Computing journey start times with recurrent traffic conditions

n this study, the authors discuss the effective usage of technology to solve the problem of deciding on journey start times for recurrent traffic conditions. The developed algorithm guides the vehicles to travel on more reliable routes that are not easily prone to congestion or travel delays, ensures that the start time is as late as possible to avoid the traveller waiting too long at their destination and attempts to minimise the travel time. Experiments show that in order to be more certain of reaching their destination on time, a traveller has to leave early and correspondingly arrive early, resulting in a large waiting time. The application developed here asks the user to set this certainty factor as per the task in hand, and computes the best start time and route.

Shared authority: courts and legislatures in legal theory

This book advances a fresh philosophical account of the relationship between the legislature and courts, opposing the common conception of law, in which it is legislatures that primarily create the law, and courts that primarily apply it. This conception has eclectic affinities with legal positivism, and although it may have been a helpful intellectual tool in the past, it now increasingly generates more problems than it solves. For this reason, the author argues, legal philosophers are better off abandoning it. At the same time they are asked to dismantle the philosophical and doctrinal infrastructure that has been based on it and which has been hitherto largely unquestioned. In its place the book offers an alternative framework for understanding the role of courts and the legislature; a framework which is distinctly anti-positivist and which builds on Ronald Dworkin’s interpretive theory of law. But, contrary to Dworkin, it insists that legal duty is sensitive to the position one occupies in the project of governing; legal interpretation is not the solitary task of one super-judge, but a collaborative task structured by principles of institutional morality such as separation of powers which impose a moral duty on participants to respect each other's contributions. Moreover this collaborative task will often involve citizens taking an active role in their interaction with the law.

The application of social marketing in reducing road traffic accidents amoung young male drivers: an investigation using physical fear threat appeals

There were 338 road fatalities on Irish roads in 2007. Research in 2007 by the Road Safety Authority in Ireland states that young male drivers (17 – 25 years) are seven times more likely to be killed on Irish roads than other road users. The car driver fatality rate was found to be approximately 10 times higher for young male drivers than for female drivers in 2000. Young male drivers in particular demonstrate a high proclivity for risky driving behaviours. These risky behaviours include drink driving, speeding, rug-driving and engaging in aggressive driving. Speed is the single largest contributing factor to road deaths in Ireland. Approximately 40% of fatal accidents are caused by excessive or inappropriate speed. This study focuses on how dangerous driving behaviours may be addressed through social marketing. This study analyses the appropriate level of fear that needs to be induced in order to change young male driving behaviour.

The Golden Age returns: Virgil's fourth Eclogue in the political panegyric of the Italian courts

E. H. Gombrich and others have analysed the uses made of language and imagery from Virgil's famous fourth Eclogue in panegyrical writing by partisans of the Medici dynasty in Florence. This study examines the appropriation of the theme of the returning Golden Age and related motifs from the fourth Eclogue in other Italian courts during the same period, by supporters of the Visconti and Sforza of Milan, the Gonzaga of Mantua, Leonello d'Este and his successors in Ferrara, and the Bentivoglio of Bologna, among others. The deployment of this Virgilian material in political panegyric is seen to be a central element in the self-definition and self-promotion of dynastic rulers throughout the peninsula.

Exposure to ambient levels of particles emitted by traffic worsens emphysema in mice

Objectives: We investigated effects of chronic exposure (2 months) to ambient levels of particulate matter (PM) on development of protease-induced emphysema and pulmonary remodeling in mice. Methods: Balb/c mice received nasal drop of either papain or normal saline and were kept in two exposure chambers situated in an area with high traffic density. One of them received ambient air and the other had filters for PM. Results: mean concentration of PM10 was 2.68 +/- 0.38 and 33.86 +/- 2.09 mu g/m(3), respectively, in the filtered and ambient air chambers (p<0.001). After 2 months of exposure, lungs from papain-treated mice kept in the chamber with ambient air presented greater values of mean linear intercept, an increase in density of collagen fibers in alveolar septa and in expression of 8-isoprostane (p = 0.002, p < 0.05 and p = 0.002, respectively, compared to papain-treated mice kept in the chamber with filtered air). We did not observe significant differences between these two groups in density of macrophages and in amount of cells expressing matrix metalloproteinase-12. There were no significant differences in saline-treated mice kept in the two chambers. Conclusions: We conclude that exposure to urban levels of PM worsens protease-induced emphysema and increases pulmonary remodeling. We suggest that an increase in oxidative stress induced by PM exposure influences this response. These pulmonary effects of PM were observed only in mice with emphysema. (C) 2009 Elsevier Inc. All rights reserved.

Comparative study in stingless bees (Meliponini) demonstrates that nest entrance size predicts traffic and defensivity

Stingless bees (Meliponini) construct their own species-specific nest entrance. The size of this entrance is under conflicting selective pressures. Smaller entrances are easier to defend; however, a larger entrance accommodates heavier forager traffic. Using a comparative approach with 26 species of stingless bees, we show that species with greater foraging traffic have significantly larger entrances. Such a strong correlation between relative entrance area and traffic across the different species strongly suggests a trade-off between traffic and security. Additionally, we report on a significant trend for higher forager traffic to be associated with more guards and for those guards to be more aggressive. Finally, we discuss the nest entrance of Partamona, known in Brazil as boca de sapo, or toad mouth, which has a wide outer entrance but a narrow inner entrance. This extraordinary design allows these bees to finesse the defensivity/traffic trade-off.

Cellular automaton model for molecular traffic jams

We consider the time evolution of an exactly solvable cellular automaton with random initial conditions both in the large-scale hydrodynamic limit and on the microscopic level. This model is a version of the totally asymmetric simple exclusion process with sublattice parallel update and thus may serve as a model for studying traffic jams in systems of self-driven particles. We study the emergence of shocks from the microscopic dynamics of the model. In particular, we introduce shock measures whose time evolution we can compute explicitly, both in the thermodynamic limit and for open boundaries where a boundary-induced phase transition driven by the motion of a shock occurs. The motion of the shock, which results from the collective dynamics of the exclusion particles, is a random walk with an internal degree of freedom that determines the jump direction. This type of hopping dynamics is reminiscent of some transport phenomena in biological systems.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

A Unified Load Generator for Geographically Distributed Generation ofNetwork Traffic

During the last decade, the Internet usage has been growing at an enormous rate which has beenaccompanied by the developments of network applications (e.g., video conference, audio/videostreaming, E-learning, E-Commerce and real-time applications) and allows several types ofinformation including data, voice, picture and media streaming. While end-users are demandingvery high quality of service (QoS) from their service providers, network undergoes a complex trafficwhich leads the transmission bottlenecks. Considerable effort has been made to study thecharacteristics and the behavior of the Internet. Simulation modeling of computer networkcongestion is a profitable and effective technique which fulfills the requirements to evaluate theperformance and QoS of networks. To simulate a single congested link, simulation is run with asingle load generator while for a larger simulation with complex traffic, where the nodes are spreadacross different geographical locations generating distributed artificial loads is indispensable. Onesolution is to elaborate a load generation system based on master/slave architecture.

A Contour-based Separation of VerticallyAttached Traffic Signs

This report presents an algorithm for locating the cut points for and separatingvertically attached traffic signs in Sweden. This algorithm provides severaladvanced digital image processing features: binary image which representsvisual object and its complex rectangle background with number one and zerorespectively, improved cross correlation which shows the similarity of 2Dobjects and filters traffic sign candidates, simplified shape decompositionwhich smoothes contour of visual object iteratively in order to reduce whitenoises, flipping point detection which locates black noises candidates, chasmfilling algorithm which eliminates black noises, determines the final cut pointsand separates originally attached traffic signs into individual ones. At each step,the mediate results as well as the efficiency in practice would be presented toshow the advantages and disadvantages of the developed algorithm. Thisreport concentrates on contour-based recognition of Swedish traffic signs. Thegeneral shapes cover upward triangle, downward triangle, circle, rectangle andoctagon. At last, a demonstration program would be presented to show howthe algorithm works in real-time environment.

Real-Time Recognition System for Traffic Signs

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.

QoS Evaluation of BandwidthSchedulers in IPTV Networks OfferedSRD Fluid Video Traffic

Internet protocol TV (IPTV) is predicted to be the key technology winner in the future. Efforts to accelerate the deployment of IPTV centralized model which is combined of VHO, encoders, controller, access network and Home network. Regardless of whether the network is delivering live TV, VOD, or Time-shift TV, all content and network traffic resulting from subscriber requests must traverse the entire network from the super-headend all the way to each subscriber's Set-Top Box (STB).IPTV services require very stringent QoS guarantees When IPTV traffic shares the network resources with other traffic like data and voice, how to ensure their QoS and efficiently utilize the network resources is a key and challenging issue. For QoS measured in the network-centric terms of delay jitter, packet losses and bounds on delay. The main focus of this thesis is on the optimized bandwidth allocation and smooth datatransmission. The proposed traffic model for smooth delivering video service IPTV network with its QoS performance evaluation. According to Maglaris et al [5] First, analyze the coding bit rate of a single video source. Various statistical quantities are derived from bit rate data collected with a conditional replenishment inter frame coding scheme. Two correlated Markov process models (one in discrete time and one incontinuous time) are shown to fit the experimental data and are used to model the input rates of several independent sources into a statistical multiplexer. Preventive control mechanism which is to be include CAC, traffic policing used for traffic control.QoS has been evaluated of common bandwidth scheduler( FIFO) by use fluid models with Markovian queuing method and analysis the result by using simulator andanalytically, Which is measured the performance of the packet loss, overflow and mean waiting time among the network users.