Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Experimental evaluation of hotspot identification methods

Identifying crash “hotspots”, “blackspots”, “sites with promise”, or “high risk” locations is standard practice in departments of transportation throughout the US. The literature is replete with the development and discussion of statistical methods for hotspot identification (HSID). Theoretical derivations and empirical studies have been used to weigh the benefits of various HSID methods; however, a small number of studies have used controlled experiments to systematically assess various methods. Using experimentally derived simulated data—which are argued to be superior to empirical data, three hot spot identification methods observed in practice are evaluated: simple ranking, confidence interval, and Empirical Bayes. Using simulated data, sites with promise are known a priori, in contrast to empirical data where high risk sites are not known for certain. To conduct the evaluation, properties of observed crash data are used to generate simulated crash frequency distributions at hypothetical sites. A variety of factors is manipulated to simulate a host of ‘real world’ conditions. Various levels of confidence are explored, and false positives (identifying a safe site as high risk) and false negatives (identifying a high risk site as safe) are compared across methods. Finally, the effects of crash history duration in the three HSID approaches are assessed. The results illustrate that the Empirical Bayes technique significantly outperforms ranking and confidence interval techniques (with certain caveats). As found by others, false positives and negatives are inversely related. Three years of crash history appears, in general, to provide an appropriate crash history duration.

Railway junction traffic control by heuristic methods

Traffic conflicts at railway junctions are very conmon, particularly on congested rail lines. While safe passage through the junction is well maintained by the signalling and interlocking systems, minimising the delays imposed on the trains by assigning the right-of-way sequence sensibly is a bonus to the quality of service. A deterministic method has been adopted to resolve the conflict, with the objective of minimising the total weighted delay. However, the computational demand remains significant. The applications of different heuristic methods to tackle this problem are reviewed and explored, elaborating their feasibility in various aspects and comparing their relative merits for further studies. As most heuristic methods do not guarantee a global optimum, this study focuses on the trade-off between computation time and optimality of the resolution.

Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways.

Component reliability estimations without field data

Maintenance activities in a large-scale engineering system are usually scheduled according to the lifetimes of various components in order to ensure the overall reliability of the system. Lifetimes of components can be deduced by the corresponding probability distributions with parameters estimated from past failure data. While failure data of the components is not always readily available, the engineers have to be content with the primitive information from the manufacturers only, such as the mean and standard deviation of lifetime, to plan for the maintenance activities. In this paper, the moment-based piecewise polynomial model (MPPM) are proposed to estimate the parameters of the reliability probability distribution of the products when only the mean and standard deviation of the product lifetime are known. This method employs a group of polynomial functions to estimate the two parameters of the Weibull Distribution according to the mathematical relationship between the shape parameter of two-parameters Weibull Distribution and the ratio of mean and standard deviation. Tests are carried out to evaluate the validity and accuracy of the proposed methods with discussions on its suitability of applications. The proposed method is particularly useful for reliability-critical systems, such as railway and power systems, in which the maintenance activities are scheduled according to the expected lifetimes of the system components.

Secure tracking for critical applications : communications, GPS and future Galileo services

Tracking/remote monitoring systems using GNSS are a proven method to enhance the safety and security of personnel and vehicles carrying precious or hazardous cargo. While GNSS tracking appears to mitigate some of these threats, if not adequately secured, it can be a double-edged sword allowing adversaries to obtain sensitive shipment and vehicle position data to better coordinate their attacks, and to provide a false sense of security to monitoring centers. Tracking systems must be designed with the ability to perform route-compliance and thwart attacks ranging from low-level attacks such as the cutting of antenna cables to medium and high-level attacks involving radio jamming and signal / data-level simulation, especially where the goods transported have a potentially high value to terrorists. This paper discusses the use of GNSS in critical tracking applications, addressing the mitigation of GNSS security issues, augmentation systems and communication systems in order to provide highly robust and survivable tracking systems.

Journalism education dilemmas : career-focussed skill set, teamwork or critical thinking?

In Australian universities, journalism educators usually come to the academy from the journalism profession and consequently place a high priority on leading students to develop a career-focussed skill set. The changing nature of the technological, political and economic environments and the professional destinations of journalism graduates place demands on journalism curricula and educators alike. The profession is diverse, such that the better description is of many ‘journalisms’ rather than one ‘journalism’ with consequential pressures being placed on curricula to extend beyond the traditional skill set, where practical ‘writing’ and ‘editing’ skills dominate, to the incorporation of critical theory and the social construction of knowledge. A parallel set of challenges faces academic staff operating in a higher education environment where change is the only constant and research takes precedent over curriculum development. In this paper, three educators at separate universities report on their attempts to implement curriculum change to imbue graduates with better skills and attributes such as enhanced team work, problem solving and critical thinking, to operate in the divergent environment of 21st century journalism. The paper uses narrative case study to illustrate the different approaches. Data collected from formal university student evaluations inform the narratives along with rich but less formal qualitative data including anecdotal student comments and student reflective assessment presentations. Comparison of the three approaches illustrates the dilemmas academic staff face when teaching in disciplines that are impacted by rapid changes in technology requiring new pedagogical approaches. Recommendations for future directions are considered against the background or learning purpose.

Persons with age-related maculopathy risk genotypes and clinically normal eyes have reduced mesopic vision

PURPOSE: To determine if participants with normal visual acuity, no ophthalmoscopically signs of age-related maculopathy (ARM) in both eyes and who are carriers of the CFH, LOC387715 and HRTA1 high-risk genotypes (“gene-positive”) have impaired rod- and cone-mediated mesopic visual function compared to persons who do not carry the risk genotypes (“gene-negative”).---------- METHODS: Fifty-three Caucasian study participants (mean 55.8 ± 6.1) were genotyped for CFH, LOC387715/ARMS2 and HRTA1 polymorphisms. We genotyped single nucleotide polymorphisms (SNPs) in the CFH (rs380390), LOC387715/ARMS2 (rs10490924) and HTRA1 (rs11200638) genes using Applied Biosystems optimised TaqMan assays. We determined the critical fusion frequency (CFF) mediated by cones alone (Long, Middle and Short wavelength sensitive cones; LMS) and by the combined activities of cones and rods (LMSR). The stimuli were generated using a 4-primary photostimulator that provides independent control of the photoreceptor excitation under mesopic light levels. Visual function was further assessed using standard clinical tests, flicker perimetry and microperimetry.---------- RESULTS: The mesopic CFF mediated by rods and cones (LMSR) was significantly reduced in gene-positive compared to gene-negative participants after correction for age (p=0.03). Cone-mediated CFF (LMS) was not significantly different between gene-positive and -negative participants. There were no significant associations between flicker perimetry and microperimetry and genotype.---------- CONCLUSIONS: This is the first study to relate ARM risk genotypes with mesopic visual function in clinically normal persons. These preliminary results could become of clinical importance as mesopic vision may be used to document sub-clinical retinal changes in persons with risk genotypes and to determine whether those persons progress into manifest disease.

Rock pools of critical thought : finding a place to think through my higher degree and what a PhD was all about

The rock pools, salt pans, cliffs and bluffs, and the banks of the Coorooman and Pumpkin Creeks within Darumbal and Woppaburra Country are used as a backdrop in this paper, which offers an exploration of one woman’s quest to undertake her PhD and develop as an Indigenous scholar. The paper describes this Country and the use of Country to nourish, develop, stimulate and support the intellect. It draws on Australian and international literature to demonstrate the intellectual growth and development of Indigenous scholars. The paper offers a highly personal narrative of intellectual journeying which shows how we can be agents of change and power in our individual lives, even while power is being exercised over us and we are being oppressed and marginalised as Indigenous peoples.

Urban renewal from the inside out: Spatial and critical literacies in a low socioeconomic school community

This article focuses on how teachers worked to build a meaningful curriculum around changes to a neighborhood and school grounds in a precinct listed for urban renewal. Drawing on a long-term relationship with the principal and one teacher, the researchers planned and designed a collaborative project to involve children as active participants in the redevelopment process, negotiating and redesigning an area between the preschool and the school. The research investigated spatial literacies, that is, ways of thinking about and representing the production of spaces, and critical literacies, in this instance how young people might have a say in remaking part of their school grounds. Data included videotapes of key events, interviews, and an archive of the elementary students' artifacts experimenting with spatial literacies. The project builds on the insights of community members and researchers working for social justice in high-poverty areas internationally that indicate the importance of education, local action, family, and youth involvement in building sustainable and equitable communities.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Cultural Science and Methodological Challenge!

The processes of digitization and deregulation have transformed the production, distribution and consumption of information and entertainment media over the past three decades. Today, researchers are confronted with profoundly different landscapes of domestic and personal media than the pioneers of qualitative audience research that came to form much of the conceptual basis of Cultural Studies first in Britain and North America and subsequently across all global regions. The process of media convergence, as a consequence of the dual forces of digitisation and deregulation, thus constitutes a central concept in the analysis of popular mass media. From the study of the internationalisation and globalisation of media content, changing regimes of media production, via the social shaping and communication technologies and conversely the impact of communication technology on social, cultural and political realities, to the emergence of transmedia storytelling, the interplay of intertextuality and genre and the formation of mediated social networks, convergence informs and shapes contemporary conceptual debates in the field of popular communication and beyond. However, media convergence challenges not only the conceptual canon of (popular) communication research, but poses profound methodological challenges. As boundaries between producers and consumers are increasingly fluent, formerly stable fields and categories of research such as industries, texts and audiences intersect and overlap, requiring combined and new research strategies. This preconference aims to offer a forum to present and discuss methodological innovations in the study of contemporary media and the analysis of the social, cultural,and political impact and challenges arising through media convergence. The preconference thus aims to focus on the following methodological questions and challenges: *New strategies of audience research responding to the increasing individualisation of popular media consumption. *Methods of data triangulation in and through the integrated study of media production, distribution and consumption. *Bridging the methodological and often associated conceptual gap between qualitative and quantitative research in the study of popular media. *The future of ethnographic audience and production research in light of blurring boundaries between media producers and consumers. *A critical re-examination of which textual configurations can be meaningfully described and studied as text. *Methodological innovations aimed at assessing the macro social, cultural and political impact of mediatization (including, but not limited to, "creative methods"). *Methodological responses to the globalisation of popular media and practicalities of international and transnational comparative research. *An exploration of new methods required in the study of media flow and intertextuality.

Critical analysis of high particle number emissions from accelerating compressed natural gas buses

Compressed natural gas (CNG) engines are thought to be less harmful to the environment than conventional diesel engines, especially in terms of particle emissions. Although, this is true with respect to particulate matter (PM) emissions, results of particle number (PN) emission comparisons have been inconclusive. In this study, results of on-road and dynamometer studies of buses were used to derive several important conclusions. We show that, although PN emissions from CNG buses are significantly lower than from diesel buses at low engine power, they become comparable at high power. For diesel buses, PN emissions are not significantly different between acceleration and operation at steady maximum power. However, the corresponding PN emissions from CNG buses when accelerating are an order of magnitude greater than when operating at steady maximum power. During acceleration under heavy load, PN emissions from CNG buses are an order of magnitude higher than from diesel buses. The particles emitted from CNG buses are too small to contribute to PM10 emissions or contribute to a reduction of visibility, and may consist of semivolatile nanoparticles.