Tieliikennetelematiikkalaitteiden huoltoon liittyvän verkoston toiminnan kehittäminen

Diplomityössä on tutkittu tieliikennetelematiikkalaitteiden huoltoon liittyvän verkoston toiminnan kehittämistä. Tutkittuun verkostoon kuuluvat Valtti-yksikkö (Valtakunnallinen liikennetelematiikka ja liikenteenhallinnan tietopalvelut), ELYkeskukset, tieliikennekeskukset, hallinta- ja valvontatoimija sekä huoltotoimijat. Tarkoituksena oli selvittää, kuinka verkoston toiminnan tehokkuutta voidaan parantaa. Tähän sisältyi verkoston toimijoiden tunnistaminen sekä toimijoiden roolien ja vastuiden määrittäminen. Lisäksi on tutkittu kuinka verkoston toimijoiden välistä tiedonkulkua voidaan parantaa ja kuinka ITIL-viitekehys soveltuu verkoston toimintaan. Diplomityötä varten on haastateltu verkoston toimijoiden edustajia heidän näkemyksistään verkoston toiminnasta ja sen kehittämistarpeista.

Automatic traffic sign inventory- and condition analysis

This thesis researches automatic traffic sign inventory and condition analysis using machine vision and pattern recognition methods. Automatic traffic sign inventory and condition analysis can be used to more efficient road maintenance, improving the maintenance processes, and to enable intelligent driving systems. Automatic traffic sign detection and classification has been researched before from the viewpoint of self-driving vehicles, driver assistance systems, and the use of signs in mapping services. Machine vision based inventory of traffic signs consists of detection, classification, localization, and condition analysis of traffic signs. The produced machine vision system performance is estimated with three datasets, from which two of have been been collected for this thesis. Based on the experiments almost all traffic signs can be detected, classified, and located and their condition analysed. In future, the inventory system performance has to be verified in challenging conditions and the system has to be pilot tested.

Keskitehoestimaattorin lisääminen diesel-sähköiseen hybridijärjestelmään

Nykyajan jatkuvasti kiristyvät päästörajoitukset ja ilmastonmuutoksen uhka ovat ajavia voimia kehittämään voimalaitosten tekniikkaa energiatehokkaampaan ja ympäristöystävällisempään suuntaan. Polttomoottoritekniikan parantaminen on tärkeä osa tätä kehitystä, mutta jo nykyisiä moottoreita voitaisiin ajaa energiate-hokkaammin käyttämällä akustoa ja älykästä säätöjärjestelmää apuna. Työssä tutkitaan simulaatioiden avulla voidaanko ulkomerellä toimivan huolto-aluksen energiatehokkuutta parantaa muokkaamalla sen tehon tuottoa keskitehoes-timaattorin ja akuston avulla.

Green welding in practice

Efficient production and consumption of energy has become the top priority of national and international policies around the world. Manufacturing industries have to address the requirements of the government in relation to energy saving and ecologically sustainable products. These industries are also concerned with energy and material usage due to their rising costs. Therefore industries have to find solutions that can support environmental preservation yet maintain competitiveness in the market. Welding, a major manufacturing process, consumes a great deal of material and energy. It is a crucial process in improving a product’s life-cycle cost, strength, quality and reliability. Factors which lead to weld related inefficiencies have to be effectively managed, if industries are to meet their quality requirements and fulfil a high-volume production demand. Therefore it is important to consider some practical strategies in welding process for optimization of energy and material consumption. The main objective of this thesis is to explore the methods of minimizing the ecological footprint of the welding process and methods to effectively manage its material and energy usage in the welding process. The author has performed a critical review of the factors including improved weld power source efficiency, efficient weld techniques, newly developed weld materials, intelligent welding systems, weld safety measures and personnel training. The study lends strong support to the fact that the use of eco-friendly welding units and the quality weld joints obtained with minimum possible consumption of energy and materials should be the main directions of improvement in welding systems. The study concludes that, gradually implementing the practical strategies mentioned in this thesis would help the manufacturing industries to achieve on the following - reduced power consumption, enhanced power control and manipulation, increased deposition rate, reduced cycle time, reduced joint preparation time, reduced heat affected zones, reduced repair rates, improved joint properties, reduced post-weld operations, improved automation, improved sensing and control, avoiding hazardous conditions and reduced exposure of welder to potential hazards. These improvement can help in promotion of welding as a green manufacturing process.

Processus cérébraux adaptés aux systèmes tutoriels intelligents

Le module de l'apprenant est l'une des composantes les plus importantes d’un Système Tutoriel Intelligent (STI). L'extension du modèle de l'apprenant n'a pas cessé de progresser. Malgré la définition d’un profil cognitif et l’intégration d’un profil émotionnel, le module de l’apprenant demeure non exhaustif. Plusieurs senseurs physiologiques sont utilisés pour raffiner la reconnaissance des états cognitif et émotionnel de l’apprenant mais l’emploi simultané de tous ces senseurs l’encombre. De plus, ils ne sont pas toujours adaptés aux apprenants dont les capacités sont réduites. Par ailleurs, la plupart des stratégies pédagogiques exécutées par le module du tuteur ne sont pas conçues à la base d’une collecte dynamique de données en temps réel, cela diminue donc de leur efficacité. L’objectif de notre recherche est d’explorer l’activité électrique cérébrale et de l’utiliser comme un nouveau canal de communication entre le STI et l’apprenant. Pour ce faire nous proposons de concevoir, d’implémenter et d’évaluer le système multi agents NORA. Grâce aux agents de NORA, il est possible d’interpréter et d’influencer l’activité électrique cérébrale de l’apprenant pour un meilleur apprentissage. Ainsi, NORA enrichit le module apprenant d’un profile cérébral et le module tuteur de quelques nouvelles stratégies neuropédagogiques efficaces. L’intégration de NORA à un STI donne naissance à une nouvelle génération de systèmes tutoriels : les STI Cérébro-sensibles (ou STICS) destinés à aider un plus grand nombre d’apprenants à interagir avec l’ordinateur pour apprendre à gérer leurs émotions, maintenir la concentration et maximiser les conditions favorable à l’apprentissage.

Matrix based Cryptographic Procedure for Efficient Image Encryption

In this paper we propose a cryptographic transformation based on matrix manipulations for image encryption. Substitution and diffusion operations, based on the matrix, facilitate fast conversion of plaintext and images into ciphertext and cipher images. The paper describes the encryption algorithm, discusses the simulation results and compares with results obtained from Advanced Encryption Standard (AES). It is shown that the proposed algorithm is capable of encrypting images eight times faster than AES.

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems

Graphical simulators for AUV development

A long development time is needed from the design to the implementation of an AUV. During the first steps, simulation plays an important role, since it allows for the development of preliminary versions of the control system to be integrated. Once the robot is ready, the control systems are implemented, tuned and tested. The use of a real-time simulator can help closing the gap between off-line simulation and real testing using the already implemented robot. When properly interfaced with the robot hardware, a real-time graphical simulation with a "hardware in the loop" configuration, can allow for the testing of the implemented control system running in the actual robot hardware. Hence, the development time is drastically reduced. These paper overviews the field of graphical simulators used for AUV development proposing a classification. It also presents NEPTUNE, a multi-vehicle, real-time, graphical simulator based on OpenGL that allows hardware in the loop simulations

Control de glicèmia en pacients crítics mitjançant CGMS

L’estudi que es realitza en aquest projecte/treball final de carrera queda englobat dins del grup de recerca MICE (Modal Intervals Control and Engeneering), el qual realitza investigacions entorn al control de glucèmia. Aquest grup de recerca vinculat a la Universitat de Girona col•labora amb l’Hospital Universitari Dr. Josep Trueta de Girona. La temàtica principal tractarà de realitzar el control de glucèmia en pacients crítics, que es troben ingressats en la unitat de cures intensives de qualsevol hospital. Com a conseqüència d’aquesta problemàtica, s’ha implementat en un entorn virtual, un pacient el qual simula la situació d’un pacient real en la unitat de cures intensives. El model emprat per a la obtenció del model de pacient virtual és el desenvolupat per Chase et al. (2005), el qual mitjançant variables com l’alimentació enteral i la sensibilitat insulínica, es podien realitzar assajos reals per a validar protocols de control ‘in silico’ per posteriorment realitzar assajos amb població real

Modelling the Human Values Scale from Consumers Transactional Data Bases

The main objective of this paper aims at developing a methodology that takes into account the human factor extracted from the data base used by the recommender systems, and which allow to resolve the specific problems of prediction and recommendation. In this work, we propose to extract the user's human values scale from the data base of the users, to improve their suitability in open environments, such as the recommender systems. For this purpose, the methodology is applied with the data of the user after interacting with the system. The methodology is exemplified with a case study

Identification and Semiactive Control of Smart Structures Equipped with Magnetorheological Actuators

This paper deals with the problem of identification and semiactive control of smart structures subject to unknown external disturbances such as earthquake, wind, etc. The experimental setup used is a 6-story test structure equipped with shear-mode semiactive magnetorheological actuators being installed in WUSCEEL. The experimental results obtained have verified the effectiveness of the proposed control algorithms

Embedding objects into Matlab/Simulink for process supervision

This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

ISMAEL : un agente BDI como cerebro de una plataforma de tele-educación

Resumen tomado del autor

WAIS seminar: Linked Cultural Media

Wednesday 9th April 2014 Speaker(s): Guus Schreiber Time: 09/04/2014 11:00-11:50 Location: B32/3077 File size: 546Mb Abstract In this talk I will discuss linked data for museums, archives and libraries. This area is known for its knowledge-rich and heterogeneous data landscape. The objects in this field range from old manuscripts to recent TV programs. Challenges in this field include common metadata schema's, inter-linking of the omnipresent vocabularies, cross-collection search strategies, user-generated annotations and object-centric versus event-centric views of data. This work can be seen as part of the rapidly evolving field of digital humanities. Speaker Biography Guus Schreiber Guus is a professor of Intelligent Information Systems at the Department of Computer Science at VU University Amsterdam. Guus’ research interests are mainly in knowledge and ontology engineering with a special interest for applications in the field of cultural heritage. He was one of the key developers of the CommonKADS methodology. Guus acts as chair of W3C groups for Semantic Web standards such as RDF, OWL, SKOS and REFa. His research group is involved in a wide range of national and international research projects. He is now project coordinator of the EU Integrated project No Tube concerned with integration of Web and TV data with the help of semantics and was previously Scientific Director of the EU Network of Excellence “Knowledge Web”.