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heart-Net: A Multi-Modal Deep Learning Approach for Diagnosing Cardiovascular Diseases

Computers, Materials and Continua 2024年第3期80卷 3967-3990页

作者： Alsekait D.M. Shdefat A.y. Nabil A. Nawaz A. Rana M.R.R. Ahmed Z. Fathi h. AbdElminaam D.S. Department of Computer Science and Information Technology Applied College Princess Nourah bint Abdulrahman University Riyadh 84428 Saudi Arabia College of Engineering and Technology American University of the Middle East Egaila 15453 Kuwait Faculty of Computers Science Misr International University Cairo 11800 Egypt University Institute of Information Technology PMAS Arid Agriculture University Rawalpindi 46000 Pakistan Department of Computer Science International Islamic University Islamabad 04436 Pakistan Jadara Research Center Jadara University Irbid 21110 Jordan Information System Department Faculty of Computers and Artificial Intelligence Benha University Banha 13511 Egypt MEU Research Unit Middle East University Amman 11831 Jordan

heart disease remains a leading cause of morbidity and mortality worldwide, highlighting the need for improved diagnostic methods. Traditional diagnostics face limitations such as reliance on single-modality data and vulnerability to apparatus faults, which can reduce accuracy, especially with poor-quality images. Additionally, these methods often require significant time and expertise, making them less accessible in resource-limited settings. Emerging technologies like artificial intelligence and machine learning offer promising solutions by integrating multi-modality data and enhancing diagnostic precision, ultimately improving patient outcomes and reducing healthcare costs. This study introduces heart-Net, a multi-modal deep learning framework designed to enhance heart disease diagnosis by integrating data from Cardiac Magnetic Resonance Imaging (MRI) and Electrocardiogram (ECG). heart-Net uses a 3D U-Net for MRI analysis and a Temporal Convolutional Graph Neural Network (TCGN) for ECG feature extraction, combining these through an attention mechanism to emphasize relevant features. Classification is performed using Optimized TCGN. This approach improves early detection, reduces diagnostic errors, and supports personalized risk assessments and continuous health monitoring. The proposed approach results show that heart-Net significantly outperforms traditional single-modality models, achieving accuracies of 92.56% for heartnet Dataset I (hNET-DSI), 93.45% for heartnet Dataset II (hNET-DSII), and 91.89% for heartnet Dataset III (hNET-DSIII), mitigating the impact of apparatus faults and image quality issues. These findings underscore the potential of heart-Net to revolutionize heart disease diagnostics and improve clinical outcomes. Copyright © 2024 The Authors. Published by Tech Science Press.

关键词： classification deep learning electrocardiogram heart diseases magnetic resonance imaging

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Evaluation of Industrial IoT Service Providers with TOPSIS Based on Circular Intuitionistic Fuzzy Sets

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Computers, Materials & Continua 2024年第7期80卷 715-746页

作者： Elif Çalo˘glu Büyükselçuk Industrial Engineering Department Fenerbahçe University˙Istanbul34758Turkey

Industrial Internet of Things(IIoT)service providers have become increasingly important in the manufacturing industry due to their ability to gather and process vast amounts of data from connected devices,enabling manufacturers to improve operational efficiency,reduce costs,and enhance product *** platforms provide manufacturers with real-time visibility into their production processes and supply chains,allowing them to optimize operations and make informed *** addition,IIoT service providers can help manufacturers create new revenue streams through the development of innovative products and services and enable them to leverage the benefits of emerging technologies such as Artificial Intelligence(AI)and machine ***,the implementation of IIoT platforms in the manufacturing industry is crucial for companies seeking to remain competitive and meet the ever-increasing demands of customers in the digital *** this study,the evaluation criteria to be considered in the selection of IIoT service provider in small andmedium-sized(SME)manufacturing enterprises will be determined and IIoT service providers alternatives will be evaluated using the technique for order preference by similarity to an ideal solution(TOPSIS)method based on circular intuitionistic fuzzy *** on the assessments conducted in accordance with the literature review and expert consultations,a set of 8 selection criteria has been *** criteria encompass industry expertise,customer support,flexibility and scalability,security,cost-effectiveness,reliability,data analytics,as well as compatibility and *** evaluating these criteria,it was observed that the security criterion holds the highest significance,succeeded by cost-effectiveness,data analytics,flexibility and scalability,reliability,and customer support criteria,in descending order of *** the evaluation of seven distinct alternatives against these criteria,it was deduced tha

关键词： IIoT manufacturing TOPSIS circular intuitionistic fuzzy sets

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Exponentially Convergent Multiscale Finite Element Method

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Communications on Applied Mathematics and Computation 2024年第2期6卷 862-878页

作者： yifan Chen Thomas y.hou yixuan Wang Applied and Computational Mathematics CaltechPasadena 91106USA

We provide a concise review of the exponentially convergent multiscale finite element method(ExpMsFEM)for efficient model reduction of PDEs in heterogeneous media without scale separation and in high-frequency wave *** ExpMsFEM is built on the non-overlapped domain decomposition in the classical MsFEM while enriching the approximation space systematically to achieve a nearly exponential convergence rate regarding the number of basis *** most generalizations of the MsFEM in the literature,the ExpMsFEM does not rely on any partition of unity *** general,it is necessary to use function representations dependent on the right-hand side to break the algebraic Kolmogorov n-width barrier to achieve exponential ***,there are online and offline parts in the function representation provided by the *** online part depends on the right-hand side locally and can be computed in parallel *** offline part contains basis functions that are used in the Galerkin method to assemble the stiffness matrix;they are all independent of the right-hand side,so the stiffness matrix can be used repeatedly in multi-query scenarios.

关键词： Multiscale method Exponential convergence helmholtz's equation Domain decomposition Nonlinear model reduction

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Convexification of hybrid AC-DC Optimal Power Flow with Line-Commutated Converters

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 617-628页

作者： hongyuan Liang Zhigang Li J.h.Zheng Q.h.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Line-commutated converter (LCC)-based high-voltage DC (hVDC) systems have been integrated with bulk AC power grids for interregional transmission of renewable power. The nonlinear LCC model brings additional nonconvexity to optimal power flow (OPF) of hybrid AC-DC power grids. A convexification method for the LCC station model could address such nonconvexity but has rarely been discussed. We devise an equivalent reformulation for classical LCC station models that facilitates second-order cone convex relaxation for the OPF of LCC-based AC-DC power grids. We also propose sufficient conditions for exactness of convex relaxation with its proof. Equivalence of the proposed LCC station models and properties, exactness, and effectiveness of convex relaxation are verified using four numerical simulations. Simulation results demonstrate a globally optimal solution of the original OPF can be efficiently obtained from relaxed model.

关键词： AC-DC power system convex relaxation linecommutated converter optimal power flow second-order cone programming

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Shell-model representations of the microscopic version of the Bohr-Mottelson collective model

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Communications in Theoretical Physics 2024年第8期76卷 79-90页

作者： h G Ganev Joint Institute for Nuclear Research DubnaRussia Institute of Mechanics Bulgarian Academy of SciencesSofiaBulgaria

The structure of the irreducible collective spaces of the group Sp(12,R),which many-particle nuclear states are classified according to the chain Sp(12,R)⊃U(6)⊃SO(6)⊃SU_(pn)(3)⊗SO(2)⊃SO(3)of the proton-neutron symplectic model(PNSM),is considered in *** chain of the PNSM was recently shown to correspond to a microscopic shell-model version of the Bohr-Mottelson collective *** construction of the relevant shell-model representations of the Sp(12,R)group along this chain is considered for three nuclei with varying collective properties and from different mass *** is shown that the SU_(pn)(3)basis states of the Sp(12,R)representations belonging to the SO(6)irreps with seniorityυ≥υ0,withυ0 denoting the maximal seniority SO(6)irrep contained in the Sp(12,R)bandhead,are always Pauli allowed,but organized in a different way into different SO(6)*** is in contrast to the case of filling the levels of the standard three-dimensional harmonic oscillator and using the plethysm *** the SU_(pn)(3)multiplets withinυhe present work are important for the practical application of the microscopic version of the Bohr-Mottelson collective model.

关键词： microscopic shell-model version of the Bohr-Mottelson model proton-neutron symplectic model Sp(12,R)dynamical algebra shell-model representations

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Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第6期16卷 2198-2218页

作者： Mengqi Wang y.T.Feng Shaoheng Guan Tongming Qu Zienkiewicz Centre for Computational Engineering Faculty of Science and EngineeringSwansea UniversitySwanseaWalesSA18EPUK Institute of Theoretical and Computational Physics Graz University of TechnologyGraz8010Austria Department of Civil and Environmental Engineering Hong Kong University of Science and TechnologyClearwater BayKowloonHong KongChina

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading *** this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular *** obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing *** obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved *** results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

关键词： Granular materials history-dependence Multi-layer perceptron(MLP) Discrete element method FEM-DEM Machine learning

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Multi-population particle swarm optimization algorithm for automatic design of steel frames

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Frontiers of Structural and Civil Engineering 2024年第1期18卷 89-103页

作者： Wenchen ShAN Jiepeng LIU yao DING y.Frank ChEN Junwen ZhOU Institute of Smart City and Intelligent Transportation Southwest Jiaotong UniversityChengdu 610000China School of Civil Engineering Chongqing UniversityChongqing 400045China Department of Civil Engineering the Pennsylvania State UniversityMiddletownPA 17057USA

Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost ***,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design *** are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative *** proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design *** related parameter influences on optimization results are *** the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65% and can obtain frame with the weight for at least 2.4%lighter.A similar trend can also be observed in cases subjected to Chinese design *** addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO *** purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design *** aims to provide a reference for automatic structural optimization design problems even with dimensional *** proposed method can be easily generalized to the optimization problem of other structural systems.

关键词： steel frame multi-population particle swarm optimization automatic structural optimization design

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Photometric and Spectroscopic Study of Ten Low Mass Ratio Contact Binary Systems:Orbital Stability,O'Connell Effect and Infrared Calcium Line Filling

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Research in Astronomy and Astrophysics 2024年第8期24卷 212-222页

作者： Surjit S.Wadhwa Adam Popowicz Raúl Michel Petar Kostić Oliver Vince Nick F.h.Tothill Ain y.De horta Miroslav D.Filipović School of Science Western Sydney UniversityLocked Bag 1797PenrithNSW 2751Australia Department of Electronics Electrical Engineering and MicroelectronicsSilesian University of TechnologyAkademicka 1644120 GliwicePoland Instituto de Astronomía UNAM.A.P.87722800 EnsenadaBCMéxico Astronomical Observatory Volgina 711060 BelgradeSerbia

Low mass ratio contact binary systems are more likely to have unstable orbits and potentially *** addition,such systems exhibit characteristics such as starspots and high energy emissions(UV)suggestive of chromospheric and magnetic *** curve modeling of ten contact binary systems is *** were found to be of extreme low mass ratio ranging from 0.122 to 0.24 and three were found to be potentially unstable and possible merger *** of the infrared calcium absorption lines is a marker of increased chromospheric *** use the available Large Sky Area Multi-Object Fiber Spectroscopic Telescope spectra along with matched standard spectra(broadened for rotation)to measure the excess filling of the central core depression flux of the two main infrared calcium absorption linesλ8542 andλ*** find that all reported contact binaries have excess filling of the core flux in the infrared calcium *** of the systems reported were also observed by the Galaxy Evolution Explorer mission and we find that all three have features of excess ultraviolet emissions further adding evidence for increased chromospheric activity in low mass ratio contact *** of both orbital stability and absorption line filling is dependent on the determination of geometric and absolute parameters from light curve *** an insignificant number of contact binary light curves exhibit the O’Connell effect,usually attributed to *** discuss the inclusion of starspots in light curve solutions and how they influence the geometric and absolute parameters.

关键词： (stars)binaries eclipsing-techniques photometric-stars chromospheres

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Marinoan glaciation in the Indian subcontinent——Anatomy and global implications

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Journal of Palaeogeography 2024年第2期13卷 293-308页

作者： h.N.Bhattacharya Department of Earth Sciences Techno India UniversityWest BengalSector VSalt LakeKolkata700091India

Detailed sedimentological analysis of the Pokaran Boulder Bed,representing the most basal unit of the Neoproterozoic-Lower Cambrian Marwar Supergroup,clearly indicates its glacial *** glacial sediments are interpreted as an ice-contact submarine fan *** on the detrital and inherited zircon population of the Marwar Supergroup sediments and interlayered pyroclastic deposits,a Marinoan cryochron of the Cryogenian Period is envisaged for the Pokaran Boulder *** well-preserved Ediacaran elements in the post-glacial sedimentary succession also support a Cryogenian to Early Cambrian age of the Marwar *** glacial deposition at the base of the Marwar Supergroup strengthens the regional correlation between the studied sediments with the Lesser himalayan Blaini-Krol-Tal sediments and the haqf Supergroup of *** available zircon ages and paleomagnetic data of the Malani Igneous suite,along with the Marinoan glacial deposits,detrital zircon ages,and Ediacaran fossil elements of the Marwar Supergroup add significant information to the Neoproterozoic Earth history.

关键词： Neoproterozoic Marinoan glaciation Diamictites Pokaran Boulder Bed Marwar Supergroup

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Skeletal muscle as a molecular and cellular biomarker of disease progression in amyotrophic lateral sclerosis:a narrative review

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Neural Regeneration Research 2024年第4期19卷 747-753页

作者： Peter h.King Department of Neurology and Center for Neurodegeneration and Experimental Therapeutics The University of Alabama at BirminghamBirminghamALUSA Birmingham Veterans Affairs Medical Center BirminghamALUSA

Amyotrophic lateral sclerosis is a fatal multisystemic neurodegenerative disease with motor neurons being a primary *** progressive weakness is a hallmark feature of amyotrophic lateral sclerosis,there is considerable heterogeneity,including clinical presentation,progression,and the underlying triggers for disease *** on longitudinal studies with families harboring amyotrophic lateral sclerosis-associated gene mutations,it has become apparent that overt disease is preceded by a prodromal phase,possibly in years,where compensatory mechanisms delay symptom *** 85-90%of amyotrophic lateral sclerosis is sporadic,there is a strong need for identifying biomarkers that can detect this prodromal phase as motor neurons have limited capacity for *** Food and Drug Administration-approved therapies work by slowing the degenerative process and are most effective early in the *** muscle,including the neuromuscular junction,manifests abnormalities at the earliest stages of the disease,before motor neuron loss,making it a promising source for identifying biomarkers of the prodromal *** accessibility of muscle through biopsy provides a lens into the distal motor system at earlier stages and in real *** advent of“omics”technology has led to the identification of numerous dysregulated molecules in amyotrophic lateral sclerosis muscle,ranging from coding and non-coding RNAs to proteins and *** technology has opened the door for identifying biomarkers of disease activity and providing insight into disease mechanisms.A major challenge is correlating the myriad of dysregulated molecules with clinical or histological progression and understanding their relevance to presymptomatic phases of *** are two major goals of this *** first is to summarize some of the biomarkers identified in human amyotrophic lateral sclerosis muscle that have a clinicopathological correlation with disease activi

关键词： amyotrophic lateral sclerosis biomarkers clinicopathological correlation disease progression muscle biomarkers neurogenic atrophy neuromuscular junction non-coding RNAs presymptomatic stages skeletal muscle SOD1G93A mouse model

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