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A Lightweight Feature Selection Method Based on Rankability

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SSRN

SSRN 2023年

作者： Kong, Lingping Silva, Juan Domingo Velasquez Perfilieva, Irina Pant, Millie Snášel, Václav Department of Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Industrial Engineering University of Chile Santiago Chile Santiago Chile University Hospital Ostrava Czech Republic Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India Instituto Sistemas Complejos de Ingeniería Santiago Chile Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Uttarakhand Roorkee247667 India

Feature selection, as one of the essential dimensionality reduction techniques, hasbecome one popular yet challenging area in the field, such as data mining andmachine learning. Unlike feature extraction (such as principle component analysis andnon-negative matrix factorization), preserving the entire information but losing thefeature relevance. Data processing in feature selection will lose information, leading tothe need to develop lightweight, efficient, and practical methods that preserve the datainformation as much as possible while performing dimensional reduction. In this paper,we propose a rankability-based feature selection method. The rankability concept wasproposed in 2019, similar to the entropy concept, and has not been studied widely *** proposed method is lightweight in terms of complexity, which requires no iterativeoptimization or auxiliary estimator *** experimented with sixteen datasets and compared our results with four otheralgorithms. The results show that our rankability-based feature selection methodoutperforms the fuzzy entropy-based method on five datasets in eight, and the averageaccuracy increased by 0.1482, 0.1078, and 0.1157, respectively. Then, in the varieddimension-reducing experiments, the proposed method shows superiority on fourdatasets out of eight and is competitive with others on two datasets out of eight. © 2023, The Authors. All rights reserved.

关键词： Feature Selection

Sanov-type large deviations and conditional limit theorems for high-dimensional Orlicz balls

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arXiv 2021年

作者： Frühwirth, Lorenz Prochno, Joscha Institute of Mathematics and Scientific Computing University of Graz Heinrichstraße 36 Graz8010 Austria Faculty of Computer Science and Mathematics University of Passau Innstraße 33 Passau94032 Germany

In this paper, we prove a Sanov-type large deviation principle for the sequence of empirical measures of vectors chosen uniformly at random from an Orlicz ball. From this level-2 large deviation result, in a combination with Gibbs conditioning, entropy maximization and an Orlicz version of the Poincaré-Maxwell-Borel lemma, we deduce a conditional limit theorem for high-dimensional Orlicz balls. Roughly speaking, the latter shows that if V1 and V2 are Orlicz functions, then random points in the V1-Orlicz ball, conditioned on having a small V2-Orlicz radius, look like an appropriately scaled V2-Orlicz ball. In fact, we show that the limiting distribution in our Poincaré-Maxwell-Borel lemma, and thus the geometric interpretation, undergoes a phase transition depending on the magnitude of the V2-Orlicz *** Codes Primary 60F05, 60F10, 52A20, Secondary 52A23, 60D05 Copyright © 2021, The Authors. All rights reserved.

关键词： Banach spaces

EXPLICIT RUNGE–KUTTA METHODS THAT ALLEVIATE ORDER REDUCTION

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arXiv 2023年

作者： Biswas, Abhijit Ketcheson, David I. Roberts, Steven Seibold, Benjamin Shirokoff, David Computer Electrical and Mathematical Sciences & Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States Department of Mathematics Temple University PhiladelphiaPA19122 United States Department of Mathematical Sciences New Jersey Institute of Technology NewarkNJ07102 United States

Explicit Runge–Kutta (RK) methods are susceptible to a reduction in the observed order of convergence when applied to initial-boundary value problem with time-dependent boundary conditions. We study conditions on explicit RK methods that guarantee high-order convergence for linear problems;we refer to these conditions as weak stage order conditions. We prove a general relationship between the method’s order, weak stage order, and number of stages. We derive explicit RK methods with high weak stage order and demonstrate, through numerical tests, that they avoid the order reduction phenomenon up to any order for linear problems and up to order three for nonlinear *** Codes 65L04, 65L20, 65M12 Copyright © 2023, The Authors. All rights reserved.

关键词： Runge Kutta methods

A biosensing system using a multiparameter nonlinear dynamic analysis of cardiomyocyte beating for drug-induced arrhythmia recognition

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Microsystems & Nanoengineering 2022年第3期8卷 277-290页

作者： Hao Wang Yue Wu Quchao Zou Wenjian Yang Zhongyuan Xu Hao Dong Zhjing Zhu Depeng Wang Tanxing Wang Ning Hu Diming Zhang State Key Laboratory of Optoelectronic Materials and Technologies Guangdong Province Key Laboratory of Display Material and TechnologySchool of Electronics and Information TechnologySun Yat-sen UniversityGuangzhou 510006China Research Center for Itelligent Sensing Systems Zhejiang LabHangzhou 311121China ZJU-Hangzhou Global Scientific and Technological Innovation Center Department of ChemistryThe Second Affiliated Hospital Zhejiang University School of MedicineDepartment of Clinical Medical EngineeringZhejiang UniversityHangzhou 310058China Key Laboratory of Novel Target and Drug Study for Neural Repair of Zhejang Province School of MedicineSchool of Computer&Computing ScienceZhejiang University City CollegeHangzhou 310015China School of Brain Science and Brain Medicine Zhejiang UniversityHangzhou 310058China College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China E-LinkCare Meditech Co LtdHangzhou 310011China State Key Laboratory of Transducer Technology Chinese Academy of SciencesShanghai 200050China

Cardiovascular disease is the number one cause of death in ***,cardiotoxicity is one of the most important adverse effects assessed by arrhythmia recognition in drug ***,cell-based techniques developed for arhythmia recognition primarily employ linear methods such as time-domain analysis that detect and compare individual waveforms and thus fall short in some applications that require automated and efficient arrhythmia recognition from large *** carried out the frst report to develop a biosensing system that integrated impedance measurement and multiparameter nonlinear dynamic algorithm(MNDA)analysis for druginduced arrhythmia recognition and *** biosensing system cultured cardiomyocytes as physiologically relevant models,used interdigitated electrodes to detect the mechanical beating of the cardiomyocytes,and employed MNDA analysis to recognize drug-induced arrhythmia from the cardiomyocyte beating *** best performing MNDA parameter,approximate entropy,enabled the system to recognize the appearance of sertindoleand norepinephrine-induced arrhythmia in the *** MNDA reconstruction in phase space enabled the system to classify the different arrhythmias and quantify the severity of *** new biosensing system utilizing MNDA provides a promising and alternative method for drug-induced arrhythmia recognition and classification in cardiological and pharmaceutical applications.

关键词： arrhythmia cardio analysis

Incoherent Digital Holography using Spiral Rotating Point Spread Functions Created by Double-helix Beams

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Incoherent Digital Holography using Spiral Rotating Point Sp...

Digital Holography and Three-Dimensional Imaging, DH 2022

作者： Dubey, Nitin Anand, Vijayakumar Khonina, Svetlana Kumar, Ravi Reddy, Andra Naresh Kumar Rosen, Joseph School of Electrical and Computer Engineering Ben-Gurion University of the Negev P.O. Box 653 Beer-Sheva8410501 Israel Institute of Physics University of Tartu Tartu50411 Estonia School of Science Computing and Engineering Technologies Swinburne University of Technology Hawthorn MelbourneVIC3122 Australia Samara National Research University Samara443086 Russia Image Processing Systems Institute Branch of the Federal Scientific Research Centre "Crystallography and Photonics" of Russian Academy of Sciences Samara443001 Russia Hee Photonic Labs RigaLV-1002 Latvia Department of Physics of Complex Systems Weizmann Institute of Science Rehovot7610001 Israel

A new incoherent 3D imaging system with a rotating point spread function has been developed. Different computational reconstruction methods such as non-linear reconstruction and the Lucy-Richardson-Rosen algorithm wer... 详细信息

ISBN: (纸本)9781957171128

关键词： Optical transfer function

MAP-based Problem-Agnostic Diffusion Model for Inverse Problems

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arXiv 2025年

作者： Tao, Pingping Liu, Haixia Su, Jing Yang, Xiaochen Tan, Hongchen Shandong University Library No. 180 West Culture Road Shandong Weihai264209 China School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology No. 1037 Luoyu road Hubei Wuhan430074 China Dapartment of Basic Sciences Dalian University of Science and Technology No. 999-26 Harbor Road Liaoning Dalian116052 China School of Computer Science and Technology Harbin Institute of Technology No. 2 West Culture Road Shandong Weihai264209 China Institute of Future Technology Dalian University of Technology No. 2 Lingong Road Liaoning Dalian116081 China

Diffusion models have indeed shown great promise in solving inverse problems in image processing. In this paper, we propose a novel, problem-agnostic diffusion model called the maximum a posteriori (MAP)-based guided term estimation method for inverse problems. To leverage unconditionally pretrained diffusion models to address conditional generation tasks, we divide the conditional score function into two terms according to Bayes’ rule: an unconditional score function (approximated by a pretrained score network) and a guided term, which is estimated using a novel MAP-based method that incorporates a Gaussian-type prior of natural images. This innovation allows us to better capture the intrinsic properties of the data, leading to improved performance. Numerical results demonstrate that our method preserves contents more effectively compared to state-of-the-art methods—for example, maintaining the structure of glasses in super-resolution tasks and producing more coherent results in the neighborhood of masked regions during inpainting. Our numerical implementation is available at https://***/liuhaixias1/ MAP-DIFFUSION-IP. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

CNN-based Classification Framework for Tissues of Lung with Additional Information

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arXiv 2022年

作者： Hu, Huafeng Ye, Ruijie Thiyagalingam, Jeyarajan Coenen, Frans Su, Jionglong Department of Electrical and Electronic Engineering University of Liverpool Based at Xi'an Jiaotong-Liverpool University Jiangsu Suzhou215123 China Department of Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom Scientific Computing Department Science and Technologies Facilities Council Harwell Campus OxfordOX11 0GD United Kingdom School of Ai and Advanced Computing Xi'an Jiaotong-Liverpool University Jiangsu Suzhou215123 China

Interstitial lung diseases are a large group of heterogeneous diseases characterized by different degrees of alveolitis and pulmonary fibrosis. Accurately diagnosing these diseases has significant guiding value for formulating treatment plans. Although previous work has produced impressive results in classifying interstitial lung diseases, there is still room for improving the accuracy of these techniques, mainly to enhance automated decision-making. In order to improve the classification precision, our study proposes a convolutional neural networks-based framework with additional information. Firstly, ILD images are added with their medical information by re-scaling the original image in Hounsfield Units. Secondly, a modified CNN model is used to produce a vector of classification probability for each tissue. Thirdly, location information of the input image, consisting of the occurrence frequencies of different diseases in the CT scans on certain locations, is used to calculate a location weight vector. Finally, the Hadamard product between two vectors is used to produce a decision vector for the prediction. Compared to the state-of-the-art methods, the results using a publicly available ILD database show the potential of predicting these using different additional information. Copyright © 2022, The Authors. All rights reserved.

关键词： Tissue

SHAMS-Smart Hospital Assisting Multitasking System

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SHAMS-Smart Hospital Assisting Multitasking System

IEEE International Conference on Intelligent computing and Information Systems (ICICIS)

作者： Esraa Tarek Sadek Moataz Mohammed Mohammad Essam Mohammad Nagwa Lotfy Badr Mohamed Atef Mohamed Ahmed Ehab Ahmed Ahmed Ragab Abdelghany Computer Systems FCIS Ain Shams University Cairo Egypt Computer Science FCIS Ain Shams University Cairo Egypt Scientific Computing FCIS Ain Shams University Cairo Egypt FCIS Ain Shams University Cairo Egypt

ISBN: (纸本)9781665411592

Advancements in robotics and artificial intelligence technologies have added a prominent contribution in healthcare services. Due to the exponential increase in synthetic viruses specifically these days, the Covid-19 pandemic caused a high rate of infection and death of hospitals’ staff. SHAMS-Smart Hospital Assisting Multitasking System was proposed as the first line of defense between hospital staff and this epidemic. Using cutting edge technologies, SHAMS utilized robotics, embedded systems, electrical engineering, electronics, computer vision, natural language processing, and software engineering to facilitate its services. SHAMS can autonomously navigate, and sterilize the hospital, recognize hospital staff, understand speech commands, deliver medicines to patient room, and afford services to patients. Moreover, making self-sterilizing. This paper studies the development and the impact of utilizing autonomous robots in the healthcare crisis. This research paper discusses the main modules of SHAMS robot. SHAMS showed its efficiency, reliability, and scalability in the medical domain. SHAMS also paved the way for robotics to be utilized in various fields in the middle east.

关键词： COVID-19 Hospitals Scalability Surgery Speech recognition Speech enhancement Multitasking

Quadratic pseudospectrum for identifying localized states

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arXiv 2022年

作者： Cerjan, Alexander Loring, Terry A. Vides, Fredy Center for Integrated Nanotechnologies Sandia National Laboratories AlbuquerqueNM87185 United States Department of Mathematics and Statistics University of New Mexico AlbuquerqueNM87123 United States Scientific Computing Innovation Center School of Mathematics and Computer Science Universidad Nacional Autónoma de Honduras Tegucigalpa Honduras

We examine the utility of the quadratic pseudospectrum in photonics and condensed matter. Specifically, the quadratic pseudospectrum represents a method for approaching systems with incompatible observables, as it both minimizes the "eigen-error" in the joint approximate spectrum of the incompatible observables and does not increase the system's computational complexity. Moreover, we derive an important estimate relating the Clifford and quadratic pseudospectra. Finally, we prove that the quadratic pseudospectrum is local, and derive the bounds on the errors that are incurred by truncating the system in the vicinity of where the pseudospectrum is being calculated. Copyright © 2022, The Authors. All rights reserved.

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