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

OpenNebula y Hadoop : Cloud Computing con herramientas Open Source

El presente proyecto consiste en una introducción al "cloud computing" y un estudio en profundidad de las herramientas OpenNebula, dentro del modelo IaaS (Infraestructure as a Service), y Hadoop, dentro del modelo PaaS (Platform as a Service). El trabajo también incluye la instalación, integración, configuración y puesta en marcha de una plataforma "cloud computing" utilizando OpenNebula y Hadoop con el objetivo de aplicar los conceptos teóricos en una solución real dentro de un entorno de laboratorio que puede ser extrapolable a una instalación real.

An anonymous reputation mechanism for cloud computing networks using volunteer resources

One of the major problems when using non-dedicated volunteer resources in adistributed network is the high volatility of these hosts since they can go offlineor become unavailable at any time without control. Furthermore, the use ofvolunteer resources implies some security issues due to the fact that they aregenerally anonymous entities which we know nothing about. So, how to trustin someone we do not know?.Over the last years an important number of reputation-based trust solutionshave been designed to evaluate the participants' behavior in a system.However, most of these solutions are addressed to P2P and ad-hoc mobilenetworks that may not fit well with other kinds of distributed systems thatcould take advantage of volunteer resources as recent cloud computinginfrastructures.In this paper we propose a first approach to design an anonymous reputationmechanism for CoDeS [1], a middleware for building fogs where deployingservices using volunteer resources. The participants are reputation clients(RC), a reputation authority (RA) and a certification authority (CA). Users needa valid public key certificate from the CA to register to the RA and obtain thedata needed to participate into the system, as now an opaque identifier thatwe call here pseudonym and an initial reputation value that users provide toother users when interacting together. The mechanism prevents not only themanipulation of the provided reputation values but also any disclosure of theusers' identities to any other users or authorities so the anonymity isguaranteed.

Preventive medicine for epidemic outbreaks and risky behavior through mobile devices and ubiquitous computing

In this work, we have developed the first free software for mobile devices with the Android operating system that can preventively mitigate the number of contagions of sexually transmitted infections (STI), associated with risk behavior. This software runs in two modes. The normal mode allows the user to see the alerts and nearby health centers. The second mode enables the service to work in the background. This software reports the health risks, as well as the location of different test centers.

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system

Evaluación de la disponibilidad de los servicios desplegados sobre Volunteer Computing

Implementación y evaluación de un algoritmo híbrido que selecciona el conjunto de nodos de menor coste que permite desplegar un servicio, con una disponibilidad determinada, en un entorno de computación voluntaria.

Tecnologies de cloud computing Openstack/StackOps

El propòsit d'aquest TFC és investigar i fer una instal·lació des de zero d'un model de negoci basat en l'allotjament web fent servir tecnologies de Cloud Computing. El software open-source que es farà servir per aquesta finalitat serà Openstack el qual es basa en un model de servei com infraestructura (IaaS). La nostra finalitat és poder implementar el model IaaS basat en Openstack. Per duu a terme aquest desplegament es farà servir dos hipervisors (KVM i VMware ESXi) per tal de testejar diferents sistemes d¿hipervisors treballant conjuntament.

A systematic and feasible method for computing nuclear contributions to electrical properties of polyatomic molecules

An analytic method to evaluate nuclear contributions to electrical properties of polyatomic molecules is presented. Such contributions control changes induced by an electric field on equilibrium geometry (nuclear relaxation contribution) and vibrational motion (vibrational contribution) of a molecular system. Expressions to compute the nuclear contributions have been derived from a power series expansion of the potential energy. These contributions to the electrical properties are given in terms of energy derivatives with respect to normal coordinates, electric field intensity or both. Only one calculation of such derivatives at the field-free equilibrium geometry is required. To show the useful efficiency of the analytical evaluation of electrical properties (the so-called AEEP method), results for calculations on water and pyridine at the SCF/TZ2P and the MP2/TZ2P levels of theory are reported. The results obtained are compared with previous theoretical calculations and with experimental values

Virtualización y cloud computing en la PYME

El presente documento introduce a las pequeñas y medianas empresas en el mundo de la virtualización y el cloud computing. Partiendo de la presentación de ambas tecnologías, se recorren las diferentes fases por las que atraviesa un proyecto tecnológico consistente en la instalación de una plataforma virtualizada que alberga los sistemas informáticos básicos en una PYME.

Critical thoughts on computing atom condensed Fukui functions

Different procedures to obtain atom condensed Fukui functions are described. It is shown how the resulting values may differ depending on the exact approach to atom condensed Fukui functions. The condensed Fukui function can be computed using either the fragment of molecular response approach or the response of molecular fragment approach. The two approaches are nonequivalent; only the latter approach corresponds in general with a population difference expression. The Mulliken approach does not depend on the approach taken but has some computational drawbacks. The different resulting expressions are tested for a wide set of molecules. In practice one must make seemingly arbitrary choices about how to compute condensed Fukui functions, which suggests questioning the role of these indicators in conceptual density-functional theory

Applying recommendations to aligncompetences, methodology and assessment in Telematics, Computing and Electronic Engineering courses

The alignment between competences, teaching-learning methodologies and assessment is a key element of the European Higher Education Area. This paper presents the efforts carried out by six Telematics, Computer Science and Electronic Engineering Education teachers towards achieving this alignment in their subjects. In a joint work with pedagogues, a set of recommended actions were identified. A selection of these actions were applied and evaluated in the six subjects. The cross-analysis of the results indicate that the actions allow students to better understand the methodologies and assessment planned for the subjects, facilitate (self-) regulation and increase students’ involvement in the subjects.

@neurIST infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services

The increasing volume of data describing humandisease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the@neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system’s architecture is generic enough that it could be adapted to the treatment of other diseases.Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers cliniciansthe tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medicalresearchers gain access to a critical mass of aneurysm related data due to the system’s ability to federate distributed informationsources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access andwork on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand forperforming computationally intensive simulations for treatment planning and research.

Computing infinite plans for LTL goals using a classical planner

Classical planning has been notably successful in synthesizing finite plans to achieve states where propositional goals hold. In the last few years, classical planning has also been extended to incorporate temporally extended goals, expressed in temporal logics such as LTL, to impose restrictions on the state sequences generated by finite plans. In this work, we take the next step and consider the computation of infinite plans for achieving arbitrary LTL goals. We show that infinite plans can also be obtained efficiently by calling a classical planner once over a classical planning encoding that represents and extends the composition of the planningdomain and the B¨uchi automaton representingthe goal. This compilation scheme has been implemented and a number of experiments are reported.

A new hybrid summarizer based on vector Space model, statistical physics and linguistics

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.