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An Optimal Framework for SDN Based on Deep Neural Network

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Computers, Materials & Continua 2022年第10期73卷 1125-1140页

作者： Abdallah Abdallah Mohamad Khairi Ishak Nor Samsiah Sani Imran Khan Fahad RAlbogamy Hirofumi Amano Samih M.Mostafa Department of Industrial Engineering School of Applied Technical Sciences German Jordanian UniversityAmman35247Jordan School of Electrical and Electronic Engineering Universiti Sains MalaysiaNibong Tebal14300Malaysia Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyThe National University of Malaysia(UKM)Bangi43600SelangorMalaysia Department of Electrical Engineering University of Engineering and TechnologyPeshawar814Pakistan Turabah University College Computer Sciences ProgramTaif UniversityTaif21944Saudi Arabia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Software-defined networking(SDN)is a new paradigm that promises to change by breaking vertical integration,decoupling network control logic from the underlying routers and switches,promoting(logical)network control centralization,and introducing network ***,the controller is similarly vulnerable to a“single point of failure”,an attacker can execute a distributed denial of service(DDoS)attack that invalidates the controller and compromises the network security in *** address the problem of DDoS traffic detection in SDN,a novel detection approach based on information entropy and deep neural network(DNN)is *** approach contains a DNN-based DDoS traffic detection module and an information-based entropy initial inspection *** initial inspection module detects the suspicious network traffic by computing the information entropy value of the data packet’s source and destination Internet Protocol(IP)addresses,and then identifies it using the DDoS detection module based on *** assaults were found when suspected irregular traffic was *** reveal that the algorithm recognizes DDoS activity at a rate of more than 99%,with a much better accuracy *** false alarm rate(FAR)is much lower than that of the information entropy-based detection ***,the proposed framework can shorten the detection time and improve the resource utilization efficiency.

关键词： Deep neural network computer networks data security optimization

Coarse-graining conformational dynamics with multi-dimensional generalized Langevin equation: how, when, and why

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arXiv 2024年

作者： Xie, Pinchen Qiu, Yunrui Weinan, E. Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Department of Chemistry University of Wisconsin-Madison MadisonWI53706 United States AI for Science Institute Beijing100080 China Center for Machine Learning Research School of Mathematical Sciences Peking University Beijing100084 China

A data-driven ab initio generalized Langevin equation (AIGLE) approach is developed to learn and simulate high-dimensional, heterogeneous, coarse-grained conformational dynamics. Constrained by the fluctuation-dissipation theorem, the approach can build coarse-grained models in dynamical consistency with all-atom molecular dynamics. We also propose practical criteria for AIGLE to enforce long-term dynamical consistency. Case studies of a toy polymer, with 20 coarse-grained sites, and the alanine dipeptide, with two dihedral angles, elucidate why one should adopt AIGLE or its Markovian limit for modeling coarse-grained conformational dynamics in practice. © 2024, CC BY.

关键词： Coarse-grained modeling

Heat transport and convective velocities in compositionally-driven convection in neutron star and white dwarf interiors

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arXiv 2023年

作者： Fuentes, J.R. Cumming, Andrew Castro-Tapia, Matias Anders, Evan H. Department of Applied Mathematics University of Colorado Boulder BoulderCO80309-0526 United States Department of Physics Trottier Space Institute McGill University MontrealQCH3A 2T8 Canada Center for Interdisciplinary Exploration and Research in Astrophysics Northwestern University EvanstonIL60201 United States

We investigate heat transport associated with compositionally-driven convection driven by crystallization at the ocean-crust interface in accreting neutron stars, or growth of the solid core in cooling white dwarfs. We study the effect of thermal diffusion and rapid rotation on the convective heat transport, using both mixing length theory and numerical simulations of Boussinesq convection. We determine the heat flux, composition gradient and Péclet number, Pe (the ratio of thermal diffusion time to convective turnover time) as a function of the composition flux. We find two regimes of convection with a rapid transition between them as the composition flux increases. At small Pe, the ratio between the heat flux and composition flux is independent of Pe, because the loss of heat from convecting fluid elements due to thermal diffusion is offset by the smaller composition gradient needed to overcome the reduced thermal buoyancy. At large Pe, the temperature gradient approaches the adiabatic gradient, saturating the heat flux. We discuss the implications for neutron star and white dwarf cooling. Convection in neutron stars spans both regimes. We find rapid mixing of neutron star oceans, with a convective turnover time of order weeks to minutes depending on rotation. Except during the early stages of core crystallization, white dwarf convection is in the thermal-diffusion-dominated fingering regime. We find convective velocities much smaller than recent estimates for crystallization-driven dynamos. The small fraction of energy carried as kinetic energy calls into question the effectiveness of crystallization-driven dynamos as an explanation for observed white dwarf magnetic fields. © 2023, CC BY.

关键词： Heat flux

An immersed peridynamics model of fluid-structure interaction accounting for material damage and failure

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arXiv 2022年

作者： Kim, Keon Ho Bhalla, Amneet P.S. Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States Department of Mechanical Engineering San Diego State University San DiegoCA United States Departments of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States

This paper develops and benchmarks an immersed peridynamics method to simulate the deformation, damage, and failure of hyperelastic materials within a fluid-structure interaction framework. The immersed peridynamics method describes an incompressible structure immersed in a viscous incompressible fluid. It expresses the momentum equation and incompressibility constraint in Eulerian form, and it describes the structural motion and resultant forces in Lagrangian form. Coupling between Eulerian and Lagrangian variables is achieved by integral transforms with Dirac delta function kernels, as in standard immersed boundary methods. The major difference between our approach and conventional immersed boundary methods is that we use peridynamics, instead of classical continuum mechanics, to determine the structural forces. We focus on non-ordinary state-based peridynamic material descriptions that allow us to use a constitutive correspondence framework that can leverage well-characterized nonlinear constitutive models of soft materials. The convergence and accuracy of our approach are compared to both conventional and immersed finite element methods using widely used benchmark problems of nonlinear incompressible elasticity. We demonstrate that the immersed peridynamics method yields comparable accuracy with similar numbers of structural degrees of freedom for several choices of the size of the peridynamic horizon. We also demonstrate that the method can generate grid-converged simulations of fluid-driven material damage growth, crack formation and propagation, and rupture under large deformations. © 2022, CC BY-SA.

关键词： Continuum mechanics

A class of dimension-free metrics for the convergence of empirical measures

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arXiv 2021年

作者： Han, Jiequn Hu, Ruimeng Long, Jihao Department of Mathematics Princeton University PrincetonNJ08544-1000 United States Department of Mathematics Department of Statistics and Applied Probability University of California Santa BarbaraCA93106-3080 United States The Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544-1000 United States

This paper concerns the convergence of empirical measures in high dimensions. We propose a new class of probability metrics and show that under such metrics, the convergence is free of the curse of dimensionality (CoD). Such a feature is critical for high-dimensional analysis and stands in contrast to classical metrics (e.g., the Wasserstein metric). The proposed metrics fall into the category of integral probability metrics, for which we specify criteria of test function spaces to guarantee the property of being free of CoD. Examples of the selected test function spaces include the reproducing kernel Hilbert spaces, Barron space, and flow-induced function spaces. Three applications of the proposed metrics are presented: 1. The convergence of empirical measure in the case of random variables;2. The convergence of n-particle system to the solution to McKean-Vlasov stochastic differential equation;3. The construction of an Ε-Nash equilibrium for a homogeneous n-player game by its mean-field limit. As a byproduct, we prove that, given a distribution close to the target distribution measured by our metric and a certain representation of the target distribution, we can generate a distribution close to the target one in terms of the Wasserstein metric and relative entropy. Overall, we show that the proposed class of metrics is a powerful tool to analyze the convergence of empirical measures in high dimensions without *** Codes 60B10, 60E15, 60K35, 91A16, 60H10 © 2021, CC BY.

关键词： Stochastic systems

Random conical tilt reconstruction without particle picking in cryo-electron microscopy

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arXiv 2021年

作者： Lan, Ti-Yen Boumal, Nicolas Singer, Amit Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Institute of Mathematics EPFL LausanneCH-1015 Switzerland Department of Mathematics Princeton University PrincetonNJ08544 United States

We propose a method to reconstruct the 3-D molecular structure from micrographs collected at just one sample tilt angle in the random conical tilt scheme in cryo-electron microscopy. Our method uses autocorrelation analysis on the micrographs to estimate features of the molecule which are invariant under certain nuisance parameters such as the positions of molecular projections in the micrographs. This enables us to reconstruct the molecular structure directly from micrographs, completely circumventing the need for particle picking. We demonstrate reconstructions with simulated data and investigate the effect of the missing-cone region. These results show promise to reduce the size limit for single particle reconstruction in cryo-electron microscopy. © 2021, CC BY.

关键词： Electron microscopes

Coupled Chemical Reactions: Effects of Electric Field, Diffusion and Boundary Control

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arXiv 2023年

作者： Xu, Shixin Eisenberg, Robert Song, Zilong Huang, Huaxiong Zu Chongzhi Center for Mathematics and Computational Sciences Duke Kunshan University 8 Duke Ave Jiangsu Kunshan China Department of Applied Mathematics Illinois Institute of Technology ChicagoIL60616 United States Department of Physiology and Biophysics Rush University Chicago IL60612 United States Math and Statistics Department Utah State University Old Main Hill Logan UT84322 United States Research Center for Mathematics Advanced Institute of Natural Sciences Beijing Normal University Guangdong Zhuhai519088 China Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNU-HKBU United International College Guangdong Zhuhai519088 China Laboratory of Mathematics and Complex Systems MOE Beijing Normal University Beijing100875 China Department of Mathematics and Statistics York University TorontoONM3J 1P3 Canada

MSC Codes 92E20, 92B05, 35Q92Chemical reactions involve the movement of charges, and this work presents a mathematical model for describing chemical reactions in electrolytes. The model is developed using an energy variational method that aligns with classical thermodynamics principles. It encompasses both electrostatics and chemical reactions within consistently defined energetic and dissipative functionals. Furthermore, the energy variation method is extended to account for open systems that involve the input and output of charge and mass. Such open systems have the capability to convert one form of input energy into another form of output energy. In particular, a two-domain model is developed to study a reaction system with self-regulation and internal switching, which plays a vital role in the electron transport chain of mitochondria responsible for ATP generation-a crucial process for sustaining life. Simulations are conducted to explore the influence of electric potential on reaction rates and switching dynamics within the two-domain system. It shows that the electric potential inhibits the oxidation reaction while accelerating the reduction reaction. © 2023, CC BY.

关键词： Open systems

An Immersed Peridynamics Model of Fluid-Structure Interaction Accounting for Material Damage and Failure

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SSRN

SSRN 2022年

作者： Kim, Keon Ho Bhalla, Amneet Pal Singh Griffith, Boyce E. Department of Mathematics University of North Carolina Chapel HillNC United States Department of Mechanical Engineering San Diego State University San DiegoCA United States Departments of Mathematics Applied Physical Sciences and Biomedical Engineering University of North Carolina Chapel HillNC United States Carolina Center for Interdisciplinary Applied Mathematics University of North Carolina Chapel HillNC United States Computational Medicine Program University of North Carolina Chapel HillNC United States McAllister Heart Institute University of North Carolina Chapel HillNC United States

This paper develops and benchmarks an immersed peridynamics method to simulate the deformation, damage, and failure of hyperelastic materials within a fluid-structure interaction framework. The immersed peridynamics method describes an incompressible structure immersed in a viscous incompressible fluid. It expresses the momentum equation and incompressibility constraint in Eulerian form, and it describes the structural motion and resultant forces in Lagrangian form. Coupling between Eulerian and Lagrangian variables is achieved by integral transforms with Dirac delta function kernels, as in standard immersed boundary (IB) methods. The major difference between our approach and conventional IB methods is that we use peridynamics, instead of classical continuum mechanics, to determine the structural forces. We focus on non-ordinary state-based peridynamic material descriptions that allow us to use a constitutive correspondence framework that can leverage well characterized nonlinear constitutive models of soft materials. The convergence and accuracy of our approach are compared to both conventional and immersed finite element methods using widely used benchmark problems of nonlinear incompressible elasticity. We demonstrate that the immersed peridynamics method yields comparable accuracy with similar numbers of structural degrees of freedom for several choices of the size of the peridynamic horizon. We also demonstrate that the method can generate grid-converged simulations of fluid-driven material damage growth, crack formation and propagation, and rupture under large deformations. © 2022, The Authors. All rights reserved.

关键词： Fluid structure interaction

Nonlinear vibration analysis of cantilever beams: Analytical, numerical and experimental perspectives

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Partial Differential Equations in applied mathematics 2025年 13卷

作者： Abbas, Qamar Nawaz, Rab Yaqoob, Haseeb Ali, Hafiz Muhammad Jamil, Muhammad Musaddiq Department of Mechanical Engineering King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia Center for Applied Mathematics and Bioinformatics (CAMB) Gulf University for Science and Technology Hawally 32093 Kuwait Department of Mathematics COMSATS University Islamabad Park Road Islamabad Tarlai Kalan 45550 Pakistan Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES) King Fahd University of Petroleum & Minerals Dhahran 31261 Saudi Arabia Department of Computer Science Friedrich-Alexander-Universität Erlangen-Nürnberg 91054 Germany

This study investigates the vibrational behavior of a mild steel cantilever beam with and without an attached end mass using experimental, numerical, analytical, and computational methods. Vibrational frequencies were determined using LABVIEW, MATLAB, and SOLIDWORKS, with analytical results derived from Euler-Bernoulli beam (EBB) theory. Experimental results closely matched MATLAB simulations, with an average percentage error of 1.44%, but showed a 14.44% deviation from analytical results due to neglected accelerometer mass. Findings highlight the importance of precise modeling, accounting for factors like damping and mass effects, to achieve accurate results. The study underscores the significance of resonant frequency identification in mitigating vibration failures in engineering systems. © 2025 The Author(s)

关键词： Analytical Cantilever beams Experimental Nonlinear vibration analysis Numerical