Communications materials on methods of development of revenue and cost estimates to non-technical audiences

This CDROM includes PDFs of presentations on the following topics: "TXDOT Revenue and Expenditure Trends;" "Examine Highway Fund Diversions, & Benchmark Texas Vehicle Registration Fees;" "Evaluation of the JACK Model;" "Future highway construction cost trends;" "Fuel Efficiency Trends and Revenue Impact"

Stability and convergence of implicit numerical methods for a class of fractional advection-dispersion models

In this paper, a class of fractional advection-dispersion models (FADM) is investigated. These models include five fractional advection-dispersion models: the immobile, mobile/immobile time FADM with a temporal fractional derivative 0 < γ < 1, the space FADM with skewness, both the time and space FADM and the time fractional advection-diffusion-wave model with damping with index 1 < γ < 2. They describe nonlocal dependence on either time or space, or both, to explain the development of anomalous dispersion. These equations can be used to simulate regional-scale anomalous dispersion with heavy tails, for example, the solute transport in watershed catchments and rivers. We propose computationally effective implicit numerical methods for these FADM. The stability and convergence of the implicit numerical methods are analyzed and compared systematically. Finally, some results are given to demonstrate the effectiveness of our theoretical analysis.

Building Large Scale Traversability Maps Using Vehicle Experience

Traversability maps are a global spatial representation of the relative difficulty in driving through a local region. These maps support simple optimisation of robot paths and have been very popular in path planning techniques. Despite the popularity of these maps, the methods for generating global traversability maps have been limited to using a-priori information. This paper explores the construction of large scale traversability maps for a vehicle performing a repeated activity in a bounded working environment, such as a repeated delivery task.We evaluate the use of vehicle power consumption, longitudinal slip, lateral slip and vehicle orientation to classify the traversability and incorporate this into a map generated from sparse information.

Malnutrition screening tools : comparison against two validated nutrition assessment methods in older medical inpatients

Objective Although several validated nutritional screening tools have been developed to “triage” inpatients for malnutrition diagnosis and intervention, there continues to be debate in the literature as to which tool/tools clinicians should use in practice. This study compared the accuracy of seven validated screening tools in older medical inpatients against two validated nutritional assessment methods. Methods This was a prospective cohort study of medical inpatients at least 65 y old. Malnutrition screening was conducted using seven tools recommended in evidence-based guidelines. Nutritional status was assessed by an accredited practicing dietitian using the Subjective Global Assessment (SGA) and the Mini-Nutritional Assessment (MNA). Energy intake was observed on a single day during first week of hospitalization. Results In this sample of 134 participants (80 ± 8 y old, 50% women), there was fair agreement between the SGA and MNA (κ = 0.53), with MNA identifying more “at-risk” patients and the SGA better identifying existing malnutrition. Most tools were accurate in identifying patients with malnutrition as determined by the SGA, in particular the Malnutrition Screening Tool and the Nutritional Risk Screening 2002. The MNA Short Form was most accurate at identifying nutritional risk according to the MNA. No tool accurately predicted patients with inadequate energy intake in the hospital. Conclusion Because all tools generally performed well, clinicians should consider choosing a screening tool that best aligns with their chosen nutritional assessment and is easiest to implement in practice. This study confirmed the importance of rescreening and monitoring food intake to allow the early identification and prevention of nutritional decline in patients with a poor intake during hospitalization.

The hygienic efficacy of different hand-drying methods : a review of the evidence

The transmission of bacteria is more likely to occur from wet skin than from dry skin; therefore, the proper drying of hands after washing should be an integral part of the hand hygiene process in health care. This article systematically reviews the research on the hygienic efficacy of different hand-drying methods. A literature search was conducted in April 2011 using the electronic databases PubMed, Scopus, and Web of Science. Search terms used were hand dryer and hand drying. The search was limited to articles published in English from January 1970 through March 2011. Twelve studies were included in the review. Hand-drying effectiveness includes the speed of drying, degree of dryness, effective removal of bacteria, and prevention of cross-contamination. This review found little agreement regarding the relative effectiveness of electric air dryers. However, most studies suggest that paper towels can dry hands efficiently, remove bacteria effectively, and cause less contamination of the washroom environment. From a hygiene viewpoint, paper towels are superior to electric air dryers. Paper towels should be recommended in locations where hygiene is paramount, such as hospitals and clinics.

Correlation-based damage detection for complicated truss bridges using multi-layer genetic algorithms

The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.

Understanding teachers' reporting of child sexual abuse : measurement methods matter

The present study considered factors influencing teachers' reporting of child sexual abuse (CSA). Conducted in three Australian jurisdictions with different reporting laws and policies, the study focused on teachers' actual past and anticipated future reporting of CSA. A sample of 470 teachers within randomly selected rural and urban schools was surveyed, to identify training and experience; knowledge of reporting legislation and policy; attitudes; and reporting practices. Factors influencing actual past reporting and anticipated future reporting were identified using logistic regression modelling. This is the first study to simultaneously examine the effect of important influences in reporting practice using both retrospective and prospective approaches across jurisdictions with different reporting laws. Teachers who have actually reported CSA in the past are more likely have higher levels of policy knowledge, and hold more positive attitudes towards reporting CSA along three specific dimensions: commitment to the reporting role; confidence in the system's effective response to their reporting; and they are more likely to be able to override their concerns about the consequences of their reporting. Teachers indicating intention to report hypothetical scenarios are more likely to hold reasonable grounds for suspecting CSA, to recognise that significant harm has been caused to the child, to know that their school policy requires a report, and to be able to override their concerns about the consequences of their reporting.

Novel methods and the maximum likelihood estimation technique for estimating traffic critical gap

Most unsignalised intersection capacity calculation procedures are based on gap acceptance models. Accuracy of critical gap estimation affects accuracy of capacity and delay estimation. Several methods have been published to estimate drivers’ sample mean critical gap, the Maximum Likelihood Estimation (MLE) technique regarded as the most accurate. This study assesses three novel methods; Average Central Gap (ACG) method, Strength Weighted Central Gap method (SWCG), and Mode Central Gap method (MCG), against MLE for their fidelity in rendering true sample mean critical gaps. A Monte Carlo event based simulation model was used to draw the maximum rejected gap and accepted gap for each of a sample of 300 drivers across 32 simulation runs. Simulation mean critical gap is varied between 3s and 8s, while offered gap rate is varied between 0.05veh/s and 0.55veh/s. This study affirms that MLE provides a close to perfect fit to simulation mean critical gaps across a broad range of conditions. The MCG method also provides an almost perfect fit and has superior computational simplicity and efficiency to the MLE. The SWCG method performs robustly under high flows; however, poorly under low to moderate flows. Further research is recommended using field traffic data, under a variety of minor stream and major stream flow conditions for a variety of minor stream movement types, to compare critical gap estimates using MLE against MCG. Should the MCG method prove as robust as MLE, serious consideration should be given to its adoption to estimate critical gap parameters in guidelines.

Innovative damage assessment of steel truss bridges using modal strain energy correlation

As a part of vital infrastructure and transportation network, bridge structures must function safely at all times. Bridges are designed to have a long life span. At any point in time, however, some bridges are aged. The ageing of bridge structures, given the rapidly growing demand of heavy and fast inter-city passages and continuous increase of freight transportation, would require diligence on bridge owners to ensure that the infrastructure is healthy at reasonable cost. In recent decades, a new technique, structural health monitoring (SHM), has emerged to meet this challenge. In this new engineering discipline, structural modal identification and damage detection have formed a vital component. Witnessed by an increasing number of publications is that the change in vibration characteristics is widely and deeply investigated to assess structural damage. Although a number of publications have addressed the feasibility of various methods through experimental verifications, few of them have focused on steel truss bridges. Finding a feasible vibration-based damage indicator for steel truss bridges and solving the difficulties in practical modal identification to support damage detection motivated this research project. This research was to derive an innovative method to assess structural damage in steel truss bridges. First, it proposed a new damage indicator that relies on optimising the correlation between theoretical and measured modal strain energy. The optimisation is powered by a newly proposed multilayer genetic algorithm. In addition, a selection criterion for damage-sensitive modes has been studied to achieve more efficient and accurate damage detection results. Second, in order to support the proposed damage indicator, the research studied the applications of two state-of-the-art modal identification techniques by considering some practical difficulties: the limited instrumentation, the influence of environmental noise, the difficulties in finite element model updating, and the data selection problem in the output-only modal identification methods. The numerical (by a planer truss model) and experimental (by a laboratory through truss bridge) verifications have proved the effectiveness and feasibility of the proposed damage detection scheme. The modal strain energy-based indicator was found to be sensitive to the damage in steel truss bridges with incomplete measurement. It has shown the damage indicator's potential in practical applications of steel truss bridges. Lastly, the achievement and limitation of this study, and lessons learnt from the modal analysis have been summarised.

Evaluation of precision time synchronisation methods for substation applications

Many substation applications require accurate time-stamping. The performance of systems such as Network Time Protocol (NTP), IRIG-B and one pulse per second (1-PPS) have been sufficient to date. However, new applications, including IEC 61850-9-2 process bus and phasor measurement, require accuracy of one microsecond or better. Furthermore, process bus applications are taking time synchronisation out into high voltage switchyards where cable lengths may have an impact on timing accuracy. IEEE Std 1588, Precision Time Protocol (PTP), is the means preferred by the smart grid standardisation roadmaps (from both the IEC and US National Institute of Standards and Technology) of achieving this higher level of performance, and integrates well into Ethernet based substation automation systems. Significant benefits of PTP include automatic path length compensation, support for redundant time sources and the cabling efficiency of a shared network. This paper benchmarks the performance of established IRIG-B and 1-PPS synchronisation methods over a range of path lengths representative of a transmission substation. The performance of PTP using the same distribution system is then evaluated and compared to the existing methods to determine if the performance justifies the additional complexity. Experimental results show that a PTP timing system maintains the synchronising performance of 1-PPS and IRIG-B timing systems, when using the same fibre optic cables, and further meets the needs of process buses in large substations.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

Hardness of silicon nitride thin films characterised by nanoindentation and nanoscratch deconvolution methods

Plasma enhanced chemical vapour deposition silicon nitride thin films are widely used in microelectromechanical system devices as structural materials because the mechanical properties of those films can be tailored by adjusting deposition conditions. However, accurate measurement of the mechanical properties, such as hardness, of films with thicknesses at nanometric scale is challenging. In the present study, the hardness of the silicon nitride films deposited on silicon substrate under different deposit conditions was characterised using nanoindentation and nanoscratch deconvolution methods. The hardness values obtained from the two methods were compared. The effect of substrate on the measured results was discussed.

Solution methods for advection-diffusion-reaction equations on growing domains and subdomains, with application to modelling skin substitutes

Problems involving the solution of advection-diffusion-reaction equations on domains and subdomains whose growth affects and is affected by these equations, commonly arise in developmental biology. Here, a mathematical framework for these situations, together with methods for obtaining spatio-temporal solutions and steady states of models built from this framework, is presented. The framework and methods are applied to a recently published model of epidermal skin substitutes. Despite the use of Eulerian schemes, excellent agreement is obtained between the numerical spatio-temporal, numerical steady state, and analytical solutions of the model.

Gender differences in recreational and transport cycling : a cross-sectional mixed-methods comparison of cycling patterns, motivators, and constraints

Background: Gender differences in cycling are well-documented. However, most analyses of gender differences make broad comparisons, with few studies modeling male and female cycling patterns separately for recreational and transport cycling. This modeling is important, in order to improve our efforts to promote cycling to women and men in countries like Australia with low rates of transport cycling. The main aim of this study was to examine gender differences in cycling patterns and in motivators and constraints to cycling, separately for recreational and transport cycling. Methods: Adult members of a Queensland, Australia, community bicycling organization completed an online survey about their cycling patterns; cycling purposes; and personal, social and perceived environmental motivators and constraints (47% response rate). Closed and open-end questions were completed. Using the quantitative data, multivariable linear, logistic and ordinal regression models were used to examine associations between gender and cycling patterns, motivators and constraints. The qualitative data were thematically analysed to expand upon the quantitative findings. Results: In this sample of 1862 bicyclists, men were more likely than women to cycle for recreation and for transport, and they cycled for longer. Most transport cycling was for commuting, with men more likely than women to commute by bicycle. Men were more likely to cycle on-road, and women off-road. However, most men and women did not prefer to cycle on-road without designed bicycle lanes, and qualitative data indicated a strong preference by men and women for bicycle-only off-road paths. Both genders reported personal factors (health and enjoyment related) as motivators for cycling, although women were more likely to agree that other personal, social and environmental factors were also motivating. The main constraints for both genders and both cycling purposes were perceived environmental factors related to traffic conditions, motorist aggression and safety. Women, however, reported more constraints, and were more likely to report as constraints other environmental factors and personal factors. Conclusion: Differences found in men’s and women’s cycling patterns, motivators and constraints should be considered in efforts to promote cycling, particularly in efforts to increase cycling for transport.