11,332 research outputs found
A minimalistic approach for fast computation of geodesic distances on triangular meshes
The computation of geodesic distances is an important research topic in
Geometry Processing and 3D Shape Analysis as it is a basic component of many
methods used in these areas. In this work, we present a minimalistic parallel
algorithm based on front propagation to compute approximate geodesic distances
on meshes. Our method is practical and simple to implement and does not require
any heavy pre-processing. The convergence of our algorithm depends on the
number of discrete level sets around the source points from which distance
information propagates. To appropriately implement our method on GPUs taking
into account memory coalescence problems, we take advantage of a graph
representation based on a breadth-first search traversal that works
harmoniously with our parallel front propagation approach. We report
experiments that show how our method scales with the size of the problem. We
compare the mean error and processing time obtained by our method with such
measures computed using other methods. Our method produces results in
competitive times with almost the same accuracy, especially for large meshes.
We also demonstrate its use for solving two classical geometry processing
problems: the regular sampling problem and the Voronoi tessellation on meshes.Comment: Preprint submitted to Computers & Graphic
Dictionary Learning-based Inpainting on Triangular Meshes
The problem of inpainting consists of filling missing or damaged regions in
images and videos in such a way that the filling pattern does not produce
artifacts that deviate from the original data. In addition to restoring the
missing data, the inpainting technique can also be used to remove undesired
objects. In this work, we address the problem of inpainting on surfaces through
a new method based on dictionary learning and sparse coding. Our method learns
the dictionary through the subdivision of the mesh into patches and rebuilds
the mesh via a method of reconstruction inspired by the Non-local Means method
on the computed sparse codes. One of the advantages of our method is that it is
capable of filling the missing regions and simultaneously removes noise and
enhances important features of the mesh. Moreover, the inpainting result is
globally coherent as the representation based on the dictionaries captures all
the geometric information in the transformed domain. We present two variations
of the method: a direct one, in which the model is reconstructed and restored
directly from the representation in the transformed domain and a second one,
adaptive, in which the missing regions are recreated iteratively through the
successive propagation of the sparse code computed in the hole boundaries,
which guides the local reconstructions. The second method produces better
results for large regions because the sparse codes of the patches are adapted
according to the sparse codes of the boundary patches. Finally, we present and
analyze experimental results that demonstrate the performance of our method
compared to the literature
Design and Experimental Validation of a Software-Defined Radio Access Network Testbed with Slicing Support
Network slicing is a fundamental feature of 5G systems to partition a single
network into a number of segregated logical networks, each optimized for a
particular type of service, or dedicated to a particular customer or
application. The realization of network slicing is particularly challenging in
the Radio Access Network (RAN) part, where multiple slices can be multiplexed
over the same radio channel and Radio Resource Management (RRM) functions shall
be used to split the cell radio resources and achieve the expected behaviour
per slice. In this context, this paper describes the key design and
implementation aspects of a Software-Defined RAN (SD-RAN) experimental testbed
with slicing support. The testbed has been designed consistently with the
slicing capabilities and related management framework established by 3GPP in
Release 15. The testbed is used to demonstrate the provisioning of RAN slices
(e.g. preparation, commissioning and activation phases) and the operation of
the implemented RRM functionality for slice-aware admission control and
scheduling
A Belief-Based Decision-Making Framework for Spectrum Selection in Cognitive Radio Networks
This paper presents a comprehensive cognitive management framework for spectrum selection in cognitive radio (CR) networks. The framework uses a belief vector concept as a means to predict the interference affecting the different spectrum blocks (SBs) and relies on a smart analysis of the scenario dynamicity to properly determine an adequate observation strategy to balance the tradeoff between achievable performance and measurement requirements. In this respect, the paper shows that the interference dynamics in a given SB can be properly characterized through the second highest eigenvalue of the interference state transition matrix. Therefore, this indicator is retained in the proposed framework as a relevant parameter to drive the selection of both the observation strategy and spectrum selection decision-making criterion. This paper evaluates the proposed framework to illustrate the capability to properly choose among a set of possible observation strategies under different scenario conditions. Furthermore, a comparison against other state-of-the-art solutions is presented
The use of sound intensity for characterisation of reflected energy in small rooms
The sound field in rooms of small dimensions used for music reproduction ischaracteristically different from that found in larger rooms for music performance such as auditoria. Key differences between small critical listening spaces and large auditoria are the vastly different ranges of energy decay, 100 ms for the former and up to 8 s for the latter, and its directional behaviour, typically non-diffuse for the former and approximating a diffuse field for the latter. Despite these substantial differences, most of the metrics developed to describe the sound field in large spaces are evoked to quantify the performance of small rooms. This project focuses on developing measurement methods to characterise temporal and spatial qualities of sound in small rooms. A number of methods based on currently available acoustic probes have been developed. The implementation requisites and accuracy for each method has been quantified. Factors such as direction, time of arrival and strength of reflections have been extracted using signal analysis techniques based on the active instantaneous intensity and short-time Fourier transform. These factors are subsequently mapped to allow a description of their evolution through the energy decay in the room for a given measurement location. The best performing system, based on the use of one-dimensional p-p intensity probe mounted in a custom cradle, achieves a minimum overall mean error of 0.226 degrees and 2.971 degrees for the direct sound and first reflection respectively, which is near or below the measured human minimum audible angle (MAA). The method developed has direct applications in the quantification of small room acoustic sound fields for critical listeningpurposes
Solving Large Scale Instances of the Distribution Design Problem Using Data Mining
In this paper we approach the solution of large instances of the distribution design problem. The traditional approaches do not consider that the instance size can significantly reduce the efficiency of the solution process. We propose a new approach that includes compression methods to transform the original instance into a new one using data mining techniques. The goal of the transformation is to condense the operation access pattern of the original instance to reduce the amount of resources needed to solve the original instance, without significantly reducing the quality of its solution. In order to validate the approach, we tested it proposing two instance compression methods on a new model of the replicated version of the distribution design problem that incorporates generalized database objects. The experimental results show that our approach permits to reduce the computational resources needed for solving large instances by at least 65%, without significantly reducing the quality of its solution. Given the encouraging results, at the moment we are working on the design and implementation of efficient instance compression methods using other data mining techniques
Is It Feasible to Use CMV-Specific T-Cell Adoptive Transfer as Treatment Against Infection in SOT Recipients?
During the last decade, many studies have demonstrated the role of CMV specific T-cell immune response on controlling CMV replication and dissemination. In fact, it is well established that transplanted patients lacking CMV-specific T-cell immunity have an increased occurrence of CMV replication episodes and CMV-related complications. In this context, the use of adoptive transfer of CMV-specific T-cells has been widely investigated and applied to Hematopoietic Stem Cell Transplant patients and may be useful as a therapeutic alternative, to reconstitute the CMV specific T-cell response and to control CMV viremia in patients receiving a transplantation. However, only few authors have explored the use of T-cell adoptive transfer in SOT recipients. We propose a novel review in which we provide an overview of the impact of using CMV-specific T-cell adoptive transfer on the control of CMV infection in SOT recipients, the different approaches to stimulate, isolate and expand CMV-specific T-cells developed over the years and a discussion of the possible use of CMV adoptive cellular therapy in this SOT population. Given the timeliness and importance of this topic, we believe that such an analysis will provide important insights into CMV infection and its treatment/prevention.This study was supported by the Spanish Ministry of Science, Innovation and University, Instituto de Salud Carlos III Grant/Award Numbers: PI17CIII-00014 (MPY110/18); DTS18CIII/00006 (MPY127/19); PI20-009 (MPY303/20). This work was supported by Plan Nacional de I + D+i 2013‐2016 and Instituto de Salud Carlos III, Subdirección General de Redes y Centros de Investigación Cooperativa, Ministry of Science, Innovation and University, Spanish Network for Research in Infectious Diseases (REIPI RD16/0016/0009), co-financed by European Development Regional Fund ‘A way to achieve Europe’. EG-R is supported by the Sara Borrell Program (CD18CIII/00007), Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades. FM is supported by the PFIS Program (F18III/00013), Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades. MN is supported by the FPU program (FPU19/05927), Ministerio de Ciencia, Innovación y Universidades.S
An X-ray study of the SNR G344.7-0.1 and the central object CXOU J170357.8-414302
Aims. We report results of an X-ray study of the supernova remnant (SNR)
G344.7-0.1 and the point-like X-ray source located at the geometrical center of
the SNR radio structure. Methods. The morphology and spectral properties of the
remnant and the central X-ray point-like source were studied using data from
the XMM-Newton and Chandra satellites. Archival radio data and infrared Spitzer
observations at 8 and 24 m were used to compare and study its multi-band
properties at different wavelengths. Results. The XMM-Newton and Chandra
observations reveal that the overall X-ray emission of G344.7-0.1 is extended
and correlates very well with regions of bright radio and infrared emission.
The X-ray spectrum is dominated by prominent atomic emission lines. These
characteristics suggest that the X-ray emission originated in a thin thermal
plasma, whose radiation is represented well by a plane-parallel shock plasma
model (PSHOCK). Our study favors the scenario in which G344.7-0.1 is a 6 x 10^3
year old SNR expanding in a medium with a high density gradient and is most
likely encountering a molecular cloud on the western side. In addition, we
report the discovery of a soft point-like X-ray source located at the
geometrical center of the radio SNR structure. The object presents some
characteristics of the so-called compact central objects (CCO). However, its
neutral hydrogen absorption column (N_{H}) is inconsistent with that of the
SNR. Coincident with the position of the source, we found infrared and optical
objects with typical early-K star characteristics. The X-ray source may be a
foreground star or the CCO associated with the SNR. If this latter possibility
were confirmed, the point-like source would be the farthest CCO detected so far
and the eighth member of the new population of isolated and weakly magnetized
neutron stars.Comment: 9 pages, 8 figures, accepted for publication in Astronomy and
Astrophysics. Higher resolution figures can be seen on A&
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