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arXiv 2021年

作者： Huang, Jiahao Ding, Weiping Lv, Jun Yang, Jingwen Dong, Hao Del Ser, Javier Xia, Jun Ren, Tiaojuan Wong, Stephen T. Yang, Guang College of Information Science and Technology Zhejiang Shuren University Hangzhou310015 China National Heart and Lung Institute Imperial College London London United Kingdom School of Information Science and Technology Nantong University Nantong226019 China School of Computer and Control Engineering Yantai University Yantai264005 China Department of Prosthodontics Peking University School Hospital of Stomatology Beijing China Center on Frontiers of Computing Studies Peking University Beijing China Derio48160 Spain Bilbao48013 Spain Department of Radiology Shenzhen Second People’s Hospital The First Affiliated Hospital of Shenzhen University Health Science Center Shenzhen China Systems Medicine and Bioengineering Department Houston Methodist Cancer Center HoustonTX77030 United States Department of Radiology Houston Methodist Hospital Weill Cornell Medicine HoustonTX77030 United States Cardiovascular Research Centre Royal Brompton Hospital London United Kingdom

In clinical medicine, magnetic resonance imaging (MRI) is one of the most important tools for diagnosis, triage, prognosis, and treatment planning. However, MRI suffers from an inherent slow data acquisition process because data is collected sequentially in k-space. In recent years, most MRI reconstruction methods proposed in the literature focus on holistic image reconstruction rather than enhancing the edge information. This work steps aside this general trend by elaborating on the enhancement of edge information. Specifically, we introduce a novel parallel imaging coupled dual discriminator generative adversarial network (PIDD-GAN) for fast multi-channel MRI reconstruction by incorporating multi-view information. The dual discriminator design aims to improve the edge information in MRI reconstruction. One discriminator is used for holistic image reconstruction, whereas the other one is responsible for enhancing edge information. An improved U-Net with local and global residual learning is proposed for the generator. Frequency channel attention blocks (FCA Blocks) are embedded in the generator for incorporating attention mechanisms. Content loss is introduced to train the generator for better reconstruction quality. We performed comprehensive experiments on Calgary-Campinas public brain MR dataset and compared our method with state-of-the-art MRI reconstruction methods. Ablation studies of residual learning were conducted on the MICCAI13 dataset to validate the proposed modules. Results show that our PIDD-GAN provides high-quality reconstructed MR images, with well-preserved edge information. The time of single-image reconstruction is below 5ms, which meets the demand of faster processing. © 2021, CC BY-NC-ND.

关键词： Generative adversarial networks

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Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2021年 12856 LNCS卷 v页

作者： Hernández-Leo, Davinia Hishiyama, Reiko Zurita, Gustavo Weyers, Benjamin Nolte, Alexander Ogata, Hiroaki Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona Spain Department of Management Control and Information Systems University of Chile Santiago Chile Institute of Computer Science University of Tartu Tartu Estonia School of Creative Science Waseda University Tokyo Japan Human-Computer Interaction Group University of Trier Trier Germany Academic Center for Computing and Media Studies Kyoto University Kyoto Japan

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Fuzzy controller of Pathological Conditions Diagnosis based on Analysis of Cytological Images 8

Fuzzy Controller of Pathological Conditions Diagnosis based ...

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8th International Conference Advanced Computer information Technologies, ACIT 2018

作者： Dubchak, Lesia Verbovyy, Serhiy Verbova, Olena Vasylkiv, Nadiia Department of Computer Engineering Ternopil National Economic University Ternopil 8 Chekhova str. Ukraine Department of Information and Computing Systems and Control Ternopil National Economic University 11 Lvivska str. Ternopil Ukraine

In this article authors proposed the fuzzy controller for the correct diagnosis of the breast pathological states. This mean can be used in medical practice by the cytologist as an additional way of diagnosis confirmi... 详细信息

ISBN: (纸本)9789666544899

关键词： Diagnosis

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Sensor attack correction for linear systems with known inputs

Sensor attack correction for linear systems with known input...

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作者： Tang, Zhanghan Kuijper, Margreta Chong, Michelle Mareels, Iven Leckie, Christopher School of Electrical and Electronic Engineering University of Melbourne Australia Department of Automatic Control KTH Royal Institute of Technology Sweden IBM Research Australia Australia School of Computing and Information Systems University of Melbourne Australia

We address the problem of attack detection and attack correction for multi-input multi-output discrete-time linear time-invariant systems under sensor attacks. More specifically, we consider the situation that a system with known input is corrupted by additive adversarial attack signals on some of the system's outputs. In this paper, we use system representation in a behavioural approach, which allows for natural and compact statements regarding linear system security. We extend our earlier results for systems with zero inputs to systems with non-zero inputs. We assume that these non-zero inputs are known. © 2018

关键词： Error correction

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Corrigendum: Qubit models of weak continuous measurements: Markovian conditional and open-system dynamics (2018 Quantum Sci. Technol. 3 024005)

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Quantum Science and Technology 2022年第2期7卷 029501-029501页

作者： Jonathan A Gross Carlton M Caves Gerard J Milburn Joshua Combes Center for Quantum Information and Control University of New Mexico Albuquerque NM 87131-0001 United States of America Centre for Engineered Quantum Systems School of Mathematics and Physics The University of Queensland St. Lucia QLD 4072 Australia Department of Applied Mathematics Institute for Quantum Computing University of Waterloo Waterloo ON Canada Perimeter Institute for Theoretical Physics 31 Caroline St. N Waterloo Ontario N2L 2Y5 Canada

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OER: Six Perspectives on Global Misconceptions and Challenges

OER: Six Perspectives on Global Misconceptions and Challenge...

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IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE)

作者： Dave Towey Sorel Reisman Henry Chan Claudio Demartini Edmundo Tovar Tiziana Margaria School of Computer Science University of Nottingham Ningbo China Ningbo People’s Republic of China Department of Information Systems and Decision Sciences California State University Fullerton Fullerton U.S.A. Department of Computing The Hong Kong Polytechnic University Hong Kong China Control & Computer Engineering Department Politecnico di Torino Turin Italy School of Computer Engineers Universidad Politécnica de Madrid Madrid Spain Department of Computer Science and Information Systems University of Limerick Limerick Ireland

ISBN: (数字)9781728126654

ISBN: (纸本)9781728126661

Open Educational Resources (OERs) are freely accessible materials for teaching, learning, and research that have been made available such that they can be freely used, modified, and shared. Prompted by the potential positive impact that OERs can have, a growing community of OER enthusiasts has been advocating for their adoption in higher education, and elsewhere. The growing demand for computer science education and training (especially in areas related to artificial intelligence, machine learning, and big data) has led to speculation as to how OERs may be best leveraged to support such teaching and learning. The recent occasion of an international OER workshop at the 2019 IEEE Conference on Computers, Software and Applications (COMPSAC) allowed for six OER enthusiasts, all with extensive OER experience, to reflect on the status of OER adoption and understanding. These reflections, addressing misconceptions and challenges, form the basis for this paper.

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Application of Cognitive Changes Markers for Diagnostics’ Purposes and in Neurofeedback Therapy

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IFAC-PapersOnLine 2019年第27期52卷 520-523页

作者： Magda Zolubak Mariusz Pelc Michal Podpora Wojciech Chlewicki Katarzyna Cichon Aleksandra Kawala-Sterniuk Opole University of Technology - Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland West Pomeranian University of Technology in Szczecin - Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland University of Greenwich - Department of Computing and Information Systems - Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK

Thanks to the automation of diagnostic processes based on the EEG signal and the creation of classifications of various attention disorders based on the analysis of the EEG signals (as diagnostic markers) - it may be possible to refer patients to appropriate specialists and provide them with appropriate neurofeedback-based treatment. The marker method proposed by the authors of the hereof paper is based on analysis of the EEG, which signal can be widely use in screening diagnostics. The proposed solution in this work may be used for neurofeedback or Brain Computer Interfaces (BCI). In this paper the authors presented implementation of markers for the purpose of analysis of some memory disorders and short-time attention disorder. The study is still in progress. Presented results have initial-study character.

关键词： EEG neurofeedback BCI algoritms

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Integrated approach to user authentication based on handwritten signature 8

Integrated approach to user authentication based on handwrit...

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8th All-Russian Scientific and Technical Conference on Secure information Technologies, BIT 2017

作者： Kostyuchenko, Evgeny Krivonosov, Egor Shelupanov, Alexander Department of Complex Information Security and Electronic Computing Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

A new approach to the integration of the results of several tools aimed at solving a single problem is considered. The approach is illustrated by the example of solving the authentication task for signature dynamics based on the naive Bayesian classifier and the neural network. The approach guarantees results not worse than any of the classifiers separately from the point of view of a monotonous combination of the probabilities of errors of the first and second kind. The obtained results can be applied in the construction of a multifactor authentication system.

关键词： Authentication

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Behavioural Approach to Network Anomaly Detection for Resource-Constrained System – Presentation of the Novel Solution – Preliminary Study

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IFAC-PapersOnLine 2019年第27期52卷 121-126页

作者： Mariusz Pelc Dawid Galus Magda Zolubak Stepan Ozana Wojciech Chlewicki Katarzyna Cichon Michal Podpora Aleksandra Kawala-Sterniuk Opole University of Technology – Faculty of Electrical Engineering Automatic Control and Informatics ul. Proszkowska 76 45-758 Opole Poland University of Greenwich – Department of Computing and Information Systems – Faculty of Architecture Computing and Humanities Old Royal Naval College Park Row SE10 9LS London UK VSB – Technical University Ostrava – FEECS Department of Cybernetics and Biomedical Engineering Ostrava Czech Republic West Pomeranian University of Technology in Szczecin – Faculty of Electrical Engineering ul. Sikorskiego 37 70-313 Szczecin Poland

In this paper some preliminary results of network anomaly detection for resource-constrained systems have been presented. All described algorithms are embedded into a three-tier system application. The presented solution is a response to nowadays trends in computer/network security domain that indicate gradual shifting from signature-based anomaly detection typically based on some selected statistical measures toward systems that are based on behavioural analysis of computer systems and/or networks. The presented system requirements, explain relevant terminology as well as we include some selected results and their analysis. The solution is potentially destined for very resource-constrained systems (IoT specifically), all tests were carried out in an example network to additionally analyse their effect of the presented approach on the computer resources.

关键词： Network Anomaly Detection Behavioural Analysis Internet of Things

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Challenges in differentiating between attention disorders based on EEG recordings in neurofeedback therapy

Challenges in differentiating between attention disorders ba...

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Applications of Electromagnetics in Modern Techniques and Medicine (PTZE)

作者： Żołubak Magda Pelc Mariusz Kawala-Janik Aleksandra Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computing and Information Systems University of Greenwitch Greenwitch England

The aim of this article is to show problems with the analysis of various cognitive disorders in the registered EEG signal and the effects of the neurofeedback therapy. Most of the disorders tested in ICD-10 have electroencephalographic readings associated with Beta bands and slow waves. All problems with attention deficit have similar records in the EEG signal and similar training protocols are used in their therapy and the results of the therapy are visible in more than 10 training sessions.

关键词： Electroencephalography Training Neurofeedback Medical treatment Protocols Cancer Pediatrics

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