Service-oriented computing and model-driven development as enablers of port information systems: an integrated view

Port information management is considered a critical instrument towards enabling international transport and trade; thus, various forms of Port Information Systems (PORTIS) have been developed today, namely Port Community Systems, Terminal Operating Systems and Single Window systems. In Europe, the nautical information system SafeSeaNet is viewed as an important e-infrastructure. PORTIS systems are expected to evolve into next-generation technological platforms in order to offer a fully integrated digital environment to a multitude of maritime business actors and public authorities towards more efficient, safe and environment-aware transport and trade infrastructures and services. We propose service-oriented computing and model-driven development techniques as a robust PORTIS modelling and development approach. We present a reference model of PORTIS and a particular enabling methodological and technological framework. The proposed approach has been tested in a maritime single-window case.     

The ‘Four Dimensions of Behaviour’ framework: a tool for characterising behaviours to help design better interventions

This paper sets out the rationale and structure of a tool for assisting policy-makers and practitioners to understand behavioural challenges and open up thinking on the design of effective ‘behaviour change’ interventions. The ‘Four Dimensions of Behaviour’ (4DB) framework is based on the theoretical and empirical research in a range of policy domains including transport and pro-environmental behaviour more generally. The 4DB framework characterises multifaceted behaviours along dimensions of actor, domain, durability and scope. Its application in workshop or structured settings opens up diverse and non-exclusive discussion on designing interventions to match salient behavioural characteristics. The use of the 4DB framework in the transport domain is demonstrated for travel behaviours of interest to policy-makers using examples of buying plug-in vehicles (PiVs), commuting by bicycle, eco-driving and making business trips by train.     

THE UNEXPECTED YARD OF SHIPREPAIR INDUSTRY COSCO ZHOUSHAN Shipyard

It was July 8th 2004 when the email on screen showing one of my company tankers was strutted by another tanker at the waterway outside of Quanzhou, without any other choices, followed by one of the underwriters'suggestion, the vessel was tugged to COSCO (Zhoushan) Shipyard, a brand new shipyard for repairing.     

Knowledge based decision support in airport terminal design

The state of the art in airport terminal design has essentially remained unchanged since the 1970s, relying on the use of detailed simulation together with empirical and statistical formulae for sizing the terminal. Air transport has altered considerably since then, with increased use of air travel for both business and leisure, together with the increased use of ‘hub’ terminals in which the terminal acts as an interchange stop on a journey involving several flights. The use of simulation involves a detailed analysis of the terminal design under one set of conditions. To change the design or operating conditions involves a complete resimulation using the new design parameters which is time consuming and computationally expensive.

By using a knowledge based approach, a system can be provided which has the flexibility and speed required to explore the consequences of implementing design decisions in a variety of conditions, together with the ability to use and alter facility sizing methodologies to reflect current and future design guidelines.     

Quantifying the Difference Between Self-Reported and Global Positioning Systems-Measured Journey Durations: A Systematic Review

Accurate measurement of travel behaviour is vital for transport planning, modelling, public health epidemiology, and assessing the impact of travel interventions. Self-reported diaries and questionnaires are traditionally used as measurement tools; advances in Global Positioning Systems (GPS) technology allow for comparison. This review aimed to identify and report about studies comparing self-reported and GPS-measured journey durations. We systematically searched, appraised, and analysed published and unpublished articles from electronic databases, reference lists, bibliographies, and websites up to December 2012. Included studies used GPS and self-report to investigate trip duration. The average trip duration from each measure was compared and an aggregated, pooled estimate of the difference, weighted by number of trips, was calculated. We found 12 results from eight eligible studies. All studies showed self-reported journey times were greater than GPS-measured times. The difference between self-report and GPS times ranged from over-reporting of +2.2 to +13.5 minutes per journey. The aggregated, pooled estimate of the difference, weighted by number of trips, was over-report of +4.4 minutes (+28.6%). Studies comparing self-reported and GPS-measured journey duration have shown self-reported to be consistently over-reported across the study sample. Our findings suggest that when using self-reported journey behaviour, the journey durations should be treated as an over-estimation.     

风雨摩纳哥：马克的2008

赛季之前的时候大家都有一个疑问，没有牵引力控制系统的比赛会是怎么样的？来到摩纳哥的时候阴云密布，我当时就在想答案就要在这个周末揭晓了。在街道赛进行雨战，不能不说是老天的良好创意。而周日的雨战很好地回答了这个问题，而且比赛场面的精彩和不可预知性使得比赛充满悬念，非常吸引人。     

Computational methodology to predict injury risk for motor vehicle crash victims: A framework for improving Advanced Automatic Crash Notification systems

Advanced Automatic Crash Notification (AACN) systems, capable of predicting post-crash injury severity and subsequent automatic transfer of injury assessment data to emergency medical services, may significantly improve the timeliness, appropriateness, and efficacy of care provided. The estimation of injury severity based on statistical field data, as incorporated in current AACN systems, lack specificity and accuracy to identify the risk of life-threatening conditions. To enhance the existing AACN framework, the goal of the current study was to develop a computational methodology to predict risk of injury in specific body regions based on specific characteristics of the crash, occupant and vehicle. The computational technique involved multibody models of the vehicle and the occupant to simulate the case-specific occupant dynamics and subsequently predict the injury risk using established physical metrics. To demonstrate the computational-based injury prediction methodology, three frontal crash cases involving adult drivers in passenger cars were extracted from the US National Automotive Sampling System Crashworthiness Data System. The representative vehicle model, anthropometrically scaled model of the occupant and kinematic information related to the crash cases, selected at different severities, were used for the blinded verification of injury risk estimations in five different body regions. When compared to existing statistical algorithms, the current computational methodology is a significant improvement toward post-crash injury prediction specifically tailored to individual attributes of the crash. Variations in the initial posture of the driver, analyzed as a pre-crash variable, were shown to have a significant effect on the injury risk.