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An efficient quantum blind digital signature scheme

science China(Information sciences) 2017年第8期60卷 226-239页

作者： Hong LAI Mingxing LUO Josef PIEPRZYK Zhiguo QU Shudong LI Mehmet A.ORGUN College of Computer and Information Science Southwest University Information Security and National Computing Grid Laboratory School of Information Science and TechnologySouthwest Jiaotong University School of Electrical Engineering and Computer Science Queensland University of Technology Institute of Computer Science Polish Academy of Sciences School of Computer and Software Nanjing University of Information Science and Technology College of Mathematics and Information Science Shandong Technology and Business University School of Computer Science National University of Defense Technology Department of Computing Macquarie University Faculty of Information Technology Macau University of Science and Technology

Recently, many quantum digital signature(QDS) schemes have been proposed to authenticate the integration of a message. However, these quantum signature schemes just consider the situation for bit messages,and the signing-verifying of one-bit modality. So, their signature efficiency is very low. In this paper, we propose a scheme based on an application of Fibonacci-, Lucas-and Fibonacci-Lucas matrix coding to quantum digital signatures based on a recently proposed quantum key distribution(QKD) system. Our scheme can sign a large number of digital messages every time. Moreover, these special matrices provide a method to verify the integration of information received by the participants, to authenticate the identity of the participants, and to improve the efficiency for signing-verifying. Therefore, our signature scheme is more practical than the existing schemes.

关键词： blind quantum digital signature Fibonacci- Lucas-and Fibonacci-Lucas matrix coding digital messages signing-verifying modality

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Common Limitations of Image Processing Metrics: A Picture Story

arXiv

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arXiv 2021年

作者： Reinke, Annika Tizabi, Minu D. Sudre, Carole H. Eisenmann, Matthias Rädsch, Tim Baumgartner, Michael Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Bankhead, Peter Benis, Arriel Blaschko, Matthew Buettner, Florian Cardoso, M. Jorge Chen, Jianxu Cheplygina, Veronika Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Engelhardt, Sandy Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hamprecht, Fred Hashimoto, Daniel A. Heckmann-Nötzel, Doreen Hirsch, Peter Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kavur, A. Emre Kenngott, Hannes Kleesiek, Jens Kleppe, Andreas Koehler, Sven Kofler, Florian Kopp-Schneider, Annette Kooi, Thijs Kozubek, Michal Kreshuk, Anna Kurc, Tahsin Landman, Bennett A. Litjens, Geert Madani, Amin Maier-Hein, Klaus Martel, Anne L. Mattson, Peter Meijering, Erik Menze, Bjoern Moher, David Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Noyan, M. Alican Petersen, Jens Polat, Gorkem Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Rieke, Nicola Riegler, Michael A. Rivaz, Hassan Saez-Rodriguez, Julio Sánchez, Clara I. Schroeter, Julien Saha, Anindo Selver, M. Alper Sharan, Lalith Shetty, Shravya Smeden, Maarten V.A.N. Stieltjes, Bram Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. Calster, Ben V.A.N. Varoquaux, Gaël Wiesenfarth, Manuel Yaniv, Ziv R. Jäger, Paul Maier-Hein, Lena Division of Intelligent Medical Systems and HI Helmholtz Imaging Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Intelligent Medical Systems Heidelberg Germany NCT Heidelberg DKFZ University Medical Center Heidelberg Germany MRC Unit for Lifelong Health and Ageing UCL Centre for Medical Image Computing Department of Computer Science University College London London United Kingdom School of Biomedical Engineering and Imaging Science King’s College London London United Kingdom Division of Medical Image Computing Heidelberg Germany Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montréal Canada Division of Computational Pathology Dept of Pathology & Laboratory Medicine Indiana University School of Medicine IU Health Information and Translational Sciences Building Indianapolis United States University of Pennsylvania Richards Medical Research Laboratories FL7 PhiladelphiaPA United States Institute of Genetics and Cancer University of Edinburgh Edinburgh United Kingdom Department of Digital Medical Technologies Holon Institute of Technology Holon Israel European Federation for Medical Informatics Le Mont-sur-Lausanne Switzerland Center for Processing Speech and Images Department of Electrical Engineering KU Leuven Kasteelpark Arenberg 10 - box 2441 Leuven3001 Belgium Frankfurt/Mainz DKFZ UCT Frankfurt-Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany Frankfurt Cancer Insititute Germany Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for St

While the importance of automatic image analysis is continuously increasing, recent meta-research revealed major flaws with respect to algorithm validation. Performance metrics are particularly key for meaningful, objective, and transparent performance assessment and validation of the used automatic algorithms, but relatively little attention has been given to the practical pitfalls when using specific metrics for a given image analysis task. These are typically related to (1) the disregard of inherent metric properties, such as the behaviour in the presence of class imbalance or small target structures, (2) the disregard of inherent data set properties, such as the non-independence of the test cases, and (3) the disregard of the actual biomedical domain interest that the metrics should reflect. This living dynamically document has the purpose to illustrate important limitations of performance metrics commonly applied in the field of image analysis. In this context, it focuses on biomedical image analysis problems that can be phrased as image-level classification, semantic segmentation, instance segmentation, or object detection task. The current version is based on a Delphi process on metrics conducted by an international consortium of image analysis experts from more than 60 institutions worldwide. © 2021, CC BY.

关键词： Medical imaging

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Satisfactory analysis for cosmetic product review comments 17

Satisfactory analysis for cosmetic product review comments

引用

2017 International Conference on Data Mining, Communications and Information Technology, DMCIT 2017

作者： Pugsee, Pakawan Sombatsri, Patcharaporn Juntiwakul, Rujiporn Innovative Network and Software Engineering Technology Laboratory Department of Mathematics and Computer Science Faculty of Science Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781450352185

Nowadays, there are various types of cosmetic products and brands. Searching and studying information about cosmetic products from reviews are more important because most people use comments from others to help make purchase decisions. They will have trouble with a lot of cosmetic product reviews. Moreover, it takes a long time to search and read all, and it is difficult to make decisions. Therefore, this paper proposed satisfactory conclusion for cosmetic product review comments to analyze the positive and negative information about various cosmetic products by sentiment analysis. The implemented methods use Naïve Bay Classifier as a machine learning to automatically classify positive or negative comments on cosmetic products. The testing results show that the classification application has high accuracy and precision on both positive and negative comments. However, it is necessary to use positive and negative data in a similar proportion to train the classification application for efficiency result. © 2017 Association for Computing Machinery.

关键词： Sentiment analysis

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Investigating the accuracy of test code size prediction using use case metrics and machine learning algorithms: An empirical study 17

Investigating the accuracy of test code size prediction usin...

引用

2017 International Conference on Machine Learning and Soft Computing, ICMLSC 2017

作者： Badri, Mourad Badri, Linda Flageol, William Toure, Fadel Software Engineering Research Laboratory Department of Mathematics and Computer Science University of Quebec Trois-RivièresQC Canada

ISBN: (纸本)9781450348287

software testing plays a crucial role in software quality assurance. It is, however, a time and resource consuming process. It is, therefore, important to predict as soon as possible the effort required to test software, so that activities can be planned and resources can be optimally allocated. Test code size, in terms of Test Lines Of Code (TLOC), is an important testing effort indicator used in many empirical studies. In this paper, we investigate empirically the early prediction of TLOC for objectoriented software using use case metrics. We used different machine learning algorithms (linear regression, k-NN, Naïve Bayes, C4.5, Random Forest, and Multilayer Perceptron) to build the prediction models. We performed an empirical study using data collected from five Java projects. The use case metrics have been compared to the well-known Use Case Points (UCP) method. Results show that the use case metrics-based approach gives a more accurate prediction of TLOC than the UCP method. © 2017 ACM.

关键词： software testing

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The science case and challenges of spaceborne sub-millimeter interferometry: the study case of TeraHertz Exploration and Zooming-in for Astrophysics (THEZA)

The science case and challenges of spaceborne sub-millimeter...

引用

IAF Symposium on Ongoing and Near Future Space Astronomy and Solar-System science Missions 2021 at the 72nd International Astronautical Congress, IAC 2021

作者： Gurvits, Leonid I. Paragi, Zsolt Amils, Ricardo I. van Bemmel, Ilse Boven, Paul Casasola, Viviana Conway, John Davelaar, Jordy Díez-González, M. Carmen Falcke, Heino Fender, Rob Frey, Sándor Fromm, Christian M. Gallego-Puyol, Juan D. García-Miró, Cristina Garrett, Michael A. Giroletti, Marcello Goddi, Ciriaco Gómez, José L. van der Gucht, Jeffrey Guirado, José Carlos Haiman, Zoltán Helmich, Frank Hudson, Ben Humphreys, Elizabeth Impellizzeri, Violette Janssen, Michael Johnson, Michael D. Kovalev, Yuri Y. Kramer, Michael Lindqvist, Michael Linz, Hendrik Liuzzo, Elisabetta Lobanov, Andrei P. López-Fernández, Isaac Malo-Gómez, Inmaculada Masania, Kunal Mizuno, Yosuke Plavin, Alexander V. Rajan, Raj T. Rezzolla, Luciano Roelofs, Freek Ros, Eduardo Rygl, Kazi L.J. Savolainen, Tuomas Schuster, Karl Venturi, Tiziana Verkouter, Harro de Vicente, Pablo Visser, Pieter N.A.M. Wiedner, Martina C. Wielgus, Maciek Wiik, Kaj Zensus, J. Anton Joint Institute for VLBI ERIC Dwingeloo Netherlands Department of Astrodynamics and Space Missions Delft University of Technology Delft Netherlands Yebes Observatory IGN Spain INAF Institute of Radio Astronomy Bologna Italy Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory Onsala Sweden Department of Astronomy and Astrophysics Laboratory Columbia University New YorkNY10027 United States Center for Computational Astrophysics Flatiron Institute 162 Fifth Avenue New YorkNY10010 United States Radboud University Nijmegen Netherlands Oxford University United Kingdom Konkoly Observatory Res. Centre for Astronomy and Earth Sciences Budapest Hungary Institute of Physics ELTE Eötvös Loránd University Budapest Hungary Goethe-Universität Frankfurt Germany Jodrell Bank Centre for Astrophysics The University of Manchester United Kingdom Leiden Observatory Leiden University Netherlands Instituto de Astrofísica de Andalucía – CSIC Granada Spain Observatorio Astronómico University of Valencia Spain SRON Netherlands Institute for Space Research Netherlands Kapteyn Institute University of Groningen Netherlands KISPE Space Systems Limited United Kingdom ESO Garching Germany Max-Planck-Institut für Radioastronomie Auf dem Hügel 69 BonnD-53121 Germany Center for Astrophysics Harvard & Smithsonian CambridgeMA02138 United States Black Hole Initiative Harvard University CambridgeMA02138 United States Astro Space Center Lebedev Physical Institute Moscow Russia Moscow Institute of Physics and Technology Dolgoprudnyi Russia Max Planck Institute for Astronomy Heidelberg Germany Shaping Matter Lab Faculty of Aerospace Engineering TU Delft Netherlands Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft Netherlands Aalto University Department of Electronics and Nanoengineering Finland Aalto University Metsähovi Radio Observatory Finland IRAM Grenoble France Observ

ISBN: (纸本)9781713843009

Ultra-high angular resolution in astronomy has always been an important vehicle for making fundamental discoveries. Recent results in direct imaging of the vicinity of the super-massive black hole in the nucleus of the radio galaxy M87 by the millimeter VLBI system Event Horizon Telescope (EHT) and various pioneering results of the Space VLBI mission RadioAstron provided new momentum in high angular resolution astrophysics. In both mentioned cases, the angular resolution reached the values of about 10−20 microrcseconds (0.05−0.1 nanoradian). Angular resolution is proportional to the observing wavelength and inversely proportional to the interferometer baseline length. In the case of Earth-based EHT, the highest angular resolution was achieved by combining the shortest possible wavelength of 1.3 mm with the longest possible baselines, comparable to the Earth’s diameter. For RadioAstron, operational wavelengths were in the range from 92 cm down to 1.3 cm, but the baselines were as long as ∼350,000 km. However, these two highlights of radio astronomy, EHT and RadioAstron do not"saturate" the interest to further increase in angular resolution. Quite opposite: the science case for further increase in angular resolution of astrophysical studies becomes even stronger. A natural and, in fact, the only possible way of moving forward is to enhance mm/sub-mm VLBI by extending baselines to extraterrestrial dimensions, i.e. creating a mm/sub-mm Space VLBI system. The inevitable move toward space-borne mm/sub-mm VLBI is a subject of several concept studies. In this presentation we will focus on one of them called TeraHertz Exploration and Zooming-in for Astrophysics (THEZA), prepared in response to the ESA’s call for its next major science program Voyage 2050 (Gurvits et al. 2021). The THEZA rationale is focused at the physics of spacetime in the vicinity of super-massive black holes as the leading science drive. However, it will also open up a sizable new range of hitherto unrea

关键词： Astrophysics

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Cloud workload prediction based on workflow execution time discrepancies

arXiv

引用

arXiv 2018年

作者： Kecskemeti, Gabor Nemeth, Zsolt Kertesz, Attila Ranjan, Rajiv Department of Computer Science Liverpool John Moores University Laboratory of Parallel and Distributed Systems MTA SZTAKI Software Engineering Department University of Szeged School of Computing Newcastle University

Infrastructure as a service clouds hide the complexity of maintaining the physical infrastructure with a slight disadvantage: they also hide their internal working details. Should users need knowledge about these details e.g., to increase the reliability or performance of their applications, they would need solutions to detect behavioural changes in the underlying system. Existing runtime solutions for such purposes offer limited capabilities as they are mostly restricted to revealing weekly or yearly behavioural periodicity in the infrastructure. This article proposes a technique for predicting generic background workload by means of simulations that are capable of providing additional knowledge of the underlying private cloud systems in order to support activities like cloud orchestration or workflow enactment. Our technique uses long-running scientific workflows and their behaviour discrepancies and tries to replicate these in a simulated cloud with known (trace-based) workloads. We argue that the better we can mimic the current discrepancies the better we can tell expected workloads in the near future on the real life cloud. We evaluated the proposed prediction approach with a biochemical application on both real and simulated cloud infrastructures. The proposed algorithm has shown to produce significantly (∼20%) better workload predictions for the future of simulated clouds than random workload selection. Copyright © 2018, The Authors. All rights reserved.

关键词： Infrastructure as a service (IaaS)

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Real-time and generic queue time estimation based on mobile crowdsensing

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Frontiers of computer science 2017年第1期11卷 49-60页

作者： Jiangtao WANG Yasha WANG Daqing ZHANG Leye WANG Chao CHEN Jae Woong LEE Yuanduo HE Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing 100871 China School of Electronics Engineering and Computer Science Peking University Beijing 100871 China Beida (Binhai) Information Research Tianjin 300450 China National Engineering Research Center of Software Engineering Peking University Beijing 100871 China Network & Services Department Institut Mines-Telecom/Telecom SudParis Evry 91011 France Department of Computer Science Chongqing University Chongqing 400044 China Department of Mathematics and Computer Science University of Central Missouri Warrensburg MO 64093 USA

People often have to queue for a busy service in many places around a city, and knowing the queue time can be helpful for making better activity plans to avoid long queues. Traditional solutions to the queue time monitoring are based on pre-deployed infrastructures, such as cameras and infrared sensors, which are costly and fail to deliver the queue time information to scattered citizens. This paper presents CrowdQTE, a mobile crowdsensing system, which utilizes the sensor-enhanced mobile devices and crowd hu- man intelligence to monitor and provide real-time queue time information for various queuing scenarios. When people are waiting in a line, we utilize the accelerometer sensor data and ambient contexts to automatically detect the queueing behav- ior and calculate the queue time. When people are not waiting in a line, it estimates the queue time based on the information reported manually by participants. We evaluate the perfor- mance of the system with a two-week and 12-person deploy- ment using commercially-available smartphones. The results demonstrate that CrowdQTE is effective in estimating queu- ing status.

关键词： mobile crowdsensing queue time estimation opportunistic and participatory sensing

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A Time Effect based Collaborative Filtering Approach for User Preference Statistics and Recommendation

引用

Journal of Physics: Conference Series 2020年第1期1453卷

作者： Yuxi Chen Xiaotong Zhang Qing Zhao Faheem Akhtar School of Statistics and Mathematics Country Central University of Finance and Economics Beijing 100081 China Harpur College of Arts and Sciences Binghamton University-SUNY New York 13902 America Faculty of Information Technology Beijing University of Technology Beijing 100124 China. Department of Computer Science Vrije Universiteit Amsterdam 1081 HV The Netherlands School of Software Engineering Beijing University of Technology Beijing Engineering Research Center for IoT Software and Systems Beijing 100124 China Department of Computer Science Sukkur IBA University Sukkur 65200 Pakistan

With the rapid development of the information technologies in the financial field, extracting meaningful information from a massive amount of data is hugely significant for efficient business decision making. The recommendation system is an intelligent system that applies historical knowledge of users to infer their preferences and make a personalized recommendation. However, it suffers from the problem of time effect of user's behaviour, which means a user's interests may change over time. To overcome this problem, we propose a time effect based collaborative filtering approach to adaptively statistics the change of user preferences. Firstly, Item-based collaborative filtering is used to calculate rating similarity between items. Since an Item-based collaborative filtering algorithm doesn't consider the time effect; next, the time decay function is proposed to statistics the change of user interests. Experimental results show that the proposed scheme retained higher accuracy compare to traditional collaborative filtering method.

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Secure Beamforming Design for MISO SWIPT systems: An Indirectly Optimized Approach

Secure Beamforming Design for MISO SWIPT Systems: An Indirec...

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2019 IEEE Global Communications Conference (GLOBECOM)

作者： Yao Yu Siyu Wang Shumei Liu Lei Guo Zhaolong Ning Shimin Gong Mohammad S. Obaidat School of Computer Science and Engineering Northeastern University Shenyang China Chongqing University of Posts and Telecommunications China State Key Laboratory for Novel Software Technology Nanjing University China School of Intelligent Systems Engineering Sun Yat-sen University China ECE Department Nazarbayev University Astana Kazakhstan College of Computing and Informatics University of Sharjah UAE The King Abdullah II School of Information Technology The University of Jordan Amman Jordan University of Science and Technology Beijing China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

By considering the Simultaneous Wireless Information and Power Transfer (SWIPT) schemes, this paper focuses on secure transmission model design in multiple-input-single-output (MISO) channels. In these channels, the channel state information is assumed to be perfect. Our objective is to maximize the worst-case secrecy rate with respect to both potential eavesdroppers and obvious eavesdroppers under the constraints of energy-harvesting and total transmission power. We present an optimization model to indirectly obtain maximum security rate in a single receiver system. Due to the high computational complexity of the solution process caused by the formulated non-convex optimization problem, we propose a novel indirect method to handle this issue. Then, a Semi-Definite Programming (SDP) relaxation method is used to approach the optimal solution. Moreover, we reveal the conditions for ensuring that the above semi-definite relaxation is compact. Simulation results demonstrate that the gained performance in our system is much better than those of the existing competing schemes.

关键词： Receivers Interference Signal to noise ratio Transmitters Optimization Security Communication system security

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The repertoire of mutational signatures in human cancer (vol 578, pg 94, 2020)

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NATURE 2023年第7948期614卷 E41-E41页

作者： Alexandrov, Ludmil B. Kim, Jaegil Haradhvala, Nicholas J. Huang, Mi Ni Ng, Alvin Wei Tian Wu, Yang Boot, Arnoud Covington, Kyle R. Gordenin, Dmitry A. Bergstrom, Erik N. Islam, S. M. Ashiqul Lopez-Bigas, Nuria Klimczak, Leszek J. McPherson, John R. Morganella, Sandro Sabarinathan, Radhakrishnan Wheeler, David A. Mustonen, Ville Getz, Gad Rozen, Steven G. Stratton, Michael R. Department of Cellular and Molecular Medicine Department of Bioengineering Moores Cancer Center University of California San Diego CA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Cellular and Molecular Medicine and Department of Bioengineering University of California San Diego La Jolla CA USA UC San Diego Moores Cancer Center San Diego CA USA University of California San Diego San Diego CA USA Broad Institute of MIT and Harvard Cambridge MA USA Center for Cancer Research Massachusetts General Hospital Boston MA USA Massachusetts General Hospital Boston MA USA Department of Pathology Massachusetts General Hospital Boston MA USA Harvard Medical School Boston MA USA Laboratory for Medical Science Mathematics RIKEN Center for Integrative Medical Sciences Yokohama Japan Computational Biology Program Ontario Institute for Cancer Research Toronto ON Canada Programme in Cancer & Stem Cell Biology Duke-NUS Medical School Singapore Singapore Centre for Computational Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Duke-NUS Medical School Singapore Singapore Programme in Cancer and Stem Cell Biology Centre for Computational Biology Duke-NUS Medical School Singapore Singapore SingHealth Duke-NUS Institute of Precision Medicine National Heart Centre Singapore Singapore Singapore Cancer Science Institute of Singapore National University of Singapore Singapore Singapore Institute of Molecular and Cell Biology Singapore Singapore Laboratory of Cancer Epigenome Division of Medical Science National Cancer Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore Human Genome Sequencing Center Baylor College of Medicine Houston TX USA Dan L. Duncan Cancer Center Baylor College of Medicine Houston TX USA Department of Molecular and Human Genetics Baylor College of Medicine Houston TX USA Genome Integrity and Structural Biology Laboratory National Ins

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