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525 A population-based study of phenoconversion to parkinsonism from REM sleep behavior: a Population-based Study in the CLSA

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Sleep 2021年第SUPPLEMENT_2期44卷 A207–A207页

作者： Yao, Chun Zolfaghari, Sheida Chaudhuri, Paramita Saha Pelletier, Amelie Wolfson, Christina Postuma, Ronald Integrated Program in Neuroscience McGill Department of Mathematics and Statistics Vermont RI-MUHC Medicine McGill McGill University Department of Neurology and Neurosurgery

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Set stability for switched Boolean networks with open-loop and closed-loop switching signals

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Science China(Information Sciences) 2018年第9期61卷 232-240页

作者： Xiaohua LI Jianquan LU Jianlong QIU Xiangyong CHEN Xiaodi LI Fuad E.ALSAADI School of Automation and Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of Shandong Linyi University School of Mathematics and Statistics Shandong Normal University School of Mathematics Southeast University Department of Electrical and Computer Engineering King Abdulaziz University

This paper mainly analyzes the set stability of switched Boolean networks(SBNs) by considering two different methods of switching signals in the form of open-loop and closed-loop switching. First, the definitions of set stability are proposed for SBNs with such switching signals. Then, we propose two different algorithms to find the largest open-loop switching invariant set and largest closed-loop switching invariant set. Furthermore, the corresponding set stability conditions for SBNs are given in each case. In addition,the constructive procedures are presented to design the switching signal sequence to achieve set stability under the two different methods of switching signals. Finally, the effectiveness of the proposed algorithms and research results are demonstrated using two numerical examples.

关键词： switched Boolean network set stability semi-tensor product switching signal design

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State-dependent parameter model identification for inverse dead-zone control of a hydraulic manipulator⁎

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IFAC-PapersOnLine 2018年第15期51卷 126-131页

作者： West, C. Wilson, E.D. Clairon, Q. Monk, S. Montazeri, A. Taylor, C.J. Engineering Department Lancaster University United Kingdom School of Mathematics and Statistics University of Newcastle United Kingdom

The robotic platform in this study has dual, seven-function, hydraulically actuated manipulators, which are being used for research into assisted tele-operation for common nuclear decommissioning tasks, such as pipe cutting. The article concerns the identification of state-dependent parameter (SDP) models for joint angle control. Compared to earlier SDP analysis of the same device, the present work proposes a new way of representing the state-dependent gain and parametrises this using novel regret-regression methods. A mechanistic interpretation of this model yields dead-zone and angular velocity saturation coefficients, and facilitates SDP-based control with an inverse dead-zone. This approach integrates the input signal calibration, system identification and nonlinear control system design steps, using a relatively small data-set, allowing for straightforward recalibration when the dynamic characteristics have changed due to age and use, or after the installation of replacement parts. © 2018

关键词： Manipulators Design Inverse problems Nonlinear analysis Nonlinear systems Parameter estimation Regression analysis Religious buildings Robotics Anti windup Identification for control Mechanistic interpretations Nuclear decommissioning Parameter varying systems Robotic manipulators State dependent parameter models State dependent parameters

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Utilizing web based GIS services for retrieving and disseminating geographic information for disaster management 3

Utilizing web based GIS services for retrieving and dissemin...

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3rd International Conference on Natural and Environmental Sciences 2019, ICONES 2019

作者： Nizamuddin Ardiansyah Sofyan, H. Muzailin Aldika, W.A. Informatics Department Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Electrical and Computer Engineering Department Faculty of Engineering Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia Statistics Department Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Darussalam Banda Aceh23111 Indonesia

The development of Information and Communication Technology (ICT) related to web-based services such as portals, web services and databases (DB) services for searching, retrieving, disseminating and sharing information has also happened in the field of Geographic Information Systems (GIS) through web-based GIS Services. In GIS, the portal is replaced by Geoportal, Web Service by Web Mapping Service (WMS) and Web Feature Service (WFS) while DB Services is replaced by Geographic Database (GeoDB) services. Web based GIS services can be classified as Geoportal, WMS, WFS and GeoDB Services. This research developed a prototype of web-based GIS services for the management of Geographic Information related to disaster management. There are several techniques for developing GIS based web services such as using Content Management Systems for GIS, namely OpenGeo Suite, GeoNode, and ArcGIS based GIS Services. This research focuses on Web-based GIS Services with the ArcGIS platform. The prototype of Web-based GIS Services was built focusing on Geographic information in disaster management cycles such as recovery (rehabilitation and reconstruction), prevention (mitigation), preparedness and emergency response periods. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Geographic information systems

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Unexpected frequency of horizontal oscillations of magnetic structures in the solar photosphere

arXiv

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arXiv 2024年

作者： Berretti, M. Stangalini, M. Verth, G. Jafarzadeh, S. Jess, D.B. Berrilli, F. Grant, S.D.T. Duckenfield, T. Fedun, V. University of Trento Via Calepina 14 Trento38122 Italy University of Rome Tor Vergata Department of Physics Via della Ricerca Scientifica 3 Rome00133 Italy ASI Italian Space Agency Via del Politecnico snc Rome00133 Italy Plasma Dynamics Group School of Mathematics and Statistics The University of Sheffield Hicks Building Hounsfield Road SheffieldS3 7RH United Kingdom Max Planck Institute for Solar System Research Justus-von-Liebig-Weg 3 Göttingen37077 Germany Niels Bohr International Academy Niels Bohr Institute Blegdamsvej 17 CopenhagenDK-2100 Denmark Astrophysics Research Centre School of Mathematics and Physics Queen’s University Belfast Northern Ireland BelfastBT7 1NN United Kingdom Department of Physics and Astronomy California State University Northridge NorthridgeCA91330 United States Plasma Dynamics Group Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

It is well known that the dominant frequency of oscillations in the solar photosphere is ≈3 mHz, which is the result of global resonant modes pertaining to the whole stellar structure. However, analyses of the horizontal motions of nearly 1 million photospheric magnetic elements spanning the entirety of solar cycle 24 have revealed an unexpected dominant frequency, ≈5 mHz, a frequency typically synonymous with the chromosphere. Given the distinctly different physical properties of the magnetic elements examined in our statistical sample, when compared to largely quiescent solar plasma where ≈3 mHz frequencies are omnipresent, we argue that the dominant ≈5 mHz frequency is not caused by the buffeting of magnetic elements, but instead is due to the nature of the underlying oscillatory driver itself. This novel result was obtained by exploiting the unmatched spatial and temporal coverage of magnetograms acquired by the Helioseismic and Magnetic Imager (HMI) on board NASA’s Solar Dynamics Observatory (SDO). Our findings provide a timely avenue for future exploration of the magnetic connectivity between sub-photospheric, photospheric, and chromospheric layers of the Sun’s dynamic atmosphere. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic structure

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Enhancing COVID-19 vaccination and medication distribution routing strategies in rural regions of Morocco: A comparative metaheuristics analysis

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Informatics in Medicine Unlocked 2024年 46卷

作者： Mzili, Toufik Mzili, Ilyass Riffi, Mohammed Essaid Kurdi, Mohamed Ali, Ali Hasan Pamucar, Dragan Abualigah, Laith Department of Computer Science Faculty of Science Chouaib Doukkali University EI Jadida Morocco Department of Business Management Al-imam University College Balad Iraq Department of Computer Science Faculty of Economics and Management Hasan 1st University Settat Morocco Faculty of Informatics Engineering Idlib University Idlib Syrian Arab Republic Institute of Mathematics University of Debrecen Pf. 400 Debrecen H-4002 Hungary College of Engineering Technology National University of Science and Technology Dhi Qar 64001 Iraq Technical Engineering College Al-Ayen University Dhi Qar 64001 Iraq Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia College of Engineering Yuan Ze University Taiwan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan Applied science research center Applied science private university Amman 11931 Jordan

The optimization of the vaccination campaign and medication distribution in rural regions of Morocco conducted by the Ministry of Health can be significantly improved by employing metaheuristic algorithms in conjunction with a tour planning system. This research proposes the utilization of six metaheuristic algorithms: genetic algorithm, rat swarm optimization, whale optimization, spotted hyena optimizer, penguins search optimization, and particle swarm optimization, to determine the most efficient routes for equipped trucks carrying vaccines and medications. These algorithms consider critical field constraints, such as operating hours of vaccination centers, vaccine availability, and distances between centers while minimizing the overall journey duration. In addition, a comprehensive tour planning system is integrated into the optimization framework accounting for transportation costs such as fuel expenses and truck maintenance costs. By incorporating these factors, the Ministry of Health aims to achieve the maximum efficiency while minimizing the financial burden associated with the vaccination campaign in rural areas. The integration of metaheuristics and the tour planning system presents a robust and data-driven solution for the Ministry of Health to enhance the effectiveness of their vaccination and medication distribution campaigns in rural regions of Morocco. This approach not only minimizes costs but also improves overall efficiency by ensuring timely access to vaccines and medications for the rural population. The findings of this research contribute to the growing body of knowledge in the field of healthcare logistics optimization and provide valuable insights for policymakers and practitioners involved in similar campaigns worldwide. © 2024 The Authors

关键词： Healthcare logistics Medication distribution Metaheuristics Route optimization Tour planning system Transportation Vaccination campaign

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Path integral based convolution and pooling for graph neural networks 20

Path integral based convolution and pooling for graph neural...

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Proceedings of the 34th International Conference on Neural Information Processing Systems

作者： Zheng Ma Junyu Xuan Yu Guang Wang Ming Li Pietro Liò Department of Physics Princeton University Centre for Artificial Intelligence Faculty of Engineering and Information Technology University of Technology Sydney Max Planck Institute for Mathematics in the Sciences & School of Mathematics and Statistics University of New South Wales Department of Educational Technology Zhejiang Normal University Department of Computer Science and Technology University of Cambridge

ISBN: (纸本)9781713829546

Graph neural networks (GNNs) extends the functionality of traditional neural networks to graph-structured data. Similar to CNNs, an optimized design of graph convolution and pooling is key to success. Borrowing ideas from physics, we propose a path integral based graph neural networks (PAN) for classification and regression tasks on graphs. Specifically, we consider a convolution operation that involves every path linking the message sender and receiver with learnable weights depending on the path length, which corresponds to the maximal entropy random walk. It generalizes the graph Laplacian to a new transition matrix we call maximal entropy transition (MET) matrix derived from a path integral formalism. Importantly, the diagonal entries of the MET matrix are directly related to the subgraph centrality, thus lead to a natural and adaptive pooling mechanism. PAN provides a versatile framework that can be tailored for different graph data with varying sizes and structures. We can view most existing GNN architectures as special cases of PAN. Experimental results show that PAN achieves state-of-the-art performance on various graph classification/regression tasks, including a new benchmark dataset from statistical mechanics we propose to boost applications of GNN in physical sciences.

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Line-of-Sight Pursuit in Monotone and Scallop Polygons

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International Journal of Computational Geometry and Applications 2019年第4期29卷 307-351页

作者： Berry, Lindsay Beveridge, Andrew Butterfield, Jane Isler, Volkan Keller, Zachary Shine, Alana Wang, Junyi Statistical Science Department Duke University Durham 27708 NC United States Department of Mathematics Statistics and Computer Science Macalester College St. Paul 55105 MN United States Department of Mathematics and Statistics University of Victoria Victoria V8X 2X6 BC Canada Department of Computer Science and Engineering University of Minnesota Minneapolis 55455 MN United States Department of Mathematics University of Minnesota Minneapolis 55455 MN United States Department of Computer Science University of Southern California Los Angeles 90089 CA United States

We study a turn-based game in a simply connected polygonal environment Q between a pursuer and an adversarial evader . Both players can move in a straight line to any point within unit distance during their turn. The pursuer wins by capturing the evader, meaning that their distance satisfies d(,) ≤ 1, while the evader wins by eluding capture forever. Both players have a map of the environment, but they have different sensing capabilities. The evader always knows the location of . Meanwhile, only has line-of-sight visibility: observes the evader's position only when the line segment connecting them lies entirely within the polygon. Therefore must search for when the evader is hidden from view. We provide a winning strategy for in two families of polygons: monotone polygons and scallop polygons. In both families, a straight line L can be moved continuously over Q so that (1) L n Q is a line segment and (2) every point on the boundary ?Q is swept exactly once. These are both subfamilies of strictly sweepable polygons. The sweeping motion for a monotone polygon is a single translation, and the sweeping motion for a scallop polygon is a single rotation. Our algorithms use rook's strategy during its pursuit phase, rather than the well-known lion's strategy. The rook's strategy is crucial for obtaining a capture time that is linear in the area of Q. For both monotone and scallop polygons, our algorithm has a capture time of O(n(Q) + area(Q)), where n(Q) is the number of polygon vertices. © 2019 World Scientific Publishing Company.

关键词： monotone polygon Pursuit-evasion sweepable polygon

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A Manifold Proximal Linear Method for Sparse Spectral Clustering with Application to Single-Cell RNA Sequencing Data Analysis

arXiv

引用

arXiv 2020年

作者： Wang, Zhongruo Liu, Bingyuan Chen, Shixiang Ma, Shiqian Xue, Lingzhou Zhao, Hongyu Department of Mathematics UC Davis Department of Statistics Penn State University United States Department of Industrial & Systems Engineering Texas A&M University United States Department of Biostatistics Yale University United States

Spectral clustering is one of the fundamental unsupervised learning methods widely used in data analysis. Sparse spectral clustering (SSC) imposes sparsity to the spectral clustering and it improves the interpretability of the model. This paper considers a widely adopted model for SSC, which can be formulated as an optimization problem over the Stiefel manifold with nonsmooth and nonconvex objective. Such an optimization problem is very challenging to solve. Existing methods usually solve its convex relaxation or need to smooth its nonsmooth part using certain smoothing techniques. In this paper, we propose a manifold proximal linear method (ManPL) that solves the original SSC formulation. We also extend the algorithm to solve the multiple-kernel SSC problems, for which an alternating ManPL algorithm is proposed. Convergence and iteration complexity results of the proposed methods are established. We demonstrate the advantage of our proposed methods over existing methods via the single-cell RNA sequencing data analysis. Copyright © 2020, The Authors. All rights reserved.

关键词： Clustering algorithms

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Someα−ϕ-Fuzzy Cone Contraction Results with Integral Type Application

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Journal of mathematics 2021年第1期2021卷

作者： Saif Ur Rehman Shamoona Jabeen Sami Ullah Khan Mohammed M. M. Jaradat Department of Mathematics Gomal University Dera Ismail Khan 29050 Pakistangu.edu.pk School of Mathematical Sciences Beihang University Beijing 100191 *** Mathematics Program Department of Mathematics Statistics and Physics College of Arts and Sciences Doha 2713 Qatar

In this paper, we define α -admissible and α - ϕ -fuzzy cone contraction in fuzzy cone metric space to prove some fixed point theorems. Some related sequences with contraction mappings have been discussed. Ultimately, our theoretical results have been utilized to show the existence of the solution to a nonlinear integral equation. This application is also illustrative of how fuzzy metric spaces can be used in other integral type operators.

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