Microscopic cooperative traffic based on NGSIM data

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Vehicles are able to communicate on the local traffic state in real time, which could result in an automatic and therefore better reaction to the mechanism of traffic jam formation. An upstream single hop radio broadcast network can improve the perception of each cooperative driver within radio range and hence the traffic stability. The impact of a cooperative law on traffic congestion appearance is investigated, analytically and through simulation. Ngsim field data is used to calibrate the Optimal Velocity with Relative Velocity (OVRV) car following model and the MOBIL lane-changing model is implemented. Assuming that congestion can be triggered either by a perturbation in the instability domain or by a critical lane changing behavior, the calibrated car following behavior is used to assess the impact of a microscopic cooperative law on abnormal lane changing behavior. The cooperative law helps reduce and delay traffic congestion as it increases traffic flow stability.

Essential elements for recruitment and retention : Generation Y

Purpose: Generation Y (Gen Y) is the newest and largest generation entering the workforce. Gen Y may differ from previous generations in work-related characteristics which may have recruitment and retention repercussions. Currently, limited theoretically-based research exists regarding Gen Y’s work expectations and goals in relation to undergraduate students and graduates. Design/methodology/approach: This study conducted a theoretically-based investigation of the work expectations and goals of student- and working-Gen Y individuals based within a framework incorporating both expectancy-value and goal setting theories. N = 398 provided useable data via an on-line survey. Findings: Overall, some support was found for predictions with career goals loading on a separate component to daily work expectations and significant differences between student- and working- Gen Y on career goals. No significant differences were found, however, between the two groups in daily work expectations. Research limitations/implications: Future research may benefit from adopting a theoretical framework which assesses both daily work expectations and career goals when examining the factors which motivate Gen Y’s decisions to join and remain at a particular organisation. Practical implications: At a practical level, based on the findings, some examples are provided of the means by which organisations may draw upon daily work expectations and career goals of importance to Gen Y and, in doing so, influence the likelihood that a Gen Y individual will join and remain at their particular organisation. Originality/value: This research has demonstrated the utility of adopting a sound theoretical framework in furthering understanding about the motivations which influence organisations’ ability to recruit and retain Gen Y, among both student Gen Y as well as those Gen Y individuals who are already working.

Application-level simulation for network security

NeSSi (network security simulator) is a novel network simulation tool which incorporates a variety of features relevant to network security distinguishing it from general-purpose network simulators. Its capabilities such as profile-based automated attack generation, traffic analysis and support for detection algorithm plug-ins allow it to be used for security research and evaluation purposes. NeSSi has been successfully used for testing intrusion detection algorithms, conducting network security analysis and developing overlay security frameworks. NeSSi is built upon the agent framework JIAC, resulting in a distributed and extensible architecture. In this paper, we provide an overview of the NeSSi architecture as well as its distinguishing features and briefly demonstrate its application to current security research projects.

Supplementary Information : Hogan, Holland, Holloway, Petit and Read : Read Classification for Next Generation Sequencing, ESANN 2013, April 2013

This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

Design of open source framework for traffic and travel simulation

For the evaluation, design, and planning of traffic facilities and measures, traffic simulation packages are the de facto tools for consultants, policy makers, and researchers. However, the available commercial simulation packages do not always offer the desired work flow and flexibility for academic research. In many cases, researchers resort to designing and building their own dedicated models, without an intrinsic incentive (or the practical means) to make the results available in the public domain. To make matters worse, a substantial part of these efforts pertains to rebuilding basic functionality and, in many respects, reinventing the wheel. This problem not only affects the research community but adversely affects the entire traffic simulation community and frustrates the development of traffic simulation in general. For this problem to be addressed, this paper describes an open source approach, OpenTraffic, which is being developed as a collaborative effort between the Queensland University of Technology, Australia; the National Institute of Informatics, Tokyo; and the Technical University of Delft, the Netherlands. The OpenTraffic simulation framework enables academies from geographic areas and disciplines within the traffic domain to work together and contribute to a specific topic of interest, ranging from travel choice behavior to car following, and from response to intelligent transportation systems to activity planning. The modular approach enables users of the software to focus on their area of interest, whereas other functional modules can be regarded as black boxes. Specific attention is paid to a standardization of data inputs and outputs for traffic simulations. Such standardization will allow the sharing of data with many existing commercial simulation packages.

Hazard based models for freeway traffic incident duration

Assessing and prioritising cost-effective strategies to mitigate the impacts of traffic incidents and accidents on non-recurrent congestion on major roads represents a significant challenge for road network managers. This research examines the influence of numerous factors associated with incidents of various types on their duration. It presents a comprehensive traffic incident data mining and analysis by developing an incident duration model based on twelve months of incident data obtained from the Australian freeway network. Parametric accelerated failure time (AFT) survival models of incident duration were developed, including log-logistic, lognormal, and Weibul-considering both fixed and random parameters, as well as a Weibull model with gamma heterogeneity. The Weibull AFT models with random parameters were appropriate for modelling incident duration arising from crashes and hazards. A Weibull model with gamma heterogeneity was most suitable for modelling incident duration of stationary vehicles. Significant variables affecting incident duration include characteristics of the incidents (severity, type, towing requirements, etc.), and location, time of day, and traffic characteristics of the incident. Moreover, the findings reveal no significant effects of infrastructure and weather on incident duration. A significant and unique contribution of this paper is that the durations of each type of incident are uniquely different and respond to different factors. The results of this study are useful for traffic incident management agencies to implement strategies to reduce incident duration, leading to reduced congestion, secondary incidents, and the associated human and economic losses.

Analysis of traffic injury severity in a mega city of a developing country

Despite a considerable amount of research on traffic injury severities, relatively little is known about the factors influencing traffic injury severity in developing countries, and in particular in Bangladesh. Road traffic crashes are a common headline in daily newspapers of Bangladesh. It has also recorded one of the highest road fatality rates in the world. This research identifies significant factors contributing to traffic injury severity in Dhaka – a mega city and capital of Bangladesh. Road traffic crash data of 5 years from 2007 to 2011 were collected from the Dhaka Metropolitan Police (DMP), which included about 2714 traffic crashes. The severity level of these crashes was documented in a 4-point ordinal scale: no injury (property damage), minor injury, severe injury, and death. An ordered Probit regression model has been estimated to identify factors contributing to injury severities. Results show that night time influence is associated with a higher level injury severity as is for individuals involved in single vehicle crashes. Crashes on highway sections within the city are found to be more injurious than crashes along the arterial and feeder roads. There is a lower likelihood of injury severity, however, if the road sections are monitored and enforced by the traffic police. The likelihood of injuries is lower on two-way traffic arrangements than one-way, and at four-legged intersections and roundabouts compare to road segments. The findings are compared with those from developed countries and the implications of this research are discussed in terms of policy settings for developing countries.

Peer assisted learning, skills development and Generation Y : a case study of a first year undergraduate law unit

The majority of current first year university students belong to Generation Y. Consequently, research suggests that, in order to more effectively engage them, their particular learning preferences should be acknowledged in the organisation of their learning environments and in the support provided. These preferences are reflected in the Torts Student Peer Mentor Program, which, as part of the undergraduate law degree at the Queensland University of Technology, utilises active learning, structured sessions and teamwork to supplement student understanding of the substantive law of Torts with the development of life-long skills. This article outlines the Program, and its relevance to the learning styles and experiences of Generation Y first year law students transitioning to university, in order to investigate student perceptions of its effectiveness – both generally and, more specifically, in terms of the Program’s capacity to assist students to develop academic and work-related skills.

Decentralized detector generation in cooperative intrusion detection system

We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.

Sources of ultrafine particles and chemical species along a traffic corridor : comparison of the results from two receptor models

Particulate matter is common in our environment and has been linked to human health problems particularly in the ultrafine size range. A range of chemical species have been associated with particulate matter and of special concern are the hazardous chemicals that can accentuate health problems. If the sources of such particles can be identified then strategies can be developed for the reduction of air pollution and consequently, the improvement of the quality of life. In this investigation, particle number size distribution data and the concentrations of chemical species were obtained at two sites in Brisbane, Australia. Source apportionment was used to determine the sources (or factors) responsible for the particle size distribution data. The apportionment was performed by Positive Matrix Factorisation (PMF) and Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS), and the results were compared with information from the gaseous chemical composition analysis. Although PCA/APCS resolved more sources, the results of the PMF analysis appear to be more reliable. Six common sources identified by both methods include: traffic 1, traffic 2, local traffic, biomass burning, and two unassigned factors. Thus motor vehicle related activities had the most impact on the data with the average contribution from nearly all sources to the measured concentrations higher during peak traffic hours and weekdays. Further analyses incorporated the meteorological measurements into the PMF results to determine the direction of the sources relative to the measurement sites, and this indicated that traffic on the nearby road and intersection was responsible for most of the factors. The described methodology which utilised a combination of three types of data related to particulate matter to determine the sources could assist future development of particle emission control and reduction strategies.

Utility of an alternative bicycle commute route of lower proximity to motorised traffic in decreasing exposure to ultra-fine particles, respiratory symptoms and airway inflammation - a structured exposure experiment

Background: Bicycle commuting in an urban environment of high air pollution is known as a potential health risk, especially for susceptible individuals. While risk management strategies aimed to reduce motorised traffic emissions exposure have been suggested, limited studies have assessed the utility of such strategies in real-world circumstances. Objectives: The potential of reducing exposure to ultrafine particles (UFP; < 0.1 µm) during bicycle commuting by lowering interaction with motorised traffic was investigated with real-time air pollution and acute inflammatory measurements in healthy individuals using their typical, and an alternative to their typical, bicycle commute route. Methods: Thirty-five healthy adults (mean ± SD: age = 39 ± 11 yr; 29% female) each completed two return trips of their typical route (HIGH) and a pre-determined altered route of lower interaction with motorised traffic (LOW; determined by the proportion of on-road cycle paths). Particle number concentration (PNC) and diameter (PD) were monitored in real-time in-commute. Acute inflammatory indices of respiratory symptom incidence, lung function and spontaneous sputum (for inflammatory cell analyses) were collected immediately pre-commute, and one and three hours post-commute. Results: LOW resulted in a significant reduction in mean PNC (1.91 x e4 ± 0.93 x e4 ppcc vs. 2.95 x e4 ± 1.50 x e4 ppcc; p ≤ 0.001). Besides incidence of in-commute offensive odour detection (42 vs. 56 %; p = 0.019), incidence of dust and soot observation (33 vs. 47 %; p = 0.038) and nasopharyngeal irritation (31 vs. 41 %; p = 0.007), acute inflammatory indices were not significantly associated to in-commute PNC, nor were these indices reduced with LOW compared to HIGH. Conclusions: Exposure to PNC, and the incidence of offensive odour and nasopharyngeal irritation, can be significantly reduced when utilising a strategy of lowering interaction with motorised traffic whilst bicycle commuting, which may bring important benefits for both healthy and susceptible individuals.

Optimisation of bio-oil extraction process from Beauty Leaf (Calophyllum inophyllum) oil seed as a second generation biodiesel source

The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using n-hexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made.

Vibrational spectroscopy of natural cave mineral monetite CaHPO4 and the synthetic analog

Monetite is a phosphate mineral formed by the reaction of the chemicals in bat guano with calcite substrates and is commonly found in caves. The analog of the mineral monetite CaHPO4 has been synthesized and the Raman and infrared spectra of the natural monetite originating from the Murra-el-elevyn Cave, Eucla, Western Australia, compared. Monetite is characterized by a complex set of phosphate bands that arise because of two sets of pairs of phosphate units in the unit cell. Raman and infrared bands are assigned to HPO4(2-), OH stretching and bending vibrations. Infrared bands at 1346 and 1402 cm−1 are assigned to POH deformation modes. Vibrational spectroscopy confirms the presence of monetite in the cave system.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.