Three essays on major trends in a slow clockspeed industry : the case of industrial automation

The motivation for this research initiated from the abrupt rise and fall of minicomputers which were initially used both for industrial automation and business applications due to their significantly lower cost than their predecessors, the mainframes. Later industrial automation developed its own vertically integrated hardware and software to address the application needs of uninterrupted operations, real-time control and resilience to harsh environmental conditions. This has led to the creation of an independent industry, namely industrial automation used in PLC, DCS, SCADA and robot control systems. This industry employs today over 200'000 people in a profitable slow clockspeed context in contrast to the two mainstream computing industries of information technology (IT) focused on business applications and telecommunications focused on communications networks and hand-held devices. Already in 1990s it was foreseen that IT and communication would merge into one Information and communication industry (ICT). The fundamental question of the thesis is: Could industrial automation leverage a common technology platform with the newly formed ICT industry? Computer systems dominated by complex instruction set computers (CISC) were challenged during 1990s with higher performance reduced instruction set computers (RISC). RISC started to evolve parallel to the constant advancement of Moore's law. These developments created the high performance and low energy consumption System-on-Chip architecture (SoC). Unlike to the CISC processors RISC processor architecture is a separate industry from the RISC chip manufacturing industry. It also has several hardware independent software platforms consisting of integrated operating system, development environment, user interface and application market which enables customers to have more choices due to hardware independent real time capable software applications. An architecture disruption merged and the smartphone and tablet market were formed with new rules and new key players in the ICT industry. Today there are more RISC computer systems running Linux (or other Unix variants) than any other computer system. The astonishing rise of SoC based technologies and related software platforms in smartphones created in unit terms the largest installed base ever seen in the history of computers and is now being further extended by tablets. An underlying additional element of this transition is the increasing role of open source technologies both in software and hardware. This has driven the microprocessor based personal computer industry with few dominating closed operating system platforms into a steep decline. A significant factor in this process has been the separation of processor architecture and processor chip production and operating systems and application development platforms merger into integrated software platforms with proprietary application markets. Furthermore the pay-by-click marketing has changed the way applications development is compensated: Three essays on major trends in a slow clockspeed industry: The case of industrial automation 2014 freeware, ad based or licensed - all at a lower price and used by a wider customer base than ever before. Moreover, the concept of software maintenance contract is very remote in the app world. However, as a slow clockspeed industry, industrial automation has remained intact during the disruptions based on SoC and related software platforms in the ICT industries. Industrial automation incumbents continue to supply systems based on vertically integrated systems consisting of proprietary software and proprietary mainly microprocessor based hardware. They enjoy admirable profitability levels on a very narrow customer base due to strong technology-enabled customer lock-in and customers' high risk leverage as their production is dependent on fault-free operation of the industrial automation systems. When will this balance of power be disrupted? The thesis suggests how industrial automation could join the mainstream ICT industry and create an information, communication and automation (ICAT) industry. Lately the Internet of Things (loT) and weightless networks, a new standard leveraging frequency channels earlier occupied by TV broadcasting, have gradually started to change the rigid world of Machine to Machine (M2M) interaction. It is foreseeable that enough momentum will be created that the industrial automation market will in due course face an architecture disruption empowered by these new trends. This thesis examines the current state of industrial automation subject to the competition between the incumbents firstly through a research on cost competitiveness efforts in captive outsourcing of engineering, research and development and secondly researching process re- engineering in the case of complex system global software support. Thirdly we investigate the industry actors', namely customers, incumbents and newcomers, views on the future direction of industrial automation and conclude with our assessments of the possible routes industrial automation could advance taking into account the looming rise of the Internet of Things (loT) and weightless networks. Industrial automation is an industry dominated by a handful of global players each of them focusing on maintaining their own proprietary solutions. The rise of de facto standards like IBM PC, Unix and Linux and SoC leveraged by IBM, Compaq, Dell, HP, ARM, Apple, Google, Samsung and others have created new markets of personal computers, smartphone and tablets and will eventually also impact industrial automation through game changing commoditization and related control point and business model changes. This trend will inevitably continue, but the transition to a commoditized industrial automation will not happen in the near future.

Effect of Video Camera-Based Remote Roadway Condition Monitoring on Snow Removal-Related Maintenance Operations. 2014

Remote monitoring through the use of cameras is widely utilized for traffic operation, but has not been utilized widely for roadway maintenance operations. The Utah Department of Transportation (UDOT) has implemented a new remote monitoring system, referred to as a Cloud-enabled Remote Video Streaming (CRVS) camera system for snow removal-related maintenance operations in the winter. The purpose of this study was to evaluate the effectiveness of the use of the CRVS camera system in snow removal-related maintenance operations. This study was conducted in two parts: opinion surveys of maintenance station supervisors and an analysis on snow removal-related maintenance costs. The responses to the opinion surveys mostly displayed positive reviews of the use of the CRVS cameras. On a scale of 1 (least effective) to 5 (most effective), the average overall effectiveness given by the station supervisors was 4.3. An expedition trip for this study was defined as a trip that was made to just check the roadways if snow-removal was necessary. The average of the responses received from surveys was calculated to be a 33 percent reduction in expedition trips. For the second part of this study, an analysis was performed on the snow removal-related maintenance cost data provided by UDOT to see if the installation of a CRVS camera had an effect in reducing expedition trips. This expedition cost comparison was performed for 10 sets of maintenance stations within Utah. It was difficult to make any definitive inferences from the comparison of expedition costs over the years for which precipitation and expedition cost data were available; hence a statistical analysis was performed using the Mixed Model ANOVA. This analysis resulted in an average of 14 percent higher ratio of expedition costs at maintenance stations with a CRVS camera before the installation of the camera compared to the ratio of expedition costs after the installation of the camera. This difference was not proven to be statistically significant at the 95 percent confident level, but indicated that the installation of CRVS cameras was on the average helpful in reducing expedition costs and may be considered practically significant. It is recommended that more detailed and consistent maintenance cost records be prepared for accurate analysis of cost records for this type of study in the future.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

Open source software in translator training

La formació de traductors implica l´ús de procediments i eines que permetin els estudiants familiaritzar-se amb contextos professionals. El software lliure especialitzat inclou eines de qualitat professional i procediments accessibles per a les institucions acadèmiques i els estudiants a distància que treballen a casa seva. Els projectes reals que utilitzen software lliure i traducció col·laborativa (crowdsourcing) constitueixen recursos indispensables en la formació de traductors.

Evaluación y optimización de los servicios de un taller de mantenimiento mediante el software de simulación ARENA

Debido a la necesidad de diferenciarse y hacer frente a la competencia, las empresas han apostado por desarrollar operaciones que den valor al cliente, por eso muchas de ellas han visto en las herramientas lean la oportunidad para mejorar sus operaciones. Esta mejora implica la reducción de dinero, personas, equipos grandes, inventario y espacio, con dos objetivos: eliminar despilfarro y reducir la variabilidad. Para conseguir los objetivos estratégicos de la empresa es imprescindible qué éstos estén alineados con los planes de la gerencia a nivel medio y a su vez con el trabajo realizado por los empleados para asegurar que cada persona está alineada en la misma dirección y al mismo tiempo. Ésta es la filosofía de la planificación estratégica. Por ello uno de los objetivos de este proyecto será el desarrollar una herramienta que facilite la exposición de los objetivos de la empresa y la comunicación de los mismos a todos los niveles de la organización para a partir de ellos y tomando como referencia la necesidad de reducir inventarios en la cadena de suministro se realizará un estudio de la producción de un componente de control del aerogenerador para conseguir nivelarla y reducir su inventario de producto terminado. Los objetivos particulares en este apartado serán reducir el inventario en un 28%, nivelar la producción reduciendo la variabilidad del 31% al 24%, mantener un stock máximo de 24 unidades garantizando el suministro ante una demanda variable, incrementar la rotación del inventario en un 10% y establecer un plan de acción para reducir el lead time entre un 40-50%. Todo ello será posible gracias a la realización del mapa de valor presente y futuro para eliminar desperdicios y crear un flujo continuo y el cálculo de un supermercado que mantenga el stock en un nivel óptimo.

MyTopRoom : Aplicación para Android: Buscador de ofertas de hoteles

El objetivo de este proyecto es el desarrollo de una aplicación móvil para dispositivos con sistema operativo Android que permita la búsqueda de ofertas de hotel de una forma diferente a las actuales. Para ello se ha empleado el modelo del ciclo de vida en cascada, con las fases de análisis, diseño, construcción y pruebas del sistema desarrollado. El software final sigue una arquitectura de tipo cliente/servidor y ha sido realizado con Java como lenguaje base de programación, haciendo uso de algunas librerías como Apache HTTP Request para las conexiones con el servidor remoto como las propias de Android, que facilitan la creación de interfaces gráficas y la gestión de los recursos de los dispositivos en el desarrollo de aplicaciones móviles.

Las TIC como instrumento para la colaboración en red, en el ámbito de la Formación Profesional: Una aplicación de Software Libre para colaboración entre centro-empresa en el I.E.S El Palau.

En la era digital actual, Internet forma parte de nuestras vidas, y ha aportado cambios a lasociedad globalizada. Algunos de estos cambios nos permiten nuevas formas de relacionarnos y degestionar el conocimiento, dando sentido al término que hoy entendemos como sociedad-red.Por eso, en el entorno que nos envuelve existen continuamente acciones colaborativas globales quefomentan la comunicación y se comparte información de diversos tipos, con la finalidad deaprender y mantenerse constantemente informado. Específicamente, los centros educativos no sequedan al margen ya que requiere preparar estudiantes para esta sociedad.Estos cambios en la sociedad presentan grandes desafíos para el centro educativo, que nopermiten ser afrontados solamente desde el aula. Los centros requieren adaptarse a un modelocompatible con la sociedad-red, y por ello, se sugieren un modelo centro-red, que presente unaestructura de una organización compatible con la era en el que estamos inmersos.Las redes de colaboración en los centros permite intercambiar información y aportar valor a laeducación con el objetivo de la mejora educativa. En este sentido, los centros educativos debendisponer de características que permitan ser flexibles, adaptarse a los agentes y organizaciones quele envuelven. Pero la estructura actual de un centro educativo es rígida y por tanto esta evoluciónrepresenta uno de los mayores desafíos para el sistema educativo.En esta linea, en los centros de Formación Profesional existe una tendencia hacia modeloscolaborativos con el tejido empresarial, entre otros agentes, y es en este punto donde este proyectopretende centrar el foco de la investigación. Con más exactitud, en la creación de una red decolaboración con el agente que el centro educativo seleccione.Específicamente las TIC forman un papel esencial, y se deben poner al servicio del problemaque apuntábamos para ayudar a solventarlo. En este sentido, es adecuado un diseño del artefactocon Software Libre que tiene múltiples beneficios para este objetivo, pero que destacamos el que ami parecer es el más importante; la vinculación con la filosofía de compartir el conocimiento, quegarantiza la simbiosis con la red colaborativa y es por esta razón que el tema de la investigación esrelevante para el centro educativo.Tal y como se mencionaba previamente, las TIC pueden ayudar a fomentar la red colaborativa,pero no sólo el artefacto TIC generado en este proyecto debe cumplir características como laflexibilidad, también es crítico que el centro educativo y los agentes de la red interioricen la culturacolaborativa en sus acciones con la implicación y compromiso que se requiere. Pero como podemosPágina 6Universitat Oberta de Catalunya Trabajo Final de Máster - Software Libreimaginar, ese cambio de cultura, no es una tarea sencilla y presenta problemas. Para mitigarlos yfomentar la cultura en red, se requieren procesos específicos que permitan incorporarla en la medidade lo posible. Para ello, la combinación de la innovación sistémica y el diseño de la investigación eneducación resultan metodologías apropiadas.Por eso, investigaremos durante este proceso cómo las redes de colaboración y el SoftwareLibre permiten adaptar el centro al entorno, cómo pueden ayudar al centro a potenciar la FormaciónProfesional y garantizar la durabilidad de las acciones, con el objetivo que perdure el conocimientoy la propia red de colaboración para una mejora educativa.

Implantación de un sistema VoIP basado en software libre con Asterisk

Este proyecto busca analizar, diseñar e implementar una nueva solución de telefonía para el Centro Social de Oficiales de la Policía Nacional contemplando la posibilidad de optar por una migración hacia un sistema VoIP bajo software libre con Asterisk. En consecuencia, se deben evaluar las tecnologías actuales buscando proveer nuevas funcionalidades en el servicio telefónico generando bajos costos en su implementación, funcionamiento y mantenimiento.

Remote collaborative multi-user informal learning experiences: design and evaluation

This paper presents a customizable system used to develop a collaborative multi-user problem solving game. It addresses the increasing demand for appealing informal learning experiences in museum-like settings. The system facilitates remote collaboration by allowing groups of learners tocommunicate through a videoconferencing system and by allowing them to simultaneously interact through a shared multi-touch interactive surface. A user study with 20 user groups indicates that the game facilitates collaboration between local and remote groups of learners. The videoconference and multitouch surface acted as communication channels, attracted students’ interest, facilitated engagement, and promoted inter- and intra-group collaboration—favoring intra-group collaboration. Our findings suggest that augmentingvideoconferencing systems with a shared multitouch space offers newpossibilities and scenarios for remote collaborative environments and collaborative learning.

The Use of Remote Sensing Techniques Compared to Traditional Archaeological Phase II Testing Methods: A Cost-Benefit Analysis, HR-524, 1986

Remote sensing was utilized in the Phase II Cultural Resources Investigation for this project in lieu of extensive excavations. The purpose of the present report is to compare the costs and benefits of the use of remote sensing to the hypothetical use of traditional excavation methods for this project. Estimates for this hypothetical situation are based on the project archaeologist's considerable past experience in conducting similar investigations. Only that part of the Phase II investigation involving field investigations is addressed in this report. Costs for literature review, laboratory analysis, report preparation, etc., are not included. The project manager proposed the use of this technique for the fol lowing logistic, safety and budgetary reasons.

Programari de consulta offline al campus virtual de la UOC

L'objectiu del projecte és el desenvolupament d'una aplicació d'escriptori que permeti a l'estudiant la consulta offline de les darreres novetats disponibles a les aules del campus UOC. Es tracta d'automatitzar el procés de consulta i descàrrega local de dades per tal de poder consultar-les posteriorment fora de línia.

Iowa Bridge Backwater Software User Manual, Version 2.0, TR-564, 2010

This manual describes how to use the Iowa Bridge Backwater software. It also documents the methods and equations used for the calculations. The main body describes how to use the software and the appendices cover technical aspects. The Bridge Backwater software performs 5 main tasks: Design Discharge Estimation; Stream Rating Curves; Floodway Encroachment; Bridge Backwater; and Bridge Scour. The intent of this program is to provide a simplified method for analysis of bridge backwater for rural structures located in areas with low flood damage potential. The software is written in Microsoft Visual Basic 6.0. It will run under Windows 95 or newer versions (i.e. Windows 98, NT, 2000, XP and later).

Ingeniería del software: portal web inmobiliario

En la actualidad las tecnologías de la información son utilizadas en todos los ámbitos empresariales. Desde sistemas de gestión (ERPs) pasando por la gestión documental, el análisis de información con sistema de Bussines Intelligence, pudiendo incluso convertirse en toda una nueva plataforma para proveer a las empresas de nuevos canales de venta, como es el caso deInternet.De la necesidad inicial de nuestro cliente en comenzar a expandirse por un nuevo canal de venta para poder llegar a nuevos mercados y diversificar sus clientes se inicia la motivación de este TFC.Dadas las características actuales de las tecnologías de la información e internet, estas conforman un binomio perfecto para definir este TFC que trata todos los aspectos necesarios para llegar a obtener un producto final como es un portal web inmobiliario adaptado a los requisitos demandados por los usuarios actuales de Internet.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Las TIC como instrumento para la colaboración en red, en el ámbito de la Formación Profesional : Una aplicación de software libre para colaboración entre centro-empresa en el I.E.S El Palau

Investigaremos cómo las redes de colaboración y el softwarelibre permiten adaptar el centro educativo al entorno, cómo pueden ayudar al centro a potenciar la formación profesional y garantizar la durabilidad de las acciones, con el objetivo que perdure el conocimiento y la propia red de colaboración para una mejora educativa.