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arXiv 2022年

作者： Horodecki, Karol Zhou, Jingfang Stankiewicz, Maciej Salazar, Roberto Horodecki, Pawel Raussendorf, Robert Horodecki, Ryszard Ramanathan, Ravishankar Tyhurst, Emily Institute of Informatics National Quantum Information Centre Faculty of Mathematics Physics and Informatics University of Gdańsk Wita Stwosza 57 Gdańsk80-308 Poland International Centre for Theory of Quantum Technologies University of Gdańsk Wita Stwosza 63 Gdańsk80-308 Poland Department of Applied Physics Graduate School of Engineering University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków30-348 Poland Faculty of Applied Physics and Mathematics National Quantum Information Centre Gdańsk University of Technology Gabriela Narutowicza 11/12 Gdańsk80-233 Poland Department of Physics and Astronomy University of British Columbia VancouverBCV6T 1Z1 Canada Department of Computer Science The University of Hong Kong Pokfulam Road Hong Kong Department of Physics University of Toronto TorontoON Canada

Quantum contextuality is one of the most recognized resources in quantum communication and computing scenarios. We provide a new quantifier of this resource, the rank of contextuality (RC). We define RC as the minimum number of non-contextual behaviors that are needed to simulate a contextual behavior. We show that the logarithm of RC is a natural contextuality measure satisfying several properties considered in the spirit of the resource-theoretic approach. The properties include faithfulness, monotonicity, and additivity under tensor product. We also give examples of how to construct contextual behaviors with an arbitrary value of RC exhibiting a natural connection between this quantifier and the arboricity of an underlying hypergraph. We also discuss exemplary areas of research in which the new measure appears as a natural quantifier. Copyright © 2022, The Authors. All rights reserved.

关键词： Quantum communication

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The role of wireless network in remote monitoring of electromechanical equipment

International Journal of Mechatronics and Applied Mechanics

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International Journal of Mechatronics and Applied Mechanics 2020年第8期2卷 77-85页

作者： Guo, Liang Luu, Viet Hung Kasim, Shahreen Department of Mathematics and Information Engineering Dongchang College of Liaocheng University Shandong Liaocheng252000 China Maritime College No. 1 Haiphong Viet Nam Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Malaysia

– To study the remote monitoring electromechanical equipment of wireless network, the wireless vibration sensor monitoring system is designed for rotating mechanical equipment. Firstly, for the overall design of the system, problems to be considered in the design process are proposed, and the system structure is improved in this research. Secondly, the wireless vibration monitoring node and the wireless vibration base station are modularized, and the devices details are given. Thirdly, the communication protocol of wireless network is designed, the topology of wireless network is improved, and the packet format is standardized. Finally, the data transmission performance of the designed monitoring system is tested and compared with that of YD-82 piezoelectric acceleration sensor. The results show that after 10 data transmission experiments, the data loss rate is lower than 0.2%. Furthermore, the frequency and amplitude of the main spectral lines of YD-82 sensor are close to that of the monitoring system designed in this study, whereas, the spectral line amplitude of the monitoring system is lower than that of YD-82 sensor. Therefore, the wireless network monitoring system designed in this study can meet the vibration monitoring requirements of electromechanical equipment. © 2020, Cefin Publishing House. All rights reserved.

关键词： Remote control

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Theoretical assessment of the impact of desert aerosols on the dynamical transmission of meningitidis serogroup A

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International Journal of Biomathematics 2019年第5期12卷 263-299页

作者： A. Otimar Bah M. Lam A. Rah S. Bowong Department of Mathematics Faculty of Science and Technic Universie Cheikh Anta Diopde DakarDakar-FannSenegal Department of Computer Engineering National Advanced School of Engineering Universite Cheikh Anta Diopde Dakar Dakar-FannSenegal Laboratory of Mathematics Department of Mathematics and Computer ScienceFaculty of ScienceUniversity of Douala P.O.Box 24157DoualaCameroon UMI 209 1RD and UPMC UMMISCO 32 Avenue Henri Varagnat 93143 Bondy CedexFrance Project Team GRIMCAPE University of Yaounde YaoundeCameroon The African Center of Excellence in Information and Communication Technologies(CETIC)National Advanced School of Engineering University of Yaounde 1 YaoundeCameroon

This paper has been motivated by the following biological question: how influential me desert uerosols in the transmission of meningitidis serogroup A (MenA)? A mathematical model for the dynamical transmission of MenA is considered,with the aim of investigating the impact of desert *** analysis of the model has been performed in order to determine the impact of related parameters on meningitis *** derive the basic reproduction number *** prove that there exists a threshold parameter ζ such that when R0 <ζ< 1,the disease-free equilibrium is globally asymptotically stable (GAS).However,when ζ< R0 < 1,the model exhibits the phenomenon of backward *** the endemic level,we show that the number of infectious individuals in the presence of desert aerosols is larger than the correspond-ing number without the presence of desert *** conjunction with the inequality R0^0< R0 where R0^0 is the basic reproduction number without desert aerosols,we found that the ingestion of aerosols by carriers will increase the endemic level,and the severity of the *** suggests that the control of MenA passes through a combination of a large coverage vaccination of young susceptible individuals and the production of a vaccine with a high level of efficacy as well as respecting the hygienic rules to avoid the inhalation of desert *** results are supported by numerical simulations.

关键词： Nonlinear dynamical systems epidemiological models serogroup A meningococcal infection stability bifurcation

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Theoretical assessment of the impact of environmental contamination on the dynamical transmission of polio

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International Journal of Biomathematics 2019年第2期12卷 1-35页

作者： C.Balde M.Lam A.Bah S.Bowong J.J.Tewa Department of Mathematics Faculty of Science and Technic University Cheikh Anta DiopDakarSenegal Department of Computer Engineering National Advanced School of Engineering University Cheikh Anta Diop DakarSenegal Laboratory of Mathematics Department of Mathematics and Computer Science Faculty of Science University of Douala P.O.Box 24157 DoualaCameroon National Advanced School of Engineering University of Yaounde I P.O.Box 8390 YaoundeCameroon IRD Sorbonne UniversityUHH1SCOF-93143BondyFrance Team GRIMCAPEYaoundeCameroon The African Center of Excellence in Information and Communication Technologies(CETIC)University of Yaounde 1Cameroon

A mathematical model for the dynamical transmission of polio is considered,with the aim of investigating the impact of environment *** model captures two infection pathways through both direct human-to-human transmission and indirect human-to-environment-to-human transmission by incorporating the environment as a transition and/or reservoir of *** derive the basic reproduction number R0^env We show that the disease free equilibrium is globally asymptotically stable(GAS)if R0^env<1,while if R0^env>1,there exists a unique endemic equilibrium which is locally asymptotically stable(LAS).Similar results hold for environmental contamination free sub-model(without the incorporation of the indirect transmission).At the endemic level,we show that the number of infected individuals for the model with the environ mental-related contagion is greater than the corresponding number for the environmental contamination free *** conjunction with the inequality R0

关键词： Poliovirus environment contamination human shedding rate mathematical models stability

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Automation of camel race by controlling DC motor speed using Blynk application through IoT

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AIP Conference Proceedings 2023年第1期2690卷

作者： Chandramma P. Prakash Praful Nandankar H. Roopa I. Kathir Prabhdeep Singh 1Department of Computer Science and Engineering Jain Deemed-To-Be University Bangalore-562112 Karnataka India 2Department of Electronics and Communication Engineering Sri Sairam Engineering College Chennai Tamil Nadu–600044 India 3Department of Electrical Engineering Government College of Engineering Nagpur - 441108 Maharashtra India 4Department of Information Science and Engineering Bangalore Institute of Technology Bangalore–560004 Karnataka India 5Department of Electrical & Electronics Engineering V.S.B. Engineering College Karur–639111 Tamil Nadu India 6Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun - 248002 Uttarakhand India

In this day and age, the D.C motors have been commonly used in many enterprises, sports, kind toys, and in several home appliances since of its outstanding features like reliability, a extensive limit of torque-speed, better performance, good starting torque, lower electrical control range, weight/torque ratio and noise. In contemporary Gulf Arab societies for centuries, camel racing has been part of Arabian culture, in one type or another, with some historians dating races to the seventh century. In this project work, the camel is fitted with the DC motor on its back depend on the speed of the motor the beat stick attached at the end will slash the camel to move fast forward. This allows the camel to acknowledge that still a person is sitting back and driving them. By adhering to the latest technologies like the Internet of Things (IoT) the camel may be driven from a remote location. This proposed method will have a controller like Arduino which acts as a central processing unit for the controlled action of the motor. The ESP8266 module is connected with the Arduino for providing an internet facility for supporting IoT. Blynk, a mobile application provides the platform to control the connected devices online through IoT. Here the DC motor speed set control is given as the slide switch in the Blynk app which in turn controls the speed of the motor through Wi-Fi employing IoT. This makes the racing environment without the case of a vehicle which may drastically reduce the air pollution.

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Better, Not Just More: Data-Centric Machine Learning for Earth Observation

arXiv

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arXiv 2023年

作者： Roscher, Ribana Rußwurm, Marc Gevaert, Caroline Kampffmeyer, Michael dos Santos, Jefersson A. Vakalopoulou, Maria Hänsch, Ronny Hansen, Stine Nogueira, Keiller Prexl, Jonathan Tuia, Devis Data Science for Crop Systems Group Forschungszentrum Jülich GmbH Wilhelm-Johnen-Straße Jülich52428 Germany Remote Sensing Group University of Bonn Niebuhrstr. 1a Bonn53113 Germany Laboratory of Geo-information Science and Remote Sensing Wageningen University Droevendaalsesteeg 3 Wageningen Gelderland6708 PB Netherlands Department of Earth Observation Science Faculty ITC University of Twente Drienerlolaan 5 Enschede Overijssel7522 NB Netherlands Department of Physics and Technology UiT The Arctic University of Norway Klokkargårdsbakken 35 Tromsø9019 Norway Department of Computer Science University of Sheffield Sheffield City Centre 211 Portobello SheffieldS1 4DP United Kingdom Münchner Str. 20 Oberpfaffenhofen-Wessling82234 Germany Computing Science and Mathematics University of Stirling StirlingFK9 4LA United Kingdom Department of Aerospace Engineering University of the Bundeswehr Munich Werner-Heisenberg-Weg 39 Neubiberg Bavaria85579 Germany Ronquos 86 Sion1951 Switzerland

Recent developments and research in modern machine learning have led to substantial improvements in the geospatial field. Although numerous deep learning architectures and models have been proposed, the majority of them have been solely developed on benchmark datasets that lack strong real-world relevance. Furthermore, the performance of many methods has already saturated on these datasets. We argue that a shift from a model-centric view to a complementary data-centric perspective is necessary for further improvements in accuracy, generalization ability, and real impact on end-user applications. Furthermore, considering the entire machine learning cycle—from problem definition to model deployment with feedback—is crucial for enhancing machine learning models that can be reliable in unforeseen situations. This work presents a definition as well as a precise categorization and overview of automated data-centric learning approaches for geospatial data. It highlights the complementary role of data-centric learning with respect to model-centric in the larger machine learning deployment cycle. We review papers across the entire geospatial field and categorize them into different groups. A set of representative experiments shows concrete implementation examples. These examples provide concrete steps to act on geospatial data with data-centric machine learning approaches. © 2023, CC BY.

关键词： Adversarial machine learning

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Convolutional neural network-based MRI brain tumor classification system

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AIP Conference Proceedings 2022年第1期2519卷

作者： M. Amanullah J. Visumathi Naresh Sammeta Maram Ashok 1Department of Information Technology Aalim Muhammed Salegh College of Engineering Chennai Tamil Nadu India 2Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India 3Department of Computer Science and Engineering RMK College of Engineering and Technology Puduvoyal Tamil Nadu India 4Department of Computer Science and Engineering Malla Reddy Institute of Engineering and Technology Secunderabad Telangana India

A brain tumor, the cause of more death rate among all cancers, is diagnosed using uncontrollable cell growth and abnormal brain cell partitioning. The recent progress in Deep Learning (DL) neural network technology aids the health service department in medical imaging diagnose several death-causing diseases. The visual learning of image recognition manually may result in fault detection and can be overcome by the most prevalent task of machine learning. In our paper, the Convolutional Neural Network (CNN) model is designed with data augmentation and image processing techniques to identify the brain MRI scan images into cancerous or non-cancerous and classify various brain tumor types. The performance comparison of our proposed CNN model uses the Transfer Learning (TL) method. With a very small dataset, the experimental result shows that our model is very effective at low computational power with less complexity and achieves better accuracy compared to an existing model.

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Internet connected patient healthcare monitoring in smart phones using Raspberry Pi

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AIP Conference Proceedings 2022年第1期2519卷

作者： Porandla Srinivas K. Kalimuthu C. Balarengadurai C. Viswanathan 1Department of Information Technology Malla Reddy Institute of Engineering and Technology Secunderabad Telangana India 2Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu India 3Department of Computer Science and Engineering Marri Laxman Reddy Institute of Technology and Management Dundigal Telangana India 4Department of Computer Science and Engineering Chennai Institute of Technology Malayambakkam Tamil Nadu India

Today the Environment of health has established research and knowledge based on Technology-oriented wireless sensing node. Patients are confronted with the problem of unanticipated death because of the particular cause of cardiac difficulties and attacks that occur at the necessary time owing to a lack of adequate care for patients. In contemporary health industry, the use of medical gadgets is significant, which is causing a lot of disruption in the patient’s space as well as the doctor’s analysis. As a result, we highlight our major healthcare electronics initiatives in this paper, with an emphasis on electronic medical records. Uniqueness and ease of use characterize the designed systems, which were planned with a very high level of efficiency (so-called "smarter" gadgets). It was created as a handheld gadget to allow for real-time rescue in the event of an accident without the requirement for continuous patient care of the data. We also show a low-cost computerized healthcare practice that can analyze respiratory activities in real time, non-invasively, and continuously.

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On existence, stability and many-particle approximation of solutions of 1D Hughes model with linear costs

arXiv

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arXiv 2021年

作者： Andreianov, Boris Rosini, Massimiliano D. Stivaletta, Graziano Institut Denis Poisson CNRS UMR7013 Université de Tours Université d'Orléans Parc Grandmont Tours37200 France Peoples' Friendship University of Russia RUDN University 6 Miklukho-Maklaya St Moscow117198 Russia Department of Mathematics and Computer Science University of Ferrara I-44121 Italy Uniwersytet Marii Curie-Sklodowskiej Plac Marii Curie-Sklodowskiej 1 Lublin20-031 Poland Department of Information Engineering Computer Science and Mathematics University of L'Aquila I-67100 Italy

This paper deals with the one-dimensional formulation of Hughes model for pedestrian flows in the setting of entropy solutions, which authorizes non-classical shocks at the location of the so-called turning curve. We consider linear cost functions, whose slopes α > 0 correspond to different crowd behaviours. We prove existence and partial well-posedness results in the framework of entropy solutions. The proofs of existence are based on a a sharply formulated many-particle approximation scheme with careful treatment of interactions of particles with the turning curve, and on local reductions to the well-known Lighthill-Whitham-Richards model. For the special case of BV-regular entropy solutions without non-classical shocks, locally Lipschitz continuous dependence of such solutions on the initial datum ρ and on the cost parameter α is proved. Differently from the stability argument and from existence results available in the literature, our existence result allows for the possible presence of non-classical shocks. First, we explore convergence of the many-particle approximations under the assumption of uniform space variation control. Next, by a local compactness argument that permits to circumvent the possible absence of global BV bounds, we obtain existence of solutions for general measurable data. Finally, we illustrate numerically that the model is able to reproduce typical behaviours in case of evacuation. Special attention is devoted to the impact of the parameter α on the evacuation time. Copyright © 2021, The Authors. All rights reserved.

关键词： Entropy

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Diagnosing covid-19 lung inflammation using machine learning algorithms: A comparative study

Studies in Big Data

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Studies in Big Data 2020年 80卷 91-105页

作者： Ali, Abbas M. Ghafoor, Kayhan Zrar Maghdid, Halgurd S. Mulahuwaish, Aos Department of Software Engineering Salahaddin University-Erbil Erbil Iraq School of Mathematics and Computer Science University of Wolverhampton Wulfruna Street WolverhamptonWV1 1LY United Kingdom Department of Software Engineering Faculty of Engineering Koya University Kurdistan Region Koysinjaq Iraq Department of Computer Science and Information Systems Saginaw Valley State University 7400 Bay Rd Science East 174 University Center Itta BenaMI48710 United States

In this paper, we performed a comparative analysis using machine learning algorithms named support vector machine (SVM), decision tree (DT), k-nearest neighbor (kNN), and convolution neural network (CNN) to classify pneumonia level (mild, progressive, and severe stage) of the COVID-19 confirmed patients. More precisely, the proposed model consists of two phases: first, the model computes the volume and density of lesions and opacities of the CT images using morphological approaches. In the second phase, we use machine learning algorithms to classify the pneumonia level of the confirmed COVID-19 patient. Extensive experiments have been carried out and the results show the accuracy of 91.304%, 91.4%, 87.5%, 95.622% for kNN, SVM, DT, and CNN, respectively. © Springer International Publishing AG 2018.

关键词： COVID-19

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