Thesis (M.S.)--Oregon Graduate Center, 1981.

Thesis (Ph. D.)--Oregon Graduate Institute of Science and Technology, 1996.

A evaluation of Ruby on Rails regarding performance.

The thesis compares web frameworks Ruby on Rails and Grails. The main goal of the thesis is to compare which of these frameworks is more convenient for development of web applications using wide range of criteria. The first part of the thesis defines fundamental terms to understand the web frameworks topic. Subsequently the thesis analyzes the history, language and fundamental characteristics of both frameworks. The next section describes all the details of the reference applications in Ruby on Rails and Grails, that are part of this diploma thesis. The most important part of this thesis is the comparison of both frameworks using a number of criteria. The thesis should provide sufficient amount of information to understand the web frameworks, to obtain the fundamentals for working with the web frameworks Ruby and Rails and Grails and it should bring enough information for optimum choice between these frameworks for development of web application and for future studies. The thesis could be of benefit to both students, that decide what to study in the future, and managers or project leaders, that decide which web framework to use.

This thesis deals with the complex event processing problem. In theoretical part you can find explanation of basic terms and description of used technologies. Reader also becomes fammiliar with basics of work with esper. Practical part is about building administrative interface, which after connecting to server part of application enables user to use basic functionality of esper engine without previous programming knowledge. Part of this chapter is about system set-up, installation and launching the application as it is not considered to be a trivial task.

Focusing on the Denver and Rio Grande Western Railway from Grand Junction, Colorado to Green River, Utah, this study examines the working circumstances of nineteenth-century railroad laborers, the ecological limitations of the isolating desert where they worked, and their relations with railroad management and local communities. It begins by investigating the experiences of the railroad surveyors and construction laborers. The study then examines the experiences of workers' response to labor organization in the communities of Green River, Utah and Grand Junction, Colorado. The study identifies ecological changes spawned by the railroad and addresses issues of worker autonomy and labor organization in the American West in the late nineteenth century.

The objective of this research is to determine the longitudinal stress in rails by using the polarization of Rayleigh waves. Analytical models are developed to describe the effect of applied stress on wave speed and on the polarization of Rayleigh waves. A numerical simulation is performed to find the effect of applied stress on wave velocity and Rayleigh wave polarization. The effect of uncertainties in material properties on wave velocity and polarization of Rayleigh wave is also examined in the simulation. The experiment uses a laser Doppler vibrometer (LDV) to measure the particle velocities. The in-plane and out-of-plane velocity components are obtained from the measured particle velocities. The polarization of Rayleigh wave, which is defined as the ratio between the in-plane and out-of-plane displacements, is calculated. Furthermore, the polarization of the Rayleigh wave is considered as a measure to identify applied stress. The experiment is performed on unstressed and stressed rail specimen. Thus, Rayleigh wave polarization is obtained as a function of applied stress. The experimental results are compared with the analytical model. The result shows a good agreement with the theoretical values for unstressed rail.

Cette thèse porte sur la fonction de détection d'obstacles dans le domaine ferroviaire à partir de la vision par ordinateur. Il s'agit d'assurer une perception de l'environnement situé à l'avant du train afin de détecter et d'évaluer les distances des obstacles situés sur la voie.Nous avons donc proposé un module détection de rails à partir des images à niveaux de gris, pour déterminer une zone libre d'obstacles à l'avant du train. Cette détection est basée dans l'algorithme de RANSAC et une estimation de la voie par un polynôme de degré 2. Elle s'est montrée robuste à notre base de données et a permis de détecter les rails à des distances supérieures à la distance d'arrêt. Aussi, un algorithme d'étalonnage des caméras installées dans le train a été proposé à partir de la morphologie de la voie.Comme support de la reconnaissance de rails, nous présentons un module de détection et classification des appareils de voie basé dans le descripteur HOG extrait des images IPM (Inverse Perspective Mapping). Un classifieur SVM (Support Vector Machines) binaire a été utilisé pour la détection et un SVM multi-classe pour différencier les appareils de voie existants sur la ligne.Après avoir élaboré le module de détection des rails, nous avons implémenté un détecteur de trains. À partir d'un échantillon des images de trains de la ligne en question et des images négatives comme des voitures ou des bus, nous avons créé une base de données d'obstacles pour trouver un descripteur robuste qui arrive à décrire la forme des trains et permet à un classifieur SVM de discriminer les images et détecter les trains. Par la suite, ce classifieur est utilisé par le système global pour déterminer la présence d'un train au-delà de la détection de la voie. À la distance maximale de détection, un rectangle de la taille d'un train est extrait de l'image pour vérifier la présence d'un train. Ces rectangles font l'objet d'une classification au moyen de descripteurs globaux de type HOG et une structure SVM binaire.Cette étude permettra non seulement de déboucher sur des applications concrètes, mais surtout d'évaluer la maturité des technologies de traitements d'images pour réaliser des fonctions sûres appliquées aux systèmes ferroviaires. / This thesis deals with obstacle detection in a railway setting using computer vision. The main task is to provide perception of the environment in front ofthe train using an optical sensor to detect and evaluate distances to obstacles along the track path.We present a module for detecting rails from grayscale images to determine an obstacle-free zone in front of the train. This detection is based on the RANSACalgorithm and fitting the track to a second degree polynomial. The method has shown itself robust to our dataset and allows detecting the rails at distancesgreater than the emergency stopping distance. In addition, a method for calibrating the cameras installed on the train is proposed based on the morphology ofthe track.To supplement rail detection, we present a new module for detecting and classifying junctions based on the HOG descriptor extracted from InversePerspective Mapping (IPM) images. A Support Vector Machines (SVM) binary classifier was used for detection and a multi-class SVM for distinguishing ofjunctions along the rails.In the sequel, a train detector was implemented. Using a set of images of trains found on the studied line and negative images such as cars or buses, we havecreated a database of obstacles to find a robust descriptor which is able to model the form of trains and allows a SVM classifier to distinguish images anddetect trains. Next this classifier is used by the overall system to determine the presence of a train in addition to detecting rails. At the maximum detectiondistance, a train-sized rectangle is extracted from the image in order to confirm the presence of a train. These rectangles are classified by means of HOG-typeglobal descriptors and a binary SVM structure.In addition to its applications to concrete problems, this study permits to evaluate the maturity of image processing technologies forfail-safe railway systems.

Web programming is getting more and more important every day and as a consequence, many new tools are created in order to help developers design and construct applications quicker, easier and better structured. Apart from different IDEs and Technologies, nowadays Web Frameworks are gaining popularity amongst users since they offer a large range of methods, classes, etc. that allow programmers to create and maintain solid Web systems.This research focuses on two different Web Frameworks: Ruby on Rails and Google Web Toolkit and within this document we will examine some of the most important differences between them during a Web development.

Ingeniero Civil en Computación / En este documento se detalla el trabajo realizado para la elaboración de una red social para el fomento de la lectura, como parte del proyecto de La Biblioteca Libre. Acá se explica la solución implementada y las tecnologías utilizadas para el desarrollo de la misma. La Biblioteca Libre nace como una iniciativa para promover la lectura. Mediante el intercambio de libros, se ha logrado liberar 60 mil libros que permanecían sin uso. Esto ha generado una comunidad en torno al proyecto que no ha sido aprovechada en todo su potencial. Para esto, se planteó la creación de una red social que permita buscar libros, para luego valorarlos, criticarlos y comentarlos. Así, cada usuario puede revisar y descubrir nuevos libros a partir de lo descrito por otros usuarios, además de recibir recomendaciones de textos por parte del sistema. En la actualidad, sólo existían sitios de habla inglesa con estas características. Para validar la solución se encuestó a participantes recurrentes de La Biblioteca Libre, además de contar con casos de pruebas para las funcionalidades principales. Esta solución fue desarrollada usando Ruby on Rails, ya que se buscó un lenguaje expresivo y un framework que entregara herramientas para un trabajo rápido y expedito. La aplicación se encuentra en los servidores de Heroku y necesitará conectarse a Amazon, tanto para buscar información sobre los libros como para guardar imágenes. También es necesario realizar conexiones a Facebook para que los usuarios puedan usar sus cuentas en el sitio.