Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots

Hot spot identification (HSID) aims to identify potential sites—roadway segments, intersections, crosswalks, interchanges, ramps, etc.—with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Traversability estimation for a planetary rover via experimental kernel learning in a Gaussian process framework

A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

Hot spot detection and spatio-temporal dispersion of dengue fever in Hanoi, Vietnam

INTRODUCTION Dengue fever (DF) in Vietnam remains a serious emerging arboviral disease, which generates significant concerns among international health authorities. Incidence rates of DF have increased significantly during the last few years in many provinces and cities, especially Hanoi. The purpose of this study was to detect DF hot spots and identify the disease dynamics dispersion of DF over the period between 2004 and 2009 in Hanoi, Vietnam. METHODS Daily data on DF cases and population data for each postcode area of Hanoi between January 1998 and December 2009 were obtained from the Hanoi Center for Preventive Health and the General Statistic Office of Vietnam. Moran's I statistic was used to assess the spatial autocorrelation of reported DF. Spatial scan statistics and logistic regression were used to identify space-time clusters and dispersion of DF. RESULTS The study revealed a clear trend of geographic expansion of DF transmission in Hanoi through the study periods (OR 1.17, 95% CI 1.02-1.34). The spatial scan statistics showed that 6/14 (42.9%) districts in Hanoi had significant cluster patterns, which lasted 29 days and were limited to a radius of 1,000 m. The study also demonstrated that most DF cases occurred between June and November, during which the rainfall and temperatures are highest. CONCLUSIONS There is evidence for the existence of statistically significant clusters of DF in Hanoi, and that the geographical distribution of DF has expanded over recent years. This finding provides a foundation for further investigation into the social and environmental factors responsible for changing disease patterns, and provides data to inform program planning for DF control.

Process modelling and simulation of tissue damage during mechanical peeling of pumpkin as a tough skinned vegetable

Food waste is a current challenge that both developing and developed countries face. This project applied a novel combination of available methods in Mechanical, agricultural and food engineering to address these challenges. A systematic approach was devised to investigate possibilities of reducing food waste and increasing the efficiency of industry by applying engineering concepts and theories including experimental, mathematical and computational modelling methods. This study highlights the impact of comprehensive understanding of agricultural and food material response to the mechanical operations and its direct relation to the volume of food wasted globally.

The Royal Commission into the NSW Police Service : process corruption and the limits of judicial reflexivity

This paper will offer an examination of the Reports of the Royal Commission into the NSW Police Service (Interim Report February 1996; Interim Report: Immediate Measures November 1996; Final Report Vol I: Corruption; Final Report Vol II: Reform; Final Report Vol III: Appendices May 1997) excluding the Report on Paedophilia, August 1997. The examination will be confined essentially to one question: to what extent do the published Reports consider the part played by the judiciary, prosecutors and lawyers, in the construction of a form of criminal justice revealed by the Commission itself, to be disfigured by serious process corruption? The examination will be conducted by way of a chronological trawl through the Reports of the Commission in an attempt to identify all references to the role of the judiciary, prosecutors and lawyers. The adequacy of any such treatment will then be considered. In order to set the scene a brief and generalised overview of the Wood Commission will be offered together with the Commission's definition of process corruption.

Sectional analysis of the pollutant wash-off process based on runoff hydrograph

The validity of using rainfall characteristics as lumped parameters for investigating the pollutant wash-off process such as first flush occurrence is questionable. This research study introduces an innovative concept of using sector parameters to investigate the relationship between the pollutant wash-off process and different sectors of the runoff hydrograph and rainfall hyetograph. The research outcomes indicated that rainfall depth and rainfall intensity are two key rainfall characteristics which influence the wash-off process compared to the antecedent dry period. Additionally, the rainfall pattern also plays a critical role in the wash-off process and is independent of the catchment characteristics. The knowledge created through this research study provides the ability to select appropriate rainfall events for stormwater quality treatment design based on the required treatment outcomes such as the need to target different sectors of the runoff hydrograph or pollutant species. The study outcomes can also contribute to enhancing stormwater quality modelling and prediction in view of the fact that conventional approaches to stormwater quality estimation is primarily based on rainfall intensity rather than considering other rainfall parameters or solely based on stochastic approaches irrespective of the characteristics of the rainfall event.

Criminal Laws : Materials and Commentary on Criminal Law and Process in NSW [Fifth Edition]

"The success of Criminal Laws lies both in its distinctive features and in its appeal to a range of readerships. As one review put it, it is simultaneously a "textbook, casebook, handbook and reference work". As such it is ideal for criminal law and criminal justice courses as a teaching text, combining as it does primary sources with extensive critical commentary and a contextual perspective. It is likewise indispensable to practitioners for its detailed coverage of substantive law and its extensive references and inter-disciplinary approach make it a first point of call for researchers from all disciplines. This fifth edition strengthens these distinctive features. All chapters have been systematically updated to incorporate the plethora of legislative, case law, statistical and research material which has emerged since the previous edition. The critical, thematic, contextual and interdisciplinary perspectives have been continued."--Publisher's website. Table of Contents: 1. Some themes -- 2. Criminalisation -- 3. The criminal process -- 4. Components of criminal offences -- 5. Homicide: murder and involuntary manslaughter -- 6. Defences -- 7. Assault and sexual assault -- 8. Public order offences -- 9. Drugs offences -- 10. Dishonest acquisition -- 11. Extending criminal liability: complicity, conspiracy and association -- 12. Sentencing and penality.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

The consultative process used in outreach : a narrative account

Aim The aim of this paper was to provide a narrative account of the communication skills used in an effective outreach consultation utilizing Neighbour’s consultative model. Other consultation models were considered; however, because of their overly comprehensive approach or emphasis on behaviour modification, these were deemed inappropriate. Background The nursing profession has endured significant changes of late and as a result is developing more autonomous roles in both the community and the acute health care settings. In the past, the term consultancy was used within the medical context; nowadays, there are advance nurse practitioners for whom consultancy is an integral part of their role. Although every nursing interaction is in essence a consultation, the fact that nurses are taking up on new advanced roles highlights the necessity for nurses to develop their consultation skills even further. Therefore, it makes sense to explore what aspects of that consultancy role needs special consideration in order to ensure that positive outcomes are achieved. Conclusions This paper has used a narrative account to uncover those salient skills needed to enhance the therapeutic relationship with a patient requiring the services of outreach. Furthermore, the application of a recognized consultation model was used to elucidate the underpinning knowledge of systematic history taking and assessment as well as demonstrating the communication skills and strategies needed to increase the patient’s participation and empowerment throughout the consultation. Relevance to clinical practice Effective communication skills encompassed in a consultative model are integral to the success in safeguarding the well-being of patients requiring advanced levels of care. Prejudging or pre-empting information being conveyed can be detrimental to patient safety and may prolong or complicate treatment plans.

Impact of passenger group dynamics on an airport evacuation process using an agent-based model

The safety of passengers is a major concern to airports. In the event of crises, having an effective and efficient evacuation process in place can significantly aid in enhancing passenger safety. Hence, it is necessary for airport operators to have an in-depth understanding of the evacuation process of their airport terminal. Although evacuation models have been used in studying pedestrian behaviour for decades, little research has been done in considering the evacuees’ group dynamics and the complexity of the environment. In this paper, an agent-based model is presented to simulate passenger evacuation process. Different exits were allocated to passengers based on their location and security level. The simulation results show that the evacuation time can be influenced by passenger group dynamics. This model also provides a convenient way to design airport evacuation strategy and examine its efficiency. The model was created using AnyLogic software and its parameters were initialised using recent research data published in the literature.

A novel process of group-oriented question reduction for rule-based recommendation websites

Several websites utilise a rule-base recommendation system, which generates choices based on a series of questionnaires, for recommending products to users. This approach has a high risk of customer attrition and the bottleneck is the questionnaire set. If the questioning process is too long, complex or tedious; users are most likely to quit the questionnaire before a product is recommended to them. If the questioning process is short; the user intensions cannot be gathered. The commonly used feature selection methods do not provide a satisfactory solution. We propose a novel process combining clustering, decisions tree and association rule mining for a group-oriented question reduction process. The question set is reduced according to common properties that are shared by a specific group of users. When applied on a real-world website, the proposed combined method outperforms the methods where the reduction of question is done only by using association rule mining or only by observing distribution within the group.

Rolling contact fatigue in rail - insulated rail joints (IRJ)

The insulated rail joint (IRJ) is an essential component in a track circuit that controls the signaling system. Failure of IRJs leads to improper functioning of the signals,with potential for catastrophic results. Therefore, IRJs are regarded as safety-critical sections of rail network; hence, all of their components must be maintained in pristine design condition.

Contributions towards a process for sustainable development in coastal Queensland, Australia

The measures by which major developments are officially approved for construction are - by common agreement - complex, time-consuming, and of questionable merit in terms of maintaining ecological viability.