9,161 research outputs found

    Compact union of disjoint boxes: An efficient decomposition model for binary volumes

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    This paper presents in detail the CompactUnion of Disjoint Boxes (CUDB), a decomposition modelfor binary volumes that has been recently but brieflyintroduced. This model is an improved version of aprevious model called Ordered Union of Disjoint Boxes(OUDB). We show here, several desirable features thatthis model has versus OUDB, such as less unitary basicelements (boxes) and thus, a better efficiency in someneighborhood operations. We present algorithms forconversion to and from other models, and for basiccomputations as area (2D) or volume (3D). We alsopresent an efficient algorithm for connected-componentlabeling (CCL) that does not follow the classical two-passstrategy. Finally we present an algorithm for collision (oradjacency) detection in static environments. We test theefficiency of CUDB versus existing models with severaldatasets.Peer ReviewedPostprint (published version

    Estado del arte sobre Frameworks de infraestructura para Big Data

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    En la actualidad, el análisis Big Data se ha convertido en un gran reto para las organizaciones educativas, gubernamentales y comerciales, esto debido a la gran cantidad de datos procesados, por lo tanto resulta muy difícil llevar a cabo los diferentes procesos de análisis con herramientas de bases de datos y analíticas convencionales. Las tendencias Big Data traen consigo una gran cantidad de herramientas y aplicaciones que han sido desarrolladas específicamente para el apoyo al crecimiento de dicha tecnología para el análisis de datos, algunas de éstas trabajan en conjunto en soluciones de arquitecturas ya implementadas en las que se fundamenta gran parte de este trabajo monográfico, sintetizando la información necesaria para generar una propuesta de una arquitectura Big Data. Este trabajo pretende mostrar los componentes necesarios de infraestructura para brindar soporte al análisis Big Data basados en soluciones implementadas por los proveedores más conocidos, tomando como referencia modelos, diagramas y herramientas de software, enfocadas a los distintos despliegues que se puedan generar con base a unos requerimientos específicos, obteniendo como resultado una solución para una arquitectura Big Data utilizando las características de los escenarios propuestos en este trabajo

    Facial Geometry Identification through Fuzzy Patterns with RGBD Sensor

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    Automatic human facial recognition is an important and complicated task; it is necessary to design algorithms capable of recognizing the constant patterns in the face and to use computing resources efficiently. In this paper we present a novel algorithm to recognize the human face in real time; the systems input is the depth and color data from the Microsoft KinectTM device. The algorithm recognizes patterns/shapes on the point cloud topography. The template of the face is based in facial geometry; the forensic theory classifies the human face with respect to constant patterns: cephalometric points, lines, and areas of the face. The topography, relative position, and symmetry are directly related to the craniometric points. The similarity between a point cloud cluster and a pattern description is measured by a fuzzy pattern theory algorithm. The face identification is composed by two phases: the first phase calculates the face pattern hypothesis of the facial points, configures each point shape, the related location in the areas, and lines of the face. Then, in the second phase, the algorithm performs a search on these face point configurations

    A bibliometric overview of University-business collaboration between 1980 and 2016

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    Bibliometrics is a research field that analyses bibliographic material from a quantitative point of view. Aiming at providing a comprehensive overview, this study scrutinises the academic literature in university business collaboration and technology transfer research for the period post the Bayh-Dole Act (1980-2016). The study employs the Web of Science as the main database from where information is collected. Bibliometric indicators such as number of publications, citations, productivity, and the H-index are used to analyse the results. The main findings are displayed in the form of tables and are further discussed. The focus is on the identification of the most relevant journals in this area, the most cited papers, most prolific authors, leading institutions, and countries. The results show that the USA, England, Spain, Italy, and the Netherlands are highly active in this area. Scientific production tends to fall within the research areas of business and economics, engineering or public administration, and is mainly published in journals such as Research Policy, Technovation and Journal of Technology Transfer.Peer ReviewedPostprint (published version

    Research on nonlinear and quantum optics at the photonics and quantum information group of the University of Valladolid

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    We outline the main research lines in Nonlinear and Quantum Optics of the Group of Photonics and Quantum Information at the University of Valladolid. These works focus on Optical Solitons, Quantum Information using Photonic Technologies and the development of new materials for Nonlinar Optics. The investigations on optical solitons cover both temporal solitons in dispersion managed fiber links and nonparaxial spatial solitons as described by the Nonlinear Helmholtz Equation. Within the Quantum Information research lines of the group, the studies address new photonic schemes for quantum computation and the multiplexing of quantum data. The investigations of the group are, to a large extent, based on intensive and parallel computations. Some associated numerical techniques for the development of the activities described are briefly sketched

    Solving constrained optimization using a T-Cell artificial immune system

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    In this paper, we present a novel model of an artificial immune system (AIS), based on the process that suffers the T-Cell. The proposed model is used for solving constrained (numerical) optimization problems. The model operates on three populations: Virgins, Effectors and Memory. Each of them has a different role. Also, the model dynamically adapts the tolerance factor in order to improve the exploration capabilities of the algorithm. We also develop a new mutation operator which incorporates knowledge of the problem. We validate our proposed approach with a set of test functions taken from the specialized literature and we compare our results with respect to Stochastic Ranking (which is an approach representative of the state-of-the-art in the area) and with respect to an AIS previously proposed.En este trabajo, se presenta un nuevo modelo de Sistema Inmune Artificial (SIA), basado en el proceso que sufren las células T. El modelo propuesto se usa para resolver problemas de optimización (numéricos) restringidos. El modelo trabaja sobre tres poblaciones: Vírgenes, Efectoras y de Memoria. Cada una de ellas tiene un rol diferente. Además, el modelo adapta dinamicamente el factor de tolerancia para mejorar las capacidades de exploración del algoritmo. Se desarrolló un nuevo operador de mutación el cual incorpora conocimiento del problema. El modelo fue validado con un conjunto de funciones de prueba tomado de la literatura especializada y se compararon los resultados con respecto a Stochastic Ranking (el cual es un enfoque representativo del estado del arte en el área) y con respecto a un SIA propuesto previamente.VIII Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

    Variable neighborhood search for solving the DNA fragment assembly problem

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    The fragment assembly problem consists in the building of the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project, since the accuracy of the rest of the phases depends of the result of this stage. In addition, real instances are very large and therefore, the efficiency is also a very important issue in the design of fragment assemblers. In this paper, we propose two Variable Neighborhood Search variants for solving the DNA fragment assembly problem. These algorithms are specifically adapted for the problem being the difference between them the optimization orientation (fitness function). One of them maximizes the Parsons’s fitness function (which only considers the overlapping among the fragments) and the other estimates the variation in the number of contigs during a local search movement, in order to minimize the number of contigs. The results show that doesn’t exist a direct relation between these functions (even in several cases opposite values are generated) although for the tested instances, both variants allow to find similar and very good results but the second option reduces significatively the consumed-time.VIII Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

    FPGA-Based Digital filters using Bit-Serial arithmetic

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    This paper presents an efficient method for implementation of digital filters targeted FPGA architectures. The traditional approach is based on application of general purpose multipliers. However, multipliers implemented in FPGA architectures do not allow to construct economic Digital Filters. For this reason, multipliers are replaced by Lookup Tables and Adder-Substractor, which use Bit-Serial Arithmetic. Lookup Tables can be of considerable size in high order filters, thus interconnection techniques will be used to construct high order filters from a set of low order filters. The paper presents several examples confirming that these techniques allow a reduction in logic cells utilization of filters implementation based on Bit-Serial Arithmetic concept.II Workshop de Arquitecturas, Redes y Sistemas OperativosRed de Universidades con Carreras en Informática (RedUNCI

    FPGA-Based Digital filters using Bit-Serial arithmetic

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    This paper presents an efficient method for implementation of digital filters targeted FPGA architectures. The traditional approach is based on application of general purpose multipliers. However, multipliers implemented in FPGA architectures do not allow to construct economic Digital Filters. For this reason, multipliers are replaced by Lookup Tables and Adder-Substractor, which use Bit-Serial Arithmetic. Lookup Tables can be of considerable size in high order filters, thus interconnection techniques will be used to construct high order filters from a set of low order filters. The paper presents several examples confirming that these techniques allow a reduction in logic cells utilization of filters implementation based on Bit-Serial Arithmetic concept.II Workshop de Arquitecturas, Redes y Sistemas OperativosRed de Universidades con Carreras en Informática (RedUNCI

    Greedy seeding procedure for GAs solving a strip packing problem

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    In this paper, the two-dimensional strip packing problem with 3-stage level patterns is tackled using genetic algorithms (GAs). We evaluate the usefulness of a greedy seeding procedure for creating the initial population, incorporating problem knowledge. This is motivated by the expectation that the seeding will speed up the GA by starting the search in promising regions of the search space. An analysis of the impact of the seeded initial population is offered, together with a complete study of the influence of these modifications on the genetic search. The results show that the use of an appropriate seeding of the initial population outperforms existing GA approaches on all the used problem instances, for all the metrics used, and in fact it represents the new state of the art for this problem.Red de Universidades con Carreras en Informática (RedUNCI
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