The Texas driver responsibility program: A preliminary analysis of the impact on impaired driving and trauma system funding

Objective. In 2003, the State of Texas instituted the Driver Responsibility Program (TDRP), a program consisting of a driving infraction point system coupled with a series of graded fines and annual surcharges for specific traffic violations such as driving while intoxicated (DWI). Approximately half of the revenues generated are earmarked to be disbursed to the state's trauma system to cover uncompensated trauma care costs. This study examined initial program implementation, the impact of trauma system funding, and initial impact on impaired driving knowledge, attitudes and behaviors. A model for targeted media campaigns to improve the program's deterrence effects was developed. ^ Methods. Data from two independent driver survey samples (conducted in 1999 and 2005), department of public safety records, state health department data and a state auditor's report were used to evaluate the program's initial implementation, impact and outcome with respect to drivers' impaired driving knowledge, attitudes and behavior (based on constructs of social cognitive theory) and hospital uncompensated trauma care funding. Survey results were used to develop a regression model of high risk drivers who should be targeted to improve program outcome with respect to deterring impaired driving. ^ Results. Low driver compliance with fee payment (28%) and program implementation problems were associated with lower surcharge revenues in the first two years ($59.5 million versus $525 million predicted). Program revenue distribution to trauma hospitals was associated with a 16% increase in designated trauma centers. Survey data demonstrated that only 28% of drivers are aware of the TDRP and that there has been no initial impact on impaired driving behavior. Logistical regression modeling suggested that target media campaigns highlighting the likelihood of DWI detection by law enforcement and the increased surcharges associated with the TDRP are required to deter impaired driving. ^ Conclusions. Although the TDRP raised nearly $60 million in surcharge revenue for the Texas trauma system over the first two years, this study did not find evidence of a change in impaired driving knowledge, attitudes or behaviors from 1999 to 2005. Further research is required to measure whether the program is associated with decreased alcohol-related traffic fatalities. ^

Classified Adélie penguin colonies from Landsat data

Breeding distribution of the Adelie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data along the coastline of Antarctica, an area covering approximately 330° of longitude. An algorithm was designed to minimize the radiometric contribution from exogenous sources and to retrieve Adelie penguin colony location and spatial extent from the ETM+ data. In all, 9143 individual pixels were classified as belonging to an Adelie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m, and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adelie penguin colonies, ranging in size from a single pixel (900 m**2) to a maximum of 875 pixels (0.788 km**2). Colony retrievals have a very low error of commission, on the order of 1 percent or less, and the error of omission was estimated to be 2.9 percent by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals can successfully locate Adelie penguin colonies that account for ~97 percent of a regional population. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adelie penguin colonies were found that are believed to be unreported in the literature.

Analysis of Thematic Classified Aerial Images Trough Multispectral and LIDAR Data

The application of thematic maps obtained through the classification of remote images needs the obtained products with an optimal accuracy. The registered images from the airplanes display a very satisfactory spatial resolution, but the classical methods of thematic classification not always give better results than when the registered data from satellite are used. In order to improve these results of classification, in this work, the LIDAR sensor data from first return (Light Detection And Ranging) registered simultaneously with the spectral sensor data from airborne are jointly used. The final results of the thematic classification of the scene object of study have been obtained, quantified and discussed with and without LIDAR data, after applying different methods: Maximum Likehood Classification, Support Vector Machine with four different functions kernel and Isodata clustering algorithm (ML, SVM-L, SVM-P, SVM-RBF, SVM-S, Isodata). The best results are obtained for SVM with Sigmoide kernel. These allow the correlation with others different physical parameters with great interest like Manning hydraulic coefficient, for their incorporation in a GIS and their application in hydraulic modeling.

VLC oriented energy efficient driver techniques

LEDs are substituting fluorescent and incandescent bulbs as illumination sources due to their low power consumption and long lifetime. Visible Light Communications (VLC) makes use of the LEDs short switching times to transmit information. Although LEDs switching speed is around Mbps range, higher speeds (hundred of Mbps) can be reached by using high bandwidth-efficiency modulation techniques. However, the use of these techniques requires a more complex driver which elevates drastically its power consumption. In this work an energy efficiency analysis of the different VLC modulation techniques and drivers is presented. Besides, the design of new schemes of VLC drivers is described.

Licensing patterns for Linked Data

Rights expression languages declare the permitted and prohibited actions to be performed on a resource. Along this work, six rights expression languages are compared, abstracting their commonalities and outlining their underlying pattern. Linked Data, which can be object of protection by the intellectual property laws or its access be restricted by an access control system, can be the asset in rights expressions. The requirements for a pattern for licensing Linked Data resources are listed.

Linked Data Rights 2.0: extension of ODRL for Licensing Linked Data

Linked Data assets (RDF triples, graphs, datasets, mappings...) can be object of protection by the intellectual property law, the database law or its access or publication be restricted by other legal reasons (personal data pro- tection, security reasons, etc.). Publishing a rights expression along with the digital asset, allows the rightsholder waiving some or all of the IP and database rights (leaving the work in the public domain), permitting some operations if certain conditions are satisfied (like giving attribution to the author) or simply reminding the audience that some rights are reserved.

Embedded Linux integration using Linuxlink tool and peripheral driver development for Zedboard

This project is divided into two main parts: The first part shows the integration of an Embedded Linux operating system on a development hardware platform named Zedboard. This platform contains a Zynq-7000 System on Chip (Soc) which is composed by two dual core ARM Cortex-A9 processors and a FPGA Artix-7. The Embedded Linux is built with Linuxlink, a Timesys tool. Meanwhile, the platform hardware configuration is done with Xilinx Vivado. The system is loaded with an SD card which requires to have every files needed for the booting process and for the operation. Some of these files are generated with Xilinx SDK software. The second part starts up from the system already built to integrate a peripheral in the Zynq-7000 FPGA. Also the drivers for controlling the peripheral from the operating system are developed. Finally, a user space program is created to test both of them. RESUMEN. Este proyecto consta de dos partes: La primera muestra la integración de un sistema operativo Linux embebido en una plataforma de desarrollo hardware llamada Zedboard. Esta plataforma utiliza un System on Chip (SoC) Zynq-7000 que está formado por dos procesadores ARM Cortex-A9 de doble núcleo y una FPGA Artix-7. El Linux embebido se construye utilizando la herramienta Linuxlink de Timesys, mientras que el hardware de la plataforma de desarrollo se configura con Vivado de Xilinx. El sistema se carga en una tarjeta SD que debe tener todos los archivos necesarios para completar el arranque y hacer funcionar el sistema. Algunos de esos archivos se generan con la herramienta SDK de Xilinx. En la segunda parte se utiliza el sistema construido para integrar un periférico en la FPGA del Zynq-7000, haciendo uso de Vivado, y se desarrollan los drivers necesarios para utilizarlo mediante el sistema operativo. Para probar esta última parte se desarrolla un programa de espacio de usuario.

Atlantic salmon (Salmo salar) parr as a model to predict the optimum inclusion of air classified faba bean protein concentrate in feeds for seawater salmon

Peer reviewed

Linear chaos for the Quick-Thinking-Driver model.

In recent years, the topic of car-following has experimented an increased importance in traffic engineering and safety research. This has become a very interesting topic because of the development of driverless cars (Google driverless cars, http://en.wikipedia.org/wiki/Google_driverless_car). Driving models which describe the interaction between adjacent vehicles in the same lane have a big interest in simulation modeling, such as the Quick-Thinking-Driver model. A non-linear version of it can be given using the logistic map, and then chaos appears. We show that an infinite-dimensional version of the linear model presents a chaotic behaviour using the same approach as for studying chaos of death models of cell growth.

Análise de consistência de traçado de uma rodovia de múltiplas faixas.

O número de acidentes de trânsito é crescente nas últimas décadas no Brasil. Uma das principais causas de acidentes em rodovias brasileiras é o excesso de velocidade, que contribui para a possibilidade de ocorrência de acidentes. As velocidades praticadas pelos motoristas são também função dos elementos geométricos que compõem a via (raio, rampa, largura da faixa, etc). A consistência de traçado não afeta a expectativa dos motoristas e garante uma operação segura. A maioria dos motoristas consegue perceber as falhas de coordenação, mas tecnicamente, por exemplo, desconhecem a origem das mesmas. Esta pesquisa apresenta como objetivo a análise de consistência de um trecho de uma determinada rodovia do país de múltiplas faixas, com elevado índice de acidentes e alto fluxo de veículos comerciais. Os pontos com maior ocorrência de acidentes foram identificados e realizaram-se medições de velocidade para elaboração de um modelo de previsão de velocidade operacional (V85) do trecho de estudo. De posse deste modelo, procedeu-se à análise de consistência através do método dos critérios de segurança, que identificou 2 seções com problemas de consistência. Por fim, verificou-se se estas seções correspondiam aos locais de maior número de acidentes: a tangente T5 precede uma curva com alto índice de acidentes (km 511+000); o local com maior concentração de acidentes (km 514) foi classificado como RAZOÁVEL.