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arXiv 2021年

作者： Teng, Yuankai Wang, Zhu Ju, Lili Gruber, Anthony Zhang, Guannan Department of Mathematics University of South Carolina ColumbiaSC29208 United States Department of Scientific Computing Florida State University TallahasseeFL32306 United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

Due to the curse of dimensionality and the limitation on training data, approximating high-dimensional functions is a very challenging task even for powerful deep neural networks. Inspired by the Nonlinear Level set Learning (NLL) method that uses the reversible residual network (RevNet), in this paper we propose a new method of Dimension Reduction via Learning Level Sets (DRiLLS) for function approximation. Our method contains two major components: one is the pseudo-reversible neural network (PRNN) module that effectively transforms high-dimensional input variables to low-dimensional active variables, and the other is the synthesized regression module for approximating function values based on the transformed data in the low-dimensional space. The PRNN not only relaxes the invertibility constraint of the nonlinear transformation present in the NLL method due to the use of RevNet, but also adaptively weights the influence of each sample and controls the sensitivity of the function to the learned active variables. The synthesized regression uses Euclidean distance in the input space to select neighboring samples, whose projections on the space of active variables are used to perform local least-squares polynomial fitting. This helps to resolve numerical oscillation issues present in traditional local and global regressions. Extensive experimental results demonstrate that our DRiLLS method outperforms both the NLL and Active Subspace methods, especially when the target function possesses critical points in the interior of its input domain. Copyright © 2021, The Authors. All rights reserved.

关键词： Regression analysis

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Harmony Search: Current Studies and Uses on Healthcare Systems

arXiv

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arXiv 2022年

作者： Abdulkhaleq, Maryam T. Rashid, Tarik A. Alsadoon, Abeer Hassan, Bryar A. Mohammadi, Mokhtar Abdullah, Jaza M. Chhabra, Amit Ali, Sazan L. Othman, Rawshan N. Hasan, Hadil A. Azad, Sara Mahmood, Naz A. Abdalrahman, Sivan S. Rasul, Hezha O. Bacanin, Nebojsa Vimal, S. Department of Computer Science and Engineering University of Kurdistan Hewler KRI Iraq School of Computing and Mathematics Charles Sturt University Sydney Australia Information Technology Department Sydney Australia Department of Information Technology Kurdistan Institution for Strategic Studies and Scientific Research Sulaimani46001 Iraq Department of Information Technology Lebanese French University KRI Erbil Iraq Computer Science Department College of Science Komar University of Science and Technology KRI Sulaymaniyah Iraq Information Technology College of Commerce University of Sulaimani KRI Sulaymaniyah Iraq Department of Computer Engineering and Technology Guru Nanak Dev University Amritsar India Department of Pharmaceutical Chemistry College of Medicals and Applied Sciences Charmo University Peshawa Street Chamchamal Sulaimani46023 Iraq Singidunum University Danijelova 32 Belgrade11000 Serbia

One of the popular metaheuristic search algorithms is Harmony Search (HS). It has been verified that HS can find solutions to optimization problems due to its balanced exploratory and convergence behavior and its simple and flexible structure. This capability makes the algorithm preferable to be applied in several real-world applications in various fields, including healthcare systems, different engineering fields, and computer science. The popularity of HS urges us to provide a comprehensive survey of the literature on HS and its variants on health systems, analyze its strengths and weaknesses, and suggest future research directions. In this review paper, the current studies and uses of harmony search are studied in four main domains. (i) The variants of HS, including its modifications and hybridization. (ii) Summary of the previous review works. (iii) Applications of HS in healthcare systems. (iv) And finally, an operational framework is proposed for the applications of HS in healthcare systems. The main contribution of this review is intended to provide a thorough examination of HS in healthcare systems while also serving as a valuable resource for prospective scholars who want to investigate or implement this method. © 2022, CC BY.

关键词： Optimization

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A visual analytics framework for distributed data analysis systems

arXiv

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arXiv 2021年

作者： Nayeem, Abdullah-Al-Raihan Elshambakey, Mohammed Dobbs, Todd Lee, Huikyo Crichton, Daniel Zhu, Yimin Chokwitthaya, Chanachok Tolone, William J. Cho, Isaac College of Computing and Informatics University of North Carolina at Charlotte Charlotte United States Computer Science University of North Carolina at Greensboro Greensboro United States City of Scientific Research and Technological Applications Alexandria Egypt Jet Propulsion Laboratory California Institute of Technology Pasadena United States Construction Management Louisiana State University Rouge United States Computer Science Utah State University Logan United States

This paper proposes a visual analytics framework that addresses the complex user interactions required through a command-line interface to run analyses in distributed data analysis systems. The visual analytics framework facilitates the user to manage access to the distributed servers, incorporate data from the source, run data-driven analysis, monitor the progress, and explore the result using interactive visualizations. We provide a user interface embedded with generalized functionalities and access protocols and integrate it with a distributed analysis system. To demonstrate our proof of concept, we present two use cases from the earth science and Sustainable Human Building Ecosystem research domain. © 2021, CC BY.

关键词： Visualization

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Cell-Free Massive MIMO-OFDM for High-Speed Train Communications

arXiv

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arXiv 2022年

作者： Zheng, Jiakang Zhang, Jiayi Björnson, Emil Li, Zhetao Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Department of Computer Science KTH Royal Institute of Technology Kista Sweden The Hunan International Scientific and Technological Cooperation Base of Intelligent Network Key Laboratory of Intelligent Computing & Information Processing Ministry of Education Xiangtan University Hunan411105 China The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Cell-free (CF) massive multiple-input multiple-output (MIMO) systems show great potentials in low-mobility scenarios, due to cell boundary disappearance and strong macro diversity. However, the great Doppler frequency offset (DFO) leads to serious inter-carrier interference in orthogonal frequency division multiplexing (OFDM) technology, which makes it difficult to provide high-quality transmissions for both high-speed train (HST) operation control systems and passengers. In this paper, we focus on the performance of CF massive MIMO-OFDM systems with both fully centralized and local minimum mean square error (MMSE) combining in HST communications. Considering the local maximum ratio (MR) combining, the large-scale fading decoding (LSFD) cooperation and the practical effect of DFO on system performance, exact closed-form expressions for uplink spectral efficiency (SE) expressions are derived. We observe that cooperative MMSE combining achieves better SE performance than uncooperative MR combining. In addition, HST communications with small cell and cellular massive MIMO-OFDM systems are compared in terms of SE. Numerical results reveal that the CF massive MIMO-OFDM system achieves a larger and more uniform SE than the other systems. Finally, the train antenna centric (TA-centric) CF massive MIMO-OFDM system is designed for practical implementation in HST communications, and three power control schemes are adopted to optimize the propagation of TAs for reducing the impact of the DFO. Copyright © 2022, The Authors. All rights reserved.

关键词： MIMO systems

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Topical Issue scientific Machine Learning (1/2)

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GAMM Mitteilungen 2021年第1期44卷 e202100010-e202100010页

作者： Benner, Peter Klawonn, Axel Stoll, Martin Computational Methods in Systems and Control Theory Max Planck institute for Dynamics of Complex Technical Systems Magdeburg Germany Fakultät für Mathematik Otto-von-Guericke Universität Magdeburg Germany Department of Mathematics and Computer Science University of Cologne Germany Center for Data and Simulation Science University of Cologne Germany Chair of Scientific Computing Department of Mathematics TU Chemnitz Germany

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A Visual Analytics Framework for Distributed Data Analysis Systems

A Visual Analytics Framework for Distributed Data Analysis S...

引用

IEEE International Conference on Big Data

作者： Abdullah-Al-Raihan Nayeem Mohammed Elshambakey Todd Dobbs Huikyo Lee Daniel Crichton Yimin Zhu Chanachok Chokwitthaya William J. Tolone Isaac Cho College of Computing and Informatics University of North Carolina at Charlotte Charlotte United States City of Scientific Research and Technological Applications Alexandria Egypt Computer Science University of North Carolina at Greensboro Greensboro United States Jet Propulsion Laboratory California Institute of Technology Pasadena United States Construction Management Louisiana State University Rouge United States Computer Science Utah State University Logan United States

ISBN: (纸本)9781665445993

关键词： Data analysis Visual analytics Ecosystems Data visualization Distributed databases Configuration management Geoscience

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Solving bang-bang problems using the immersed interface method and integer programming

arXiv

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arXiv 2021年

作者： Vogt, Ryan H. Strikwerda, Sarah Department of Mathematics North Carolina State University RaleighNC27695 United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States

In this paper we study numerically solving optimal control problems with bang-bang control functions. We present a formal Lagrangian approach for solving the optimal control problem, and address difficulties encountered when numerically solving the state and adjoint equations by using the immersed interface method. We note that our numerical approach does not approximate the discontinuous control function with smooth functions, instead we solve the true bang-bang optimal control problem. Our approach for solving the optimal control problem uses an adjoint-based gradient. We use the gradient in our first-order trust-region method to generate a local minimizing control. We present detailed numerical results to demonstrate the effectiveness of our method. © 2021, CC BY.

关键词： Constrained optimization

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Sparse dual-graph regularized quadratic dimensionality reduction algorithm based on subspace learning

引用

Digital Signal Processing: A Review Journal 2025年 164卷

作者： Ma, Ziping Huang, Yulei Ma, Jinlin Li, Huirong School of Mathematics and Information Science North Minzu University Yinchuan750030 China School of Mathematics and Statistics Ningxia University Yinchuan750030 China School of Computer Science and Engineering North Minzu University Yinchuan750030 China School of Mathematics and Computer Application Shangluo University Shangluo726000 China Ningxia Collaborative Innovation Center for Scientific Computing and Intelligent Information Processing North Minzu University Yinchuan750030 China

Nonnegative matrix factorization (NMF) has been attracting more and more attention due to its significant performance in dimensionality reduction. NMF performs dimensionality reduction by mapping high-dimensional data into low-dimensional space, which might lead to the uncontrollability, i.e. quantity and quality, of dimensions in dimensionality reduction. To address this issue, we innovatively propose a novel sparse dual-graph regularized quadratic dimensionality reduction (SDQDR) algorithm by embedding feature selection mechanism to semi-supervised NMF, which are fused as a whole rather than the simple combinations of NMF and feature selection in existing methods. The proposed SDQDR not only inherits the advantages of semi-supervised NMF but also demonstrates some special and important properties, such as controllability of dimensionality reduction, higher clustering performance, and significant dimensionality reduction with low time cost, etc. Then, to reinforce the sparsity structure and retain the manifold structures of both the data and the feature space simultaneously, 1-2,1/2 sparse constraint and dual graph regularization are incorporated into the proposed framework. Finally, the objective function, convergence proof, and iterative update rules are presented. In comparison with 15 state-of-the-art algorithms, relevant results demonstrate the proposed method is competitive, especially in terms of the efficiency of dimensionality reduction. © 2025 Elsevier Inc.

关键词： Non-negative matrix factorization

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High order semi-implicit WENO schemes for all mach full euler system of gas dynamics

arXiv

引用

arXiv 2021年

作者： Boscarino, Sebastiano Qiu, Jing-Mei Russo, Giovanni Xiong, Tao Department of Mathematics and Computer Science University of Catania Catania95127 Italy Department of Mathematics University of Delaware NewarkDE19716 United States School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University Fujian Xiamen361005 China

In this paper, we propose a new high order semi-implicit scheme for the all Mach full Euler equations of gas dynamics. Material waves are treated explicitly, while acoustic waves are treated implicitly, thus avoiding severe CFL restrictions for low Mach flows. High order accuracy in time is obtained by semi-implicit temporal integrator based on the IMEX Runge-Kutta (IMEX-RK) framework. High order in space is achieved by finite difference WENO schemes with characteristic-wise reconstructions adapted to the semi-implicit IMEX-RK time discretization. Type A IMEX schemes are constructed to handle not well-prepared initial conditions. Besides, these schemes are proven to be asymptotic preserving and asymptotically accurate as the Mach number vanishes for well-prepared initial conditions. Divergence-free property of the time-discrete schemes is proved. The proposed scheme can also well capture discontinuous solutions in the compressible regime, especially for two dimensional Riemann problems. Numerical tests in one and two space dimensions will illustrate the effectiveness of the proposed schemes. © 2021, CC BY.

关键词： Mach number

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Inter-slice image augmentation based on frame interpolation for boosting medical image segmentation accuracy

arXiv

引用

arXiv 2020年

作者： Wu, Zhaotao Wei, Jia Yuan, Wenguang Wang, Jiabing Tasdizen, Tolga School of Computer Science and Engineering South China University of Technology Guangzhou China Scientific Computing and Imaging Institute University of Utah Salt Lake City United States

We introduce the idea of inter-slice image augmentation whereby the numbers of the medical images and the corresponding segmentation labels are increased between two consecutive images in order to boost medical image segmentation accuracy. Unlike conventional data augmentation methods in medical imaging, which only increase the number of training samples directly by adding new virtual samples using simple parameterized transformations such as rotation, flipping, scaling, etc., we aim to augment data based on the relationship between two consecutive images, which increases not only the number but also the information of training samples. For this purpose, we propose a frame-interpolation-based data augmentation method to generate intermediate medical images and the corresponding segmentation labels between two consecutive images. We train and test a supervised U-Net liver segmentation network on SLIVER07 and CHAOS2019, respectively, with the augmented training samples, and obtain segmentation scores exhibiting significant improvement compared to the conventional augmentation methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Sampling

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