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Decentralized robust spectrum allocation for cognitive radio wireless mesh networks
No full textTrabajo publicado en Ad Hoc Networks, v. 36, part 1, 2016, pp. 1-20During the last decade we have seen an explosive growth in the deployment of wireless networks in unlicensed frequency bands, mainly driven by the great success of the IEEE 802.11 standard. In addition to its traditional last-hop usage, it has also been widely employed for Internet access infrastructure such as wireless mesh networks (WMNs). A problem that is envisioned in the near future is the spectrum scarcity, which could be a serious threat to cope with the ever increasing demand. Regulators are aware about this problem and they have already started to look for more available spectrum. One of the possibilities that has emerged is to allow secondary assignments in licensed bands, based on the recent cognitive radio networks (CRNs) paradigm. In this context, we focus our work in the analysis of optimum spectrum allocation mechanisms for a cognitive wireless multihop mesh network. We introduce a stochastic model to formulate the problem, considering primary users activity and a periodically scheduled assignment scheme. To solve the problem we propose a novel robust solution, for which we develop a decentralized algorithm implementation. Furthermore, we evaluate our proposal through extensive simulations, showing for instance its superiority compared with an expectation based approach
Opportunities for a more efficient use of the spectrum based in cognitive radio
No full textTrabajo publicado en IEEE Latin America Transactions, v. 14, no. 2, 2016Different studies about the use of radio spectrum have shown the existence of underutilized bands, like the ones destined to television broadcasting. This provides an interesting opportunity considering the exponential growth in wireless communications and applications, which results in an important demand for higher bandwidth to achieve an adequate performance. To operate in bands that are already licensed, it is necessary to ensure that this operation does not cause any interference to the primary user, and always gives priority to it. In this context the IEEE has been defining a standard with functionalities of Cognitive Radio that allows operation in licensed bands opportunistically, and without causing interference. From there comes the IEEE 802.22 standard, which has a set of features and procedures to measure, monitor and manage the radio spectrum, essential to ensure the protection of primary user s transmissions. Some pilot projects have demonstrated the potential of this standard to provide broadband services comparable to classical ADSL services,especially in remote or rural areas inaccessible to deploy fixed networks. One of the great challenges to install such systems commercially, is to achieve the permissions for the operation and to have a defined regulation for these systems, decisions that are in the hands of the telecommunications services regulators in each country. This paper presents an overview of these issues with the intention of promoting a more efficient use of the spectrum
Uplink wireless transmission overview in bi-directional VLC systems
No full textTrabajo presentado en International Conference on Electronics, Circuits and Systems (ICECS), Monte Carlo, Monaco, 11-14 dic. 2016.This paper introduces the concept of uplink wireless transmission technologies for visible light communication (VLC). An overview of the different uplink existing methods and its feasibility in various applications such us indoor positioning is presented. We also showed that, unlike existing technologies of wireless communication like, Bluetooth, WiFi and Zigbee, Wireless Power Transfer (WPT) can be not only used for uplink transmission but also provides energy for certain power hungry devices. Simulation results and analytical approximations show that around 450 kbps uplink throughput can be achieved in a system capable of delivering up to 1.3 mW to small indoor devices (94.6x56.8x3.65 mm)
Internet of things for a smart and ubiquitous ehealth system
No full textTrabajo aceptado en International Conference on Computational Intelligence and Communication Networks (CICN), Jabalpur, India, 2015,Connected data has always been considered as a primary source to knowledge. Internet of Things uses the virtue of connecting this data from different entities and creates a pool of knowledge for providing smart services to users, based on rigorous analysis and processing over the knowledge. The communication in this context scales to not only between machine to machine but also between a large number of heterogeneous entities and persons. This genius technology of Internet of Things holds paramount importance and application in healthcare technologies. Considering health technologies, a large number of devices generate huge amount of data related to a patient. Assimilating the data from heterogeneous sources and using it to generate intelligence is one of the primary tasks in a smart environment. In the context of eHealth, Internet of Things is of immense importance since connected data about patient would facilitate treatment with more efficiency and comprehensive knowledge. Virtually storing the patient data and making it ubiquitously accessible to concerned healthcare personnel would be the first step toward mutual knowledge sharing. Another important aspect of using this connected data is the design of an intelligent clinical decision support system which would assist the doctors in every possible way during the treatment phase. A model has been proposed with an inclusive approach of Internet of Things in eHealth scenario for a smart medical environment and providing ubiquitous services at its best. Several issues pertaining to the system has also been discussed accordingly. Nevertheless, the enormous spread of Internet of Things for efficient and intelligent healthcare services holds quite inevitable. Rather it adds to the foundation notion of ubiquitous services by making available to everyone and everywhere. The new age eHealth facilities are expected to enable end-to-end monitoring systems even at remote scenarios, helping medical services reach the unreached
Ecología de la comunidad de meiofauna de Bahía Collins, Isla Rey Jorge (Antártida): una zona costera afectada por retracción glaciar reciente
No full textLa península antártica ha mostrado una fuerte tendencia al calentamiento en los últimos años, y una acelerada retracción de sus glaciares, con consecuencias en el ambiente marino y las comunidades bentónicas. La meiofauna ha demostrado ser una herramienta útil para monitorear los efectos del cambio climático, además de cumplir un importante rol trófico y en los ciclos biogeoquímicos, sin embargo, actualmente el conocimiento sobre la meiofauna polar continúa siendo limitado. Este trabajo tuvo como objetivo explorar los taxones que integran la meiofauna antártica de la Bahía Collins (Isla Rey Jorge) y su relación con las propiedades biogeoquímicas del sedimento en áreas con distinta influencia glaciar. Para esto se extrajeron muestras de sedimento (draga van Veen) y meiofauna (minicorer) de 3 transectas: transecta 1 (estaciones 1A-1C) y 2 (2A- 2C), a 2000 y 3000 metros respectivamente del frente marino del Glaciar Collins; y transecta 3 (3A-3D), frente a la cañada de deshielo cercana a la Base Artigas. Para poder caracterizar las estaciones de muestreo, se estudió la granulometría del sedimento, el contenido orgánico y las variables físico-químicas del agua de fondo. Se identificaron en total 58383 individuos agrupados en 32 taxones, siendo los grupos más abundantes los nematodos (81%) y los copépodos (7,1%). La comunidad de meiofauna varió entre transectas en respuesta a la influencia glaciar, siendo más diversa y uniforme en la transecta 2 que en las otras, donde el mayor contenido orgánico y la presencia de sedimento más homogéneo sugirieron un menor impacto del glaciar en el área. En contraste, el aporte por escorrentía superficial de la cañada propició una comunidad menos diversa y uniforme en la transecta 3, dominada por nematodos, lo que podría deberse a la gran resistencia a perturbaciones en el ambiente por parte de este grupo. Los análisis de varianza entre transectas registraron diferencias significativas en las abundancias de cladóceros, tardígrados, ostrácodos, loricíferos, gastrotricos, bivalvos, y aplacóforos, mostrando que los taxones “raros” o poco frecuentes son más susceptibles a variaciones ambientales. La presencia de grupos sensibles al estrés ambiental en la transecta 1 sugirió un menor impacto en la estructura de la comunidad en la zona cercana al glaciar, en comparación con el área afectada por el deshielo de la cañada. Las diferencias en las abundancias de los grupos respondieron principalmente a variaciones en el contenido orgánico (CHO, TOC%) y parámetros físico-químicos del agua (temperatura y profundidad), y en menor medida a la granulometría del sedimento (limos y arcillas%)
Programa de Metodología de Radioisótopos: Módulo Básico
No full textEl objetivo del curso es capacitar en el manejo y las posibilidades de aplicación de los radionucleidos. Está dirigido a estudiantes y profesionales de diferentes orientaciones. Es de fundamental importancia en la formación de quienes trabajan en laboratorios con radionucleidos, tanto en investigación como en aplicaciones médicas, veterinarias, industriales, etc. El curso consta de clases teóricas, teórico-prácticas y prácticas con participación activa de los estudiantes. El curso es de carácter intensivo con una carga horaria 3 hs. diarias. En el curso se pretende desarrollar la capacidad de análisis, síntesis y razonamiento, resolución de problemas, y la comprensión de las destrezas necesarias para el trabajo en el laboratorio de radiofarmacia. Durante el curso teórico se promoverá la adquisición de conocimientos basado en problemas, con énfasis en: modos de decaimiento, efecto biológico de las radiaciones, y protección radiológica. Así también se adquirirá conocimiento sobre normas de trabajo con fuentes abiertas y cerradas, y gestión de desechos
Programa de Ecuaciones en Derivadas Parciales
No full textSe pretende introducir al estudiante a las ecuaciones en derivadas parciales, abordando temas clásicos en el área
A bayesian hyperprior approach for joint image denoising and interpolation, with an application to HDR imaging
Get PDFPublicado en IEEE Transactions on Computational Imaging, v.3, no. 4, 2017Recently, impressive denoising results have been achieved by Bayesian approaches which assume Gaussian models for the image patches. This improvement in performance can be attributed to the use of per-patch models. Unfortunately such an approach is particularly unstable for most inverse problems beyond denoising. In this work, we propose the use of a hyperprior to model image patches, in order to stabilize the estimation procedure. There are two main advantages to the proposed restoration scheme: Firstly it is adapted to diagonal degradation matrices, and in particular to missing data problems (e.g. inpainting of missing pixels or zooming). Secondly it can deal with signal dependent noise models, particularly suited to digital cameras. As such, the scheme is especially adapted to computational photography. In order to illustrate this point, we provide an application to high dynamic range imaging from a single image taken with a modified sensor, which shows the effectiveness of the proposed schem
Similarity measure for cell membrane fusion proteins identification
Get PDFTrabajo presentado en Computer Vision, and Applications. CIARP 2016This work proposes a similarity measure between secondary structures of proteins capable of fusing cell membranes and its implementation in a classification system. For the evaluation of the metric we used secondary structures estimated from amino acid sequences of Class I and Class II viral fusogens (VFs), as well as VFs precursor proteins. We evaluated three different classifiers based on k-Nearest Neighbors, Support Vector Machines and One-Class Support Vector Machines in different configurations. This is a first approach to the similarity measure with satisfactory results. It is possible that this method could allow the identification of unknown membrane fusion proteins in other biological models than the proposed in this work. Keywords: Cell Membrane Fusion, Viral Fusogen, Similarity Measure, Support Vector Machines, One-Class Support Vector Machines, k-Nearest Neighbor
Deep video deblurring for hand-held cameras
Get PDFVersión de acceso abierto disponibilizada por Computer Vision FoundationMotion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on the alignment of nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task that requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-toend to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high frame rate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baseline