La telefonía móvil : el impacto social

El objetivo de este proyecto ha sido el de realizar un análisis del importante desarrollo que han sufrido las telecomunicaciones, haciendo un especial hincapié en la telefonía móvil y el impacto y repercusión que ha causado actualmente en nuestra sociedad. Para ello se hará un repaso evolutivo de las tecnologías de la información y las telecomunicaciones, y se establecerá una relación entre la gran difusión de éstas y su efecto sobre los usos, y cambios percibidos por los consumidores del nuevo siglo. Ciertamente la historia de la tecnología, nos enseña que la gente y las organizaciones acaban utilizándola para unos propósitos muy diferentes de aquellos que inicialmente fueron concebidas. Además cuanto más interactiva sea una tecnología, tanto más probable será que los usuarios se conviertan en productores o modificadores de la misma. Por tanto, la sociedad necesita resolver las incógnitas que pueda suscitar el rápido y continúo cambio de las comunicaciones. Este proyecto trata de ayudar a responder alguna de las cuestiones que actualmente se están planteando. ¿Son los teléfonos móviles una expresión de identidad, artilugios de moda, herramientas de la vida cotidiana, o todo lo anterior? ¿Existen nuevos modelos de comportamiento y conducta social? ¿La comunicación móvil está favoreciendo la aparición de una nueva cultura joven con un lenguaje propio basado en la comunicación textual y multimodal? ¿Tienen los teléfonos móviles efectos nocivos en la salud? La respuesta a estas preguntas afecta a nuestras vidas y también condiciona las políticas públicas y las estrategias de negocio, por eso requiere adquirir un conocimiento cimentado en la información, y la recopilación de datos de diversas fuentes, tanto de estadísticas provenientes de diferentes estudios e investigaciones, como de empresas consultoras, siempre basada en una perspectiva global. En conjunto, se espera dentro de los límites del conocimiento actual, contribuir a establecer las bases para el análisis y valoración de la relación existente entre comunicación, tecnología y sociedad en todo el mundo. Abstract The purpose of this project has been to analyse the significant development undergone by telecommunications, putting a special emphasis on mobile phones and the impact it has caused in society. We will go over the evolution of IT technologies and telecommunications as well as establish a relationship between its spread and effect of its uses and changes understood by the new century consumers. Technology history shows us that people and organizations use it for very different purposes from those originally thought. Furthermore, the more interactive technologies are, the more users will modify or produce it. Therefore, society needs to solve the mysteries of the quick and continuous change of communications. This project tries to help and answer some of the questions considered these days. Are mobile phones an expression of identity, fashionable devices, tools for everyday life or all at once? Are there any new models of performance and social behaviour? Is mobile communication favouring the existence of a new young culture with a typical language based on textual and multimodal communication? Are mobile phones bad for our health? The answer to these questions affects us all and conditions public politics and business strategies so it is required to get firm knowledge based on information. It is also important to compile data from various sources, from statistics of research and studies, based on a global perspective. As a whole, we hope to contribute to establish the bases for the future analysis and assessment of a fundamental trend that is redefining the relationship between communication, technology and society worldwide by transforming the wireless networks that make our lives.

PSO and neural networks: Optimal combination to solve non linear complex problems

Swarm colonies reproduce social habits. Working together in a group to reach a predefined goal is a social behaviour occurring in nature. Linear optimization problems have been approached by different techniques based on natural models. In particular, Particles Swarm optimization is a meta-heuristic search technique that has proven to be effective when dealing with complex optimization problems. This paper presents and develops a new method based on different penalties strategies to solve complex problems. It focuses on the training process of the neural networks, the constraints and the election of the parameters to ensure successful results and to avoid the most common obstacles when searching optimal solutions.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.