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Skeletonization via Local Separators

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arXiv 2020年

作者： Bærentzen, Andreas Rotenberg, Eva Dept. of Applied Mathematics and Computer Science Technical University of Denmark Denmark

We propose a new algorithm for curve skeleton computation which differs from previous algorithms by being based on the notion of local separators. The main benefits of this approach are that it is able to capture relatively fine details and that it works robustly on a range of shape representations. Specifically, our method works on shape representations that can be construed as a spatially embedded graphs. Such representations include meshes, volumetric shapes, and graphs computed from point clouds. We describe a simple pipeline where geometric data is initially converted to a graph, optionally simplified, local separators are computed and selected, and finally a skeleton is constructed. We test our pipeline on polygonal meshes, volumetric shapes, and point clouds. Finally, we compare our results to other methods for skeletonization according to performance and quality. Copyright © 2020, The Authors. All rights reserved.

关键词： Separators

On the role of helicity in the three-dimensional Navier-Stokes equations 14

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On the role of helicity in the three-dimensional Navier-Stok...

14th European Turbulence Conference, ETC 2013

作者： Luca, Biferale Stefano, Musacchio Edriss, Titi S. Federico, Toschi Department of Physics INFN University of Rome "Tor Vergata" Italy CNRS Lab. J.A. Dieudonné UMR 6621 Parc Valrose Nice06108 France Dept. of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot76100 Israel Dept. of Mathematics Dept. of Mechanica and Aerospace Engineering University of California IrvunCA92697 United States Dept. Physics Dept. Mathematics and Computer Science Eindhoven University of Technology Eindhoven5600 MB Netherlands CNR-IAC Via dei Taurini 19 Rome00185 Italy

By introducing an helical-decimated version of the three-dimensional Navier-Stokes equations (dNS) we show that all flows in nature posses a subset of triadic interactions leading to a split cascade regime, with energy going toward large scales and helicity toward small scales even in a fully periodic and isotropic statistical ensemble [1, 2]. Results concerning the statisical properties of the velocity field in both the direct-helicity and the inverse-energy regimes are studied. Finally, global (for all times and for all intial data) existence, uniqueness and continuos dependence on the initial data of solutions for such a model are rigorously proved [3]. Copyright © ETC 2013 - 14th European Turbulence *** rights reserved.

关键词： Navier Stokes equations

Deep unfolding for non-negative matrix factorization with application to mutational signature analysis

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arXiv 2021年

作者： Nasser, Rami Eldar, Yonina C. Sharan, Roded Dept. of Statistics and Operations Research Tel Aviv University Tel Aviv69978 Israel Department of Math and Computer Science Weizmann Institute of Science Rehovot Israel Blavatnik School of Computer Science Tel Aviv University Tel Aviv69978 Israel

Non-negative matrix factorization (NMF) is a fundamental matrix decomposition technique that is used primarily for dimensionality reduction and is increasing in popularity in the biological domain. Although finding a unique NMF is generally not possible, there are various iterative algorithms for NMF optimization that converge to locally optimal solutions. Such techniques can also serve as a starting point for deep learning methods that unroll the algorithmic iterations into layers of a deep network. Here we develop unfolded deep networks for NMF and several regularized variants in both a supervised and an unsupervised setting. We apply our method to various mutation data sets to reconstruct their underlying mutational signatures and their exposures. We demonstrate the increased accuracy of our approach over standard formulations in analyzing simulated and real mutation data. Copyright © 2021, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

Optimizing Handwritten Numeral Recognition for English and Devanagari Using MNIST and CPAR Data

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Optimizing Handwritten Numeral Recognition for English and D...

Innovative Approaches in Smart Technologies (ISAS), International Symposium on

作者： Kamred Udham Singh Ankit Kumar Gaurav Kumar Teekam Singh Tanupriya Choudhury Ketan Kotecha School of Computing Graphic Era Hill University Dehradun India Department of Computer Engineering & Applications GLA University Mathura UP India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun CSE Dept. Symbiosis Institute of Technology Symbiosis International (Deemed University) Lavale Campus Pune India Symbiosis Centre for Applied Artificial Intelligence Symbiosis Institute of Technology Symbiosis International (Deemed University) Pune India

In this paper, a technique for the categorization of offline handwritten digits in the Devanagari script as well as the Roman script (English numbers) is presented. Finding out how to get the best possible recognition results while concurrently working with several scripts is the primary purpose of this study. The approach that has been described makes use of an easy profiling method for the extraction of features, together with an innovative implementation of Linear Discriminant Analysis (LDA), and a neural network architecture that has been adapted specifically for numeral classification. An exhaustive series of trials including 36,000 examples of handwritten numerals were carried out as part of the evaluation of the effectiveness of this approach. These samples were chosen at random from the CPAR datasets, with 22,000 being put to use in the construction of the training set and the remaining 14,000 being assigned to the role of the test set. In addition, the well-known MNIST database was used, which provided 60,000 samples for training purposes and 10,000 samples specifically for testing. It was determined via thorough testing that the LDA classifier produced variable results. These varying results are essential in emphasising the success of the method as well as possible areas for improvement for the method. According to the results, this strategy, which combines profile-based feature extraction with advanced classification algorithms, has the potential to lead to major breakthroughs in the area of handwritten number identification.

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To trust or not to trust – the million dollar question in IoT security 10

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To trust or not to trust – the million dollar question in I...

10th International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2019

作者： Soceanu, Alexandru Vasylenko, Maksym Goga, Nicolae Dept. of Computer Science and Mathematics Munich University of Applied Sciences Munich Germany Dept. of Computer Science University Politehnica Bucharest Bucharest Romania

This work-in-progress report addresses the issue of trust in Internet of Things (IoT) systems. By 2020, 30 billion devices (things) will be networked within IoT systems in support of various applications. However, one of the greatest customer concerns is the degree of protection against security attacks. An analysis of attacks on generic computer networks reveals: protection tools are not properly set up or not used at all. Similarly, numerous IoT systems do not harness all the embedded protection offered by the standards. No wonder that networks are often hacked and customers lose trust in deploying such systems. The central question is: How to engender greater trust in IoT systems? We therefore analyzed (1) to what extent security protections embedded into the standard specifications offer effective and satisfactory protection and (2) to what extent this may foster trust in deploying IoT systems for non-critical applications. To investigate this, we simulated experimental IoT applications using the open source platform ContikiOS and the Cooja simulator. The purpose of this research is to foster an understanding of the concept of trust in IoTs where trust evaluation metrics cannot be implemented. Copyright 2019. © by the International Institute of Informatics and Systemics. All rights reserved.

关键词： Internet of things

Tunable Source of Quantum-Correlated Photons with Integrated Pump Rejection in a Silicon CMOS Platform

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Tunable Source of Quantum-Correlated Photons with Integrated...

Frontiers in Optics + Laser science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Fargas Cabanillas, Josep M. Kramnik, Danielius Ramesh, Anirudh Gentry, Cale M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

ISBN: (纸本)9781557528209

A wavelength-tunable, silicon photon-pair source based on spontaneous four-wave mixing, integrated with a pump rejection filter in a single, flip-chip packaged CMOS chip, is demonstrated with a coincidence-to-accidentals ratio of 9.1 with no off-chip pump filtering. Frontiers in Optics / Laser science © Optica Publishing Group 2021.

关键词： CMOS integrated circuits

Automated symbolic and numerical testing of DLMF formulae using computer algebra systems

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arXiv 2021年

作者： Cohl, Howard S. Greiner-Petter, André Schubotz, Moritz Applied and Computational Mathematics Division National Institute of Standards and Technology Mission ViejoCA United States Dept. of Computer and Information Science University of Konstanz Konstanz Germany

We have developed an automated procedure for symbolic and numerical testing of formulae extracted from the NIST Digital Library of mathematical Functions (DLMF). For the NIST Digital Repository of mathematical Formulae, we have developed conversion tools from semantic LATEX to the computer Algebra System (CAS) MAPLE which relies on Youssef’s part-of-math tagger. We convert a test data subset of 4,078 semantic LATEX DLMF formulae to the native CAS representation and then apply an automated scheme for symbolic and numerical testing and verification. Our framework is implemented using Java and MAPLE. We describe in detail the conversion process which is required so that the CAS can correctly interpret the mathematical representation of the formulae. We describe the improvement of the effectiveness of our automated scheme through incremental enhancement (making more precise) of the mathematical semantic markup for the formulae. © 2021, CC BY.

关键词： Automation

Dynamic Mapping of Temperature Using Phase-Change Materials

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Dynamic Mapping of Temperature Using Phase-Change Materials

Conference on Lasers and Electro-Optics (CLEO)

作者： Nicholas Nobile John Erickson Carlos Ríos Yifei Zhang Juejun Hu Feng Xiong Nathan Youngblood Dept. of Electrical and Computer Engineering Univ. of Pittsburgh Pittsburgh PA USA Department of Materials Science & Engineering University of Maryland College Park MD USA Institute for Research in Electronics and Applied Physics University of Maryland College Park MD USA Department of Materials Science & Engineering MIT Cambridge MA USA

GST pixels are fabricated on metallic heaters where the optical reflection is observed and used to extract dynamic temperature changes. Our results provide a new way to measure the thermal response of microsystems in ... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Temperature measurement Radio frequency Phase change materials Phase measurement Optical switches Optical variables measurement Real-time systems

Defending medical image diagnostics against privacy attacks using generative methods: Application to retinal diagnostics

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arXiv 2021年

作者： Paul, William Cao, Yinzhi Zhang, Miaomiao Burlina, Phil Johns Hopkins University Applied Physics Laboratory LaurelMD United States Johns Hopkins University Dept. of Computer Science University of Virginia Dept. of Electrical Engineering Johns Hopkins University Malone Center for Engineering in Healthcare

Machine learning (ML) models used in medical imaging diagnostics can be vulnerable to a variety of privacy attacks, including membership inference attacks, that lead to violations of regulations governing the use of medical data and threaten to compromise their effective deployment in the clinic. In contrast to most recent work in privacy-aware ML that has been focused on model alteration and post-processing steps, we propose here a novel and complementary scheme that enhances the security of medical data by controlling the data sharing process. We develop and evaluate a privacy defense protocol based on using a generative adversarial network (GAN) that allows a medical data sourcer (e.g. a hospital) to provide an external agent (a modeler) a proxy dataset synthesized from the original images, so that the resulting diagnostic systems made available to model consumers is rendered resilient to privacy attackers. We validate the proposed method on retinal diagnostics AI used for diabetic retinopathy that bears the risk of possibly leaking private information. To incorporate concerns of both privacy advocates and modelers, we introduce a metric to evaluate privacy and utility performance in combination, and demonstrate, using these novel and classical metrics, that our approach, by itself or in conjunction with other defenses, provides state of the art (SOTA) performance for defending against privacy attacks. Copyright © 2021, The Authors. All rights reserved.

关键词： Ophthalmology