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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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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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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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FRI0311 Neuropsychiatric Lupus: Combining Advanced Morphometric Methods, Diffusion Tensor Imaging and Conventional MRI Leads To The Pathways of Brain Abnormalities. Correlation with Clinical and Laboratory Data

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Annals of the Rheumatic Diseases 2016年 75卷 547-548页

作者： M.I. Sarbu P. Toledano A. Calvo N. Sarbu E. Roura G. Espinosa X. Lladό R. Cervera N. Bargallό 1Departament of Rheumatology CHU Saint Pierre and Erasme University Hospital ULB Bruxelles Belgium 2Departament of Autoimmune Diseases Hospital Clinic Barcelona Spain 3Magnetic Resonance Image Core Facility Institut d'Investigacions Biomèdiques August Pi I Sunyer (IDIBAPS) Barcelona Spain 4Neuroadiology Erasme University Hospital ULB Bruxelles Belgium 5Departament of Computer Architecture and Technology University of Girona Girona 6Departament of Autoimmune Diseases IDIBAPS Hospital Clinic Barcelona Spain 7Magnetic Resonance Image Core Facility IDIBAPS Department of Radiology Neuroradiology Section Hospital Clinic Barcelona Spain

Objectives To combine conventional and advanced magnetic resonance imaging (MRI) to describe brain abnormalities in neuropsychiatric (NP) systemic lupus erythematosus (SLE), and to correlate them with clinical data. Methods Prospective study including patients presenting central primary NPSLE, non-NPSLE and healthy controls (HC) undergoing brain MRI at 3T in 2014–2015. Conventional MRI data using visual scales for atrophy and white matter (WM) lesions, brain volumetry (voxel-based morphometry and Freesurfer), and diffusion-tensor imaging (DTI) were analyzed. Group differences were correlated with clinical, laboratory and treatment data. Results Twenty-eight females with NPSLE, 22 non-NPSLE and 20 HC, mean age around 40 years, were recruited. Conventional MRI showed brain atrophy in NPSLE (p=0.005). Total cortical volume was reduced in NPSLE compared to HC (p=0,042). Non-NPSLE had a reduction of left temporal gray-matter (GM) volume compared to HC (p=0.028). NPSLE had a decrease of left frontal WM volume compared with HC (p=0.002). Corpus callosum was reduced in NPSLE compared to HC (p=0.033) and non-NPSLE (p=0.043). DTI showed increased diffusivity (mean, axial and radial: MD, AD, RD) in bilateral temporal WM (p<0,010) and reduced fractional anisotropy (FA) in right frontal WM (p=0.018) in NPSLE versus HC. SLEDAI score was correlated with atrophy (p=0.046); negatively with left temporal cortex volume (p=0.029) and with FA in WM hippocampal regions (p=0.002 left, p=0.048 right). SLICC score was correlated with diffusivity in bilateral temporal WM (MD:p=0.033; AD:p=0.039; RD:p=0.016) and right frontal WM (p=0.005); and negatively with FA in left WM hippocampal regions (p<0.001). SLE duration was correlated with diffusivity in temporal WM (MD:p=0.007; AD:p=0.007 and RD:p=0.007); and negatively with FA in right frontal and left temporo-occipital WM (p<0.0005 and p=0.014) and with right frontal cortex volume (p=0.028). Low C4 and CH50 were inversely correlated with left

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Combined Measurement of the Higgs Boson Mass in pp Collisions at s=7 and 8 TeV with the ATLAS and CMS Experiments

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Physical Review Letters 2015年第19期114卷 191803-191803页

作者： G. Aad B. Abbott J. Abdallah O. Abdinov R. Aben M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu Y. Abulaiti B. S. Acharya L. Adamczyk D. L. Adams J. Adelman S. Adomeit T. Adye A. A. Affolder T. Agatonovic-Jovin J. A. Aguilar-Saavedra S. P. Ahlen F. Ahmadov G. Aielli H. Akerstedt T. P. A. Åkesson G. Akimoto A. V. Akimov G. L. Alberghi J. Albert S. Albrand M. J. Alconada Verzini M. Aleksa I. N. Aleksandrov C. Alexa G. Alexander T. Alexopoulos M. Alhroob G. Alimonti L. Alio J. Alison S. P. Alkire B. M. M. Allbrooke P. P. Allport A. Aloisio A. Alonso F. Alonso C. Alpigiani A. Altheimer B. Alvarez Gonzalez D. Álvarez Piqueras M. G. Alviggi B. T. Amadio K. Amako Y. Amaral Coutinho C. Amelung D. Amidei S. P. Amor Dos Santos A. Amorim S. Amoroso N. Amram G. Amundsen C. Anastopoulos L. S. Ancu N. Andari T. Andeen C. F. Anders G. Anders J. K. Anders K. J. Anderson A. Andreazza V. Andrei S. Angelidakis I. Angelozzi P. Anger A. Angerami F. Anghinolfi A. V. Anisenkov N. Anjos A. Annovi M. Antonelli A. Antonov J. Antos F. Anulli M. Aoki L. Aperio Bella G. Arabidze Y. Arai J. P. Araque A. T. H. Arce F. A. Arduh J-F. Arguin S. Argyropoulos M. Arik A. J. Armbruster O. Arnaez V. Arnal H. Arnold M. Arratia O. Arslan A. Artamonov G. Artoni S. Asai N. Asbah A. Ashkenazi B. Åsman L. Asquith K. Assamagan R. Astalos M. Atkinson N. B. Atlay B. Auerbach K. Augsten M. Aurousseau G. Avolio B. Axen M. K. Ayoub G. Azuelos M. A. Baak A. E. Baas C. Bacci H. Bachacou K. Bachas M. Backes M. Backhaus E. Badescu P. Bagiacchi P. Bagnaia Y. Bai T. Bain J. T. Baines O. K. Baker P. Balek T. Balestri F. Balli E. Banas Sw. Banerjee A. A. E. Bannoura H. S. Bansil L. Barak S. P. Baranov E. L. Barberio D. Barberis M. Barbero T. Barillari M. Barisonzi T. Barklow N. Barlow S. L. Barnes B. M. Barnett R. M. Barnett Z. Barnovska A. Baroncelli G. Barone A. J. Barr F. Barreiro J. Barreiro Guimarães da Costa R. Bartoldus A. E. Barton P. Bartos A. Bassalat A. Basye R. L. Bates S. J. Batista J. R. Batley M. Battaglia M. Bauce F. Bauer H. S. Bawa J. B. Beach CPPM Aix-Marseille Université and CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA Institute of Physics Academia Sinica Taipei Taiwan Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam Netherlands Department of Physics and Astronomy Michigan State University East Lansing Michigan USA Department of Physics University of Toronto Toronto Ontario Canada Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion: Israel Institute of Technology Haifa Israel CERN Geneva Switzerland Department of Physics Stockholm University Sweden The Oskar Klein Centre Stockholm Sweden INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Physics Department Brookhaven National Laboratory Upton New York USA Department of Physics Northern Illinois University DeKalb Illinois USA Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Institute of Physics University of Belgrade Belgrade Serbia Laboratorio de Instrumentacao e Fisica Experimental de Particulas-LIP Lisboa Portugal Departamento de Fisica Teorica y del Cosmos and CAFPE Universidad de Granada Granada (Spain) Portugal Department of Physics Boston University Boston Massachusetts USA Joint Institute for Nuclear Research JINR Dubna Dubna Russia INFN Sezione di Roma Tor Vergata Roma Italy Dipartimento di Fisica Università di Roma Tor Vergata Roma Italy Fysiska institutionen Lunds universitet Lund Sweden International Center for Elementary Particle Physics and Depart

A measurement of the Higgs boson mass is presented based on the combined data samples of the ATLAS and CMS experiments at the CERN LHC in the H→γγ and H→ZZ→4ℓ decay channels. The results are obtained from a simultaneous fit to the reconstructed invariant mass peaks in the two channels and for the two experiments. The measured masses from the individual channels and the two experiments are found to be consistent among themselves. The combined measured mass of the Higgs boson is mH=125.09±0.21 (stat)±0.11 (syst) GeV.

关键词： HIGGS bosons RESEARCH COLLISIONS (Nuclear physics) ATLAS (computer program language) REST mass (Relativity) BOSONS

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Space network time distribution and synchronization protocol development for Mars proximity link

Space network time distribution and synchronization protocol...

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SpaceOps 2010 Conference

作者： Woo, Simon S. Gao, Jay L. Mills, David Communication Architecture and Research Section Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive M/S 238-420 Pasadena CA 91109 United States Electrical and Computer Engineering University of Delaware Newark DE 19716 United States

ISBN: (纸本)9781624101649

Time distribution and synchronization in space networking are challenging due to long propagation delays, spacecraft movements, and relativistic effects, and therefore the Network Time Protocol (NTP) designed for terrestrial networks may not work properly. In this work, we consider a time distribution protocol that is based on time message exchanges similar to Network Time Protocol (NTP) but customized for the proximity space links such as the RF links between Mars orbiters and rovers. This protocol is called the Proximity-1 Space Link Interleaved Time Synchronization (PITS) protocol and is designed with goal of integrating with the CCSDS Proximity-1 Space Data Link Protocol's existing time capture capability. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and misordering which underlying protocol mechanisms provide. This paper describes the current progress of implementing and validating the correctness of the PITS algorithm at JPL, using the Mars Proximity link communications scenarios as our baseline. © 2010 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： Synchronization

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High-performance computing in remotely sensed hyperspectral imaging: The pixel purity index algorithm as a case study 20

High-performance computing in remotely sensed hyperspectral ...

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20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006

作者： Plaza, Antonio Valencia, David Plaza, Javier Computer Architecture and Technology Section Computer Science Department University of Extremadura Avda. de la Universidad s/n E-10071 Caceres Spain

ISBN: (纸本)1424400546

The incorporation of last-generation sensors to airborne and satellite platforms is currently producing a nearly continual stream of high-dimensional data, and this explosion in the amount of collected information has rapidly created new processing challenges. For instance, hyperspectral imaging is a new technique in remote sensing that generates hundreds of spectral bands at different wavelength channels for the same area on the surface of the Earth. The price paid for such a wealth of spectral information available from latest-generation sensors is the enormous amounts of data that they generate. In recent years, several efforts have been directed towards the incorporation of high-performance computing (HPC) models in remote sensing missions. This paper explores three HPC-based paradigms for efficient information extraction from remote sensing data using the Pixel Purity Index (PPI) algorithm (available from the popular Kodak's Research Systems ENVI software) as a case study for algorithm optimization. The three considered approaches are: 1) Commodity cluster-based parallel computing;2) Distributed computing using heterogeneous networks of workstations;and 3) FPGA-based hardware implementations. Combined, these parts deliver an excellent snapshot of the state-of-the-art in those areas, and offer a thoughtful perspective on the potential and emerging challenges of adapting HPC models to remote sensing problems. © 2006 IEEE.

关键词： Sensors

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Parallel morphological processing of hyperspectral image data on heterogeneous networks of computers 20

Parallel morphological processing of hyperspectral image dat...

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20th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2006

作者： Plaza, Antonio J. Computer Architecture and Technology Section Computer Science Department University of Extremadura Avda. de la Universidad s/n E-10071 Caceres Spain

ISBN: (纸本)1424400546

Recent advances in space and computer technologies are revolutionizing the way remotely sensed data is collected, managed and interpreted. The development of efficient techniques for transforming the massive amount of collected data into scientific understanding is critical for space-based Earth science and planetary exploration. Although most currently available parallel processing strategies for hyperspectral image analysis assume homogeneity in the computing platform, heterogeneous networks of computers represent a very promising cost-effective solution expected to play a major role in the design of high-performance computing platforms for many on-going and planned remote sensing missions. This paper explores techniques for mapping morphological hyperspectral analysis algorithms, characterized by their scalability and sub-pixel accuracy, onto heterogeneous parallel computers. Important aspects in algorithm design are illustrated by using both homogeneous and heterogeneous parallel computing facilities available at NASA 's Goddard Space Flight Center and University of Maryland. Experiments reveal that heterogeneous networks of workstations represent a source of computational power that is both accessible and applicable in many remote sensing studies. © 2006 IEEE.

关键词： Parallel processing systems

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Parallel morphological processing of hyperspectral image data on heterogeneous networks of computers 06

Parallel morphological processing of hyperspectral image dat...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： A.J. Plaza Computer Architecture and Technology Section Computer Science Department University of Extremadura Caceres Spain

ISBN: (纸本)9781424400546

Advances in space and computer technologies are revolutionizing the way remotely sensed data is collected, managed and interpreted. The development of efficient techniques for transforming the massive amount of collected data into scientific understanding is critical for space-based Earth science and planetary exploration. Although most currently available parallel processing strategies for hyperspectral image analysis assume homogeneity in the computing platform, heterogeneous networks of computers represent a very promising cost-effective solution expected to play a major role in the design of high-performance computing platforms for many on-going and planned remote sensing missions. This paper explores techniques for mapping morphological hyperspectral analysis algorithms, characterized by their scalability and sub-pixel accuracy, onto heterogeneous parallel computers. Important aspects in algorithm design are illustrated by using both homogeneous and heterogeneous parallel computing facilities available at NASA's Goddard Space Flight Center and University of Maryland. Experiments reveal that heterogeneous networks of workstations represent a source of computational power that is both accessible and applicable in many remote sensing studies

关键词： Hyperspectral imaging computer networks Concurrent computing Hyperspectral sensors Space technology Parallel processing Remote sensing Algorithm design and analysis technology management Geoscience

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