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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for Computer Graphics, EG 2019

作者： Langenfeld, Florent Axenopoulos, Apostolos Benhabiles, Halim Daras, Petros Giachetti, Andrea Han, Xusi Hammoudi, Karim Kihara, Daisuke Lai, Tuan M. Liu, Haiguang Melkemi, Mahmoud Mylonas, Stelios K. Terashi, Genki Wang, Yufan Windal, Feryal Montes, Matthieu Laboratoire GBCM EA7528 Conservatoire National des Arts-et-Métiers 2 rue Conté Paris75003 France Team Information Technologies Institute Centre for Research and Technology Hellas Greece ISEN-Lille Yncréa Hauts de France Department of Computer Science Università di Verona Strada le Grazie 15 Verona37134 Italy Department of Biological Sciences Purdue University West LafayetteIN United States Université Haute-Alsace IRIMAS EA 7499 MulhouseF-68100 France Department of Computer Science Purdue University West LafayetteIN United States Complex Systems Division Beijing Computational Science Research Center Beijing100193 China School of Software Engineering University of Science and Technology China Suzhou Jiangsu215123 China

ISBN: (纸本)9783038680772

This track aimed at retrieving protein evolutionary classification based on their surfaces meshes only. Given that proteins are dynamic, non-rigid objects and that evolution tends to conserve patterns related to their activity and function, this track offers a challenging issue using biologically relevant molecules. We evaluated the performance of 5 different algorithms and analyzed their ability, over a dataset of 5,298 objects, to retrieve various conformations of identical proteins and various conformations of ortholog proteins (proteins from different organisms and showing the same activity). All methods were able to retrieve a member of the same class as the query in at least 94% of the cases when considering the first match, but show more divergent when more matches were considered. Last, similarity metrics trained on databases dedicated to proteins improved the results. © 2019 The Author(s)

关键词： Proteins

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Experimental cryptographic verification for near-term quantum cloud computing

arXiv

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arXiv 2018年

作者： Chen, Xi Cheng, Bin Li, Zhaokai Nie, Xinfang Yu, Nengkun Yung, Man-Hong Peng, Xinhua Hefei230026 China CAS Key Laboratory of Microscale Magnetic Resonance USTC Hefei230026 China Synergetic Innovation Center of Quantum Information and Quantum Physics USTC Hefei230026 China Institute for Quantum Science and Engineering Department of Physics Southern University of Science and Technology Shenzhen518055 China Centre for Quantum Software and Information School of Software Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and Technology Shenzhen518055 China Central Research Institute Huawei Technologies Shenzhen518129 China

Recently, there are more and more organizations offering quantum-cloud services, where any client can access a quantum computer remotely through the internet. In the near future, these cloud servers may claim to offer quantum computing power out of reach of classical devices. An important task is to make sure that there is a real quantum computer running, instead of a simulation by a classical device. Here we explore the applicability of a cryptographic verification scheme that avoids the need of implementing a full quantum algorithm or requiring the clients to communicate with quantum resources. In this scheme, the client encodes a secret string in a scrambled IQP (instantaneous quantum polynomial) circuit sent to the quantum cloud in the form of classical message, and verify the computation by checking the probability bias of a class of output strings generated by the server. We provided a theoretical extension and implemented the scheme on a 5-qubit NMR quantum processor in the laboratory and a 5-qubit and 16-qubit processors of the IBM quantum cloud. We found that the experimental results of the NMR processor can be verified by the scheme with about 2.5% error, after noise compensation by standard techniques. However, the fidelity of the IBM quantum cloud is currently too low to pass the test (about 42% error). This verification scheme shall become practical when servers claim to offer quantum-computing resources that can achieve quantum supremacy. Copyright © 2018, The Authors. All rights reserved.

关键词： Quantum theory

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The MR neuroimaging protocol for the Accelerating Medicines Partnership® Schizophrenia Program

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Schizophrenia 2025年第1期11卷 1-14页

作者： Harms, Michael P. Cho, Kang-Ik K. Anticevic, Alan Bolo, Nicolas R. Bouix, Sylvain Campbell, Dylan Cannon, Tyrone D. Cecchi, Guillermo Goncalves, Mathias Haidar, Anastasia Hughes, Dylan E. Izyurov, Igor John, Omar Kapur, Tina Kim, Nicholas Kotler, Elana Kubicki, Marek Kuperman, Joshua M. Laulette, Kristen Lindberg, Ulrich Markiewicz, Christopher Ning, Lipeng Poldrack, Russell A. Rathi, Yogesh Romo, Paul A. Tamayo, Zailyn Wannan, Cassandra Wickham, Alana Yassin, Walid Zhou, Juan Helen Addington, Jean Alameda, Luis Arango, Celso Breitborde, Nicholas J. K. Broome, Matthew R. Cadenhead, Kristin S. Calkins, Monica E. Chen, Eric Yu Hai Choi, Jimmy Conus, Philippe Corcoran, Cheryl M. Cornblatt, Barbara A. Diaz-Caneja, Covadonga M. Ellman, Lauren M. Fusar-Poli, Paolo Gaspar, Pablo A. Gerber, Carla Glenthøj, Louise Birkedal Horton, Leslie E. Hui, Christy Lai Ming Kambeitz, Joseph Kambeitz-Ilankovic, Lana Keshavan, Matcheri S. Kim, Sung-Wan Koutsouleris, Nikolaos Kwon, Jun Soo Langbein, Kerstin Mamah, Daniel Mathalon, Daniel H. Mittal, Vijay A. Nordentoft, Merete Pearlson, Godfrey D. Perez, Jesus Perkins, Diana O. Powers, Albert R. Rogers, Jack Sabb, Fred W. Schiffman, Jason Shah, Jai L. Silverstein, Steven M. Smesny, Stefan Stone, William S. Strauss, Gregory P. Thompson, Judy L. Upthegrove, Rachel Verma, Swapna K. Wang, Jijun Wolf, Daniel H. Kahn, Rene S. Kane, John M. McGorry, Patrick D. Nelson, Barnaby Woods, Scott W. Shenton, Martha E. Wood, Stephen J. Bearden, Carrie E. Pasternak, Ofer Department of Psychiatry Washington University School of Medicine St. Louis MO United States Department of Psychiatry Brigham and Women’s Hospital Harvard Medical School Boston MA United States Department of Psychiatry Yale University School of Medicine New Haven CT United States Department of Psychiatry Beth Israel Deaconess Medical Center Harvard Medical School Boston MA United States Department of Software Engineering and Information Technology École de technologie supérieure Montréal QC Canada Department of Psychology Yale University New Haven CT United States T.J. Watson Research Laboratory IBM Research Yorktown Heights NY United States Department of Psychology Stanford University Stanford CA United States Department of Psychology University of California Los Angeles CA United States Department of Psychiatry and Psychotherapy Jena University Hospital Jena Germany Massachusetts General Hospital Harvard Medical School Boston MA United States Department of Radiology Brigham and Women’s Hospital Harvard Medical School Boston MA United States Department of Radiology University of California San Diego CA United States Department of Clinical Physiology and Nuclear Medicine Copenhagen University Hospital - Rigshospitalet Glostrup Denmark Seaman Family MR Research Centre Calgary AB Canada Orygen Parkville VIC Australia Centre for Sleep and Cognition and Centre for Translational MR Research Yong Loo Lin School of Medicine National University of Singapore Singapore Singapore Department of Psychiatry Hotchkiss Brain Institute University of Calgary Calgary AB Canada General Psychiatry Service Treatment and Early Intervention in Psychosis Program Lausanne University Hospital and University of Lausanne Lausanne Switzerland Department of Child and Adolescent Psychiatry Institute of Psychiatry and Mental Health Hospital General Universitario Gregorio Marañón Instituto de Salud Carlos III School of Medicine Universidad Complutense Madrid Spain

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including the rationale for various choices. This protocol includes T1- and T2-weighted structural scans, resting-state fMRI, and diffusion-weighted imaging collected at two time points, approximately 2 months apart. We also present preliminary variance component analyses of several measures, such as signal- and contrast-to-noise ratio (SNR/CNR) and spatial smoothness, to provide quantitative data on the relative percentages of participant, site, and platform (i.e., scanner model) variance. Site-related variance is generally small (typically <10%). For the SNR/CNR measures from the structural and fMRI scans, participant variance is the largest component (as desired;40–76%). However, for SNR/CNR in the diffusion scans, there is substantial platform-related variance (>55%) due to differences in the diffusion imaging hardware capabilities of the different scanners. Also, spatial smoothness generally has a large platform-related variance due to inherent, difficult to control, differences between vendors in their acquisitions and reconstructions. These results illustrate some of the factors that will need to be considered in analyses of the AMP SCZ neuroimaging data, which will be the largest CHR cohort to date. Watch Dr. Harms discuss this article at https://vimeo.

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Publisher Correction: Global estimates on the number of people blind or visually impaired by cataract: a meta-analysis from 2000 to 2020

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Eye (London, England) 2024年第11期38卷 2229-2231页

作者： Konrad Pesudovs Hugh R. Taylor Tabassom Sedighi Rupert R. A. Bourne Shahina Pardhan Van Charles Lansingh John H. Kempen Ian Tapply Arthur G. Fernandes Maria Vittoria Cicinelli Alessandro Arrigo Nicolas Leveziel Serge Resnikoff Seth Flaxman Mukkharram M. Bikbov Tasanee Braithwaite Alain Bron Ching-Yu Cheng Monte A. Del Monte Joshua R. Ehrlich Leon B. Ellwein David Friedman João M. Furtado Gus Gazzard Ronnie George M. Elizabeth Hartnett Jost B. Jonas Rim Kahloun Moncef Khairallah Rohit C. Khanna Janet Leasher Julie-Anne Little Vinay Nangia Michal Nowak Tunde Peto Pradeep Ramulu Fotis Topouzis Mitiadis Tsilimbaris Ya Xing Wang Ningli Wang Paul Svitil Briant Theo Vos Katrin Burkart Kaleb Coberly Xiaochen Dai Stephen S. Lim Tomislav Mestrovic Ali H. Mokdad Christopher J. L. Murray Jaimie D. Steinmetz Awoke Misganaw Yohannes Habtegiorgis Abate Mohammad Abdollahi Mozhan Abdollahi Ayele Mamo Abebe Olumide Abiodun Richard Gyan Aboagye Woldu Aberhe Abrha Hasan Abualruz Hiwa Abubaker Ali Eman Abu-Gharbieh Salahdein Aburuz Tadele Girum Girum Adal Mesafint Molla Adane Isaac Yeboah Addo Qorinah Estiningtyas Sakilah Adnani Muhammad Sohail Afzal Muhammad Umair Shahin Aghamiri Bright Opoku Ahinkorah Aqeel Ahmad Sajjad Ahmad Ali Ahmadi Siamak Sabour Ayman Ahmed Haroon Ahmed Ahmad Samir Alfaar Abid Ali Syed Shujait Shujait Ali Awais Altaf Hubert Amu Emmanuel Manu Sofia Androudi Rodrigo Anguita Abhishek Anil Rimple Jeet Kaur Muhammad Aaqib Shamim Saeid Anvari Anayochukwu Edward Anyasodor Francis Appiah Jalal Arabloo Haleh Ayatollahi Mosab Arafat Damelash Areda Reza Arefnezhad Brhane Berhe Aregawi Akeza Awealom Asgedom Tahira Ashraf Seyyed Shamsadin Athari Bantalem Tilaye Tilaye Atinafu Birhan Tsegaw Taye Maha Moh’d Wahbi Atout Alok Atreya Ahmed Y. Azzam Hassan Babamohamadi Sara Bagherieh Yogesh Bahurupi Atif Amin Baig Shumaila Nargus Biswajit Banik Mainak Bardhan Saurav Basu Kavita Batra Nebiyou Simegnew Bayileyegn Fatemeh Bazvand Addisu Shunu Beyene Awoke Masrie Asrat Derese Devidas S. Bhagat Akshaya Srikanth Bhagavathula Pankaj Bh Medicine & Health University of New South Wales Sydney NSW Australia School of Optometry and Vision Science University of New South Wales Sydney NSW Australia School of Population and Global Health University of Melbourne Carlton VIC Australia Vision and Eye Research Institute Anglia Ruskin University Cambridge UK HelpMeSee Instituto Mexicano de Oftalmologia Santiago de Querétaro Mexico University of Miami Gables FL USA University of Utah Salt Lake City UT USA Chief Medical Office HelpMeSee New York NY USA Mexican Institute of Ophthalmology Queretaro Mexico Department of Ophthalmology Massachusetts Eye and Ear/Shepens Eye Research Institute/Harvard Medical School Boston MA USA Eye Unit MyungSung Christian Medical Center (MCM) Comprehensive Specialized Hospital and MyungSun Medical College Addis Ababa Ethiopia Department of Ophthalmology Addis Ababa University Addis Ababa Ethiopia Sight for Souls Bellevue WA USA Department of Ophthalmology Harvard University Boston MA USA Eye Unit MyungSung Medical College Addis Ababa Ethiopia Addenbrooke’s Hospital Cambridge UK Department of Ophthalmology Cambridge University Hospitals Cambridge UK Federal University of Sao Paolo Sao Paolo SP Brazil University of Calgary Calgary AB Canada Department of Ophthalmology and Visual Sciences Federal University of São Paulo Sao Paulo Brazil School of Medicine Vita-Salute San Raffaele University Milan Italy Department of Ophthalmology IRCCS San Raffaele Scientific Institute Milan Italy Department of Ophthalmology San Raffaele Scientific Institute Milano Italy IRCCS San Raffaele Scientific Institute Vita-Salute University Milan Italy Scientific Institute San Raffaele Hospital Vita-Salute University Milan Italy University of Poitiers Poitiers France CHU de Poitiers Poitiers France Ophthalmology Department CHU de Poitiers (Poitiers University Hospital) Poitiers France Unité 1084 National Institute of Health and Medical Research (INSERM) Poitiers France

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Framework for adaptive computation offloading in IoT applications 17

Framework for adaptive computation offloading in IoT applica...

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9th Asia-Pacific Symposium on Internetware, Internetware 2017

作者： Chen, Shihong Liu, Bichun Chen, Xing Zhang, Ying Huang, Gang College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Institute of Software School of Electronics Engineering and Computer Science Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China

ISBN: (纸本)1595930361

The internet of things (IoT) attracts great interest in many application domains concerned with monitoring and control of physical phenomena. IoT applications try to provide more and more functionality and then they inevitably become so complex as to make the limits of devices worse, which may lead to poor performance of applications. Computation offloading is a promising way to improve the performance of an IoT application by executing some parts of the application on remote devices or servers. However, supporting such capability is not easy for application developers due to (1) adaptability: IoT applications often face changes of runtime environments so that the adaptation on offloading is needed. (2) effectiveness: when the device context changes, it needs to dynamically decide the deployment plan of computation tasks, and the reduced execution time must be greater than the network delay and extra overheads caused by offloading. This paper proposes a framework which supports IoT applications with adaptive computation offloading capability. First, a design pattern is proposed to enable an application to be computation offloaded on-demand. Second, an estimation model is presented to automatically decide the deployment plan for offloading. Third, a framework is implemented to support the design pattern and the estimation model. A thorough zxevaluation on the real-world application is proposed, and the results show that our approach can help reduce execution time by over 45% in most scenarios.

关键词： computation offloading

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OPENREQ: Recommender systems in requirements engineering

OPENREQ: Recommender systems in requirements engineering

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2017 International Conference on Knowledge technologies and Data-Driven Business Workshop, i-Know-WS 2017

作者： Felfernig, Alexander Atas, Müslüm Stettinger, Martin Reiterer, Stefan Palomares, Cristina Falkner, Andreas Franch, Xavier Institute for Software Technology Inffeldgasse 16b/2 GrazA-8010 Austria Department of Service and Information System Engineering Calle Jordi Girona 1-3 BarcelonaESP-08034 Spain Siemens AG Austria Siemensstrasse 90 ViennaA-1210 Austria

The major focus of OPENREQ is the development of recommendation and decision technologies that efficiently support requirements engineering processes in large and distributed software projects. Example scenarios thereof are the bid management in industrial systems, requirements engineering in cross-plattform open source software development, and requirements management in large user communities (telecommunications sector). The aim of this paper is to provide an overview of OPENREQ and to provide insights into related application scenarios and research issues.

关键词： Requirements engineering

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Model-driven deep learning for physical layer communications

arXiv

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arXiv 2018年

作者： He, Hengtao Jin, Shi Wen, Chao-Kai Gao, Feifei Li, Geoffrey Ye Xu, Zongben National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Institute of Communications Engineering National Sun Yat-sen University Kaohsiung804 Taiwan State Key Lab of Intelligent Technologies and Systems Tsinghua University Department of Automation Tsinghua University Beijing China School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Institute for Information and System Sciences Xian Jiaotong University Xi'an710049 China

Intelligent communication is gradually becoming a mainstream direction. As a major branch of machine learning, deep learning (DL) has been applied in physical layer communications and demonstrated an impressive performance improvement in recent years. However, most of the existing works related to DL focus on data-driven approaches, which consider the communication system as a black box and train it by using a huge volume of data. Training a network requires sufficient computing resources and extensive time, both of which are rarely found in communication devices. By contrast, modeldriven DL approaches combine communication domain knowledge with DL to reduce the demand for computing resources and training time. This article discusses the recent advancements in model-driven DL approaches in physical layer communications, including transmission schemes, receiver design, and channel information recovery. Several open issues for future research are also highlighted. Copyright © 2018, The Authors. All rights reserved.

关键词： Deep learning

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A composition theorem for randomized query complexity via max conflict complexity ∗

arXiv

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arXiv 2018年

作者： Gavinsky, Dmitry Lee, Troy Santha, Miklos Sanyal, Swagato Institute of Mathematics Czech Academy of Sciences 115 67 Žitna 25 Praha 1 Czech Republic Centre for Quantum Software and Information Faculty of Engineering and Information Technology University of Technology Sydney Australia Centre for Quantum Technologies National University of Singapore Block S15 3 Science Drive 2 Singapore117543 Singapore IRIF Université Paris Diderot CNRS Paris75205 France MajuLab UMI 3654 Singapore Indian Institute of Technology Kharagpur

Let Rǫ(·) stand for the bounded-error randomized query complexity with error ǫ > 0. For any relation f ⊆ {0, 1}n × S and partial Boolean function g ⊆ {0, 1}m × {0, 1}, we show that R1/3(f ◦ gn) ∈ Ω(R4/9(f) · pR1/3(g)), where f ◦ gn ⊆ ({0, 1}m)n × S is the composition of f and g. We give an example of a relation f and partial Boolean function g for which this lower bound is tight. We prove our composition theorem by introducing a new complexity measure, the max conflict complexity χ¯(g) of a partial Boolean function g. We show χ¯(g) ∈ Ω(pR1/3(g)) for any (partial) function g and R1/3(f ◦ gn) ∈ Ω(R4/9(f) · χ¯(g));these two bounds imply our composition result. We further show that χ¯(g) is always at least as large as the sabotage complexity of g, introduced by Ben-David and Kothari [BK16]. Copyright © 2018, The Authors. All rights reserved.

关键词： Boolean functions

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Identification of electrical equivalent circuits of research objects by phase-frequency characteristics

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IOP Conference Series: Materials Science and engineering 2020年第3期862卷

作者： Svetlana N Medvedeva Vladimir I Chernetsov Mikhail V Chernetsov Margarita M Chernetsova Penza State University Department of Power and Electrical Engineering 440026 40 Krasnaya St. Penza Russia Penza Cossack Institute of Technology (branch) of K.G. Razumovsky Moscow State University of Technologies and Management (the First Cossack University) Department of Technical Service and Power Engineering 440039 11a Gagarin St. Bldg. 12 Penza Russia Penza State Technological University Department of Technical Quality Management 440039 1a Baidukov Ave./11 Gagarin St. Penza Russia Bauman Moscow State Technical University Department of Computer Software and Information Technologies 105005 5 2nd Baumanskaya St. Bldg. 1 Moscow Russia

The paper discusses methods for identifying electrical equivalent circuits of the studied object based on the analysis of phase-frequency and differential phase-frequency characteristics of the output signal in a wide frequency range, using MathCAD software. As a result, the following possibilities are revealed: establishing a method for connecting several electrical links of the same type in a single electrical circuit; identification of topology of bipolar electrical equivalent circuits for parametric sensors of various types, both separately and as part of bipolar electrical circuits; identification of equivalent circuits of metal-insulator-semiconductor (MIS) structures described by equivalent amplitude-frequency characteristics. A technique for the analysis of electrical equivalent circuits is proposed, based on the study of phase characteristics in the coordinates of phase-frequency and differential-frequency dependencies, called by the authors as 'phase portraits' of equivalent circuits of the parametric research object, which allowed determining changes in the values of the equivalent circuit elements. This approach is promising from a metrological point of view, since in measuring phase-frequency parameters, frequency being the most stable parameter measured with very high accuracy compared to other analog values, can be used as a measure to increase the objectivity of the analysis result.

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An attention-based approach for single image super resolution

arXiv

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arXiv 2018年

作者： Liu, Yuan Wang, Yuancheng Li, Nan Cheng, Xu Zhang, Yifeng Huang, Yongming Lu, Guojun School of Information Science and Engineering Southeast University Nanjing210096 China Nanjing Institute of Communications Technologies Nanjing211100 China State Key Lab. for Novel Software Technology Nanjing University Nanjing210093 China School of automation Southeast University Nanjing210096 China Faculty of Science and Technology Federation University Australia Melbourne Australia

The main challenge of single image super resolution (SISR) is the recovery of high frequency details such as tiny textures. However, most of the state-of-the-art methods lack specific modules to identify high frequency areas, causing the output image to be blurred. We propose an attention-based approach to give a discrimination between texture areas and smooth areas. After the positions of high frequency details are located, high frequency compensation is carried out. This approach can incorporate with previously proposed SISR networks. By providing high frequency enhancement, better performance and visual effect are achieved. We also propose our own SISR network composed of DenseRes blocks. The block provides an effective way to combine the low level features and high level features. Extensive benchmark evaluation shows that our proposed method achieves significant improvement over the state-of-the-art works in SISR. Copyright © 2018, The Authors. All rights reserved.

关键词： Textures

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