Large-scale network partitioning for decentralized traffic management and other transportation applications

For numerous large-scale engineering and science problems, domain decomposition (DD) has generally been accepted by research communities as among the most attractive methods to obtain solutions efficiently. As a prerequisite for the DD solution process, a large domain must be partitioned into several smaller subdomains, with the key to success (of any DD partitioning algorithm) being the number of system boundary nodes. The lower this number, the more efficiently the subdomains can be processed. Although various transportation researchers have hinted at the use of DD, for example, in intelligent transportation systems-enabled decentralized traffic management, it is assumed that the partition is given. This article presents a simple, efficient, and effective algorithm to decompose a transportation network into a predefined number of interconnected subdomains such that the number of system boundary nodes is small (first priority) and the number of nodes in each subdomain is of similar size (second priority). To assess the effectiveness (in terms of minimizing the number of system boundary nodes) of the proposed Shortest Distance Decomposition Algorithm, it is compared with METIS version 5.1.0, currently among the most widely used graph partitioning algorithms worldwide. Using large-scale, real-world transportation test networks, it was found that the Shortest Distance Decomposition Algorithm is better than METIS in 21 of the 27 examples tested; on average, it provided (approximately) 42.0% of the system boundary nodes (as compared to METIS results) in our large-scale examples.     

Changes in private car ownership associated with car sharing: gauging differences by residential location and car share typology

Transportation - While a large body of literature shows that car share encourages low car ownership, the evidence is rather limited in the context of different types of car share (fleet-based...     

New appraisal values of travel time saving and reliability in Great Britain

Transportation - This paper provides an overview of the study ‘Provision of market research for value of time savings and reliability’ undertaken by the Arup/ITS Leeds/Accent consortium...     

Separation and visualization of arteries and heart in 3D computed tomography angiography images

The visualization of arteries and heart usually plays a crucial role in the clinical diagnosis, but researchers face the problems of region selection and mutual occlusion in clinical visualization. Therefore, the arteries and the heart cannot be easily visualized by current visualization methods. To solve the problems, we propose a new framework for arteries and cardiac visualization by combining a priori knowledge and the set operations. Firstly, a suitable region can be easily determined in the transfer function space with a priori knowledge and the visual feedback results. Secondly, the arteries and the heart can be directly extracted by the marked seed point. Finally, the arteries and the heart are separated for solving mutual occlusion through the set operations. This framework can easily solve the mutual occlusion problem in clinical visualization and greatly improve the region selection method in the transfer function space. Its effectiveness has been demonstrated on the basis of many experimental results.     

Application of Elementary Neural Networks and Preview Sensors for Representing Driver Steering Control Behaviour

This paper demonstrates the use of elementary neural networks for modelling and representing driver steering behaviour in path regulation control tasks. Areas of application include uses by vehicle simulation experts who need to model and represent specific instances of driver steering control behaviour, potential on-board vehicle technologies aimed at representing and tracking driver steering control behaviour over time, and use by human factors specialists interested in representing or classifying specific families of driver steering behaviour. Example applications are shown for data obtained from a driver/vehicle numerical simulation, a basic driving simulator, and an experimental on-road test vehicle equipped with a camera and sensor processing system.     

Genetic mouse models for otitis media

GeneticsofOtitisMedia (OM ) :OMisaffectedbymultiplefactorsincludingeustachiantube (ET )structureandfunction ,immunestatus ,innatemucosaldefense ,geneticsusceptibility ,andpathogens .Infec tiousdiseasecanbeviewedasabattlebetweenhostsandpathogens,inwhichthecommandsareencodedinthegenomesoftherespectiveorganismsandarethenexecutedbygeneproductsincludingcomponentsoftheimmuneresponseofthehostanddrug resistancemech anismsofbacteria .Whilecliniciansmaynotgetusedtothinkingofgeneticsasafactorinthedeve…     

Barriers to energy efficiency in shipping

The shipping industry shows potential for improvements in energy efficiency. Nonetheless, shipping companies appear reluctant to adopt these seemingly cost-efficient technical and operational measures aiming at reducing energy costs. Such phenomenon is not specific to the shipping industry and is commonly referred to as the energy efficiency gap. Decades of research in other sectors have contributed to the development of taxonomy of economic, organizational and psychological barriers that determine energy efficiency gaps through the use of a variety of research frameworks. This article aims to apply this research in the shipping context through interviews and review of existing literature and applications from other industries, with the objective of providing useful insight for shipping managers. The article discusses examples of barriers that are typical to shipping and that are related to information asymmetries and power structures within organizations. Managers of shipping firms are encouraged to look through their organizations in search of principal agent problems and power structures among the possible causes for energy efficiency gaps in their companies’ operations and possibly strive towards organizational change.