Benefits and issues of urban network travel time prediction

This paper presents the benefits and issues related to travel time prediction on urban network. Travel time information quantifies congestion and is perhaps the most important network performance measure. Travel time prediction has been an active area of research for the last five decades. The activities related to ITS have increased the attention of researchers for better and accurate real-time prediction of travel time. Majority of the literature on travel time prediction is applicable to freeways where, under non-incident conditions, traffic flow is not affected by external factors such as traffic control signals and opposing traffic flows. On urban environment the problem is more complicated due to conflicting areas (intersections), mid-link sources and sinks etc. and needs to be addressed.

Study on road traffic noise prediction model taking into account the citywide network

For the further noise reduction in the future, the traffic management which controls traffic flow and physical distribution is important. To conduct the measure by the traffic management effectively, it is necessary to apply the model for predicting the traffic flow in the citywide road network. For this purpose, the existing model named AVENUE was used as a macro-traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model, and the new road traffic noise prediction model was established. By using this prediction model, the noise map of entire city can be made. In this study, first, the change of traffic flow on the road network after the establishment of new roads was estimated, and the change of the road traffic noise caused by the new roads was predicted. As a result, it has been found that this prediction model has the ability to estimate the change of noise map by the traffic management. In addition, the macro-traffic flow model and our conventional micro-traffic flow model were combined, and the coverage of the noise prediction model was expanded.

Prediction and measurement of multiuser MIMO-OFDM channel in rural Australia

Commonwealth Scientific and Industrial Research Organization (CSIRO) has recently conducted a technology demonstration of a novel fixed wireless broadband access system in rural Australia. The system is based on multi user multiple-input multiple-output orthogonal frequency division multiplexing (MU-MIMO-OFDM). It demonstrated an uplink of six simultaneous users with distances ranging from 10 m to 8.5 km from a central tower, achieving 20 bits s/Hz spectrum efficiency. This paper reports on the analysis of channel capacity and bit error probability simulation based on the measured MUMIMO-OFDM channels obtained during the demonstration, and their comparison with the results based on channels simulated by a novel geometric optics based channel model suitable for MU-MIMO OFDM in rural areas. Despite its simplicity, the model was found to predict channel capacity and bit error rate probability accurately for a typical MU-MIMO-OFDM deployment scenario.

Evaluation of the skills for preventing injury in youth program : impact on health risk behaviors, injury and school connectedness

Injury is the leading cause of death among young people, and involvement in health risk behaviors, such as alcohol use and transport-related risks, is related to increased risk for injury. Effective health promotion programs for adolescents focus on multiple levels, including relationships with peers and parents, student knowledge, behavior and attitudes, and school-level factors such as school connectedness. This study describes the pilot evaluation of a comprehensive, multi-level injury prevention program for 13-14 year old adolescents, targeting change in injury associated with transport and alcohol risks. The program, called Skills for Preventing Injury in Youth (SPIY), incorporates two primary elements: an 8-week, teacher delivered attitude and behavior change curriculum with peer protection and first aid messages; and professional development for program teachers focusing on strategies to increase students’ connectedness to school. Five Australian high schools were recruited for the pilot evaluation research, with three being assigned to receive intervention components and two assigned as curriculum-as-usual controls. In the intervention schools, 118 Year 8 students participated in surveys at baseline, with 105 completing surveys at follow up, six months following the intervention. In the control schools, 196 Year 8 students completed surveys at baseline and 207 at follow up. Survey measures included self-reported injury, risk taking behavior and school connectedness. Results showed that students in the control schools were significantly more likely to report riding bikes without helmets, riding with dangerous drivers, having driven cars on the road, and using alcohol six months after the program, while the intervention group showed no such increase in these behaviors. Additionally, students in the control schools were significantly more likely to report having had pedestrian-related injuries at follow up than they were at the baseline measurement, while intervention school students showed no change. There was also a trend observed in terms of a decrease in bicycle related injuries among intervention school students, compared with a slight increasing trend in bicycle injuries among control students. Overall, scores on the school connectedness scale decreased significantly from baseline to follow up for both intervention and control students, however measurement limitations may have impacted on results relating to students’ connectedness. Overall, the SPIY program has shown promising results in regards to prevention of students’ health risk behavior and injuries. Evidence suggests that the curriculum component was important; however there was limited evidence to suggest that teacher training in school connectedness strategies contributed to these promising results. While school connectedness may be an important factor to target in risk and injury prevention programs, programs may need to incorporate whole-of-school strategies or target a broader range of teachers than were selected for the current research.

Prevention of pelvic sepsis in major open pelviperineal injury

Compound pelvic fractures are deemed to be one of the most severe orthopaedic injuries with an extremely high morbidity and mortality. After the initial resuscitation phase the prevention of pelvic sepsis is one of the main treatment goals for patients with an open pelvic fracture. If there is a suspicion of a rectal injury or if the wounds are in the perineal area, The Princess Alexandra Hospital's management plan includes early faecal diversion combined with vigorous soft tissue debridement, VAC(®) therapy and (if indicated) external fixation of the pelvic fracture. We present our flowchart for the treatment of trauma patients with compound pelvic fractures illustrated by a case report describing a 32 year old patient who sustained an open pelvic ring injury in a workplace accident. The aim of this paper is to underline the importance of a safe, straightforward approach to compound pelvic fractures.

Condition deterioration prediction of bridge elements using Dynamic Bayesian Networks (DBNs)

The ability of bridge deterioration models to predict future condition provides significant advantages in improving the effectiveness of maintenance decisions. This paper proposes a novel model using Dynamic Bayesian Networks (DBNs) for predicting the condition of bridge elements. The proposed model improves prediction results by being able to handle, deterioration dependencies among different bridge elements, the lack of full inspection histories, and joint considerations of both maintenance actions and environmental effects. With Bayesian updating capability, different types of data and information can be utilised as inputs. Expert knowledge can be used to deal with insufficient data as a starting point. The proposed model established a flexible basis for bridge systems deterioration modelling so that other models and Bayesian approaches can be further developed in one platform. A steel bridge main girder was chosen to validate the proposed model.

Developing safer passengers through a school-based injury prevention program

Motor vehicle crashes are a leading cause of death among young people. Fourteen percent of adolescents aged 13-14 report passenger-related injuries within three months. Intervention programs typically focus on young drivers and overlook passengers as potential protective influences. Graduated Driver Licensing restricts passenger numbers, and this study focuses on a complementary school-based intervention to increase passengers’ personal- and peer-protective behavior. The aim of this research was to assess the impact of the curriculum-based injury prevention program, Skills for Preventing Injury in Youth (SPIY), on passenger-related risk-taking and injuries, and intentions to intervene in friends’ risky road behavior. SPIY was implemented in Grade 8 Health classes and evaluated using survey and focus group data from 843 students across 10 Australian secondary schools. Intervention students reported less passenger-related risk-taking six months following the program. Their intention to protect friends from underage driving also increased. The results of this study show that a comprehensive, school-based program targeting individual and social changes can increase adolescent passenger safety.

Adolescent involvement in anti-social and delinquent behaviours : predicting future injury risk

The purpose of this study was to challenge the broadly based focus of injury prevention strategies towards concern with the needs of young adolescents who engage in multiple anti-social and delinquent behaviours. Five hundred and forty 13-14 year olds reported on injuries and truancy, violence, illegal road behaviours, drug, and alcohol use. Engagement in these behaviours was found to contribute to the likelihood of an injury. Those engaging in the most anti-social and delinquent behaviours were around five times more likely to report medically-treated injuries in the past three months. Their likelihood of future injury was 1.8 times more likely when they were followed up three months later. The engagement in multiple delinquent and illegal behaviours thus significantly increased the likelihood of injury and identifies a particularly vulnerable group. The findings also suggest that reaching these young people represents a key target for change strategies in injury prevention programs.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

Prediction of pull-out force of multi-walled carbon nanotube (MWCNT) in sword-in-sheath mode

The pull-out force of some outer walls against other inner walls in multi-walled carbon nanotubes (MWCNTs) was systematically studied by molecular mechanics simulations. The obtained results reveal that the pull-out force is proportional to the square of the diameter of the immediate outer wall on the sliding interface, which highlights the primary contribution of the capped section of MWCNT to the pull-out force. A simple empirical formula was proposed based on the numerical results to predict the pull-out force for an arbitrary pull-out in a given MWCNT directly from the diameter of the immediate outer wall on the sliding interface. Moreover, tensile tests for MWCNTs with and without acid-treatment were performed with a nanomanipulator inside a vacuum chamber of a scanning electron microscope (SEM) to validate the present empirical formula. It was found that the theoretical pull-out forces agree with the present and some previous experimental results very well.

Design and rationale of a Prospective, Observational European Multicenter study on the efficacy of acute surgical decompression after traumatic Spinal Cord Injury: the SCI-POEM study

Objectives:Despite many years of research, there is currently no treatment available that results in major neurological or functional recovery after traumatic spinal cord injury (tSCI). In particular, no conclusive data related to the role of the timing of decompressive surgery, and the impact of injury severity on its benefit, have been published to date. This paper presents a protocol that was designed to examine the hypothesized association between the timing of surgical decompression and the extent of neurological recovery in tSCI patients.Study design: The SCI-POEM study is a Prospective, Observational European Multicenter comparative cohort study. This study compares acute (<12 h) versus non-acute (>12 h, <2 weeks) decompressive surgery in patients with a traumatic spinal column injury and concomitant spinal cord injury. The sample size calculation was based on a representative European patient cohort of 492 tSCI patients. During a 4-year period, 300 patients will need to be enrolled from 10 trauma centers across Europe. The primary endpoint is lower-extremity motor score as assessed according to the 'International standards for neurological classification of SCI' at 12 months after injury. Secondary endpoints include motor, sensory, imaging and functional outcomes at 3, 6 and 12 months after injury.Conclusion:In order to minimize bias and reduce the impact of confounders, special attention is paid to key methodological principles in this study protocol. A significant difference in safety and/or efficacy endpoints will provide meaningful information to clinicians, as this would confirm the hypothesis that rapid referral to and treatment in specialized centers result in important improvements in tSCI patients.Spinal Cord advance online publication, 17 April 2012; doi:10.1038/sc.2012.34.