Monash University

About: Monash University is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Population & Poison control. The organization has 35920 authors who have published 100681 publications receiving 3027002 citations.

Driver Distraction : Theory, Effects, and Mitigation

Abstract: INTRODUCTION Introduction, M.A. Regan, K.L. Young, and J.D. Lee DEFINITIONS, THEORIES, AND MODELS OF DRIVER DISTRACTION On the Philosophical Foundations of the Distracted Driver and Driving Distraction, P.A. Hancock, M. Mouloua, and J.W. Senders Defining Driver Distraction, J.D. Lee, K.L. Young, and M.A. Regan What Drives Distraction? Distraction as a Breakdown of Multilevel Control, J. D. Lee, M.A. Regan, and K.L. Young Models of Attention, Distraction, and Highway Hazard Avoidance, C.D. Wickens and W.J. Horrey MEASUREMENT OF DRIVER DISTRACTION Measuring Exposure to Driver Distraction, S.P. McEvoy and M.R. Stevenson Measuring the Effects of Driver Distraction: Direct Driving Performance Methods and Measures, K.L. Young, M.A. Regan, and J.D. Lee Surrogate Distraction Measurement Techniques: The Lane Change Test, S. Mattes and A. Hallen Now You See It, Now You Don't: Visual Occlusion as a Surrogate Distraction Measurement Technique, J.P. Foley Distraction Assessment Methods Based on Visual Behavior and Event Detection, T.W. Victor, J. Engstrom, and J.L. Harbluk EFFECTS OF DISTRACTION ON DRIVING PERFORMANCE Cellular Phones and Driver Distraction, F.A. Drews and D.L. Strayer Sources of Distraction inside the Vehicle and Their Effects on Driving Performance, M. Bayly, K.L. Young, and M.A. Regan Distractions outside the Vehicle, T. Horberry and J. Edquist Distraction and Public Transport: Case Study of Bus Driver Distraction, P.M. Salmon, K.L. Young, and M.A. Regan DISTRACTION, CRASHES, AND CRASH RISK Sources of Driver Distraction, M.A. Regan, K.L. Young, J.D. Lee, and C.P. Gordon Crash Studies of Driver Distraction, C.P. Gordon Epidemiological Research on Driver Distraction, S.P. McEvoy and M.R. Stevenson Driver Distraction Exposure Research: A Summary of Findings, K.L. Young and M.A. Regan FACTORS MEDIATING THE EFFECTS OF DISTRACTION Factors Moderating the Impact of Distraction on Driving Performance and Safety, K.L. Young, M.A. Regan, and J.D. Lee Distraction and the Older Driver, S. Koppel, J.L. Charlton, and B. Fildes The Relationship between Driver Fatigue and Driver Distraction, A. Williamson DESIGN AND STANDARDIZATION European Approaches to Principles, Codes, Guidelines, and Checklists for In-Vehicle HMI, A. Stevens North American Approaches to Principles, Codes, Guidelines, and Checklists for In-Vehicle HMI, P.C. Burns Japanese Approaches to Principles, Codes, Guidelines, and Checklists for In-Vehicle HMI, M. Akamatsu Driver Interface Safety and Usability Standards: An Overview, P. Green PREVENTION AND MITIGATION STRATEGIES Real-Time Distraction Countermeasures, J. Engstrom and T.W. Victor Driving Task Demand-Based Distraction Mitigation, H. Zhang, M.R.H. Smith, and G.J. Witt Estimates of Driver Distraction, M.R.H. Smith, G.J. Witt, D.L. Bakowski, D. Leblanc, and J.D. Lee Designing Feedback to Mitigate Distraction, B. Donmez, L. Boyle, and J.D. Lee Driver Distraction Injury Prevention Countermeasures-Part 1: Data Collection, Legislation and Enforcement, Vehicle Fleet, Management, and Driver Licensing, M.A. Regan, K.L. Young, and J.D. Lee Driver Distraction Injury Prevention Countermeasures-Part 2: Education and Training, M. A. Regan, J.D. Lee, and K.L. Young Driver Distraction Injury Prevention Countermeasures-Part 3: Vehicle, Technology, and Road Design, T.W. Victor, M.A. Regan, J.D. Lee, and K.L. Young Government and Industry Perspectives on Driver Distraction, C. Tingvall, L. Eckstein, and M. Hammer CONCLUSIONS Some Concluding Remarks, M.A. Regan, K.L. Young, and J.D. Lee Index

Modeling Soil Processes: Review, Key Challenges, and New Perspectives

Abstract: The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate-change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.

Mechanisms involved in the resistance of Enterococcus faecalis to calcium hydroxide

Abstract: involved in the resistance of Enterococcus faecalis to calcium hydroxide. International Endodontic Journal, 35 , 221‐228, 2002. Aim This study sought to clarify the mechanisms that enable E. faecalis to survive the high pH of calcium hydroxide. Methodology E. faecalis strain JH2-2 was exposed to sublethal concentrations of calcium hydroxide, with and without various pretreatments. Blocking agents were added to determine the role of stress-induced protein synthesis and the cell wall-associated proton pump. Results E. faecalis was resistant to calcium hydroxide at a pH of 11.1, but not pH 11.5. Pre-treatment with calcium hydroxide pH 10.3 induced no tolerance to further exposure at pH 11.5. No difference in cell survival was observed when protein synthesis was blocked during stress induction, however, addition of a proton pump inhibitor resulted in a dramatic reduction of cell viability of E. faecalis in calcium hydroxide. Conclusions Survival of E. faecalis in calcium hydroxide appears to be unrelated to stress induced protein synthesis, but a functioning proton pump is critical for survival of E. faecalis at high pH.

Deep code comment generation

Abstract: During software maintenance, code comments help developers comprehend programs and reduce additional time spent on reading and navigating source code. Unfortunately, these comments are often mismatched, missing or outdated in the software projects. Developers have to infer the functionality from the source code. This paper proposes a new approach named DeepCom to automatically generate code comments for Java methods. The generated comments aim to help developers understand the functionality of Java methods. DeepCom applies Natural Language Processing (NLP) techniques to learn from a large code corpus and generates comments from learned features. We use a deep neural network that analyzes structural information of Java methods for better comments generation. We conduct experiments on a large-scale Java corpus built from 9,714 open source projects from GitHub. We evaluate the experimental results on a machine translation metric. Experimental results demonstrate that our method DeepCom outperforms the state-of-the-art by a substantial margin.

GW150914: The Advanced LIGO Detectors in the Era of First Discoveries

Abstract: Following a major upgrade, the two advanced detectors of the Laser Interferometer Gravitational-wave Observatory (LIGO) held their first observation run between September 2015 and January 2016. With a strain sensitivity of $10^{-23}/\sqrt{\mathrm{Hz}}$ at 100 Hz, the product of observable volume and measurement time exceeded that of all previous runs within the first 16 days of coincident observation. On September 14th, 2015 the Advanced LIGO detectors observed a transient gravitational-wave signal determined to be the coalescence of two black holes [Phys. Rev. Lett. 116, 061102 (2016)], launching the era of gravitational-wave astronomy. The event, GW150914, was observed with a combined signal-to-noise ratio of 24 in coincidence by the two detectors. Here we present the main features of the detectors that enabled this observation. At full sensitivity, the Advanced LIGO detectors are designed to deliver another factor of three improvement in the signal-to-noise ratio for binary black hole systems similar in masses to GW150914.