The Strategic Adaptation of Party Organizations to New Information and Communication Technologies : A Study of Catalan and Spanish Parties

Aquest document se centra en els casos dels dos principals partits espanyols (PP i PSOE) i catalans (PSC i CDC) en el període immediatament després de les eleccions generals espanyoles de maig de 2008, quan aquests celebraren els seus congressos. En general, es poden distingir tres tipus d'actors: en primer lloc, els ciberactivistes que tracten d'obtenir el reconeixement formal de la seva activitat en els seus partits. Així com, els líders del partit que poden intentar promoure la presència del partit en el ciberespai, però que també poden romandre indecisos perquè no és clar l'impacte electoral a la xarxa del ciberactivisme. Finalment, alguns militants tradicionals (off-line) solen ser reticents al reconeixement del ciberactivisme perquè amenaça les recompenses previstes dins del partit. Aquest article mostra com els nostres partits varen respondre al desafiament del ciberactivisme i arriba a la conclusió que la seva situació electoral, mediada per la seva ideologia, estructura organitzativa i el tipus de militància, poden ajudar-nos a comprendre el grau diferent d'institucionalització en l'organització del partit.

Testing Delivery Systems in Transnational virtual learning: the vocational management training for the european tourism industry (VocMat) case study

This article discusses the lessons learned from developing and delivering the Vocational Management Training for the European Tourism Industry (VocMat) online training programme, which was aimed at providing flexible, online distance learning for the European tourism industry. The programme was designed to address managers ‘need for flexible, senior management level training which they could access at a time and place which fitted in with their working and non-work commitments. The authors present two main approaches to using the Virtual Learning Environment, the feedback from the participants, and the implications of online Technology in extending tourism training opportunities

Using problem-based learning for introducing producer theory and market structure in intermediate microeconomics

This paper shows how instructors can use the problem‐based learning method to introduce producer theory and market structure in intermediate microeconomics courses. The paper proposes a framework where different decision problems are presented to students, who are asked to imagine that they are the managers of a firm who need to solve a problem in a particular business setting. In this setting, the instructors’ role isto provide both guidance to facilitate student learning and content knowledge on a just‐in‐time basis

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

Efficient learning of reactive robot behaviors with a Neural-Q_learning approach

The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an underwater robot in a target following task. Real experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed

Semi-online neural-Q_leaming for real-time robot learning

Reinforcement learning (RL) is a very suitable technique for robot learning, as it can learn in unknown environments and in real-time computation. The main difficulties in adapting classic RL algorithms to robotic systems are the generalization problem and the correct observation of the Markovian state. This paper attempts to solve the generalization problem by proposing the semi-online neural-Q_learning algorithm (SONQL). The algorithm uses the classic Q_learning technique with two modifications. First, a neural network (NN) approximates the Q_function allowing the use of continuous states and actions. Second, a database of the most representative learning samples accelerates and stabilizes the convergence. The term semi-online is referred to the fact that the algorithm uses the current but also past learning samples. However, the algorithm is able to learn in real-time while the robot is interacting with the environment. The paper shows simulated results with the "mountain-car" benchmark and, also, real results with an underwater robot in a target following behavior

A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Autonomous underwater vehicle control using reinforcement learning policy search methods

Autonomous underwater vehicles (AUV) represent a challenging control problem with complex, noisy, dynamics. Nowadays, not only the continuous scientific advances in underwater robotics but the increasing number of subsea missions and its complexity ask for an automatization of submarine processes. This paper proposes a high-level control system for solving the action selection problem of an autonomous robot. The system is characterized by the use of reinforcement learning direct policy search methods (RLDPS) for learning the internal state/action mapping of some behaviors. We demonstrate its feasibility with simulated experiments using the model of our underwater robot URIS in a target following task

Towards Direct Policy Search Reinforcement Learning for Robot Control

This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task

Adaptive intelligent agent approach to guide the web navigation on the PLAN-G distance learning platform

Hypermedia systems based on the Web for open distance education are becoming increasinglypopular as tools for user-driven access learning information. Adaptive hypermedia is a new direction in research within the area of user-adaptive systems, to increase its functionality by making it personalized [Eklu 961. This paper sketches a general agents architecture to include navigationaladaptability and user-friendly processes which would guide and accompany the student during hislher learning on the PLAN-G hypermedia system (New Generation Telematics Platform to Support Open and Distance Learning), with the aid of computer networks and specifically WWW technology [Marz 98-1] [Marz 98-2]. The PLAN-G actual prototype is successfully used with some informatics courses (the current version has no agents yet). The propased multi-agent system, contains two different types of adaptive autonomous software agents: Personal Digital Agents {Interface), to interacl directly with the student when necessary; and Information Agents (Intermediaries), to filtrate and discover information to learn and to adapt navigation space to a specific student

A teaching/learning support tool for introductory programming courses

In This work we present a Web-based tool developed with the aim of reinforcing teaching and learning of introductory programming courses. This tool provides support for teaching and learning. From the teacher's perspective the system introduces important gains with respect to the classical teaching methodology. It reinforces lecture and laboratory sessions, makes it possible to give personalized attention to the student, assesses the degree of participation of the students and most importantly, performs a continuous assessment of the student's progress. From the student's perspective it provides a learning framework, consisting in a help environment and a correction environment, which facilitates their personal work. With this tool students are more motivated to do programming

Innovation typology in tourism

Innovation is a research topic with a broad tradition. However, learning processes,from which innovations emerge, and the dynamics of change and development havetraditionally been studied in relation with the manufacturing sector. Moreover, theobjects of study have been usually process and tangible product innovations. Althoughrecently researchers have focused their attention in other sectors, more research onservice innovation should be carried out. Furthermore, regarding innovation intourism, there is a need to adapt generic theories to the tourism sector and tocontribute with new ideas.In order to find out, which are the origins of innovation processes, it is necessary tolook into two fundamental subjects that are inherent to innovation, which are learningand interaction. Both are closely related. The first appears to be an intrinsic conditionof individuals. Moreover, it can also be identified in organizations. Thus, learning allowsindividuals as well as organizations to develop. However, learning and development isnot possible without taking the environment into account. Hence, it is necessary thatinteractions take place between individuals, groups of individuals, organizations, etc.Furthermore, the concept of interaction implies the transfer of knowledge, which isthe basis for innovations.The purposes of this master thesis are to study in detail several of these topics and to develop a conceptual framework for the research on innovation in tourism

The interactional space in CLIL (Content and Language Integrated Learning) and EFL (English as a Foreign Language) classrooms

Aquest estudi pretén investigar els intercanvis verbals mestre/a – aprenent(s) en dos contextos d'instrucció diferents: classes amb un enfocament AICLE (Aprenentatge Integrat de Continguts Curriculars i Llengua Estrangera) on s’aprenen continguts no lingüístics a través de l’anglès, per una banda, i classes 'tradicionals' d'anglès com a llengua estrangera, on l’anglès és alhora objecte d’estudi i vehicle de comunicació, per una altra banda. Més concretament, les preguntes que formula el/la mestre/a, la producció oral dels aprenents i el 'feedback' del/de la mestre/a en els episodis d’atenció a la forma s’han estudiat a la llum de les principals teories provinents del camp de l’Adquisició de Segones Llengües (SLA) per tal de demostrar el seu paper en l’aprenentatge de l’anglès. El corpus de dades prové de l’enregistrament de 7 sessions AICLE i d'11 sessions EFL enregistrades en format àudio i vídeo en dos centres públics d’Educació Primària (EP) de Catalunya. A cadascuna de les escoles, el/la mateix/a mestre/a és l’encarregat/da dels dos tipus d’instrucció amb el mateix grup d’aprenents (10-11 anys d’edat), fet que permet eliminar variables individuals com l'aptitud dels aprenents o l'estil del/de la mestre/a.Els resultats mostren un cert nombre de similituds discursives entre AICLE i EFL donat que ambdós enfocaments tenen lloc en el context-classe amb unes característiques ben definides. Tal com apunta la recerca realitzada en aquest camp, la instrucció AICLE reuneix un seguit de condicions idònies per un major desenvolupament dels nivells de llengua anglesa més enllà de les classes ‘tradicionals’ d’anglès. Malgrat això, aquest estudi sembla indicar que el potencial d'AICLE pel que fa a facilitar una exposició rica a l’anglès i una producció oral significativa no s’explota degudament. En aquest sentit, els resultats d’aquest estudi poden contribuir a la formació dels futurs professors d'AICLE si es busca l’assoliment d’una complementarietat d’ambdós contextos amb l’objectiu últim de millorar els nivells de domini de la llengua anglesa.

Association between HIV status and HIV knowledge in the population attending Non-Governmental Organizations to perform the rapid HIV test in Catalonia

Human Immunodeficiency Virus continues to be a pandemic. Spain is one of the European countries with the highest incidence of HIV. Within Catalonia, Spain many projects have been implemented with the intention of improving HIV knowledge and lowering the incidence. HIV knowledge is also known to have a positive effect on lowering stigma and discrimination of the people living with HIV. However, few studies study the distribution of HIV knowledge and its association to HIV status, age, sex, geographical zone of origin and level of education within the same study. Objectives: To identify if HIV knowledge is associated with HIV status, age, sex, geographical zone of origin and level of education. Method: Quantitative, cross-sectional, centre-based study comprising of people receiving an HIV test in Catalonia, Spain. Data will be collected from the 11 HIV Non-Governmental Organisations in Catalonia, Spain. The Brief HIV Knowledge Scale will be used to assess HIV knowledge; information from the HIV test session will be used to assess HIV status, age, sex, geographic zone of origin and level of education. The association between HIV knowledge and the afore mentioned variables will then be calculated.