The nonprofit board as a team : pilot results and initial insights

There is a growing desire for boards of nonprofits to deliver better governance to the organizations they control. Consequently, self-evaluation has become an important tool for nonprofit boards to meet these expectations and demonstrate that they are discharging their responsibilities effectively. This article describes initial results aimed at developing a psychometrically sound, survey-based board evaluation instrument, based on the Team Development Survey (TDS), that assesses the team attributes of an organization’s board. Our results indicate that while constructs applicable to teams generally appear to apply to boards, there are also important differences. We highlight how a perception of board objective clarity, appropriate skills mix, resource availability, and psychological safety were positively and significantly associated with measures of board, management and organizational performance.

"My friend was over the alcohol limit, so I asked him not to drive" : Young females intervening in alcohol-impaired driving

Potential to strengthen a commitment to intervene within a friendship group: – all knew the other passengers, – 3 in 4 discussed intervening with other passengers, – expectations of friends was a key predictive factor. - young women have potential and willingness to intervene in their friends’ drink driving behaviour - majority of campaigns and strategies to reduce alcohol related crashes target the driver however it is arguable that some strategies should target the young female passenger.

An evaluation framework for assessing the impact of public bicycle share schemes

INTRODUCTION • Public bicycle share schemes have emerged as a method of increasing rates of bicycle riding. • The overwhelming majority of schemes have begun since 2005, taking advantage of various tracking and payment technologies making short term rental practical and affordable. • Very little research has been undertaken to determine their potentially broad impact on transport behaviour and consequently, it is difficult to understand the performance of these schemes in terms of reduced emissions and congestion, as well as possible increases in physical activity.

Young, inexperienced and on the road : do novice drivers comply with road rules?

The graduated driver licensing (GDL) program in Queensland, Australia, was considerably enhanced in July 2007. This paper explores the compliance of young Learner and Provisional (intermediate) drivers with current GDL requirements and general road rules. Unsupervised driving, Learner logbook accuracy, and experiences of punishment avoidance were explored, along with speeding as a Provisional driver. Participants (609 females; M = 17.43 years) self-reported sociodemographic characteristics, driving behaviours and licensing experiences as Learners. A subset of participants (238 females, 105 males) completed another survey six months later exploring their Provisional behaviours and experiences. While the majority of the participants reported compliance with both the GDL requirements and general road rules such as stopping at red lights on their Learner licence; a considerable proportion reported speeding. Furthermore, they reported becoming less compliant during the Provisional phase, particularly with speed limits. Self-reported speeding was predicted by younger age at licensure, being in a relationship, driving unsupervised, submitting inaccurate Learner logbooks, and speeding as a Learner. Enforcement and education countermeasures should focus upon curtailing noncompliance, targeting speeding in particular. Novice drivers should be encouraged to comply with all road rules, including speed limits, and safe driving behaviours should be developed and reinforced during the Learner and early Provisional periods. Novice drivers have been found to model their parents’ driving, and parents are pivotal in regulating novice driving. It is vital young novice drivers and parents alike are encouraged to comply with all road rules, including GDL requirements.

FPGA implementation of an evolutionary algorithm for autonomous unmanned aerial vehicle on-board path planning

In this paper, a hardware-based path planning architecture for unmanned aerial vehicle (UAV) adaptation is proposed. The architecture aims to provide UAVs with higher autonomy using an application specific evolutionary algorithm (EA) implemented entirely on a field programmable gate array (FPGA) chip. The physical attributes of an FPGA chip, being compact in size and low in power consumption, compliments it to be an ideal platform for UAV applications. The design, which is implemented entirely in hardware, consists of EA modules, population storage resources, and three-dimensional terrain information necessary to the path planning process, subject to constraints accounted for separately via UAV, environment and mission profiles. The architecture has been successfully synthesised for a target Xilinx Virtex-4 FPGA platform with 32% logic slices utilisation. Results obtained from case studies for a small UAV helicopter with environment derived from LIDAR (Light Detection and Ranging) data verify the effectiveness of the proposed FPGA-based path planner, and demonstrate convergence at rates above the typical 10 Hz update frequency of an autopilot system.

See and avoid using on-board computer vision

The integration of unmanned aircraft into civil airspace is a complex issue. One key question is whether unmanned aircraft can operate just as safely as their manned counterparts. The absence of a human pilot in unmanned aircraft automatically points to a deficiency that is the lack of an inherent see-and-avoid capability. To date, regulators have mandated that an “equivalent level of safety” be demonstrated before UAVs are permitted to routinely operate in civil airspace. This chapter proposes techniques, methods, and hardware integrations that describe a “sense-and-avoid” system designed to address the lack of a see-and-avoid capability in UAVs.

The lived experience of post-traumatic stress disorder as described by motor vehicle accident victims in Jordan

Aim: To explore the lived experience of post-traumatic stress disorder (PTSD) as described by individuals who have been involved in a motor vehicle accident (MVA) in Jordan. Background: Motor vehicle accident (MVA) survivors who develop post-traumatic stress disorder (PTSD) have become an important health issue. The World Health Organisation (WHO) states that trauma resulting from MVAs is a phenomenon of increasing concern, with death from injuries projected to rise from 5.1 million in 1990 to 8.4 million in 2020 particularly in developing countries such as Jordan (WHO, 2002). The impact of trauma from MVAs inevitably compromises the victim’s quality of life (WHO, 2002; Blanchard & Hickling, 2007) resulting in psychological and emotional distress, occupational disability, family disintegration, and socio-economic difficulty (Jordan Ministry of Health, 2005). The development of PTSD as a result of an MVA is not limited to the individual, but also extends to the family, friends, and the health care team involved in the person's care and rehabilitation. Design: A descriptive phenomenological approach was used for this study. Method: This study was conducted in an orthopaedic unit in Amera Basma Hospital in Irbid Jordan. Fifteen (15) participants were voluntary recruited through the process of purposeful sampling. Data was collected by face-to-face in depth-interviews. Interviews were digitally recorded and transcribed verbatim. The process of analysis was undertaken using Colaizzi’s (1978) eight step approach with the addition of two extra steps. Findings: The process of analysis identified seven themes explicated from the participants’ transcripts of interview. The seven themes were: 1. Feeling frustrated at a diminishing health status 2. Struggling to maintain a sense of independence 3. Harbouring feelings of not being able to recover 4. Feeling discriminated against and marginalised by society 5. Feeling ignored and neglected by health care professionals 6. Feeling abandoned by family, and 7. Moving toward acceptance through having faith in Allah. Conclusion: The findings of this study have the potential to make a significant contribution to extant knowledge on the topic which can inform future nursing practice, education, policy development, and research initiatives in Jordan and internationally.

Examining Exposure of Motorcycles at Signalized Intersections

Crash statistics in Singapore from 2001 to 2005 have shown that motorcycles are involved in about 54% of intersection crashes. The overall involvement of motorcycles in crashes as the not-at-fault party is about 43% but at intersections, the corresponding percentage is increased to 57%. Quasi-induced exposure estimates show that the motorcycle exposure rate at signalized intersections is 41.7% even though motorcycles account for only 19% of the vehicle population. This study seeks to examine in greater details, the problem of motorcycle exposure at signalized intersections. In particular, the exposure arising from potential crashes with red light running vehicles from the conflicting stream at four signalized intersections is investigated. The results show that motorcycles are more exposed because they tend to accumulate near the stop-line during the red phase to facilitate an earlier discharge during the initial period of the green which is the more vulnerable period. At sites where there are more weaving opportunities because the lanes are wider or where there are exclusive right-turn lanes, the accumulation is higher and hence an increased exposure is observed. The analysis also shows that the presence of heavy vehicles tends to decrease motorcycle exposure as their weaving opportunities become restricted as well as there is a greater reluctance for them to weave past or queue alongside the heavy vehicles and their effects intensify for narrower lane width.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Right-angle crash vulnerability of motorcycles at signalized intersections : mixed logit analysis

Motorcycles are particularly vulnerable in right-angle crashes at signalized intersections. The objective of this study is to explore how variations in roadway characteristics, environmental factors, traffic factors, maneuver types, human factors as well as driver demographics influence the right-angle crash vulnerability of motorcycles at intersections. The problem is modeled using a mixed logit model with a binary choice category formulation to differentiate how an at-fault vehicle collides with a not-at-fault motorcycle in comparison to other collision types. The mixed logit formulation allows randomness in the parameters and hence takes into account the underlying heterogeneities potentially inherent in driver behavior, and other unobserved variables. A likelihood ratio test reveals that the mixed logit model is indeed better than the standard logit model. Night time riding shows a positive association with the vulnerability of motorcyclists. Moreover, motorcyclists are particularly vulnerable on single lane roads, on the curb and median lanes of multi-lane roads, and on one-way and two-way road type relative to divided-highway. Drivers who deliberately run red light as well as those who are careless towards motorcyclists especially when making turns at intersections increase the vulnerability of motorcyclists. Drivers appear more restrained when there is a passenger onboard and this has decreased the crash potential with motorcyclists. The presence of red light cameras also significantly decreases right-angle crash vulnerabilities of motorcyclists. The findings of this study would be helpful in developing more targeted countermeasures for traffic enforcement, driver/rider training and/or education, safety awareness programs to reduce the vulnerability of motorcyclists.

An estimate of road accident costs in Singapore

An earlier study by the Asian Development Bank (ADB) showed that the annual cost of road traffic accidents in 2001 was S$699.36 million which was 0.5% of the annual GDP. This paper attempts to update of the cost estimates of road traffic accidents. More precise methods of computing the human cost, lost output and property damage are adopted which grew in an annual cost of S$610.3 million or 0.338% of the annual GDP in 2003. A more conservative estimate of S$878,000 for fatal accident is also obtained, compared to the earlier figure of S$1.4 million. This study has shown that it is necessary to update the annual traffic accident costs regularly, as the figures vary with the number of accidents which change with time.

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.

Factors affecting motorcycle crashes at signalized intersections

Singapore crash statistics show that motorcycles are involved in about 54% of crashes at intersections. Moreover, about 46% of fatal and 67% of injury motorcycle crashes occur at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and three-legged signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag 1 dependent specification in the error term is the most suitable. Analysis of the results shows the number of lanes at the intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median at four-legged intersections and an exclusive right-turn lane and an uncontrolled left-turn lane at three-legged intersections exacerbate this potential hazard. Moreover, motorcycle crashes increase on high-speed roadways because of the vulnerability of the motorcyclists. The presence of red light cameras reduces motorcycle crashes significantly on the intersection roadways for both four-legged and three-legged intersections. With the red-light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.

Using BIM for smarter and safer scaffolding and formwork construction: a preliminary methodology

The goal of this research project is to develop specific BIM objects for temporary construction activities which are fully integrated with object design, construction efficiency and safety parameters. Specifically, the project will deliver modularised electronic scaffolding and formwork objects that will allow designers to easily incorporate them into BIM models to facilitate smarter and safer infrastructure and building construction. This research first identified there is currently a distinct lack of BIM objects for temporary construction works resulting in productivity loss during design and construction, and opportunities for improved consideration of safety standards and practices with the design of scaffolding and formwork. This is particularly relevant in Australia, given the “harmonisation” of OHS legislation across all states and territories from 1 January 2012, meaning that enhancements to Queensland practices will have direct application across Australia. Thus, in conjunction with government and industry partners in Queensland, Australia, the research team developed a strategic three-phase research methodology: (1) the preliminary review phase on industrial scaffolding and formwork practices and BIM implementation; (2) the BIM object development phase with specific safety and productivity functions; and (3) the Queensland-wide workshop phase for product dissemination and training. This paper discusses background review findings, details of the developed methodology, and expected research outcomes and their contributions to the Australian construction industry.