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IEEE Cognitive Communications for Aerospace Applications Workshop (CCAAW)

作者： Larissa C Suzuki Vinton G Cerf Jordan L Torgerson Thiago S Suzuki Telecommunications Division Communications Architecture and Research Section Jet Propulsion Laboratory Pasadena CA USA Internet Evangelism Google Reston VA USA Computer Science Department Birkbeck University of London London United Kingdom

Communication between the Earth and distant spacecraft is challenging, since there are frequent link outages due to orbital trajectories, loss of signal due to noise or antenna pointing problems, and long and highly variable, one-way light time delays due to the extreme orbits and distances involved. Deep space link reliability has traditionally required manual intervention by Mission Operations teams, and new Solar System Internetworking protocols known as Delay and Disruption-Tolerant Networking (DTN) have been developed to automate space communications. This automation now provides a mechanism for space networking and link performance optimization using artificial intelligence (AI) and machine learning (ML) methods which we present in this paper. We discuss Federated Learning (FL) and our application of FL to monitoring and optimization of DTN networks. Federated learning is a distributed learning framework that enables machine learning to be performed on decentralized data with improved protection for each collaborator’s data privacy and communication efficiency. This work outlines a novel approach to advancing current AI applications running over delay and disruption tolerant networks by leveraging two forms of federated learning for space applications, and the core DTN Bundle Protocol to produce smarter ‘on-edge device’ machine learning models. Our work demonstrates that the network can operate with more link bandwidth efficiency and less resource consumption, while ensuring privacy and quality constraints. Experiments on a popular image dataset show that DTN-ML can have similar or better performance when compared to existing alternatives, but with much less communication overhead.

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Simulating pandemic emergency scenarios considering mobility patterns through an agent-based model 1

Simulating pandemic emergency scenarios considering mobility...

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1st Workshop on Agent-Based Modeling and Policy-Making, AMPM 2021

作者： Fazio, Martina Pluchino, Alessandro Inturri, Giuseppe Le Pira, Michela Giuffrida, Nadia Ignaccolo, Matteo Department of Physics and Astronomy University of Catania Via Santa Sofia 64 Catania Italy INFN Section of Catania Catania Italy Department of Electrical Electronic and Computer Engineering University of Catania Via Santa Sofia 64 Catania Italy Department of Civil Engineering and Architecture University of Catania Via Santa Sofia 64 Catania Italy Spatial Dynamics Lab University College Dublin UCD Richview Campus Belfield DublinD04 V1W8 Ireland

One of the main policies to contain a pandemic spreading is to reduce people mobility. However, it is not easy to predict its actual impact, and this is a limitation for policy-makers who need to act effectively and timely to limit virus spreading. Data are fundamental for monitoring purposes;however, models are needed to predict the impact of different scenarios at a granular scale. Based on this premise, this paper presents the first results of an agent-based model (ABM) able to dynamically simulate a pandemic spreading under mobility restriction scenarios. The model is here used to reproduce the first wave of COVID-19 pandemic in Italy and considers factors that can be attributed to the diffusion and lethality of the virus and population mobility patterns. The model is calibrated with real data (considering the first wave), and it is based on a combination of static and dynamic parameters. First results show the ability of the model to reproduce the pandemic spreading considering the lockdown strategy adopted by the Italian Government and pave the way for scenario analysis of different mobility restrictions. This could be helpful to support policy-making by providing a strategic decision-tool to contrast pandemics. © 2021 Copyright for this paper by its authors.

关键词： Viruses

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Multiple material decomposition with a combined X-ray spectral and phase imaging system

Multiple material decomposition with a combined X-ray spectr...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： F. Arfelli L. Brombal P. Perion F. Brun S. Donato L. Sbuelz P. Delogu P. Oliva R.H. Menk Department of Physics University of Trieste Trieste Italy Istituto Nazionale di Fisica Nucleare Section of Trieste Trieste Italy Department of Engineering and Architecture University of Trieste Trieste Italy Department of Physics University of Calabria Cosenza Italy Istituto Nazionale di Fisica Nucleare Section of Frascati Roma Italy CNR IOM Trieste Italy Department of Physical Science Earth and Environment University of Siena Siena Italy Division of Pisa Istituto Nazionale di Fisica Nucleare Pisa Italy Department of Chemical Physical Mathematical and Natural Sciences University of Sassari Sassari Italy Istituto Nazionale di Fisica Nucleare Section of Cagliari Cagliari Italy Elettra Sincrotrone Trieste Trieste Italy Department of Computer and Electrical Engineering Mid Sweden University Sundsvall Sweden

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

The combined approach of X-ray spectral and phase contrast imaging brings complementary advantages for comprehensive imaging and analysis of complex samples thanks to the simultaneous visualization of structural features and elemental composition for quantitative multimodal characterization of materials with diverse compositions and properties. This integration offers a dual advantage; it enhances the visibility of soft tissues while effectively isolating high-Z materials, thus augmenting the capabilities of X-ray imaging system. Its potential impact is notable for instance in medical imaging, materials science, and cultural heritage. We have developed a novel X-ray imaging system that yields spectral information and retrieves the phase simultaneously in a single acquisition procedure. The spectral information is obtained utilizing a bent Si Laue crystal, which energetically disperses a polychromatic synchrotron X-ray beam focused into narrow line where the sample is placed. The system can be tuned such that multiple absorption edges can be captured simultaneously in the vertical direction of a 2-D detector allowing multi-material decomposition at the mg/ml level or recording spatially resolved X-ray absorption fine structures in a single shot. On the other hand X-ray phase contrast is capable of enhancing soft tissue visibility since it is based on material refractive properties rather than attenuation. Here it is achieved through the beam tracking technique exploiting beamlets generated by an absorption mask upstream the crystal, providing absorption, refraction, and dark field images. Moreover introducing the phase image into the material decomposition algorithm allows retrieving an additional material while keeping high phase contrast sensitivity in low density samples. Here we will present our combined X-ray spectral and phase system showing preliminary imaging results on dedicated phantoms and biological samples that highlight the potential of the method.

关键词： Visualization Sensitivity Absorption Biological tissues Synchrotrons Crystals Silicon

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Ultracolor Multiplexing in QR Codes for Data Encryption and Transmission

Ultracolor Multiplexing in QR Codes for Data Encryption and ...

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2024 Frontiers in Optics, FiO 2024

作者： Ignacio-Cerrato, Sara Pacios, David Rodríguez, José Miguel Ezquerro Vázquez-Poletti, José Luis Mariño, María Estefanía Avilés Stravakakis, Konstantinos Di Iorio, Alessio Cesarano, Clemente Schetakis, Nikolaos Optics Department Faculty of Optics and Optometry Universidad Complutense de Madrid Calle Arcos de Jalón 118 Madrid28037 Spain Department of Computer Architecture and Automation Universidad Complutense de Madrid Madrid Spain Alma Sistemi Srl Guidonia Rome00012 Italy Section of Mathematics International Telematic University Uninettuno Corso Vittorio Emanuele II 39 Rome Italy Departamento de Lingüística Aplicada a la Ciencia y a la Tecnología Universidad Politécnica de Madrid Calle de José Gutiérrez Abascal 2 Madrid28006 Spain Computational Mechanics and Optimization Laboratory School of Production Engineering and Management Technical University of Crete Chania73100 Greece Quantum Innovation Pc Chania73100 Greece

This paper introduces an innovative encryption method using ultracolor codification via the Prism Algorithm, which effectively encodes large data volumes into images with base64 encoding, demonstrating practical reliability and potential for secure data transmission. © Optica Publishing Group 2024, © 2024 The Author(s)

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Long Text Classification Based on BERT 5

Long Text Classification Based on BERT

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5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Weijie, DIng Yunyi, Li Jing, Zhang Xuchen, Shen Big-data and Network Security Research Institute Zhejiang Police College Hangzhou310053 China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China Key Laboratory of Public Security Information Application Based on Big-data Architecture Ministry of Public Security Hangzhou310053 China Zhejiang Police College Department of Investigation Hangzhou310053 China Zhejiang Police College Department of Computer and Information Security Hangzhou310053 China Science and Technology Management Section Hangzhou311203 China

ISBN: (纸本)9781665415989

Existing text classification algorithms generally have limitations in terms of text length and yield poor classification results for long texts. To address this problem, we propose a BERT-based long text classification method. First, we slice the long text and use BERT to encode the sliced clauses to obtain the local semantic information. Second, we use BiLSTM to fuse the local semantic information and adopt the attention mechanism to increase the weight of important clauses in the long text, so as to obtain the global semantic information. Finally, the global semantic information is input to the softmax layer for classification. Experimental results show that the proposed method achieves higher accuracy than commonly used models. © 2021 IEEE.

关键词： Classification (of information)

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Simulating urban freight flows in e-grocery scenarios accounting for consumer heterogeneous preferences

Simulating urban freight flows in e-grocery scenarios accoun...

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2020 Forum on Integrated and Sustainable Transportation Systems, FISTS 2020

作者： Pira, M. Le Marcucci, E. Gatta, V. Pluchino, A. Fazio, M. Inturri, G. Ignaccolo, M. University of Catania Department of Civil Engineering and Architecture Catania95125 Italy Roma Tre University Department of Political Science Rome00145 Italy Faculty of Logistics Molde University College Molde6410 Norway University of Catania Department of Physics and Astronomy Catania95125 Italy INFN Section of Catania Catania95125 Italy University of Catania Department of Electric Electronic and Computer Engineering Catania95125 Italy

ISBN: (纸本)9781728195032

E-grocery is a growing phenomenon that has the potential to rapidly change the way shopping is performed and goods distributed in cities. The impacts of this innovation can vary according to the delivery service performed, thus affecting positively or negatively the overall sustainability of urban freight transport. Understanding the dynamics of demand (i.e. consumers) will be useful to know how supply (i.e. supermarkets) should adapt, and how policy-makers should deal with this phenomenon. This paper presents an agent-based model to simulate different e-grocery scenarios at a neighbourhood scale. Agents are characterized with individual utility functions from a latent class model based on a stated preference survey performed in Rome (Italy). First results of a one-month simulation allow deriving some useful conclusion on the impact different grocery channels can have on travelled distance and consumer shopping time and formulating some policy implications. © 2020 IEEE.

关键词： Technology transfer

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Exploring the impact of mobility restrictions on the COVID-19 spreading through an agent-based approach

arXiv

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arXiv 2021年

作者： Fazio, Martina Pluchino, Alessandro Inturri, Giuseppe Le Pira, Michela Giuffrida, Nadia Ignaccolo, Matteo Department of Physics and Astronomy University of Catania Catania Italy INFN Section of Catania Catania Italy Department of Electrical Electronic and Computer Engineering University of Catania Catania Italy Department of Civil Engineering and Architecture University of Catania Catania Italy Spatial Dynamics Lab University College Dublin UCD Richview Campus D04 V1W8 Belfield Dublin Ireland

Mobility restriction is considered one of the main policies to contain COVID-10 spreading. However, there are multiple ways to reduce mobility via differentiated restrictions, and it is not easy to predict the actual impact on virus spreading. This is a limitation for policy-makers who need to implement effective and timely measures. Notwithstanding the big role of data analysis to understand this phenomenon, it is also important to have more general models capable of predicting the impact of different scenarios. Besides, they should be able to simulate scenarios in a disaggregated way, so to understand the possible impact of targeted strategies, e.g. on a geographical scale or in relation to other variables associated with the potential risk of infection. This paper presents an agent-based model (ABM) able to dynamically simulate the COVID-19 spreading under different mobility restriction scenarios. The model uses the Italian case study with its 20 administrative regions and considers parameters that can be attributed to the diffusion and lethality of the virus (based on a virus spread risk model) and population mobility patterns. The model is calibrated with real data and reproduces the impact that different mobility restrictions can have on the pandemic diffusion based on a combination of static and dynamic parameters. Results suggest that virus spreading would have been similar if differentiated mobility restriction strategies based on a-priori risk parameters instead of a national lockdown would have been put in place in Italy during the first wave of the pandemic. The proposed model could give useful suggestions for decision-makers to tackle pandemics and virus spreading at a strategic level. Copyright © 2021, The Authors. All rights reserved.

关键词： Autonomous agents

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Simulation of Crushed Ore Particles Motion in the Pulp Under the Influence of High-energy Ultrasound Dynamic Effects

Simulation of Crushed Ore Particles Motion in the Pulp Under...

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IEEE International Conference on Electronics and Nanotechnology (ELNANO)

作者： Vladimir Morkun Natalia Morkun Andrey Pikilniak Nikolay Podgorodetskiy Irina Haponenko Arkadii Davidcovich Computer Science and Technology Kryvyi Rih National University Kryvyi Rih Ukraine Kryvyi Rih National University Kryvyi Rih Ukraine Donbas National Academy of Civil Engineering and Architecture Donetsk Ukraine R&D section Kryvyi Rih National University Kryvyi Rih Ukraine MCRSS Boston USA

ISBN: (数字)9781728197135

ISBN: (纸本)9781728197142

The software described in the article provides a method for determining the particle size distribution of the solid pulp phase, first implemented in world practice. The program for numerical analysis and representation of the simulation results of changes in the particle size distribution of the pulp solid phase under the controlling influence of high-energy ultrasound radiation pressure is developed. The particle distribution function according to the useful component disclosure degree is built.

关键词： ultrasound crushed ore pulp radiation pressure Particle size distribution Dental Pulp Pulp RADIATION PRESSURE Ultrasonic Waves PARTICLE MOTION simulating HIGH ENERGY crushing

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High performance CFD simulations of sloshing in a moving tank with SPH method

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AIP Conference Proceedings 2021年第1期2409卷

作者： T. Arslan M. Ozbulut J. Ragunathan J. Valstad J. C. Meyer 1NTNU Scientific Computing section IT Department Trondheim Norway 2Piri Reis University Engineering Faculty Naval Architecture & Marine Engineering Istanbul Turkey 3NTNU Department of Computer Science Trondheim Norway

The aim of this work is modeling of sway-sloshing motion in a partially filled rectangular tank while different frequency of motions are enforced. Within the study, a CFD code based on Smooth Particle Hydrodynamics (SPH) approach is developed for modelling violent free surface flows. The code is parallelized in order to run efficiently in supercomputers to solve complex flow phenomenon occurs in the cargo and fuel tanks of ships with a high resolution. It is shown that numerical results of the proposed SPH scheme are in good agreement with experimental and numerical findings of the literature and presently benefits from complex compute nodes of supercomputers.

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Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

IEEE Transactions on Technology and Society

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IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

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