Open Personalization: Involving Third Parties in Improving the User Experience of Websites

Traditional software development captures the user needs during the requirement analysis. The Web makes this endeavour even harder due to the difficulty to determine who these users are. In an attempt to tackle the heterogeneity of the user base, Web Personalization techniques are proposed to guide the users’ experience. In addition, Open Innovation allows organisations to look beyond their internal resources to develop new products or improve existing processes. This thesis sits in between by introducing Open Personalization as a means to incorporate actors other than webmasters in the personalization of web applications. The aim is to provide the technological basis that builds up a trusty environment for webmasters and companion actors to collaborate, i.e. "an architecture of participation". Such architecture very much depends on these actors’ profile. This work tackles three profiles (i.e. software partners, hobby programmers and end users), and proposes three "architectures of participation" tuned for each profile. Each architecture rests on different technologies: a .NET annotation library based on Inversion of Control for software partners, a Modding Interface in JavaScript for hobby programmers, and finally, a domain specific language for end-users. Proof-of-concept implementations are available for the three cases while a quantitative evaluation is conducted for the domain specific language.

Colaboración fabricante-distribuidor en la cadena de suministro para la tecnología aplicada al punto de venta y la mejora de la experiencia de compra

A lo largo de este trabajo se lleva a cabo una investigación sobre la evolución de las relaciones comerciales entre fabricantes y distribuidores, con especial atención en la colaboración conjunta a la hora de comercializar los productos en el punto de venta. El empleo de nuevas herramientas tecnológicas en el establecimiento facilita el merchandising de presentación, ofreciendo ventajas competitivas para los agentes de la cadena de suministros y nuevas experiencias de compra para los consumidores. Una vez analizada la parte teórico-conceptual del trabajo se lleva a cabo el análisis de un caso práctico sobre los beneficios de la tecnología Radio Frequency Identification (RFID) implantada en la empresa Decathlon. Estos sistemas se han convertido en un aliado clave para la mejora de los procesos de negocio, mejorando la gestión de la compañía y la fidelización de los clientes.

Observational constraints on the unified dark matter and dark energy model based on the quark bag model

In this work we investigate if a small fraction of quarks and gluons, which escaped hadronization and survived as a uniformly spread perfect fluid, can play the role of both dark matter and dark energy. This fluid, as developed in [1], is characterized by two main parameters: beta, related to the amount of quarks and gluons which act as dark matter; and gamma, acting as the cosmological constant. We explore the feasibility of this model at cosmological scales using data from type Ia Supernovae (SNeIa), Long Gamma-Ray Bursts (LGRB) and direct observational Hubble data. We find that: (i) in general, beta cannot be constrained by SNeIa data nor by LGRB or H(z) data; (ii) gamma can be constrained quite well by all three data sets, contributing with approximate to 78% to the energy matter content; (iii) when a strong prior on (only) baryonic matter is assumed, the two parameters of the model are constrained successfully. (C) 2014 The Authors. Published by Elsevier B.V.

Generating cluster submodels from a multistage stochastic mixed integer optimization model using break stage

We present a scheme to generate clusters submodels with stage ordering from a (symmetric or a nonsymmetric one) multistage stochastic mixed integer optimization model using break stage. We consider a stochastic model in compact representation and MPS format with a known scenario tree. The cluster submodels are built by storing first the 0-1 the variables, stage by stage, and then the continuous ones, also stage by stage. A C++ experimental code has been implemented for reordering the stochastic model as well as the cluster decomposition after the relaxation of the non-anticipativiy constraints until the so-called breakstage. The computational experience shows better performance of the stage ordering in terms of elapsed time in a randomly generated testbed of multistage stochastic mixed integer problems.

ENEKuS – a key model for managing the transformation of the normalisation of the Basque language in the workplace

The aim of this study is to develop a reference model for intervention in the language processes applied to the transformation of language normalisation within organisations of a socio-economic nature. It is based on the case study of an experience carried out over10 years within a trades’ union confederation, and has pursued a strategy of a basically qualitative research carried out in three stages: 1) undertaking field work through application of action-research methodology, 2) reconstructing experiences following processes of systematisation and conceptualisation of the systematised data, applying methodologies for the Systematisation of Experiences and Grounded Theory, and 3) formulating a model for intervention, applying the Systems Approach methodology. Finally, we identified nine key ideas that make up the conceptual framework for the ENEKuS reference model, which is structured in nine ‘action points', each having an operating sub-model applicable in practice.

Cosmological constrains on fast transition Unified Dark Matter models

In this work we show the results obtained applying a Unified Dark Matter (UDM) model with a fast transition to a set of cosmological data. Two different functions to model the transition are tested, and the feasibility of both models is explored using CMB shift data from Planck [1], Galaxy Clustering data from [2] and [3], and Union2.1 SNe Ia [4]. These new models are also statistically compared with the ACDM and quiessence models using Bayes factor through evidence. Bayesian inference does not discard the UDM models in favor of ACDM.