How much can large-scale video-on-demand benefit from users' cooperation?

We propose an analytical framework to tightly characterize the scaling laws for the additional bandwidth that servers must supply to guarantee perfect service in peer-assisted Video-on-Demand systems, taking into account essential aspects such as peer churn, bandwidth heterogeneity, and Zipf-like video popularity. Our results reveal that the catalog size and the content popularity distribution have a huge effect on the system performance. We show that users' cooperation can effectively reduce the servers' burden for a wide range of system parameters, confirming to be an attractive solution to limit the costs incurred by content providers as the system scales to large populations of user

How much can large-scale Video-On-Demand benefit from users’ cooperation?

We propose an analytical framework to tightly characterize the scaling laws for the additional bandwidth that servers must supply to guarantee perfect service in peer-assisted Video-on-Demand systems, taking into account essential aspects such as peer churn, bandwidth heterogeneity, and Zipf-like video popularity. Our results reveal that the catalog size and the content popularity distribution have a huge effect on the system performance. We show that users' cooperation can effectively reduce the servers' burden for a wide range of system parameters, confirming to be an attractive solution to limit the costs incurred by content providers as the system scales to large populations of users

Development of a surgical stereo endoscopic image dataset for validating 3D stereo reconstruction algorithms

In the last decades, endoscopic stereo images have been exploited to retrieve tissue surface information of the surgical site using 3D reconstruction algorithms. The application of such algorithms in Computer Assisted Surgery (CAS) tools for Minimally Invasive Surgery (MIS) requires a robust validation process in order to guarantee reliability and safety. 3D reconstruction algorithms are commonly evaluated comparing their result with respect to a reference Ground Truth (GT). However, few datasets providing endoscopic images and GT are openly available. Considering the increasing necessity of surgical datasets, the aim of this work is the generation of an Endoscopic Abdominal Stereo (EndoAbS) dataset composed of stereo-images with associated GT for 3D stereo-reconstruction algorithm validation. To recreate the surgical scenario, a polyurethane surgical phantom abdomen was built. Images were captured with a stereo-endoscope, while for acquiring the GT a laser scanner (calibrated with respect to the stereoendoscope) was used. This dataset is openly available on-line for the benefit of the CAS community

The OLYMPUS Internal Hydrogen Target

An internal hydrogen target system was developed for the OLYMPUS experiment at DESY, in Hamburg, Germany. The target consisted of a long, thin-walled, tubular cell within an aluminum scattering chamber. Hydrogen entered at the center of the cell and exited through the ends, where it was removed from the beamline by a multistage pumping system. A cryogenic coldhead cooled the target cell to counteract heating from the beam and increase the density of hydrogen in the target. A fixed collimator protected the cell from synchrotron radiation and the beam halo. A series of wakefield suppressors reduced heating from beam wakefields. The target system was installed within the DORIS storage ring and was successfully operated during the course of the OLYMPUS experiment in 2012. Information on the design, fabrication, and performance of the target system is reported.Comment: 9 pages, 13 figure

Label-based Optimization of Dense Disparity Estimation for Robotic Single Incision Abdominal Surgery

Minimally invasive surgical techniques have led to novel approaches such as Single Incision Laparoscopic Surgery (SILS), which allows the reduction of post-operative infections and patient recovery time, improving surgical outcomes. However, the new techniques pose also new challenges to surgeons: during SILS, visualization of the surgical field is limited by the endoscope field of view, and the access to the target area is limited by the fact that instruments have to be inserted through a single port. In this context, intra-operative navigation and augmented reality based on pre-operative images have the potential to enhance SILS procedures by providing the information necessary to increase the intervention accuracy and safety. Problems arise when structures of interest change their pose or deform with respect to pre-operative planning, as usually happens in soft tissue abdominal surgery. This requires online estimation of the deformations to correct the pre-operative plan, which can be done, for example, through methods of depth estimation from stereo endoscopic images (3D reconstruction). The denser the reconstruction, the more accurate the deformation identification can be. This work presents an algorithm for 3D reconstruction of soft tissue, focusing on the refinement of the disparity map in order to obtain an accurate and dense point map. This algorithm is part of an assistive system for intra-operative guidance and safety supervision for robotic abdominal SILS . Results show that comparing our method with state-of-the-art CPU implementations, the percentage of valid pixel obtained with our method is 24% higher while providing comparable accuracy. Future research will focus on the development of a real-time implementation of the proposed algorithm, potentially based on a hybrid CPU-GPU processing framework

EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

none5siembargoed_20190801Penza, Veronica; Ciullo, Andrea S.; Moccia, Sara; Mattos, Leonardo S.; De Momi, ElenaPenza, Veronica; Ciullo, Andrea S.; Moccia, Sara; Mattos, Leonardo S.; De Momi, Elen

EndoAbS dataset: Endoscopic abdominal stereo image dataset for benchmarking 3D stereo reconstruction algorithms

Background: 3D reconstruction algorithms are of fundamental importance for augmented reality applications in computer-assisted surgery. However, few datasets of endoscopic stereo images with associated 3D surface references are currently openly available, preventing the proper validation of such algorithms. This work presents a new and rich dataset of endoscopic stereo images (EndoAbS dataset). Methods: The dataset includes (i) endoscopic stereo images of phantom abdominal organs, (ii) a 3D organ surface reference (RF) generated with a laser scanner and (iii) camera calibration parameters. A detailed description of the generation of the phantom and the camera–laser calibration method is also provided. Results: An estimation of the overall error in creation of the dataset is reported (camera–laser calibration error 0.43 mm) and the performance of a 3D reconstruction algorithm is evaluated using EndoAbS, resulting in an accuracy error in accordance with state-of-the-art results (<2 mm). Conclusions: The EndoAbS dataset contributes to an increase the number and variety of openly available datasets of surgical stereo images, including a highly accurate RF and different surgical conditions

The LHCspin project

The LHCspin project aims to bring both unpolarized and polarized physics at the LHC through the installation of a gaseous fixed target at the upstream end of the LHCb detector. The forward geometry of the LHCb spectrometer (2 < η < 5) is perfectly suited for the reconstruction of particles produced in fixed-target collisions. The fixed-target configuration, with center-of-mass energies ranging from √sNN = 72 GeV in collisions with Pb beams to √s = 115 GeV in pp interactions, allows to cover a wide backward center-of-mass rapidity region, corresponding to the poorly explored high x-Bjorken and high x-Feynman regimes. The project has several ambitious goals regarding heavy-ion physics and new-era quantitative searches in QCD through the study of the nucleon's internal dynamics in terms of both quarks and gluons degrees of freedom. In particular, the use of transversely polarized H and D targets will allow to study the quarks TMDs in pp collisions at unique kinematic conditions. Furthermore, being LHCb specifically designed for heavy-flavor physics, final states with c- or b-quarks (e.g. inclusive quarkonia production) will be efficiently reconstructed, thus providing, among other fundamental measurememnts, access to the so-far unknown gluons TMDs. The status of the project is presented along with a selection of physics opportunities