate generalizations of the models resolve many points of controversy. This is illustrated using two USA data sets describing discovery of oil and of U 3 O 8 ; the latter set highlights an inadequacy of available official data. Review of the oil-discovery data set provides a warrant for adjusting the time-series prediction to a higher resource figure for USA petroleum. (author)

  2. Naturalistic Assessment of Novice Teenage Crash Experience

    Science.gov (United States)

    Lee, Suzanne E.; Simons-Morton, Bruce G.; Klauer, Sheila E.; Ouimet, Marie Claude; Dingus, Thomas A.

    2011-01-01

    Background Crash risk is highest during the first months after licensure. Current knowledge about teenagers’ driving exposure and the factors increasing their crash risk is based on self-reported data and crash database analyses. While these research tools are useful, new developments in naturalistic technologies have allowed researchers to examine newly-licensed teenagers’ exposure and crash risk factors in greater detail. The Naturalistic Teenage Driving Study (NTDS) described in this paper is the first study to follow a group of newly-licensed teenagers continuously for 18 months after licensure. The goals of this paper are to compare the crash and near-crash experience of drivers in the NTDS to national trends, to describe the methods and lessons learned in the NTDS, and to provide initial data on driving exposure for these drivers. Methods A data acquisition system was installed in the vehicles of 42 newly-licensed teenage drivers 16 years of age during their first 18 months of independent driving. It consisted of cameras, sensors (accelerometers, GPS, yaw, front radar, lane position, and various sensors obtained via the vehicle network), and a computer with removable hard drive. Data on the driving of participating parents was also collected when they drove the instrumented vehicle. Findings The primary findings after 18 months included the following: (1) crash and near-crash rates among teenage participants were significantly higher during the first six months of the study than the final 12 months, mirroring the national trends; (2) crash and near-crash rates were significantly higher for teenage than adult (parent) participants, also reflecting national trends; (3) teenaged driving exposure averaged between 507-710 kilometers (315-441 miles) per month over the study period, but varied substantially between participants with standard errors representing 8-14 percent of the mean; and (4) crash and near-crash types were very similar for male and female

  3. The Crash Intensity Evaluation Using General Centrality Criterions and a Geographically Weighted Regression

    Science.gov (United States)

    Ghadiriyan Arani, M.; Pahlavani, P.; Effati, M.; Noori Alamooti, F.

    2017-09-01

    Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.

  4. Crash risk analysis during fog conditions using real-time traffic data.

    Science.gov (United States)

    Wu, Yina; Abdel-Aty, Mohamed; Lee, Jaeyoung

    2018-05-01

    This research investigates the changes of traffic characteristics and crash risks during fog conditions. Using real-time traffic flow and weather data at two regions in Florida, the traffic patterns at the fog duration were compared to the traffic patterns at the clear duration. It was found that the average 5-min speed and the average 5-min volume were prone to decreasing during fog. Based on previous studies, a "Crash Risk Increase Indicator (CRII)" was proposed to explore the differences of crash risk between fog and clear conditions. A binary logistic regression model was applied to link the increase of crash risks with traffic flow characteristics. The results suggested that the proposed indicator worked well in evaluating the increase of crash risk under fog condition. It was indicated that the crash risk was prone to increase at ramp vicinities in fog conditions. Also, the average 5-min volume during fog and the lane position are important factors for crash risk increase. The differences between the regions were also explored in this study. The results indicated that the locations with heavier traffic or locations at the lanes that were closest to the median in Region 2 were more likely to observe an increase in crash risks in fog conditions. It is expected that the proposed indicator can help identify the dangerous traffic status under fog conditions and then proper ITS technologies can be implemented to enhance traffic safety when the visibility declines. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. THE CRASH INTENSITY EVALUATION USING GENERAL CENTRALITY CRITERIONS AND A GEOGRAPHICALLY WEIGHTED REGRESSION

    Directory of Open Access Journals (Sweden)

    M. Ghadiriyan Arani

    2017-09-01

    Full Text Available Today, one of the social problems influencing on the lives of many people is the road traffic crashes especially the highway ones. In this regard, this paper focuses on highway of capital and the most populous city in the U.S. state of Georgia and the ninth largest metropolitan area in the United States namely Atlanta. Geographically weighted regression and general centrality criteria are the aspects of traffic used for this article. In the first step, in order to estimate of crash intensity, it is needed to extract the dual graph from the status of streets and highways to use general centrality criteria. With the help of the graph produced, the criteria are: Degree, Pageranks, Random walk, Eccentricity, Closeness, Betweenness, Clustering coefficient, Eigenvector, and Straightness. The intensity of crash point is counted for every highway by dividing the number of crashes in that highway to the total number of crashes. Intensity of crash point is calculated for each highway. Then, criteria and crash point were normalized and the correlation between them was calculated to determine the criteria that are not dependent on each other. The proposed hybrid approach is a good way to regression issues because these effective measures result to a more desirable output. R2 values for geographically weighted regression using the Gaussian kernel was 0.539 and also 0.684 was obtained using a triple-core cube. The results showed that the triple-core cube kernel is better for modeling the crash intensity.

  6. Prediction of pipeline corrosion rate based on grey Markov models

    International Nuclear Information System (INIS)

    Chen Yonghong; Zhang Dafa; Peng Guichu; Wang Yuemin

    2009-01-01

    Based on the model that combined by grey model and Markov model, the prediction of corrosion rate of nuclear power pipeline was studied. Works were done to improve the grey model, and the optimization unbiased grey model was obtained. This new model was used to predict the tendency of corrosion rate, and the Markov model was used to predict the residual errors. In order to improve the prediction precision, rolling operation method was used in these prediction processes. The results indicate that the improvement to the grey model is effective and the prediction precision of the new model combined by the optimization unbiased grey model and Markov model is better, and the use of rolling operation method may improve the prediction precision further. (authors)

  7. An Operational Model for the Prediction of Jet Blast

    Science.gov (United States)

    2012-01-09

    This paper presents an operational model for the prediction of jet blast. The model was : developed based upon three modules including a jet exhaust model, jet centerline decay : model and aircraft motion model. The final analysis was compared with d...

  8. Data driven propulsion system weight prediction model

    Science.gov (United States)

    Gerth, Richard J.

    1994-10-01

    The objective of the research was to develop a method to predict the weight of paper engines, i.e., engines that are in the early stages of development. The impetus for the project was the Single Stage To Orbit (SSTO) project, where engineers need to evaluate alternative engine designs. Since the SSTO is a performance driven project the performance models for alternative designs were well understood. The next tradeoff is weight. Since it is known that engine weight varies with thrust levels, a model is required that would allow discrimination between engines that produce the same thrust. Above all, the model had to be rooted in data with assumptions that could be justified based on the data. The general approach was to collect data on as many existing engines as possible and build a statistical model of the engines weight as a function of various component performance parameters. This was considered a reasonable level to begin the project because the data would be readily available, and it would be at the level of most paper engines, prior to detailed component design.

  9. Predictive modeling of emergency cesarean delivery.

    Directory of Open Access Journals (Sweden)

    Carlos Campillo-Artero

    Full Text Available To increase discriminatory accuracy (DA for emergency cesarean sections (ECSs.We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTREE, and analyzed a random forest model (RFM. We used the areas under the receiver-operating-characteristic (ROC curves (AUCs to assess their DA.The magnitude of the LR+ for all putative individual RFs and ORs in the logistic regression models was low to moderate. Except for parity, all putative RFs were positively associated with ECS, including hospital fixed-effects and night-shift delivery. The DA of all logistic models ranged from 0.74 to 0.81. The most relevant RFs (pH, induction, and previous C-section in the CTREEs showed the highest ORs in the logistic models. The DA of the RFM and its most relevant interaction terms was even higher (AUC = 0.94; 95% CI: 0.93-0.95.Putative fetal, maternal, and contextual RFs alone fail to achieve reasonable DA for ECS. It is the combination of these RFs and the interactions between them at each hospital that make it possible to improve the DA for the type of delivery and tailor interventions through prediction to improve the appropriateness of ECS indications.

  10. Model Predictive Control based on Finite Impulse Response Models

    DEFF Research Database (Denmark)

    Prasath, Guru; Jørgensen, John Bagterp

    2008-01-01

    We develop a regularized l2 finite impulse response (FIR) predictive controller with input and input-rate constraints. Feedback is based on a simple constant output disturbance filter. The performance of the predictive controller in the face of plant-model mismatch is investigated by simulations...... and related to the uncertainty of the impulse response coefficients. The simulations can be used to benchmark l2 MPC against FIR based robust MPC as well as to estimate the maximum performance improvements by robust MPC....

  11. The Development of Two Composite Energy Absorbers for Use in a Transport Rotorcraft Airframe Crash Testbed (TRACT 2) Full-Scale Crash Test

    Science.gov (United States)

    Littell, Justin D.; Jackson, Karen E.; Annett, Martin S.; Seal, Michael D.; Fasanella, Edwin L.

    2015-01-01

    Two composite energy absorbers were developed and evaluated at NASA Langley Research Center through multi-level testing and simulation performed under the Transport Rotorcraft Airframe Crash Testbed (TRACT) research program. A conical-shaped energy absorber, designated the conusoid, was evaluated that consisted of four layers of hybrid carbon-Kevlar plain weave fabric oriented at [+45deg/-45deg/-45deg/+45deg] with respect to the vertical direction. A sinusoidal-shaped energy absorber, designated the sinusoid, was developed that consisted of hybrid carbon-Kevlar plain weave fabric face sheets, two layers for each face sheet oriented at +/-45deg with respect to the vertical direction, and a closed-cell ELFOAM P200 polyisocyanurate (2.0-lb/cu ft) foam core. The design goal for the energy absorbers was to achieve average floor-level accelerations of between 25- and 40-g during the full-scale crash test of a retrofitted CH-46E helicopter airframe, designated TRACT 2. Variations in both designs were assessed through dynamic crush testing of component specimens. Once the designs were finalized, subfloor beams of each configuration were fabricated and retrofitted into a barrel section of a CH-46E helicopter. A vertical drop test of the barrel section was conducted onto concrete to evaluate the performance of the energy absorbers prior to retrofit into TRACT 2. The retrofitted airframe was crash tested under combined forward and vertical velocity conditions onto soft soil. Finite element models were developed of all test articles and simulations were performed using LS-DYNA, a commercial nonlinear explicit transient dynamic finite element code. Test-analysis results are presented for each energy absorber as comparisons of time-history responses, as well as predicted and experimental structural deformations and progressive damage under impact loading for each evaluation level.

  12. Analysis, scale modeling, and full-scale test of a railcar and spent-nuclear-fuel shipping cask in a high-velocity impact against a rigid barrier

    International Nuclear Information System (INIS)

    Huerta, M.

    1981-06-01

    This report describes the mathematical analysis, the physical scale modeling, and a full-scale crash test of a railcar spent-nuclear-fuel shipping system. The mathematical analysis utilized a lumped-parameter model to predict the structural response of the railcar and the shipping cask. The physical scale modeling analysis consisted of two crash tests that used 1/8-scale models to assess railcar and shipping cask damage. The full-scale crash test, conducted with retired railcar equipment, was carefully monitored with onboard instrumentation and high-speed photography. Results of the mathematical and scale modeling analyses are compared with the full-scale test. 29 figures

  13. Methodology for Designing Models Predicting Success of Infertility Treatment

    OpenAIRE

    Alireza Zarinara; Mohammad Mahdi Akhondi; Hojjat Zeraati; Koorsh Kamali; Kazem Mohammad

    2016-01-01

    Abstract Background: The prediction models for infertility treatment success have presented since 25 years ago. There are scientific principles for designing and applying the prediction models that is also used to predict the success rate of infertility treatment. The purpose of this study is to provide basic principles for designing the model to predic infertility treatment success. Materials and Methods: In this paper, the principles for developing predictive models are explained and...

  14. Finite Unification: Theory, Models and Predictions

    CERN Document Server

    Heinemeyer, S; Zoupanos, G

    2011-01-01

    All-loop Finite Unified Theories (FUTs) are very interesting N=1 supersymmetric Grand Unified Theories (GUTs) realising an old field theory dream, and moreover have a remarkable predictive power due to the required reduction of couplings. The reduction of the dimensionless couplings in N=1 GUTs is achieved by searching for renormalization group invariant (RGI) relations among them holding beyond the unification scale. Finiteness results from the fact that there exist RGI relations among dimensional couplings that guarantee the vanishing of all beta-functions in certain N=1 GUTs even to all orders. Furthermore developments in the soft supersymmetry breaking sector of N=1 GUTs and FUTs lead to exact RGI relations, i.e. reduction of couplings, in this dimensionful sector of the theory, too. Based on the above theoretical framework phenomenologically consistent FUTs have been constructed. Here we review FUT models based on the SU(5) and SU(3)^3 gauge groups and their predictions. Of particular interest is the Hig...

  15. Revised predictive equations for salt intrusion modelling in estuaries

    NARCIS (Netherlands)

    Gisen, J.I.A.; Savenije, H.H.G.; Nijzink, R.C.

    2015-01-01

    For one-dimensional salt intrusion models to be predictive, we need predictive equations to link model parameters to observable hydraulic and geometric variables. The one-dimensional model of Savenije (1993b) made use of predictive equations for the Van der Burgh coefficient $K$ and the dispersion

  16. Neutrino nucleosynthesis in supernovae: Shell model predictions

    International Nuclear Information System (INIS)

    Haxton, W.C.

    1989-01-01

    Almost all of the 3 · 10 53 ergs liberated in a core collapse supernova is radiated as neutrinos by the cooling neutron star. I will argue that these neutrinos interact with nuclei in the ejected shells of the supernovae to produce new elements. It appears that this nucleosynthesis mechanism is responsible for the galactic abundances of 7 Li, 11 B, 19 F, 138 La, and 180 Ta, and contributes significantly to the abundances of about 15 other light nuclei. I discuss shell model predictions for the charged and neutral current allowed and first-forbidden responses of the parent nuclei, as well as the spallation processes that produce the new elements. 18 refs., 1 fig., 1 tab

  17. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid, arising......This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...... on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The approach presented is based on quadratic optimization and possess the properties of low algorithmic complexity and of scalability. In particular, the proposed design methodology...

  18. Distributed model predictive control made easy

    CERN Document Server

    Negenborn, Rudy

    2014-01-01

    The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.   This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those ...

  19. Model predictive control of a wind turbine modelled in Simpack

    International Nuclear Information System (INIS)

    Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

    2014-01-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

  20. Model predictive control of a wind turbine modelled in Simpack

    Science.gov (United States)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  1. Poisson Mixture Regression Models for Heart Disease Prediction.

    Science.gov (United States)

    Mufudza, Chipo; Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model.

  2. Safety Assessment of a Metal Cask under Aircraft Engine Crash

    Directory of Open Access Journals (Sweden)

    Sanghoon Lee

    2016-04-01

    Full Text Available The structural integrity of a dual-purpose metal cask currently under development by the Korea Radioactive Waste Agency (KORAD was evaluated, through numerical simulations and a model test, under high-speed missile impact reflecting targeted aircraft crash conditions. The impact conditions were carefully chosen through a survey on accident cases and recommendations from literature. In the impact scenario, a missile flying horizontally hits the top side of the cask, which is freestanding on a concrete pad, with a velocity of 150 m/s. A simplified missile simulating a commercial aircraft engine was designed from an impact load–time function available in literature. In the analyses, the dynamic behavior of the metal cask and the integrity of the containment boundary were assessed. The simulation results were compared with the test results for a 1:3 scale model. Although the dynamic behavior of the cask in the model test did not match exactly with the prediction from the numerical simulation, other structural responses, such as the acceleration and strain history during the impact, showed very good agreement. Moreover, the containment function of the cask survived the missile impact as expected from the numerical simulation. Thus, the procedure and methodology adopted in the structural numerical analyses were successfully validated.

  3. Predictive integrated modelling for ITER scenarios

    International Nuclear Information System (INIS)

    Artaud, J.F.; Imbeaux, F.; Aniel, T.; Basiuk, V.; Eriksson, L.G.; Giruzzi, G.; Hoang, G.T.; Huysmans, G.; Joffrin, E.; Peysson, Y.; Schneider, M.; Thomas, P.

    2005-01-01

    The uncertainty on the prediction of ITER scenarios is evaluated. 2 transport models which have been extensively validated against the multi-machine database are used for the computation of the transport coefficients. The first model is GLF23, the second called Kiauto is a model in which the profile of dilution coefficient is a gyro Bohm-like analytical function, renormalized in order to get profiles consistent with a given global energy confinement scaling. The package of codes CRONOS is used, it gives access to the dynamics of the discharge and allows the study of interplay between heat transport, current diffusion and sources. The main motivation of this work is to study the influence of parameters such plasma current, heat, density, impurities and toroidal moment transport. We can draw the following conclusions: 1) the target Q = 10 can be obtained in ITER hybrid scenario at I p = 13 MA, using either the DS03 two terms scaling or the GLF23 model based on the same pedestal; 2) I p = 11.3 MA, Q = 10 can be reached only assuming a very peaked pressure profile and a low pedestal; 3) at fixed Greenwald fraction, Q increases with density peaking; 4) achieving a stationary q-profile with q > 1 requires a large non-inductive current fraction (80%) that could be provided by 20 to 40 MW of LHCD; and 5) owing to the high temperature the q-profile penetration is delayed and q = 1 is reached about 600 s in ITER hybrid scenario at I p = 13 MA, in the absence of active q-profile control. (A.C.)

  4. Transferability and robustness of real-time freeway crash risk assessment.

    Science.gov (United States)

    Shew, Cameron; Pande, Anurag; Nuworsoo, Cornelius

    2013-09-01

    This study examines the data from single loop detectors on northbound (NB) US-101 in San Jose, California to estimate real-time crash risk assessment models. The classification tree and neural network based crash risk assessment models developed with data from NB US-101 are applied to data from the same freeway, as well as to the data from nearby segments of the SB US-101, NB I-880, and SB I-880 corridors. The performance of crash risk assessment models on these nearby segments is the focus of this research. The model applications show that it is in fact possible to use the same model for multiple freeways, as the underlying relationships between traffic data and crash risk remain similar. The framework provided here may be helpful to authorities for freeway segments with newly installed traffic surveillance apparatuses, since the real-time crash risk assessment models from nearby freeways with existing infrastructure would be able to provide a reasonable estimate of crash risk. The robustness of the model output is also assessed by location, time of day, and day of week. The analysis shows that on some locations the models may require further learning due to higher than expected false positive (e.g., the I-680/I-280 interchange on US-101 NB) or false negative rates. The approach for post-processing the results from the model provides ideas to refine the model prior to or during the implementation. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

  5. Illiquidity Contagion and Liquidity Crashes

    OpenAIRE

    Giovanni Cespa; Thierry Foucault

    2014-01-01

    Liquidity providers often learn information about an asset from prices of other assets. We show that this generates a self-reinforcing positive relationship between price informativeness and liquidity. This relationship causes liquidity spillovers and is a source of fragility: a small drop in the liquidity of one asset can, through a feedback loop, result in a very large drop in market liquidity and price informativeness (a liquidity crash). This feedback loop provides a new explanation for c...

  6. Observed and unobserved correlation between crash avoidance manoeuvers and crash severity

    DEFF Research Database (Denmark)

    Kaplan, Sigal; Prato, Carlo Giacomo

    2015-01-01

    Understanding drivers’ responses to critical events, analyzing drivers’ abilities to perform corrective manoeuvers, and investigating the correlation between these manoeuvers and crash severity provide the opportunity of increasing the knowledge about how to avoid crash occurrence or at least mit...

  7. Religion and stock price crash risk: Evidence

    Directory of Open Access Journals (Sweden)

    Wenfei Li

    2016-09-01

    Full Text Available This paper investigates whether religious traditions influence firm-specific crash risk in China. Using a sample of A-share listed firms from 2003 to 2013, we provide evidence that the more intense the religious environment, the lower the stock price crash risk, implying that religion plays an important role in Chinese corporate governance. Further, we find that (1 religion affects stock price crash risk by reducing earnings management and the management perk problem; (2 different religions have different effects, and Taoism, in particular, is unrelated to crash risk; and (3 the effects of religion are more pronounced with higher quality corporate governance and a stronger legal environment. Religion constrains the management agency problem, thus reducing stock price crash risk in China. Our paper enriches the literature on stock price crash risk and religion, and on new economic geography.

  8. Physics of collapses. Probabilistic occurrence of ELMs and crashes

    International Nuclear Information System (INIS)

    Itoh, S.-I.; Toda, S.; Yagi, M.; Itoh, K.; Fukuyama, A.

    1997-01-01

    Statistical picture for the collapse is proposed. The physics picture of the crash phenomena, which is based on the turbulence-turbulence transition, is extended to include the statistical variance of observables. The dynamics of the plasma gradient and the turbulence level is studied, with the hysteresis nature in the flux-gradient relation. The probabilistic excitation is predicted. The critical condition is described by the statistical probability. (author)

  9. Understanding traffic crash under-reporting

    DEFF Research Database (Denmark)

    Janstrup, Kira Hyldekær; Kaplan, Sigal; Hels, Tove

    2016-01-01

    Objective: This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both. Method: This study foc...... policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend)....

  10. The non-resonant kink modes triggering strong sawtooth-like crashes in the EAST tokamak

    International Nuclear Information System (INIS)

    Li, Erzhong; Xu, L; Chen, K; Shi, T; Hu, L; Igochine, V; Dumbrajs, O

    2014-01-01

    Evolution of the safety factor (q) profile during L–H transitions in the Experimental Advanced Superconducting Tokamak (EAST) was accompanied by strong core crashes prior to regular sawtooth behavior. These crashes appeared in the absence of q = 1 (q is the safety factor) rational surface inside the plasma. Analysis indicates that the m/n = 2/1 tearing mode is destabilized and phase-locked with the m/n = 1/1 non-resonant kink mode (the q = 1 rational surface is absent) due to the self-consistent evolution of plasma profiles as the L–H transition occurs (m and n are the poloidal and toroidal mode numbers, respectively). The growing m/n = 1/1 mode destabilizes the m/n = 2/2 kink mode which eventually triggers the strong crash due to an anomalous heat conductivity, as predicted by the transport model of stochastic magnetic fields using experimental parameters. It is also shown that the magnetic topology changes with the amplitude of m/n = 2/2 mode and the value of center safety factor in a reasonable range. (paper)

  11. Integrating geophysics and hydrology for reducing the uncertainty of groundwater model predictions and improved prediction performance

    DEFF Research Database (Denmark)

    Christensen, Nikolaj Kruse; Christensen, Steen; Ferre, Ty

    the integration of geophysical data in the construction of a groundwater model increases the prediction performance. We suggest that modelers should perform a hydrogeophysical “test-bench” analysis of the likely value of geophysics data for improving groundwater model prediction performance before actually...... and the resulting predictions can be compared with predictions from the ‘true’ model. By performing this analysis we expect to give the modeler insight into how the uncertainty of model-based prediction can be reduced.......A major purpose of groundwater modeling is to help decision-makers in efforts to manage the natural environment. Increasingly, it is recognized that both the predictions of interest and their associated uncertainties should be quantified to support robust decision making. In particular, decision...

  12. Novice drivers' risky driving behavior, risk perception, and crash risk: findings from the DRIVE study.

    Science.gov (United States)

    Ivers, Rebecca; Senserrick, Teresa; Boufous, Soufiane; Stevenson, Mark; Chen, Huei-Yang; Woodward, Mark; Norton, Robyn

    2009-09-01

    We explored the risky driving behaviors and risk perceptions of a cohort of young novice drivers and sought to determine their associations with crash risk. Provisional drivers aged 17 to 24 (n = 20 822) completed a detailed questionnaire that included measures of risk perception and behaviors; 2 years following recruitment, survey data were linked to licensing and police-reported crash data. Poisson regression models that adjusted for multiple confounders were created to explore crash risk. High scores on questionnaire items for risky driving were associated with a 50% increased crash risk (adjusted relative risk = 1.51; 95% confidence interval = 1.25, 1.81). High scores for risk perception (poorer perceptions of safety) were also associated with increased crash risk in univariate and multivariate models; however, significance was not sustained after adjustment for risky driving. The overrepresentation of youths in crashes involving casualties is a significant public health issue. Risky driving behavior is strongly linked to crash risk among young drivers and overrides the importance of risk perceptions. Systemwide intervention, including licensing reform, is warranted.

  13. AP English language & composition crash course

    CERN Document Server

    Hogue, Dawn

    2012-01-01

    AP English Language & Composition Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP English Language & Composition Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP English Language & Composition course description outline and actual Advanced Placement test questions. It covers only the information tested on the exam, so you can make the most of your valua

  14. AP calculus AB & BC crash course

    CERN Document Server

    Rosebush, J

    2012-01-01

    AP Calculus AB & BC Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP Calculus AB & BC Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP Calculus AB & BC course description outline and actual AP test questions. It covers only the information tested on the exams, so you can make the most of your valuable study time. Written by experienced math teachers, our

  15. Large truck and bus crash facts, 2008. 

    Science.gov (United States)

    2010-03-01

    This annual edition of Large Truck and Bus Crash Facts contains descriptive statistics about fatal, injury, and : property damage only crashes involving large trucks and buses in 2008. Selected crash statistics on passenger : vehicles are also presen...

  16. A comprehensive engineering analysis of motorcycle crashes in Maryland.

    Science.gov (United States)

    2010-12-01

    The goal of this study was to identify recurring or common road characteristics of motorcycle crashes : in Maryland from 1998 to 2007. Motorcycle crash data was obtained from the National Highway : Traffic Safety Administrations Crash Outcome Data...

  17. 2008 South Dakota motor vehicle traffic crash summary

    Science.gov (United States)

    2009-06-01

    The Motor Vehicle Traffic Crash Summary is divided into two main sections, Historical : Trends and 2008 Motor Vehicle Traffic Crash Profile. The Historical Trend section : provides information on alcohol involvement in motor vehicle crashes, severity...

  18. 2010 South Dakota motor vehicle traffic crash summary

    Science.gov (United States)

    2011-01-01

    The Motor Vehicle Traffic Crash Summary is divided into two main sections, Historical Trends and 2010 Motor Vehicle Traffic Crash Profile. The Historical Trend section provides information on alcohol involvement in motor vehicle crashes, severity of ...

  19. 2009 South Dakota motor vehicle traffic crash summary

    Science.gov (United States)

    2010-06-01

    The Motor Vehicle Traffic Crash Summary is divided into two main sections, Historical : Trends and 2009 Motor Vehicle Traffic Crash Profile. The Historical Trend section : provides information on alcohol involvement in motor vehicle crashes, severity...

  20. CDC Vital Signs: Motor Vehicle Crash Injuries: Costly but Preventable

    Science.gov (United States)

    ... Press Kit Read the MMWR Science Clips Motor Vehicle Crash Injuries Costly but Preventable Language: English (US) ... and how to prevent future crashes. Problem Motor vehicle crashes are a leading cause of injury in ...

  1. Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment

    Directory of Open Access Journals (Sweden)

    Jing Lu

    2014-11-01

    Full Text Available We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM, and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and the second part is the “neural fuzzy inference system”, which is based on the first part, but could learn new fuzzy rules from the previous ones according to the algorithm we proposed. NFIS-WPM (High Pro and NFIS-WPM (Ave are improved versions of this model. It is well known that the need for accurate weather prediction is apparent when considering the benefits. However, the excessive pursuit of accuracy in weather prediction makes some of the “accurate” prediction results meaningless and the numerical prediction model is often complex and time-consuming. By adapting this novel model to a precipitation prediction problem, we make the predicted outcomes of precipitation more accurate and the prediction methods simpler than by using the complex numerical forecasting model that would occupy large computation resources, be time-consuming and which has a low predictive accuracy rate. Accordingly, we achieve more accurate predictive precipitation results than by using traditional artificial neural networks that have low predictive accuracy.

  2. Foundation Settlement Prediction Based on a Novel NGM Model

    Directory of Open Access Journals (Sweden)

    Peng-Yu Chen

    2014-01-01

    Full Text Available Prediction of foundation or subgrade settlement is very important during engineering construction. According to the fact that there are lots of settlement-time sequences with a nonhomogeneous index trend, a novel grey forecasting model called NGM (1,1,k,c model is proposed in this paper. With an optimized whitenization differential equation, the proposed NGM (1,1,k,c model has the property of white exponential law coincidence and can predict a pure nonhomogeneous index sequence precisely. We used two case studies to verify the predictive effect of NGM (1,1,k,c model for settlement prediction. The results show that this model can achieve excellent prediction accuracy; thus, the model is quite suitable for simulation and prediction of approximate nonhomogeneous index sequence and has excellent application value in settlement prediction.

  3. Nonconvex model predictive control for commercial refrigeration

    Science.gov (United States)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  4. Predictive Modelling of Heavy Metals in Urban Lakes

    OpenAIRE

    Lindström, Martin

    2000-01-01

    Heavy metals are well-known environmental pollutants. In this thesis predictive models for heavy metals in urban lakes are discussed and new models presented. The base of predictive modelling is empirical data from field investigations of many ecosystems covering a wide range of ecosystem characteristics. Predictive models focus on the variabilities among lakes and processes controlling the major metal fluxes. Sediment and water data for this study were collected from ten small lakes in the ...

  5. Finite pressure effects on the tokamak sawtooth crash

    International Nuclear Information System (INIS)

    Nishimura, Yasutaro

    1998-07-01

    The sawtooth crash is a hazardous, disruptive phenomenon that is observed in tokamaks whenever the safety factor at the magnetic axis is below unity. Recently, Tokamak Test Fusion Reactor (TFTR) experimental data has revealed interesting features of the dynamical pressure evolution during the crash phase. Motivated by the experimental results, this dissertation focuses on theoretical modeling of the finite pressure effects on the nonlinear stage of the sawtooth crash. The crash phase has been studied numerically employed a toroidal magnetohydrodynamic (MHD) initial value code deduced from the FAR code. For the first time, by starting from a concentric equilibrium, it has been shown that the evolution through an m/n = 1/1 magnetic island induces secondary high-n ballooning instabilities. The magnetic island evolution gives rise to convection of the pressure inside the inversion radius and builds up a steep pressure gradient across the island separatrix, or current sheet, and thereby triggers ballooning instabilities below the threshold for the axisymmetric equilibrium. Due to the onset of secondary ballooning modes, concomitant fine scale vortices and magnetic stochasticity are generated. These effects produce strong flows across the current sheet, and thereby significant modify the m = 1 driven magnetic reconnection process. The resultant interaction of the high-n ballooning modes with the magnetic reconnection process is discussed

  6. STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS*

    Science.gov (United States)

    HUDOMIET, PÉTER; KÉZDI, GÁBOR; WILLIS, ROBERT J.

    2011-01-01

    SUMMARY This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households’ expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the population average of expected returns, the population average of the uncertainty about returns (subjective standard deviation), and the cross-sectional heterogeneity in expected returns (disagreement). We show estimates from simple reduced-form regressions on probability answers as well as from a more structural model that focuses on the parameters of interest and separates survey noise from relevant heterogeneity. We find a temporary increase in the population average of expectations and uncertainty right after the crash. The effect on cross-sectional heterogeneity is more significant and longer lasting, which implies substantial long-term increase in disagreement. The increase in disagreement is larger among the stockholders, the more informed, and those with higher cognitive capacity, and disagreement co-moves with trading volume and volatility in the market. PMID:21547244

  7. STOCK MARKET CRASH AND EXPECTATIONS OF AMERICAN HOUSEHOLDS.

    Science.gov (United States)

    Hudomiet, Péter; Kézdi, Gábor; Willis, Robert J

    2011-01-01

    This paper utilizes data on subjective probabilities to study the impact of the stock market crash of 2008 on households' expectations about the returns on the stock market index. We use data from the Health and Retirement Study that was fielded in February 2008 through February 2009. The effect of the crash is identified from the date of the interview, which is shown to be exogenous to previous stock market expectations. We estimate the effect of the crash on the population average of expected returns, the population average of the uncertainty about returns (subjective standard deviation), and the cross-sectional heterogeneity in expected returns (disagreement). We show estimates from simple reduced-form regressions on probability answers as well as from a more structural model that focuses on the parameters of interest and separates survey noise from relevant heterogeneity. We find a temporary increase in the population average of expectations and uncertainty right after the crash. The effect on cross-sectional heterogeneity is more significant and longer lasting, which implies substantial long-term increase in disagreement. The increase in disagreement is larger among the stockholders, the more informed, and those with higher cognitive capacity, and disagreement co-moves with trading volume and volatility in the market.

  8. Crashing galaxies, cosmic fireworks

    International Nuclear Information System (INIS)

    Keel, W.C.

    1989-01-01

    The study of binary systems is reviewed. The history of the study of interacting galaxies, the behavior of gas in binary systems, studies to identify the processes that occur when galaxies interact, and the relationship of Seyfert galaxies and quasars to binary systems are discussed. The development of an atlas of peculiar galaxies (Arp, 1966) and methods for modeling galaxy interactions are examined

  9. Seasonal predictability of Kiremt rainfall in coupled general circulation models

    Science.gov (United States)

    Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

    2017-11-01

    The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

  10. MODELLING OF DYNAMIC SPEED LIMITS USING THE MODEL PREDICTIVE CONTROL

    Directory of Open Access Journals (Sweden)

    Andrey Borisovich Nikolaev

    2017-09-01

    Full Text Available The article considers the issues of traffic management using intelligent system “Car-Road” (IVHS, which consist of interacting intelligent vehicles (IV and intelligent roadside controllers. Vehicles are organized in convoy with small distances between them. All vehicles are assumed to be fully automated (throttle control, braking, steering. Proposed approaches for determining speed limits for traffic cars on the motorway using a model predictive control (MPC. The article proposes an approach to dynamic speed limit to minimize the downtime of vehicles in traffic.

  11. Factors associated with crashes due to overcorrection or oversteering of vehicles

    Directory of Open Access Journals (Sweden)

    Praveena Penmetsa

    2018-04-01

    Full Text Available The objective of this research is to identify factors associated with crashes due to overcorrection or oversteering of vehicles. Crash data was collected from 2011 to 2013 for the State of North Carolina in the United States. Logistic regression modeling was used to analyze crash data because of the dichotomous nature of the dependent variable (overcorrection or oversteering. The crash involvement due to overcorrection or oversteering of a vehicle decreased as the age of the driver increased. Drivers are 2.22 times more likely to overcorrect or oversteer when ill, 3.44 times more likely to overcorrect or oversteer when under fatigue, and 1.61 times more likely to overcorrect or oversteer when fallen asleep compared to normal physical conditions. Overall, driver characteristics and speed limit tend to play a major role in overcorrection or oversteering of vehicles. Programs to reduce impaired driving might help in the reduction of overcorrection or oversteering related crash fatalities or injuries. Additionally, training and driver education programs focusing on identified factors associated with crashes due to overcorrection or oversteering of vehicles will benefit drivers on how to respond during emergency or panic situations. Keywords: Overcorrection, Oversteering, Vehicle, Logistic regression, Crash

  12. Injury severity in delivery-motorcycle to vehicle crashes in the Seoul metropolitan area.

    Science.gov (United States)

    Chung, Younshik; Song, Tai-Jin; Yoon, Byoung-Jo

    2014-01-01

    More than 56% of motorcycles in Korea are used for the purpose of delivering parcels and food. Since such delivery requires quick service, most motorcyclists commit traffic violations while delivering, such as crossing the centerline, speeding, running a red light, and driving in the opposite direction down one-way streets. In addition, the fatality rate for motorcycle crashes is about 12% of the fatality rate for road traffic crashes, which is considered to be high, although motorcycle crashes account for only 5% of road traffic crashes in South Korea. Therefore, the objective of this study is to analyze the injury severity of vehicle-to-motorcycle crashes that have occurred during delivery. To examine the risk of different injury levels sustained under all crash types of vehicle-to-motorcycle, this study applied an ordered probit model. Based on the results, this study proposes policy implications to reduce the injury severity of vehicle-to-motorcycle crashes during delivery. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Comparison of teen and adult driver crash scenarios in a nationally representative sample of serious crashes.

    Science.gov (United States)

    McDonald, Catherine C; Curry, Allison E; Kandadai, Venk; Sommers, Marilyn S; Winston, Flaura K

    2014-11-01

    Motor vehicle crashes are the leading cause of death and acquired disability during the first four decades of life. While teen drivers have the highest crash risk, few studies examine the similarities and differences in teen and adult driver crashes. We aimed to: (1) identify and compare the most frequent crash scenarios-integrated information on a vehicle's movement prior to crash, immediate pre-crash event, and crash configuration-for teen and adult drivers involved in serious crashes, and (2) for the most frequent scenarios, explore whether the distribution of driver critical errors differed for teens and adult drivers. We analyzed data from the National Motor Vehicle Crash Causation Survey, a nationally representative study of serious crashes conducted by the U.S. National Highway Traffic Safety Administration from 2005 to 2007. Our sample included 642 16- to 19-year-old and 1167 35- to 54-year-old crash-involved drivers (weighted n=296,482 and 439,356, respectively) who made a critical error that led to their crash's critical pre-crash event (i.e., event that made the crash inevitable). We estimated prevalence ratios (PR) and 95% confidence intervals (CI) to compare the relative frequency of crash scenarios and driver critical errors. The top five crash scenarios among teen drivers, accounting for 37.3% of their crashes, included: (1) going straight, other vehicle stopped, rear end; (2) stopped in traffic lane, turning left at intersection, turn into path of other vehicle; (3) negotiating curve, off right edge of road, right roadside departure; (4) going straight, off right edge of road, right roadside departure; and (5) stopped in lane, turning left at intersection, turn across path of other vehicle. The top five crash scenarios among adult drivers, accounting for 33.9% of their crashes, included the same scenarios as the teen drivers with the exception of scenario (3) and the addition of going straight, crossing over an intersection, and continuing on a

  14. MJO prediction skill of the subseasonal-to-seasonal (S2S) prediction models

    Science.gov (United States)

    Son, S. W.; Lim, Y.; Kim, D.

    2017-12-01

    The Madden-Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, provides the primary source of tropical and extratropical predictability on subseasonal to seasonal timescales. To better understand its predictability, this study conducts quantitative evaluation of MJO prediction skill in the state-of-the-art operational models participating in the subseasonal-to-seasonal (S2S) prediction project. Based on bivariate correlation coefficient of 0.5, the S2S models exhibit MJO prediction skill ranging from 12 to 36 days. These prediction skills are affected by both the MJO amplitude and phase errors, the latter becoming more important with forecast lead times. Consistent with previous studies, the MJO events with stronger initial amplitude are typically better predicted. However, essentially no sensitivity to the initial MJO phase is observed. Overall MJO prediction skill and its inter-model spread are further related with the model mean biases in moisture fields and longwave cloud-radiation feedbacks. In most models, a dry bias quickly builds up in the deep tropics, especially across the Maritime Continent, weakening horizontal moisture gradient. This likely dampens the organization and propagation of MJO. Most S2S models also underestimate the longwave cloud-radiation feedbacks in the tropics, which may affect the maintenance of the MJO convective envelop. In general, the models with a smaller bias in horizontal moisture gradient and longwave cloud-radiation feedbacks show a higher MJO prediction skill, suggesting that improving those processes would enhance MJO prediction skill.

  15. Head-on crashes on two-way interurban roads: a public health concern in road safety.

    Science.gov (United States)

    Olabarria, Marta; Santamariña-Rubio, Elena; Marí-Dell'Olmo, Marc; Gotsens, Mercè; Novoa, Ana M; Borrell, Carme; Pérez, Katherine

    2015-09-01

    To describe the magnitude and characteristics of crashes and drivers involved in head-on crashes on two-way interurban roads in Spain between 2007 and 2012, and to identify the factors associated with the likelihood of head-on crashes on these roads compared with other types of crash. A cross-sectional study was conducted using the National Crash Register. The dependent variables were head-on crashes with injury (yes/no) and drivers involved in head-on crashes (yes/no). Factors associated with head-on crashes and with being a driver involved in a head-on crash versus other types of crash were studied using a multivariate robust Poisson regression model to estimate proportion ratios (PR) and confidence intervals (95% CI). There were 9,192 head-on crashes on two-way Spanish interurban roads. A total of 15,412 men and 3,862 women drivers were involved. Compared with other types of crash, head-on collisions were more likely on roads 7 m or more wide, on road sections with curves, narrowings or drop changes, on wet or snowy surfaces, and in twilight conditions. Transgressions committed by drivers involved in head-on crashes were driving in the opposite direction and incorrectly overtaking another vehicle. Factors associated with a lower probability of head-on crashes were the existence of medians (PR=0.57; 95%CI: 0.48-0.68) and a paved shoulder of less than 1.5 meters (PR=0.81; 95%CI: 0.77-0.86) or from 1.5 to 2.45 meters (PR=0.90; 95%CI: 0.84-0.96). This study allowed the characterization of crashes and drivers involved in head-on crashes on two-way interurban roads. The lower probability observed on roads with median strips point to these measures as an effective way to reduce these collisions. Copyright © 2014 SESPAS. Published by Elsevier Espana. All rights reserved.

  16. Butterfly, Recurrence, and Predictability in Lorenz Models

    Science.gov (United States)

    Shen, B. W.

    2017-12-01

    Over the span of 50 years, the original three-dimensional Lorenz model (3DLM; Lorenz,1963) and its high-dimensional versions (e.g., Shen 2014a and references therein) have been used for improving our understanding of the predictability of weather and climate with a focus on chaotic responses. Although the Lorenz studies focus on nonlinear processes and chaotic dynamics, people often apply a "linear" conceptual model to understand the nonlinear processes in the 3DLM. In this talk, we present examples to illustrate the common misunderstandings regarding butterfly effect and discuss the importance of solutions' recurrence and boundedness in the 3DLM and high-dimensional LMs. The first example is discussed with the following folklore that has been widely used as an analogy of the butterfly effect: "For want of a nail, the shoe was lost.For want of a shoe, the horse was lost.For want of a horse, the rider was lost.For want of a rider, the battle was lost.For want of a battle, the kingdom was lost.And all for the want of a horseshoe nail."However, in 2008, Prof. Lorenz stated that he did not feel that this verse described true chaos but that it better illustrated the simpler phenomenon of instability; and that the verse implicitly suggests that subsequent small events will not reverse the outcome (Lorenz, 2008). Lorenz's comments suggest that the verse neither describes negative (nonlinear) feedback nor indicates recurrence, the latter of which is required for the appearance of a butterfly pattern. The second example is to illustrate that the divergence of two nearby trajectories should be bounded and recurrent, as shown in Figure 1. Furthermore, we will discuss how high-dimensional LMs were derived to illustrate (1) negative nonlinear feedback that stabilizes the system within the five- and seven-dimensional LMs (5D and 7D LMs; Shen 2014a; 2015a; 2016); (2) positive nonlinear feedback that destabilizes the system within the 6D and 8D LMs (Shen 2015b; 2017); and (3

  17. Auditing predictive models : a case study in crop growth

    NARCIS (Netherlands)

    Metselaar, K.

    1999-01-01

    Methods were developed to assess and quantify the predictive quality of simulation models, with the intent to contribute to evaluation of model studies by non-scientists. In a case study, two models of different complexity, LINTUL and SUCROS87, were used to predict yield of forage maize

  18. Models for predicting compressive strength and water absorption of ...

    African Journals Online (AJOL)

    This work presents a mathematical model for predicting the compressive strength and water absorption of laterite-quarry dust cement block using augmented Scheffe's simplex lattice design. The statistical models developed can predict the mix proportion that will yield the desired property. The models were tested for lack of ...

  19. Crash-Tech 2001. Conference; Crash-Tech 2001. Tagung

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    Improved active and passive safety of motor vehicles has resulted in a very much improved accident statistics. This conference discussed further optimisations in motor car safety. The harmonisation of test specifications world-wide was gone into, with particular interest in compatibility. Safety specifications resulting from current accident research and new legislation were gone into, and the current state of measuring and technology in crash testing was outlined. [German] Aufgrund der Verbesserungen in der aktiven und passiven Sicherheit von Fahrzeugen weisen die Unfallstatistiken in vielen europaeischen Laendern eine erfreuliche Tendenz auf. Die Tagung wird sich mit den Moeglichkeiten der weiteren Optimierung der Verkehrssicherheit befassen. Die 'Crash-Tech 2001' will sich mit dem Motto 'Sind wir auf dem Weg zum World NCAP?' der Harmonisierung der Testvorschriften unter Einbeziehung der Kompatibilitaet widmen. Dazu werden Anforderungen an die Fahrzeugsicherheit diskutiert, die sich sowohl aus der aktuellen Unfallforschung als auch aus den Vorschriften ergeben. Weiterhin wird der aktuelle Stand der Mess- und Versuchstechnik im Unfallversuch vorgestellt. (orig.)

  20. Statistical and Machine Learning Models to Predict Programming Performance

    OpenAIRE

    Bergin, Susan

    2006-01-01

    This thesis details a longitudinal study on factors that influence introductory programming success and on the development of machine learning models to predict incoming student performance. Although numerous studies have developed models to predict programming success, the models struggled to achieve high accuracy in predicting the likely performance of incoming students. Our approach overcomes this by providing a machine learning technique, using a set of three significant...

  1. Crash fatality risk and unibody versus body-on-frame structure in SUVs.

    Science.gov (United States)

    Ossiander, Eric M; Koepsell, Thomas D; McKnight, Barbara

    2014-09-01

    In crashes between cars and SUVs, car occupants are more likely to be killed than if they crashed with another car. An increasing proportion of SUVs are built with unibody, rather than truck-like body-on-frame construction. Unibody SUVs are generally lighter, less stiff, and less likely to roll over than body-on-frame SUVs, but whether unibody structure affects risk of death in crashes is unknown. To determine whether unibody SUVs differ from body-on-frame SUVs in the danger they pose to occupants of other vehicles and in the self-protection they offer to their own occupants. Case-control study of crashes between one compact SUV and one other passenger vehicle in the US during 1995-2008, in which the SUV was model year 1996-2006. Cases were all decedents in fatal crashes, one control was selected from each non-fatal crash. Occupants of passenger vehicles that crashed with compact unibody SUVs were at 18% lower risk of death compared to those that crashed with compact body-on-frame SUVs (adjusted odds ratio 0.82 (95% confidence interval 0.73-0.94)). Occupants of compact unibody SUVs were also at lower risk of death compared to occupants of body-on-frame SUVs (0.86 (0.72-1.02)). In two-vehicle collisions involving compact SUVs, unibody structure was associated with lower risk of death both in occupants of other vehicles in the crash, and in SUVs' own occupants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  2. Cannabis and crash responsibility while driving below the alcohol per se legal limit.

    Science.gov (United States)

    Romano, Eduardo; Voas, Robert B; Camp, Bayliss

    2017-11-01

    There is a growing interest in how extensively the use of marijuana by drivers relates to crash involvement. While cognitive, lab-based studies are consistent in showing that the use of cannabis impairs driving tasks, epidemiological, field-based studies have been inconclusive regarding whether cannabis use causes an increased risk of accidents. There is ample evidence that the presence of cannabis among drivers with a BAC≥0.08g/dL highly increases the likelihood of a motor vehicle crash. Less clear, however, is the contribution of cannabis to crash risk when drivers have consumed very little or no alcohol. This effort addresses this gap in knowledge. We took advantage of a unique database that merged fatal crashes in the California Statewide Integrated Traffic Records System (SWITRS) and the Fatality Analysis Reporting System (FARS), which allows for a precise identification of crash responsibility. To account for recent increase in lab testing, we restricted our sample to cover only the years 1993-2009. A total of 4294 drivers were included in the analyses. Descriptive analyses and logistic regressions were run to model the contribution of alcohol and drugs to the likelihood of being responsible in a fatal crash. We found evidence that compared with drivers negative for alcohol and cannabis, the presence of cannabis elevates crash responsibility in fatal crashes among drivers at zero BACs (OR=1.89) and with 0cannabis on fatal crashes, in particular in the absence of alcohol, are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. A comparison of freeway median crash frequency, severity, and barrier strike outcomes by median barrier type.

    Science.gov (United States)

    Russo, Brendan J; Savolainen, Peter T

    2018-08-01

    Median-crossover crashes are among the most hazardous events that can occur on freeways, often resulting in severe or fatal injuries. The primary countermeasure to reduce the occurrence of such crashes is the installation of a median barrier. When installation of a median barrier is warranted, transportation agencies are faced with the decision among various alternatives including concrete barriers, beam guardrail, or high-tension cable barriers. Each barrier type differs in terms of its deflection characteristics upon impact, the required installation and maintenance costs, and the roadway characteristics (e.g., median width) where installation would be feasible. This study involved an investigation of barrier performance through an in-depth analysis of crash frequency and severity data from freeway segments where high-tension cable, thrie-beam, and concrete median barriers were installed. A comprehensive manual review of crash reports was conducted to identify crashes in which a vehicle left the roadway and encroached into the median. This review also involved an examination of crash outcomes when a barrier strike occurred, which included vehicle containment, penetration, or re-direction onto the travel lanes. The manual review of crash reports provided critical supplementary information through narratives and diagrams not normally available through standard fields on police crash report forms. Statistical models were estimated to identify factors that affect the frequency, severity, and outcomes of median-related crashes, with particular emphases on differences between segments with varying median barrier types. Several roadway-, traffic-, and environmental-related characteristics were found to affect these metrics, with results varying across the different barrier types. The results of this study provide transportation agencies with important guidance as to the in-service performance of various types of median barrier. Copyright © 2018 Elsevier Ltd. All rights

  4. Changes in the Severity and Injury Sources of Thoracic Aorta Injuries due to Vehicular Crashes.

    Science.gov (United States)

    Ryb, Gabriel; Dischinger, Patricia; Kerns, Timothy; Burch, Cynthia; Rabin, Joseph; Ho, Shiu

    Research using the National Automotive Sampling System-Crashworthiness Data System (NASS-CDS) suggested a decreased adjusted risk of thoracic aorta injuries (TAI) for newer vehicles during near-side crashes and an increased adjusted TAI risk during frontal crashes. This study attempted to explore possible explanations of these findings. Adult front seat occupants in the Crash Injury Research and Engineering Network (CIREN) database through June 2012 were studied. TAI cases were compared with remaining cases in relation to crash and vehicular characteristics. TAI cases of later crash year (CY) (2004-2012) were compared to those in earlier CY (1996-2003) in relation to TAI severity (minor, moderate, severe and non-survivable). TAI cases in newer model year (MY) vehicles (1999-2012) were compared to those in older vehicles (1988-98) in relation to injury source (steering wheel, front, left, seat belt, air bag and other or unknown). Analysis was stratified by direction of impact (frontal and near-side) and the use of restraints. The similar TAI severity of earlier and later CY among frontal crashes suggests that the observed changes in the adjusted odds of injury seen in NASS-CDS are not due to an increase in injury detection. The decrease in TAI severity among newer vehicles in near-side crashes of later CY is consistent with a beneficial effect of crashworthiness improvements for this crash configuration. A shift of injury source in frontal crashes from the steering wheel in older vehicles to "front of vehicle structures", "seat belts" and "unknown and other" in newer vehicles should suggest potential sites for crashworthiness improvements.

  5. Activity modes selection for project crashing through deterministic simulation

    Directory of Open Access Journals (Sweden)

    Ashok Mohanty

    2011-12-01

    Full Text Available Purpose: The time-cost trade-off problem addressed by CPM-based analytical approaches, assume unlimited resources and the existence of a continuous time-cost function. However, given the discrete nature of most resources, the activities can often be crashed only stepwise. Activity crashing for discrete time-cost function is also known as the activity modes selection problem in the project management. This problem is known to be NP-hard. Sophisticated optimization techniques such as Dynamic Programming, Integer Programming, Genetic Algorithm, Ant Colony Optimization have been used for finding efficient solution to activity modes selection problem. The paper presents a simple method that can provide efficient solution to activity modes selection problem for project crashing.Design/methodology/approach: Simulation based method implemented on electronic spreadsheet to determine activity modes for project crashing. The method is illustrated with the help of an example.Findings: The paper shows that a simple approach based on simple heuristic and deterministic simulation can give good result comparable to sophisticated optimization techniques.Research limitations/implications: The simulation based crashing method presented in this paper is developed to return satisfactory solutions but not necessarily an optimal solution.Practical implications: The use of spreadsheets for solving the Management Science and Operations Research problems make the techniques more accessible to practitioners. Spreadsheets provide a natural interface for model building, are easy to use in terms of inputs, solutions and report generation, and allow users to perform what-if analysis.Originality/value: The paper presents the application of simulation implemented on a spreadsheet to determine efficient solution to discrete time cost tradeoff problem.

  6. The risk of groundling fatalities from unintentional airplane crashes.

    Science.gov (United States)

    Thompson, K M; Rabouw, R F; Cooke, R M

    2001-12-01

    The crashes of four hijacked commercial planes on September 11, 2001, and the repeated televised images of the consequent collapse of the World Trade Center and one side of the Pentagon will inevitably change people's perceptions of the mortality risks to people on the ground from crashing airplanes. Goldstein and colleagues were the first to quantify the risk for Americans of being killed on the ground from a crashing airplane for unintentional events, providing average point estimates of 6 in a hundred million for annual risk and 4.2 in a million for lifetime risk. They noted that the lifetime risk result exceeded the commonly used risk management threshold of 1 in a million, and suggested that the risk to "groundlings" could be a useful risk communication tool because (a) it is a man-made risk (b) arising from economic activities (c) from which the victims derive no benefit and (d) exposure to which the victims cannot control. Their results have been used in risk communication. This analysis provides updated estimates of groundling fatality risks from unintentional crashes using more recent data and a geographical information system approach to modeling the population around airports. The results suggest that the average annual risk is now 1.2 in a hundred million and the lifetime risk is now 9 in ten million (below the risk management threshold). Analysis of the variability and uncertainty of this estimate, however, suggests that the exposure to groundling fatality risk varies by about a factor of approximately 100 in the spatial dimension of distance to an airport, with the risk declining rapidly outside the first 2 miles around an airport. We believe that the risk to groundlings from crashing airplanes is more useful in the context of risk communication when information about variability and uncertainty in the risk estimates is characterized, but we suspect that recent events will alter its utility in risk communication.

  7. A dynamic mathematical test of international property securities bubbles and crashes

    Science.gov (United States)

    Hui, Eddie C. M.; Zheng, Xian; Wang, Hui

    2010-04-01

    This study investigates property securities bubbles and crashes by using a dynamic mathematical methodology developed from the previous research (Watanabe et al. 2007a, b [31,32]). The improved model is used to detect the bubble and crash periods in five international countries/cities (namely, United States, United Kingdom, Japan, Hong Kong and Singapore) from Jan, 2000 to Oct, 2008. By this model definition, we are able to detect the beginning of each bubble period even before it bursts. Meanwhile, the empirical results show that most of property securities markets experienced bubble periods between 2003 and 2007, and crashes happened in Apr 2008 triggered by the Subprime Mortgage Crisis of US. In contrast, Japan suffered the shortest bubble period and no evidence has documented the existence of crash there.

  8. Probabilistic Modeling and Visualization for Bankruptcy Prediction

    DEFF Research Database (Denmark)

    Antunes, Francisco; Ribeiro, Bernardete; Pereira, Francisco Camara

    2017-01-01

    In accounting and finance domains, bankruptcy prediction is of great utility for all of the economic stakeholders. The challenge of accurate assessment of business failure prediction, specially under scenarios of financial crisis, is known to be complicated. Although there have been many successful...... studies on bankruptcy detection, seldom probabilistic approaches were carried out. In this paper we assume a probabilistic point-of-view by applying Gaussian Processes (GP) in the context of bankruptcy prediction, comparing it against the Support Vector Machines (SVM) and the Logistic Regression (LR......). Using real-world bankruptcy data, an in-depth analysis is conducted showing that, in addition to a probabilistic interpretation, the GP can effectively improve the bankruptcy prediction performance with high accuracy when compared to the other approaches. We additionally generate a complete graphical...

  9. Accurate and dynamic predictive model for better prediction in medicine and healthcare.

    Science.gov (United States)

    Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

    2018-05-01

    Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

  10. A new ensemble model for short term wind power prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

    2012-01-01

    As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

  11. Testing the predictive power of nuclear mass models

    International Nuclear Information System (INIS)

    Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

    2008-01-01

    A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

  12. From Predictive Models to Instructional Policies

    Science.gov (United States)

    Rollinson, Joseph; Brunskill, Emma

    2015-01-01

    At their core, Intelligent Tutoring Systems consist of a student model and a policy. The student model captures the state of the student and the policy uses the student model to individualize instruction. Policies require different properties from the student model. For example, a mastery threshold policy requires the student model to have a way…

  13. The Complexity of Developmental Predictions from Dual Process Models

    Science.gov (United States)

    Stanovich, Keith E.; West, Richard F.; Toplak, Maggie E.

    2011-01-01

    Drawing developmental predictions from dual-process theories is more complex than is commonly realized. Overly simplified predictions drawn from such models may lead to premature rejection of the dual process approach as one of many tools for understanding cognitive development. Misleading predictions can be avoided by paying attention to several…

  14. Sweat loss prediction using a multi-model approach.

    Science.gov (United States)

    Xu, Xiaojiang; Santee, William R

    2011-07-01

    A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

  15. Comparisons of Faulting-Based Pavement Performance Prediction Models

    Directory of Open Access Journals (Sweden)

    Weina Wang

    2017-01-01

    Full Text Available Faulting prediction is the core of concrete pavement maintenance and design. Highway agencies are always faced with the problem of lower accuracy for the prediction which causes costly maintenance. Although many researchers have developed some performance prediction models, the accuracy of prediction has remained a challenge. This paper reviews performance prediction models and JPCP faulting models that have been used in past research. Then three models including multivariate nonlinear regression (MNLR model, artificial neural network (ANN model, and Markov Chain (MC model are tested and compared using a set of actual pavement survey data taken on interstate highway with varying design features, traffic, and climate data. It is found that MNLR model needs further recalibration, while the ANN model needs more data for training the network. MC model seems a good tool for pavement performance prediction when the data is limited, but it is based on visual inspections and not explicitly related to quantitative physical parameters. This paper then suggests that the further direction for developing the performance prediction model is incorporating the advantages and disadvantages of different models to obtain better accuracy.

  16. Irrational exuberance and neural crash warning signals during endogenous experimental market bubbles.

    Science.gov (United States)

    Smith, Alec; Lohrenz, Terry; King, Justin; Montague, P Read; Camerer, Colin F

    2014-07-22

    Groups of humans routinely misassign value to complex future events, especially in settings involving the exchange of resources. If properly structured, experimental markets can act as excellent probes of human group-level valuation mechanisms during pathological overvaluations--price bubbles. The connection between the behavioral and neural underpinnings of such phenomena has been absent, in part due to a lack of enabling technology. We used a multisubject functional MRI paradigm to measure neural activity in human subjects participating in experimental asset markets in which endogenous price bubbles formed and crashed. Although many ideas exist about how and why such bubbles may form and how to identify them, our experiment provided a window on the connection between neural responses and behavioral acts (buying and selling) that created the bubbles. We show that aggregate neural activity in the nucleus accumbens (NAcc) tracks the price bubble and that NAcc activity aggregated within a market predicts future price changes and crashes. Furthermore, the lowest-earning subjects express a stronger tendency to buy as a function of measured NAcc activity. Conversely, we report a signal in the anterior insular cortex in the highest earners that precedes the impending price peak, is associated with a higher propensity to sell in high earners, and that may represent a neural early warning signal in these subjects. Such markets could be a model system to understand neural and behavior mechanisms in other settings where emergent group-level activity exhibits mistaken belief or valuation.

  17. Latent Classes of Polydrug Users as a Predictor of Crash Involvement and Alcohol Consumption.

    Science.gov (United States)

    Scherer, Michael; Romano, Eduardo; Voas, Robert; Taylor, Eileen

    2018-05-01

    Polydrug users have been shown to be at higher risk for alcohol consumption and crash involvement. However, research has shown that polydrug groups differ in some important ways. It is currently unknown how polydrug-using groups differ in terms of crash involvement and alcohol consumption. The current study used latent class analysis to examine subgroups of polydrug users (n = 384) among a sample of drivers in Virginia Beach, Virginia (N = 10,512). A series of logistic regression analyses were conducted to determine the relationship between polydrug use categories and crash involvement and alcohol consumption. Four distinct subclasses of users were identified among polydrug-using drivers: Class 1 is the "marijuana-amphetamines class" and accounts for 21.6% of polydrug users. Class 2 is the "benzo-antidepressant class" and accounts for 39.0% of polydrug users. Class 3 is the "opioid-benzo class" and accounts for 32.7% of polydrug users. Finally, Class 4 is the "marijuana-cocaine class" and accounts for 6.7% of the study sample. Drivers in the opioid-benzo class were significantly more likely than those in any other class as well as non-drug users and single-drug users to be involved in a crash and were more likely than those in most other conditions to consume alcohol. No significant difference was found between marijuana-amphetamine users or benzo-antidepressant users and non-drug users on crash risk. Some polydrug users are indeed at greater risk for crash involvement and alcohol consumption; however, not all polydrug users are significantly worse than single-drug users and/or non-drug users, and the practice of lumping polydrug users together when predicting crash risk runs the risk of inaccurately attributing crash involvement to certain drivers.

  18. Modeling of Complex Life Cycle Prediction Based on Cell Division

    Directory of Open Access Journals (Sweden)

    Fucheng Zhang

    2017-01-01

    Full Text Available Effective fault diagnosis and reasonable life expectancy are of great significance and practical engineering value for the safety, reliability, and maintenance cost of equipment and working environment. At present, the life prediction methods of the equipment are equipment life prediction based on condition monitoring, combined forecasting model, and driven data. Most of them need to be based on a large amount of data to achieve the problem. For this issue, we propose learning from the mechanism of cell division in the organism. We have established a moderate complexity of life prediction model across studying the complex multifactor correlation life model. In this paper, we model the life prediction of cell division. Experiments show that our model can effectively simulate the state of cell division. Through the model of reference, we will use it for the equipment of the complex life prediction.

  19. Risk prediction model: Statistical and artificial neural network approach

    Science.gov (United States)

    Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

    2017-04-01

    Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

  20. Predictive modeling and reducing cyclic variability in autoignition engines

    Science.gov (United States)

    Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

    2016-08-30

    Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

  1. Dynamic Simulation of Human Gait Model With Predictive Capability.

    Science.gov (United States)

    Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

    2018-03-01

    In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

  2. Comparative Evaluation of Some Crop Yield Prediction Models ...

    African Journals Online (AJOL)

    A computer program was adopted from the work of Hill et al. (1982) to calibrate and test three of the existing yield prediction models using tropical cowpea yieldÐweather data. The models tested were Hanks Model (first and second versions). Stewart Model (first and second versions) and HallÐButcher Model. Three sets of ...

  3. Assessing crash risk considering vehicle interactions with trucks using point detector data.

    Science.gov (United States)

    Hyun, Kyung Kate; Jeong, Kyungsoo; Tok, Andre; Ritchie, Stephen G

    2018-03-12

    Trucks have distinct driving characteristics in general traffic streams such as lower speeds and limitations in acceleration and deceleration. As a consequence, vehicles keep longer headways or frequently change lane when they follow a truck, which is expected to increase crash risk. This study introduces several traffic measures at the individual vehicle level to capture vehicle interactions between trucks and non-trucks and analyzed how the measures affect crash risk under different traffic conditions. The traffic measures were developed using headways obtained from Inductive Loop Detectors (ILDs). In addition, a truck detection algorithm using a Gaussian Mixture (GM) model was developed to identify trucks and to estimate truck exposure from ILD data. Using the identified vehicle types from the GM model, vehicle interaction metrics were categorized into three groups based on the combination of leading and following vehicle types. The effects of the proposed traffic measures on crash risk were modeled in two different cases of prior- and non-crash using a case-control approach utilizing a conditional logistic regression. Results showed that the vehicle interactions between the leading and following vehicle types were highly associated with crash risk, and further showed different impacts on crash risk by traffic conditions. Specifically, crashes were more likely to occur when a truck following a non-truck had shorter average headway but greater headway variance in heavy traffic while a non-truck following a truck had greater headway variance in light traffic. This study obtained meaningful conclusions that vehicle interactions involved with trucks were significantly related to the crash likelihood rather than the measures that estimate average traffic condition such as total volume or average headway of the traffic stream. Copyright © 2018 Elsevier Ltd. All rights reserved.

  4. A model to predict the power output from wind farms

    Energy Technology Data Exchange (ETDEWEB)

    Landberg, L. [Riso National Lab., Roskilde (Denmark)

    1997-12-31

    This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

  5. Modelling microbial interactions and food structure in predictive microbiology

    NARCIS (Netherlands)

    Malakar, P.K.

    2002-01-01

    Keywords: modelling, dynamic models, microbial interactions, diffusion, microgradients, colony growth, predictive microbiology.

    Growth response of microorganisms in foods is a complex process. Innovations in food production and preservation techniques have resulted in adoption of

  6. Ocean wave prediction using numerical and neural network models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...

  7. A mathematical model for predicting earthquake occurrence ...

    African Journals Online (AJOL)

    We consider the continental crust under damage. We use the observed results of microseism in many seismic stations of the world which was established to study the time series of the activities of the continental crust with a view to predicting possible time of occurrence of earthquake. We consider microseism time series ...

  8. Model for predicting the injury severity score.

    Science.gov (United States)

    Hagiwara, Shuichi; Oshima, Kiyohiro; Murata, Masato; Kaneko, Minoru; Aoki, Makoto; Kanbe, Masahiko; Nakamura, Takuro; Ohyama, Yoshio; Tamura, Jun'ichi

    2015-07-01

    To determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival. We reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P  Watson ratio was 2.200. A formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

  9. Predicting Career Advancement with Structural Equation Modelling

    Science.gov (United States)

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  10. The influence of road curvature on fatal crashes in New Zealand

    DEFF Research Database (Denmark)

    Haynes, Robin; Lake, Iain R.; Kingham, Simon

    2008-01-01

    Bends in roads can cause crashes but a recent study in the UK found that areas with mostly curved roads had lower crash rates than areas with straighter roads. This present study aimed to replicate the previous research in a different country. Variations in the number of fatal road crashes...... occurring between 1996 and 2005 in 73 territorial local authorities across New Zealand were modelled against possible predictors. The predictors were traffic flow, population counts and characteristics, car use, socio-economic deprivation, climate, altitude and road characteristics including four measures...... of average road curvature. The best predictors of the number of fatal crashes on urban roads, rural state highways and other rural roads were traffic flow, speed limitation and socio-economic deprivation. Holding significant factors constant, there was no evidence that TLAs with the most curved roads had...

  11. Risk Factors Associated with Crash Severity on Low-Volume Rural Roads in Denmark

    DEFF Research Database (Denmark)

    Prato, Carlo Giacomo; Rasmussen, Thomas Kjær; Kaplan, Sigal

    2014-01-01

    Safety on low-volume rural roads is drawing attention due to the high fatality and severe injury rates in comparison with high-volume roads and the increasing awareness of sustainable rural development among policy makers. This study analyzes the risk factors associated with crash severity on low......-volume rural roads, including crash characteristics, driver attributes and behavior, vehicle type, road features, environmental conditions, distance from the nearest hospital, and zone rurality degree. The data consist of a set of crashes occurred on low-volume rural roads in Denmark between 2007 and 2011...... advantage in accommodating the ordered-response nature of severity while relaxing the proportional odds assumption. Model estimates and pseudoelasticities show that aggravated crash injury severity is significantly associated with (1) alcohol and failure to wear seatbelts, (2) involvement of vulnerable road...

  12. Statistical model based gender prediction for targeted NGS clinical panels

    Directory of Open Access Journals (Sweden)

    Palani Kannan Kandavel

    2017-12-01

    The reference test dataset are being used to test the model. The sensitivity on predicting the gender has been increased from the current “genotype composition in ChrX” based approach. In addition, the prediction score given by the model can be used to evaluate the quality of clinical dataset. The higher prediction score towards its respective gender indicates the higher quality of sequenced data.

  13. A predictive pilot model for STOL aircraft landing

    Science.gov (United States)

    Kleinman, D. L.; Killingsworth, W. R.

    1974-01-01

    An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

  14. Estimating Model Prediction Error: Should You Treat Predictions as Fixed or Random?

    Science.gov (United States)

    Wallach, Daniel; Thorburn, Peter; Asseng, Senthold; Challinor, Andrew J.; Ewert, Frank; Jones, James W.; Rotter, Reimund; Ruane, Alexander

    2016-01-01

    Crop models are important tools for impact assessment of climate change, as well as for exploring management options under current climate. It is essential to evaluate the uncertainty associated with predictions of these models. We compare two criteria of prediction error; MSEP fixed, which evaluates mean squared error of prediction for a model with fixed structure, parameters and inputs, and MSEP uncertain( X), which evaluates mean squared error averaged over the distributions of model structure, inputs and parameters. Comparison of model outputs with data can be used to estimate the former. The latter has a squared bias term, which can be estimated using hindcasts, and a model variance term, which can be estimated from a simulation experiment. The separate contributions to MSEP uncertain (X) can be estimated using a random effects ANOVA. It is argued that MSEP uncertain (X) is the more informative uncertainty criterion, because it is specific to each prediction situation.

  15. Model-based uncertainty in species range prediction

    DEFF Research Database (Denmark)

    Pearson, R. G.; Thuiller, Wilfried; Bastos Araujo, Miguel

    2006-01-01

    Aim Many attempts to predict the potential range of species rely on environmental niche (or 'bioclimate envelope') modelling, yet the effects of using different niche-based methodologies require further investigation. Here we investigate the impact that the choice of model can have on predictions...

  16. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  17. Testing and analysis of internal hardwood log defect prediction models

    Science.gov (United States)

    R. Edward Thomas

    2011-01-01

    The severity and location of internal defects determine the quality and value of lumber sawn from hardwood logs. Models have been developed to predict the size and position of internal defects based on external defect indicator measurements. These models were shown to predict approximately 80% of all internal knots based on external knot indicators. However, the size...

  18. Comparison of Simple Versus Performance-Based Fall Prediction Models

    Directory of Open Access Journals (Sweden)

    Shekhar K. Gadkaree BS

    2015-05-01

    Full Text Available Objective: To compare the predictive ability of standard falls prediction models based on physical performance assessments with more parsimonious prediction models based on self-reported data. Design: We developed a series of fall prediction models progressing in complexity and compared area under the receiver operating characteristic curve (AUC across models. Setting: National Health and Aging Trends Study (NHATS, which surveyed a nationally representative sample of Medicare enrollees (age ≥65 at baseline (Round 1: 2011-2012 and 1-year follow-up (Round 2: 2012-2013. Participants: In all, 6,056 community-dwelling individuals participated in Rounds 1 and 2 of NHATS. Measurements: Primary outcomes were 1-year incidence of “ any fall ” and “ recurrent falls .” Prediction models were compared and validated in development and validation sets, respectively. Results: A prediction model that included demographic information, self-reported problems with balance and coordination, and previous fall history was the most parsimonious model that optimized AUC for both any fall (AUC = 0.69, 95% confidence interval [CI] = [0.67, 0.71] and recurrent falls (AUC = 0.77, 95% CI = [0.74, 0.79] in the development set. Physical performance testing provided a marginal additional predictive value. Conclusion: A simple clinical prediction model that does not include physical performance testing could facilitate routine, widespread falls risk screening in the ambulatory care setting.

  19. Models for predicting fuel consumption in sagebrush-dominated ecosystems

    Science.gov (United States)

    Clinton S. Wright

    2013-01-01

    Fuel consumption predictions are necessary to accurately estimate or model fire effects, including pollutant emissions during wildland fires. Fuel and environmental measurements on a series of operational prescribed fires were used to develop empirical models for predicting fuel consumption in big sagebrush (Artemisia tridentate Nutt.) ecosystems....

  20. Refining the Committee Approach and Uncertainty Prediction in Hydrological Modelling

    NARCIS (Netherlands)

    Kayastha, N.

    2014-01-01

    Due to the complexity of hydrological systems a single model may be unable to capture the full range of a catchment response and accurately predict the streamflows. The multi modelling approach opens up possibilities for handling such difficulties and allows improve the predictive capability of

  1. A new, accurate predictive model for incident hypertension

    DEFF Research Database (Denmark)

    Völzke, Henry; Fung, Glenn; Ittermann, Till

    2013-01-01

    Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures.......Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures....

  2. Prediction models for successful external cephalic version: a systematic review

    NARCIS (Netherlands)

    Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M.; Molkenboer, Jan F. M.; van der Post, Joris A. M.; Mol, Ben W.; Kok, Marjolein

    2015-01-01

    To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015.

  3. Hidden Markov Model for quantitative prediction of snowfall

    Indian Academy of Sciences (India)

    A Hidden Markov Model (HMM) has been developed for prediction of quantitative snowfall in Pir-Panjal and Great Himalayan mountain ranges of Indian Himalaya. The model predicts snowfall for two days in advance using daily recorded nine meteorological variables of past 20 winters from 1992–2012. There are six ...

  4. Mathematical model for dissolved oxygen prediction in Cirata ...

    African Journals Online (AJOL)

    This paper presents the implementation and performance of mathematical model to predict theconcentration of dissolved oxygen in Cirata Reservoir, West Java by using Artificial Neural Network (ANN). The simulation program was created using Visual Studio 2012 C# software with ANN model implemented in it. Prediction ...

  5. Econometric models for predicting confusion crop ratios

    Science.gov (United States)

    Umberger, D. E.; Proctor, M. H.; Clark, J. E.; Eisgruber, L. M.; Braschler, C. B. (Principal Investigator)

    1979-01-01

    Results for both the United States and Canada show that econometric models can provide estimates of confusion crop ratios that are more accurate than historical ratios. Whether these models can support the LACIE 90/90 accuracy criterion is uncertain. In the United States, experimenting with additional model formulations could provide improved methods models in some CRD's, particularly in winter wheat. Improved models may also be possible for the Canadian CD's. The more aggressive province/state models outperformed individual CD/CRD models. This result was expected partly because acreage statistics are based on sampling procedures, and the sampling precision declines from the province/state to the CD/CRD level. Declining sampling precision and the need to substitute province/state data for the CD/CRD data introduced measurement error into the CD/CRD models.

  6. PEEX Modelling Platform for Seamless Environmental Prediction

    Science.gov (United States)

    Baklanov, Alexander; Mahura, Alexander; Arnold, Stephen; Makkonen, Risto; Petäjä, Tuukka; Kerminen, Veli-Matti; Lappalainen, Hanna K.; Ezau, Igor; Nuterman, Roman; Zhang, Wen; Penenko, Alexey; Gordov, Evgeny; Zilitinkevich, Sergej; Kulmala, Markku

    2017-04-01

    The Pan-Eurasian EXperiment (PEEX) is a multidisciplinary, multi-scale research programme stared in 2012 and aimed at resolving the major uncertainties in Earth System Science and global sustainability issues concerning the Arctic and boreal Northern Eurasian regions and in China. Such challenges include climate change, air quality, biodiversity loss, chemicalization, food supply, and the use of natural resources by mining, industry, energy production and transport. The research infrastructure introduces the current state of the art modeling platform and observation systems in the Pan-Eurasian region and presents the future baselines for the coherent and coordinated research infrastructures in the PEEX domain. The PEEX modeling Platform is characterized by a complex seamless integrated Earth System Modeling (ESM) approach, in combination with specific models of different processes and elements of the system, acting on different temporal and spatial scales. The ensemble approach is taken to the integration of modeling results from different models, participants and countries. PEEX utilizes the full potential of a hierarchy of models: scenario analysis, inverse modeling, and modeling based on measurement needs and processes. The models are validated and constrained by available in-situ and remote sensing data of various spatial and temporal scales using data assimilation and top-down modeling. The analyses of the anticipated large volumes of data produced by available models and sensors will be supported by a dedicated virtual research environment developed for these purposes.

  7. Impact of modellers' decisions on hydrological a priori predictions

    Science.gov (United States)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  8. Adding propensity scores to pure prediction models fails to improve predictive performance

    Directory of Open Access Journals (Sweden)

    Amy S. Nowacki

    2013-08-01

    Full Text Available Background. Propensity score usage seems to be growing in popularity leading researchers to question the possible role of propensity scores in prediction modeling, despite the lack of a theoretical rationale. It is suspected that such requests are due to the lack of differentiation regarding the goals of predictive modeling versus causal inference modeling. Therefore, the purpose of this study is to formally examine the effect of propensity scores on predictive performance. Our hypothesis is that a multivariable regression model that adjusts for all covariates will perform as well as or better than those models utilizing propensity scores with respect to model discrimination and calibration.Methods. The most commonly encountered statistical scenarios for medical prediction (logistic and proportional hazards regression were used to investigate this research question. Random cross-validation was performed 500 times to correct for optimism. The multivariable regression models adjusting for all covariates were compared with models that included adjustment for or weighting with the propensity scores. The methods were compared based on three predictive performance measures: (1 concordance indices; (2 Brier scores; and (3 calibration curves.Results. Multivariable models adjusting for all covariates had the highest average concordance index, the lowest average Brier score, and the best calibration. Propensity score adjustment and inverse probability weighting models without adjustment for all covariates performed worse than full models and failed to improve predictive performance with full covariate adjustment.Conclusion. Propensity score techniques did not improve prediction performance measures beyond multivariable adjustment. Propensity scores are not recommended if the analytical goal is pure prediction modeling.

  9. NOx PREDICTION FOR FBC BOILERS USING EMPIRICAL MODELS

    Directory of Open Access Journals (Sweden)

    Jiří Štefanica

    2014-02-01

    Full Text Available Reliable prediction of NOx emissions can provide useful information for boiler design and fuel selection. Recently used kinetic prediction models for FBC boilers are overly complex and require large computing capacity. Even so, there are many uncertainties in the case of FBC boilers. An empirical modeling approach for NOx prediction has been used exclusively for PCC boilers. No reference is available for modifying this method for FBC conditions. This paper presents possible advantages of empirical modeling based prediction of NOx emissions for FBC boilers, together with a discussion of its limitations. Empirical models are reviewed, and are applied to operation data from FBC boilers used for combusting Czech lignite coal or coal-biomass mixtures. Modifications to the model are proposed in accordance with theoretical knowledge and prediction accuracy.

  10. Aircraft crash survivability from viscous injury in vertical impacts

    OpenAIRE

    Barth, Thomas H.

    2009-01-01

    This research investigated viscous injury from vertical impact loading to determine if it is critical to survivability of aircraft accidents. A unique database was built from autopsy reports and accident investigations combining injury data with the vehicle impact data. Computer models were created and used to assess injury potential. Common design limits and actual crash data from full scale research experiments were used as inputs. The results were analyzed according to publi...

  11. Complex versus simple models: ion-channel cardiac toxicity prediction.

    Science.gov (United States)

    Mistry, Hitesh B

    2018-01-01

    There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model B net was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the B net model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  12. Complex versus simple models: ion-channel cardiac toxicity prediction

    Directory of Open Access Journals (Sweden)

    Hitesh B. Mistry

    2018-02-01

    Full Text Available There is growing interest in applying detailed mathematical models of the heart for ion-channel related cardiac toxicity prediction. However, a debate as to whether such complex models are required exists. Here an assessment in the predictive performance between two established large-scale biophysical cardiac models and a simple linear model Bnet was conducted. Three ion-channel data-sets were extracted from literature. Each compound was designated a cardiac risk category using two different classification schemes based on information within CredibleMeds. The predictive performance of each model within each data-set for each classification scheme was assessed via a leave-one-out cross validation. Overall the Bnet model performed equally as well as the leading cardiac models in two of the data-sets and outperformed both cardiac models on the latest. These results highlight the importance of benchmarking complex versus simple models but also encourage the development of simple models.

  13. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

    Science.gov (United States)

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

    2012-01-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  14. [Application of ARIMA model on prediction of malaria incidence].

    Science.gov (United States)

    Jing, Xia; Hua-Xun, Zhang; Wen, Lin; Su-Jian, Pei; Ling-Cong, Sun; Xiao-Rong, Dong; Mu-Min, Cao; Dong-Ni, Wu; Shunxiang, Cai

    2016-01-29

    To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA). SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation. The model of ARIMA (1, 1, 1) (1, 1, 0) 12 was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% CI of predicted value of the model. The prediction effect of the model was acceptable. The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

  15. Mobility Modelling through Trajectory Decomposition and Prediction

    OpenAIRE

    Faghihi, Farbod

    2017-01-01

    The ubiquity of mobile devices with positioning sensors make it possible to derive user's location at any time. However, constantly sensing the position in order to track the user's movement is not feasible, either due to the unavailability of sensors, or computational and storage burdens. In this thesis, we present and evaluate a novel approach for efficiently tracking user's movement trajectories using decomposition and prediction of trajectories. We facilitate tracking by taking advantage ...

  16. Poisson Mixture Regression Models for Heart Disease Prediction

    Science.gov (United States)

    Erol, Hamza

    2016-01-01

    Early heart disease control can be achieved by high disease prediction and diagnosis efficiency. This paper focuses on the use of model based clustering techniques to predict and diagnose heart disease via Poisson mixture regression models. Analysis and application of Poisson mixture regression models is here addressed under two different classes: standard and concomitant variable mixture regression models. Results show that a two-component concomitant variable Poisson mixture regression model predicts heart disease better than both the standard Poisson mixture regression model and the ordinary general linear Poisson regression model due to its low Bayesian Information Criteria value. Furthermore, a Zero Inflated Poisson Mixture Regression model turned out to be the best model for heart prediction over all models as it both clusters individuals into high or low risk category and predicts rate to heart disease componentwise given clusters available. It is deduced that heart disease prediction can be effectively done by identifying the major risks componentwise using Poisson mixture regression model. PMID:27999611

  17. Predicting birth weight with conditionally linear transformation models.

    Science.gov (United States)

    Möst, Lisa; Schmid, Matthias; Faschingbauer, Florian; Hothorn, Torsten

    2016-12-01

    Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs. © The Author(s) 2014.

  18. Evaluation of the crash mitigation effect of low-speed automated emergency braking systems based on insurance claims data.

    Science.gov (United States)

    Isaksson-Hellman, Irene; Lindman, Magdalena

    2016-09-01

    The aim of the present study was to evaluate the crash mitigation performance of low-speed automated emergency braking collision avoidance technologies by examining crash rates, car damage, and personal injuries. Insurance claims data were used to identify rear-end frontal collisions, the specific situations where the low-speed automated emergency braking system intervenes. We compared cars of the same model (Volvo V70) with and without the low-speed automated emergency braking system (AEB and no AEB, respectively). Distributions of spare parts required for car repair were analyzed to identify car damage, and crash severity was estimated by comparing the results with laboratory crash tests. Repair costs and occupant injuries were investigated for both the striking and the struck vehicle. Rear-end frontal collisions were reduced by 27% for cars with low-speed AEB compared to cars without the system. Those of low severity were reduced by 37%, though more severe crashes were not reduced. Accordingly, the number of injured occupants in vehicles struck by low-speed AEB cars was reduced in low-severity crashes. In offset crash configurations, the system was found to be less effective. This study adds important information about the safety performance of collision avoidance technologies, beyond the number of crashes avoided. By combining insurance claims data and information from spare parts used, the study demonstrates a mitigating effect of low-speed AEB in real-world traffic.

  19. Factors Contributing to Crashes among Young Drivers

    Directory of Open Access Journals (Sweden)

    Lyndel J. Bates

    2014-08-01

    Full Text Available Young drivers are the group of drivers most likely to crash. There are a number of factors that contribute to the high crash risk experienced by these drivers. While some of these factors are intrinsic to the young driver, such as their age, gender or driving skill, others relate to social factors and when and how often they drive. This article reviews the factors that affect the risk of young drivers crashing to enable a fuller understanding of why this risk is so high in order to assist in developing effective countermeasures.

  20. Prediction of hourly solar radiation with multi-model framework

    International Nuclear Information System (INIS)

    Wu, Ji; Chan, Chee Keong

    2013-01-01

    Highlights: • A novel approach to predict solar radiation through the use of clustering paradigms. • Development of prediction models based on the intrinsic pattern observed in each cluster. • Prediction based on proper clustering and selection of model on current time provides better results than other methods. • Experiments were conducted on actual solar radiation data obtained from a weather station in Singapore. - Abstract: In this paper, a novel multi-model prediction framework for prediction of solar radiation is proposed. The framework started with the assumption that there are several patterns embedded in the solar radiation series. To extract the underlying pattern, the solar radiation series is first segmented into smaller subsequences, and the subsequences are further grouped into different clusters. For each cluster, an appropriate prediction model is trained. Hence a procedure for pattern identification is developed to identify the proper pattern that fits the current period. Based on this pattern, the corresponding prediction model is applied to obtain the prediction value. The prediction result of the proposed framework is then compared to other techniques. It is shown that the proposed framework provides superior performance as compared to others