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arXiv 2019年

作者： Pipoli, Giuseppe Department of Information Engineering Computer Science and Mathematics Università degli Studi dell’Aquila via Vetoio 1 L’Aquila67100 Italy

We classify the translators to the mean curvature flow in the three-dimensional solvable group Sol3 that are invariant under the action of a one-parameter group of isometries of the ambient space. In particular we show that Sol3 admits graphical translators defined on a half-plane, in contrast with a rigidity result of Shahriyari [Sh] for translators in the Euclidean space. Moreover we exhibit some non-existence *** Codes 53A10, 53C42, 53C44 Copyright © 2019, The Authors. All rights reserved.

关键词： Sols

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Diagnosing COVID-19 pneumonia from x-ray and ct images using deep learning and transfer learning algorithms

arXiv

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arXiv 2020年

作者： Maghdid, Halgurd S. Asaad, Aras T. Ghafoor, Kayhan Zrar Sadiq, Ali Safaa Khan, Muhammad Khurram Department of Software Engineering Faculty of Engineering Koya University Kurdistan Region-F.R. Iraq Oxford Drug Design Oxford Centre for Innovation OxfordOX1 1BY United Kingdom Department of Software Engineering Salahaddin University-Erbil Iraq School of Mathematics and Computer Science University of Wolverhampton Wulfruna Street WolverhamptonWV1 1LY United Kingdom Centre of Excellence in Information Assurance King Saud University Riyadh Saudi Arabia

COVID-19 (also known as 2019 Novel Coronavirus) first emerged in Wuhan, China and spread across the globe with unprecedented effect and has now become the greatest crisis of the modern era. The COVID-19 has proved much more pervasive demands for diagnosis that has driven researchers to develop more intelligent, highly responsive and efficient detection methods. In this work, we focus on proposing AI tools that can be used by radiologists or healthcare professionals to diagnose COVID-19 cases in a quick and accurate manner. However, the lack of a publicly available dataset of X-ray and CT images makes the design of such AI tools a challenging task. To this end, this study aims to build a comprehensive dataset of X-rays and CT scan images from multiple sources as well as provides a simple but an effective COVID-19 detection technique using deep learning and transfer learning algorithms. In this vein, a simple convolution neural network (CNN) and modified pretrained AlexNet model are applied on the prepared X-rays and CT scan images dataset. The result of the experiments shows that the utilized models can provide accuracy up to 98% via pretrained network and 94.1% accuracy by using the modified CNN. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

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Benchmark problems for transcranial ultrasound simulation: Intercomparison of compressional wave models

arXiv

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arXiv 2022年

作者： Aubry, Jean-Francois Bates, Oscar Boehm, Christian Pauly, Kim Butts Christensen, Douglas Cueto, Carlos Gélat, Pierre Guasch, Lluis Jaros, Jiri Jing, Yun Jones, Rebecca Li, Ningrui Marty, Patrick Montanaro, Hazael Neufeld, Esra Pichardo, Samuel Pinton, Gianmarco Pulkkinen, Aki Stanziola, Antonio Thielscher, Axel Treeby, Bradley Van't Wout, Elwin Physics for Medicine Paris INSERM U1273 ESPCI Paris PSL University CNRS UMR 8063 France Department of Bioengineering Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Institute of Geophysics ETH Zürich Sonneggstrasse 5 Zürich8092 Switzerland Department of Radiology Stanford University StanfordCA United States Department of Biomedical Engineering Department of Electrical and Computer Engineering University of Utah United States Department of Surgical Biotechnology Division of Surgery and Interventional Science University College London LondonNW3 2PF United Kingdom Earth Science and Engineering Department Imperial College London London United Kingdom Centre of Excellence IT4Innovations Faculty of Information Technology Brno University of Technology Bozetechova 2 Brno612 00 Czech Republic Graduate Program in Acoustics The Pennsylvania State University University Park PA16802 United States Joint Department of Biomedical Engineering University of North Carolina at Chapel Hill North Carolina State University NC United States Department of Electrical Engineering Stanford University StanfordCA United States Zurich Switzerland Laboratory for Acoustics / Noise control Empa Swiss Federal Laboratories for Materials Science and Technology Dubendorf Switzerland Zurich Switzerland Radiology and Clinical Neurosciences Departments Cumming School of Medicine University of Calgary Canada Department of Applied Physics University of Eastern Finland Kuopio70211 Finland Department of Medical Physics and Biomedical Engineering University College London Gower Street LondonWC1E 6BT United Kingdom Technical University of Denmark Denmark Danish Research Center for Magnetic Resonance Copenhagen University Hospital Hvidovre Denmark Institute for Mathematical and Computational Engineering School of Engineering and Faculty of Mathematics Pontificia Universidad Catolica de Chile Santiago Chile

Computational models of acoustic wave propagation are frequently used in transcranial ultrasound therapy, for example, to calculate the intracranial pressure field or to calculate phase delays to correct for skull distortions. To allow intercomparison between the different modeling tools and techniques used by the community, an international working group was convened to formulate a set of numerical benchmarks. Here, these benchmarks are presented, along with intercomparison results. Nine different benchmarks of increasing geometric complexity are defined. These include a single-layer planar bone immersed in water, a multi-layer bone, and a whole skull. Two transducer configurations are considered (a focused bowl and a plane piston), giving a total of 18 permutations of the benchmarks. Eleven different modeling tools are used to compute the benchmark results. The models span a wide range of numerical techniques, including the finite-difference time-domain method, angular-spectrum method, pseudospectral method, boundary-element method, and spectral-element method. Good agreement is found between the models, particularly for the position, size, and magnitude of the acoustic focus within the skull. When comparing results for each model with every other model in a cross comparison, the median values for each benchmark for the difference in focal pressure and position are less than 10% and 1 mm, respectively. The benchmark definitions, model results, and intercomparison codes are freely available to facilitate further comparisons. Copyright © 2022, The Authors. All rights reserved.

关键词： Bone

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Understanding metric-related pitfalls in image analysis validation

arXiv

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arXiv 2023年

作者： Reinke, Annika Tizabi, Minu D. Baumgartner, Michael Eisenmann, Matthias Heckmann-Nötzel, Doreen Kavur, A. Emre Rädsch, Tim Sudre, Carole H. Acion, Laura Antonelli, Michela Arbel, Tal Bakas, Spyridon Benis, Arriel Blaschko, Matthew B. Buettner, Florian Cardoso, M. Jorge Cheplygina, Veronika Chen, Jianxu Christodoulou, Evangelia Cimini, Beth A. Collins, Gary S. Farahani, Keyvan Ferrer, Luciana Galdran, Adrian van Ginneken, Bram Glocker, Ben Godau, Patrick Haase, Robert Hashimoto, Daniel A. Hoffman, Michael M. Huisman, Merel Isensee, Fabian Jannin, Pierre Kahn, Charles E. Kainmueller, Dagmar Kainz, Bernhard Karargyris, Alexandros Karthikesalingam, Alan Kenngott, Hannes Kleesiek, Jens Kofler, Florian Kooi, Thijs Kopp-Schneider, Annette 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 Moons, Karel G.M. Müller, Henning Nichyporuk, Brennan Nickel, Felix Petersen, Jens Rafelski, Susanne M. Rajpoot, Nasir Reyes, Mauricio Riegler, Michael A. Rieke, Nicola Saez-Rodriguez, Julio Sánchez, Clara I. Shetty, Shravya Summers, Ronald M. Taha, Abdel A. Tiulpin, Aleksei Tsaftaris, Sotirios A. van Calster, Ben Varoquaux, Gaël Yaniv, Ziv R. Jäger, Paul F. Maier-Hein, Lena Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Division of Intelligent Medical Systems Germany NCT Heidelberg A Partnership Between DKFZ University Medical Center Heidelberg Germany Heidelberg Division of Medical Image Computing Germany Heidelberg Division of Intelligent Medical Systems 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 Instituto de Cálculo CONICET – Universidad de Buenos Aires Buenos Aires Argentina Centre for Medical Image Computing University College London London United Kingdom McGill University Montreal 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 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 Leuven Belgium partner site Frankfurt/Mainz a partnership between DKFZ and UCT Frankfurt Marburg Germany Heidelberg Germany Goethe University Frankfurt Department of Medicine Germany Goethe University Frankfurt Department of Informatics Germany and Frankfurt Cancer Insititute Germany Department of Computer Science IT University of Copenhagen Copenhagen Denmark Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany Imaging Platform Broad Institute of MIT and Harvard CambridgeMA United States Centre for Statistics in Medicine University of Oxford Oxford United Kingdom Center for Biomedical In

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence (AI) research and its translation into practice. However, increasing evidence shows that particularly in image analysis, metrics are often chosen inadequately. While taking into account the individual strengths, weaknesses, and limitations of validation metrics is a critical prerequisite to making educated choices, the relevant knowledge is currently scattered and poorly accessible to individual researchers. Based on a multi-stage Delphi process conducted by a multidisciplinary expert consortium as well as extensive community feedback, the present work provides the first reliable and comprehensive common point of access to information on pitfalls related to validation metrics in image analysis. While focused on biomedical image analysis, the addressed pitfalls generalize across application domains and are categorized according to a newly created, domain-agnostic taxonomy. The work serves to enhance global comprehension of a key topic in image analysis validation. © 2023, CC BY.

关键词： computer vision

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Data sharing and privacy for patient IoT devices using blockchain 7th

Data sharing and privacy for patient IoT devices using block...

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7th International Conference on Smart City and Informatization, iSCI 2019

作者： Srivastava, Gautam Parizi, Reza M. Dehghantanha, Ali Choo, Kim-Kwang Raymond Department of Mathematics and Computer Science Brandon University BrandonMBR7A 6A9 Canada Research Center for Interneural Computing China Medical University Taichung40402 Taiwan College of Computing and Software Engineering Kennesaw State University KennesawGA30144 United States Cyber Science Lab School of Computer Science University of Guelph GuelphONN1G 2W1 Canada Department of Information Systems and Cyber Security University of Texas at San Antonio San AntonioTX78249 United States

ISBN: (纸本)9789811513008

Once a fitness fad, wearable and other related Internet of Things (IoT) devices are fast becoming common place in many different smart city applications such as healthcare. However, IoT devices, particularly inexpensive devices, often trade security and privacy for usability. One solution to protect privacy in the healthcare domain which has begun to be explored is blockchain-based technology. However, there are a number of limitations underpinning the use of blockchain, which limits its adoption particularly in applications that require low energy and computational footprints. In this paper, we present a transactional protocol for remote patient monitoring using directed acyclic graphs. We use a newer blockchain protocol called GHOSTDAG in both a public blockchain and a private blockchain. Our novel proposed solution aims to resolve known security issues for healthcare, without affecting scalability (a feature of classic blockchain architecture). © Springer Nature Singapore Pte Ltd. 2019.

关键词： Internet of things

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Development of a chatbot for a car service

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AIP Conference Proceedings 2023年第1期2700卷

作者： Olga Rubleva Elena Emelyanova Tatiana Mozharova Natalya Polshakova Nadezhda Gavrilovskaya 1Department of Foreign Languages of Non-Linguistic Training Programs Vyatka State University Kirov Russia 2Department of Psychology Institute of Pedagogy and Psychology Vyatka State University Kirov Russia 3Department of Mathematical Analysis and Differential Equations Orel State University named after I. S. Turgenev Orel Russia 4Department of Information Technology and Mathematics Federal State Budgetary Educational Establishment of Higher Education Orel State Agrarian University named after N.V. Parakhin Orel Russia 5Department of Computer Aided Design and Engineering Calculation Russian State Agrarian University–Moscow Timiryazev Agricultural Academy Moscow Russia

There is an objective need to control and manage processes of data exchange between users in the virtual environment where there is electronic interaction. Therefore, automation of processing and recognition of messages is a logical and necessary stage in the further digitalization of the work of any enterprise. The purpose of the study is to develop an intelligent chat bot for automating information exchange in a car service. In this work a detailed analysis of online resources for automation of information exchange between participants of network interaction in the service market is carried out. The problem of text recognition is considered and the main stages of the solution are highlighted. In addition, neural networks for text recognition were considered: a convolutional neural network, a recurrent neural network as well as its modifications. As a result, the authors formulated a set of requirements for an intelligent chat bot and chose the language and development environment. The neural network was trained. The chatbot was tested on real data. An option for modernizing the chatbot is its testing in real conditions of information interaction in the digital environment of a car service.

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Cost optimization of a M/G/k queue with server vacation

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AIP Conference Proceedings 2020年第1期2277卷

作者： Lavanya Gowrishankar Vidhyacharan Bhaskar K. Sundarammal 1Department of Mathematics SRM Institute of Science and Technology Kattankulathur 603203 India 2Dept. of Electrical and Computer Engineering San Francisco State University USA

Queueing optimization is a science currently gaining importance in view of its contribution to operations research and marketing management. Capacity of the queue, service policy followed and the job flow into the system are the key variables which affect the cost efficiency of a system. In this proposed model we use Kingman relation to optimize M/G/k queue where the servers returns to function only if there are L jobs and also L is less than k. An expression for the expected cost for one execution cycle per unit time and the average time required for the execution of one cycle is obtained. The average cost incurred per unit time is also obtained.

关键词：

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Generalized Random Gilbert-Varshamov Codes

Generalized Random Gilbert-Varshamov Codes

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作者： Somekh-Baruch, Anelia Scarlett, Jonathan Guillén I Fàbregas, Albert Faculty of Engineering Bar-Ilan University Ramat Gan52900 Israel Department of Computer Science National University of Singapore Singapore117417 Singapore Department of Mathematics National University of Singapore Singapore119076 Singapore Department of Information and Communication Technologies Universitat Pompeu Fabra Barcelona08018 Spain Institució Catalana de Recerca i Estudis Avançats Barcelona08010 Spain Department of Engineering University of Cambridge CambridgeCB2 1PZ United Kingdom

We introduce a random coding technique for transmission over discrete memoryless channels, reminiscent of the basic construction attaining the Gilbert-Varshamov bound for codes in Hamming spaces. The code construction is based on drawing codewords recursively from a fixed type class, in such a way that a newly generated codeword must be at a certain minimum distance from all previously chosen codewords, according to some generic distance function. We derive an achievable error exponent for this construction and prove its tightness with respect to the ensemble average. We show that the exponent recovers the Csiszár and Körner exponent as a special case, which is known to be at least as high as both the random-coding and expurgated exponents, and we establish the optimality of certain choices of the distance function. In addition, for additive distances and decoding metrics, we present an equivalent dual expression, along with a generalization to infinite alphabets via cost-constrained random coding. © 1963-2012 IEEE.

关键词： Decoding

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RETRACTED ARTICLE: Facial landmark detection using artificial intelligence techniques

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Annals of Operations Research 2021年第1期326卷 63-63页

作者： Zhongshan, Chen Xinning, Feng Manickam, Adhiyaman Sathishkumar, V. E. School of Mathematics and Information Science 1 Shennong Road Qixia District Nanjing Normal University of Special Education Nanjing China College of Communication Engineering Tongda College of Nanjing University of Posts and Telecommunications Yangzhou China Research Institute for Future Media Computing College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Information and Communication Engineering Sunchon National University Suncheon Republic of Korea

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Observing Geometry of Quantum States in a Three-Level System

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Physical Review Letters 2020年第15期125卷 150401-150401页

作者： Jie Xie Aonan Zhang Ningping Cao Huichao Xu Kaimin Zheng Yiu-Tung Poon Nung-Sing Sze Ping Xu Bei Zeng Lijian Zhang National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and Manipulation (Ministry of Education) College of Engineering and Applied Sciences and School of Physics Nanjing University Nanjing 210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China Department of Mathematics & Statistics University of Guelph Guelph N1G 2W1 Ontario Canada Institute for Quantum Computing University of Waterloo Waterloo N2L 3G1 Ontario Canada Department of Mathematics Iowa State University Ames Iowa 50011 USA Department of Applied Mathematics The Hong Kong Polytechnic University 999077 Hong Kong China Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 China Department of Physics The Hong Kong University of Science and Technology Clear Water Bay Kowloon 999077 Hong Kong China

In quantum mechanics, geometry has been demonstrated as a useful tool for inferring nonclassical behaviors and exotic properties of quantum systems. One standard approach to illustrate the geometry of quantum systems is to project the quantum state space onto the Euclidean space via measurements of observables on the system. Despite the great success of this method in studying two-level quantum systems (qubits) with the celebrated Bloch sphere representation, it is still difficult to reveal the geometry of multidimensional quantum systems. Here we report the first experiment measuring the geometry of such projections beyond the qubit. Specifically, we observe the joint numerical ranges of a triple of observables in a three-level photonic system, providing a complete classification of these ranges. We further show that the geometry of different classes reveals ground-state degeneracies of a Hamiltonian as a linear combination of the observables, which is related to quantum phases in the thermodynamic limit. Our results offer a versatile geometric approach for exploring the properties of higher-dimensional quantum systems.

关键词： Geometric & topological phases Quantum foundations Quantum measurements Quantum phase transitions

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