Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

What is an expert? A systems perspective on expertise

1. Expert knowledge continues to gain recognition as a valuable source of information in a wide range of research applications. Despite recent advances in defining expert knowledge, comparatively little attention has been given to how to view expertise as a system of interacting contributory factors, and thereby, to quantify an individual’s expertise. 2. We present a systems approach to describing expertise that accounts for many contributing factors and their interrelationships, and allows quantification of an individual’s expertise. A Bayesian network (BN) was chosen for this purpose. For the purpose of illustration, we focused on taxonomic expertise. The model structure was developed in consultation with professional taxonomists. The relative importance of the factors within the network were determined by a second set of senior taxonomists. This second set of experts (i.e. supra-experts) also provided validation of the model structure. Model performance was then assessed by applying the model to hypothetical career states in the discipline of taxonomy. Hypothetical career states were used to incorporate the greatest possible differences in career states and provide an opportunity to test the model against known inputs. 3. The resulting BN model consisted of 18 primary nodes feeding through one to three higher-order nodes before converging on the target node (Taxonomic Expert). There was strong consistency among node weights provided by the supra-experts for some nodes, but not others. The higher order nodes, “Quality of work” and “Total productivity”, had the greatest weights. Sensitivity analysis indicated that although some factors had stronger influence in the outer nodes of the network, there was relatively equal influence of the factors leading directly into the target node. Despite differences in the node weights provided by our supra-experts, there was remarkably good agreement among assessments of our hypothetical experts that accurately reflected differences we had built into them. 4. This systems approach provides a novel way of assessing the overall level of expertise of individuals, accounting for multiple contributory factors, and their interactions. Our approach is adaptable to other situations where it is desirable to understand components of expertise.

Understanding player threat responses in FPS games

This paper describes the results of a study designed to understand the components contributing to a participant's assessment of threatening situations in a competitive First Person Shooter (FPS) game Quake III: Arena. The analysis process described compares theoretical, questionnaire based data with that of actual game play footage and identifies how skill and experience can affect a player's ability to accurately assess threat. This research also identifies relationships between variables contributing to a participant's threat assessment process which are not usually acknowledged in game AI design. A suggestion for integrating player-like threat based decision making processes is proposed.

Murray Valley Encephalitis

Outbreaks of an acute, severe, encephalitic illness, clinically similar to Japanese and St. Louis encephalitis, occurred in rural areas of southeastern Australia in 1917, 1918, 1922, 1925, 1951, and 1974[1,9,14-16] and in north and northwestern Australia in 1981, 1993, and 2000.[8,12,41] Approximately 420 cases were reported in these nine outbreaks.[41] They are thought to represent a single entity for which various names (Australian X disease, Murray Valley encephalitis, Australian encephalitis) have been used. Twenty-two cases were diagnosed in the 5 years between 2007 and 2011; three were fatal, and one of the fatalities occurred in a Canadian tourist on return from a holiday in northern Australia. Case-fatality rates, as high as 70 percent in the early years,[9,11] declined to 20 percent in the 1974 outbreak and have remained at about this level since then.[5,10,12] However, significant residual neurologic disability occurs in as many as 50 percent of survivors.[10,12] The presence of this disease in Papua New Guinea was confirmed in 1956.[20] The causative virus was transmitted to experimental animals as early as 1918,[6,11] although those strains could not be maintained. The definitive isolation and characterization of Murray Valley encephalitis virus in 1951[19] led to epidemiologic studies that suggested its survival in bird-mosquito cycles in northern Australia but not in the area of epidemic occurrence in southern Australia.[1] Murray Valley encephalitis is caused by Murray Valley encephalitis virus. In an effort to dissociate a disease from a specific locality, the term Australian encephalitis was proposed by residents of Murray Valley for the disease caused by Murray Valley encephalitis virus. Some researchers subsequently have attempted to expand the term Australian encephalitis to include encephalitis caused by any Australian arbovirus. Because the term Australian encephalitis has no scientific validity and is ambiguous, it should not be used.

What can we learn from the crashes of learner riders?

In some parts of Australia, people wanting to learn to ride a motorcycle are required to complete an off-road training course before they are allowed to practice on the road. In the state of Queensland, they are only required to pass a short multiple-choice road rules knowledge test. This paper describes an analysis of police-reported crashes involving learner riders in Queensland that was undertaken as part of research investigating whether pre-learner training is needed and, if so, the issues that should be addressed in training.. The crashes of learner riders and other riders were compared to identify whether there are particular situations or locations in which learner motorcyclists are over-involved in crashes, which could then be targeted in the pre-learner package. The analyses were undertaken separately for riders aged under 25 (330 crashes) versus those aged 25 and over (237 crashes) to provide some insight into whether age or riding inexperience are the more important factors, and thus to indicate whether there are merits in having different licensing or training approaches for younger and older learner riders. Given that the average age of learner riders was 33 years, under 25 was chosen to provide a sufficiently large sample of younger riders. Learner riders appeared to be involved in more severe crashes and to be more often at fault than fully-licensed riders but this may reflect problems in reporting, rather than real differences. Compared to open licence holders, both younger and older learner riders had relatively more crashes in low speed zones and relatively fewer in high speed zones. Riders aged under 25 had elevated percentages of night-time crashes and fewer single unit (potentially involving rider error only) crashes regardless of the type of licence held. The contributing factors that were more prevalent in crashes of learner riders than holders of open licences were: inexperience (37.2% versus 0.5%), inattention (21.5% versus 15.6%), alcohol or drugs (12.0% versus 5.1%) and drink riding (9.9% versus 3.1%). The pattern of contributing factors was generally similar for younger and older learner riders, although younger learners were (not surprisingly) more likely to have inexperience coded as a contributing factor (49.7% versus 19.8%). Some of the differences in crashes between learner riders and fully-licensed riders appear to reflect relatively more riding in urban areas by learners, rather than increased risks relating to inexperience. The analysis of contributing factors in learner rider crashes suggests that hazard perception and risk management (in terms of speed and alcohol and drugs) should be included in a pre-learner program. Currently, most learner riders in Queensland complete pre-licence training and become licensed within one month of obtaining their learner permit. If the introduction of pre-learner training required that the learner permit was held for a minimum duration, then the immediate effect might be more learners riding (and crashing). Thus, it is important to consider how training and licensing initiatives work together in order to improve the safety of new riders (and how this can be evaluated).

International assessments of science learning : their positive and negative contributions to science education

The establishment and continuity of two international comparative assessments of science learning—the IEA’s TIMSS project and the OECD’s PISA project—have meant that there are now high-status reference points for other national and more local approaches to assessing the efficacy of science teaching and learning. Both projects, albeit with very different senses of what the outcome of science learning should be, have contributed positively and negatively to the current state of assessment of school science. The TIMSS project looks back at the science that is commonly included in the curricula of the participating countries. It is thus not about established school science nor about innovations in it. PISA is highly innovative looking, prospectively forward to see how students can use their science learning in everyday life situations. In this chapter some of these positives and negatives are discussed.

From words to integers and beyond in corporate life

Poets have a licence to couch great truths in succinct, emotionally powerful, and perhaps slightly mysterious and ambiguous ways. On the other hand, it is the task of academics to explore such truths intellectually, in depth and detail, identifying the key constructs and their underlying relations and structures, hopefully without impairing the essential truth. So it could be said that in January 2013, around 60 academics gathered at the University of Texas, Austin under the benign and encouraging eye of their own muse, Professor Rod Hart, to play their role in exploring and explaining the underlying truth of Yan Zhen’s words. The goals of this chapter are quite broad. Rod was explicit and yet also somewhat Delphic in his expectations and aspirations for the chapter. Even though DICTION was a key analytic tool in most chapters, this chapter was not to be about DICTION per se, or simply a critique of the individual chapters forming this section of the book. Rather DICTION and these studies, as well as some others that got our attention, were to be more a launching pad for observations on what they revealed about the current state of understanding and research into the language of institutions, as well as some ‘adventurous’, but not too outlandish reflections on future challenges and opportunities.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the a mission should be aborted due to mechanical or other failure. On-board cameras provide information that can be used in the determination of potential landing sites, which are continually updated and ranked to prevent injury and minimize damage. Pulse Coupled Neural Networks have been used for the detection of features in images that assist in the classification of vegetation and can be used to minimize damage to the aerial vehicle. However, a significant drawback in the use of PCNNs is that they are computationally expensive and have been more suited to off-line applications on conventional computing architectures. As heterogeneous computing architectures are becoming more common, an OpenCL implementation of a PCNN feature generator is presented and its performance is compared across OpenCL kernels designed for CPU, GPU and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images obtained during unmanned aerial vehicle trials to determine the plausibility for real-time feature detection.

Facebook, telecollaboration, and international access to technology in the classroom

This study uses the well-known social networking site, Facebook (FB), for a study of differences in perceptions on the use of technologies in the classroom around the world. This study is part of a larger project exploring telecollaboration and the use of online discussions between graduate students in an online masters program based in Australia and students in the graduate education program at a regional university in Greece. Postings reveal more similarities between the situations and perceptions of the participants from the different countries than differences. Most participants indicated that while they and their students had access in general to computers and the internet, they did not necessarily have this access in the classroom. Even when technologies were available in schools, participants identified a critical need for professional development to increase teachers’ use of ICT. These findings are relevant to educators and policy development in terms of implementation of ICT or social networking in the language classroom.

Exploring information literacy during a natural disaster: The 2011 Brisbane Flood

This chapter presents the preliminary results of a phenomenographic study aimed at exploring people’s experience of information literacy during the 2011 flood in Brisbane, Queensland. Phenomenography is a qualitative, interpretive and descriptive approach to research that explores the different ways in which people experience various phenomena and situations in the world around them. In this study, semi-structured interviews with seven adult residents of Brisbane suggested six categories that depicted different ways people experienced information literacy during this natural disaster. Access to timely, accurate and credible information during a natural disaster can save lives, safeguard property, and reduce fear and anxiety, however very little is currently known about citizens’ information literacy during times of natural disaster. Understanding how people use information to learn during times of crisis is a new terrain for community information literacy research, and one that warrants further attention by the information research community and the emergency management sector.

A time-based quantitative approach for selecting lean strategies for manufacturing organisations

Lean strategies have been developed to eliminate or reduce waste and thus improve operational efficiency in a manufacturing environment. However, in practice, manufacturers encounter difficulties to select appropriate lean strategies within their resource constraints and to quantitatively evaluate the perceived value of manufacturing waste reduction. This paper presents a methodology developed to quantitatively evaluate the contribution of lean strategies selected to reduce manufacturing wastes within the manufacturers’ resource (time) constraints. A mathematical model has been developed for evaluating the perceived value of lean strategies to manufacturing waste reduction and a step-by-step methodology is provided for selecting appropriate lean strategies to improve the manufacturing performance within their resource constraints. A computer program is developed in MATLAB for finding the optimum solution. With the help of a case study, the proposed methodology and developed model has been validated. A ‘lean strategy-wastes’ correlation matrix has been proposed to establish the relationship between the manufacturing wastes and lean strategies. Using the correlation matrix and applying the proposed methodology and developed mathematical model, authors came out with optimised perceived value of reduction of a manufacturer's wastes by implementing appropriate lean strategies within a manufacturer's resources constraints. Results also demonstrate that the perceived value of reduction of manufacturing wastes can significantly be changed based on policies and product strategy taken by a manufacturer. The proposed methodology can also be used in dynamic situations by changing the input in the programme developed in MATLAB. By identifying appropriate lean strategies for specific manufacturing wastes, a manufacturer can better prioritise implementation efforts and resources to maximise the success of implementing lean strategies in their organisation.

Metrics for Understanding Communication on Twitter

As the systematic investigation of Twitter as a communications platform continues, the question of developing reliable comparative metrics for the evaluation of public, communicative phenomena on Twitter becomes paramount. What is necessary here is the establishment of an accepted standard for the quantitative description of user activities on Twitter. This needs to be flexible enough in order to be applied to a wide range of communicative situations, such as the evaluation of individual users’ and groups of users’ Twitter communication strategies, the examination of communicative patterns within hashtags and other identifiable ad hoc publics on Twitter (Bruns & Burgess, 2011), and even the analysis of very large datasets of everyday interactions on the platform. By providing a framework for quantitative analysis on Twitter communication, researchers in different areas (e.g., communication studies, sociology, information systems) are enabled to adapt methodological approaches and to conduct analyses on their own. Besides general findings about communication structure on Twitter, large amounts of data might be used to better understand issues or events retrospectively, detect issues or events in an early stage, or even to predict certain real-world developments (e.g., election results; cf. Tumasjan, Sprenger, Sandner, & Welpe, 2010, for an early attempt to do so).

Autonomous movement-driven place recognition calibration for generic multi-sensor robot platforms

In this paper we present a method for autonomously tuning the threshold between learning and recognizing a place in the world, based on both how the rodent brain is thought to process and calibrate multisensory data and the pivoting movement behaviour that rodents perform in doing so. The approach makes no assumptions about the number and type of sensors, the robot platform, or the environment, relying only on the ability of a robot to perform two revolutions on the spot. In addition, it self-assesses the quality of the tuning process in order to identify situations in which tuning may have failed. We demonstrate the autonomous movement-driven threshold tuning on a Pioneer 3DX robot in eight locations spread over an office environment and a building car park, and then evaluate the mapping capability of the system on journeys through these environments. The system is able to pick a place recognition threshold that enables successful environment mapping in six of the eight locations while also autonomously flagging the tuning failure in the remaining two locations. We discuss how the method, in combination with parallel work on autonomous weighting of individual sensors, moves the parameter dependent RatSLAM system significantly closer to sensor, platform and environment agnostic operation.

Brain-inspired sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

Recovering from the earthquake : early childhood teachers and children collaboratively telling stories about their experiences

Purpose – Traumatic events can cause post-traumatic stress disorder due to the severity of the often unexpected events. The purpose of this paper is to reveal how conversations around lived experiences of traumatic events, such as the Christchurch earthquake in February 2011, can work as a strategy for people to come to terms with their experiences collaboratively. By encouraging young children to recall and tell of their earthquake stories with their early childhood teachers they can begin to respond, renew, and recover (Brown, 2012), and prevent or minimise more stress being developed. Design/methodology/approach – The study involved collecting data of the participating children taking turns to wear a wireless microphone where their interactions with each other and with teachers were video recorded over one week in November 2011. A total of eight hours and 21 minutes of footage was collected; four minutes and 19 seconds of that footage are presented and analysed in this paper. The footage was watched repeatedly and transcribed using conversation analysis methods (Sacks, 1995). Findings – Through analysing the detailed turn-taking utterances between teachers and children, the orderliness of the co-production of remembering is revealed to demonstrate that each member orients to being in agreement about what actually happened. These episodes of story telling between the teachers and children demonstrate how the teachers encourage the children to tell about their experiences through actively engaging in conversations with them about the earthquake. Originality/value – The conversation analysis approach used in this research was found to be useful in investigating aspects of disasters that the participants themselves remember as important and real. This approach offers a unique insight into understanding how the earthquake event was experienced and reflected on by young children and their teachers, and so can inform future policy and provision in post-disaster situations.