检索结果-内蒙古大学图书馆

Regularized lattice Boltzmann method based maximum principle and energy stability preserving finite-difference scheme for the Allen-Cahn equation

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Chen, Ying Liu, Xi Chai, Zhenhua Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

The Allen-Cahn equation (ACE) inherently possesses two crucial properties: the maximum principle and the energy dissipation law. Preserving these two properties at the discrete level is also necessary in the numerical methods for the ACE. In this paper, unlike the traditionally top-down macroscopic numerical schemes which discretize the ACE directly, we first propose a novel bottom-up mesoscopic regularized lattice Boltzmann method based macroscopic numerical scheme for d (=1, 2, 3)-dimensional ACE, where the DdQ(2d+1) [(2d+1) discrete velocities in d-dimensional space] lattice structure is adopted. In particular, the proposed macroscopic numerical scheme has a second-order accuracy in space, and can also be viewed as an implicit-explicit finite-difference scheme for the ACE, in which the nonlinear term is discretized semi-implicitly, the temporal derivative and dissipation term of the ACE are discretized by using the explicit Euler method and second-order central difference method, respectively. Then we demonstrate that the proposed scheme can preserve the maximum bound principle and the original energy dissipation law at the discrete level under some conditions. Finally, some numerical experiments are conducted to validate our theoretical analysis. Copyright © 2023, The Authors. All rights reserved.

关键词： Maximum principle

Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19 Monitoring System

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2023年第2期74卷 2889-2903页

作者： Mahmoud Ragab Mohammed W.Al-Rabia Sami Saeed Binyamin Ahmed A.Aldarmahi Information Technology Department Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah 21589Saudi Arabia Centre for Artificial Intelligence in Precision Medicines King Abdulaziz UniversityJeddah 21589Saudi Arabia Mathematics Department Faculty of ScienceAl-Azhar UniversityNaser City 11884CairoEgypt Department of Medical Microbiology and Parasitology Faculty of MedicineKing Abdulaziz UniversityJeddah 21589Saudi Arabia Health Promotion Center King Abdulaziz UniversityJeddah 21589Saudi Arabia Computer and Information Technology Department The Applied CollegeKing Abdulaziz UniversityJeddah 21589Saudi Arabia Basic Science Department College of Science and Health ProfessionsKing Saud Bin Abdulaziz University for Health SciencesJeddah 21423Saudi Arabia King Abdullah International Medical Research Center Ministry of National Guard-Health AffairsJeddah 21423Saudi Arabia

With the increasing and rapid growth rate of COVID-19 cases,the healthcare scheme of several developed countries have reached the point of *** important and critical steps in fighting against COVID-19 is powerful screening of diseased patients,in such a way that positive patient can be treated and isolated.A chest radiology image-based diagnosis scheme might have several benefits over traditional *** accomplishment of artificial intelligence(AI)based techniques in automated diagnoses in the healthcare sector and rapid increase in COVID-19 cases have demanded the requirement of AI based automated diagnosis and recognition *** study develops an Intelligent Firefly Algorithm Deep Transfer Learning Based COVID-19Monitoring System(IFFA-DTLMS).The proposed IFFADTLMSmodelmajorly aims at identifying and categorizing the occurrence of COVID19 on chest *** attain this,the presented IFFA-DTLMS model primarily applies densely connected networks(DenseNet121)model to generate a collection of feature *** addition,the firefly algorithm(FFA)is applied for the hyper parameter optimization of DenseNet121 ***,autoencoder-long short term memory(AE-LSTM)model is exploited for the classification and identification of *** ensuring the enhanced performance of the IFFA-DTLMS model,a wide-ranging experiments were performed and the results are reviewed under distinctive *** experimental value reports the betterment of IFFA-DTLMS model over recent approaches.

关键词： COVID-19 artificial intelligence intelligent systems deep learning decision making

Gaussian Measures Conditioned on Nonlinear Observations: Consistency, MAP Estimators, and Simulation

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Chen, Yifan Hosseini, Bamdad Owhadi, Houman Stuart, Andrew M. Courant Institute of Mathematical Science New York University New YorkNY United States Department of Applied Mathematics University of Washington SeattleWA United States Department of Computing and Mathematical Sciences California Instutute of Technology PasadenaCA United States

The article presents a systematic study of the problem of conditioning a Gaussian random variable ξ on nonlinear observations of the form F °φ(ξ) where φ : X → RN is a bounded linear operator and F is nonlinear. Such problems arise in the context of Bayesian inference and recent machine learning-inspired PDE solvers. We give a representer theorem for the conditioned random variable ξ | F °φ(ξ), stating that it decomposes as the sum of an infinite-dimensional Gaussian (which is identified analytically) as well as a finite-dimensional non-Gaussian measure. We also introduce a novel notion of the mode of a conditional measure by taking the limit of the natural relaxation of the problem, to which we can apply the existing notion of maximum a posteriori estimators of posterior measures. Finally, we introduce a variant of the Laplace approximation for the efficient simulation of the aforementioned conditioned Gaussian random variables towards uncertainty quantification. Copyright © 2024, The Authors. All rights reserved.

关键词： Random variables

Ferromagnetic CrBr3-Induced Graphene Spintronics

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Behera, Sushant Kumar Ahalawat, Madhavi Ramamurthy, Praveen C. Materials Science Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Indian Institute of Science Bengaluru560012 India School of Science and Humanities Maharishi University of Information Technology Noida226013 India Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Roorkee247667 India

Our proposed spin valve prototype features an advanced design with a two-dimensional graphene bilayer sandwiched between layers of CrBr3 ferromagnetic insulators. In this configuration, proximity coupling plays a crucial role in determining the magnetization orientations of the graphene layers and significantly influences the in-plane conductivity of the CrBr3 layers. In our study, we place the graphene bilayer between two CrBr3 ferromagnetic insulator layers to create this spin valve structure. Utilizing density functional theory (DFT), we perform comprehensive calculations to investigate the electronic structure of this layered system. Our results reveal a substantial band gap of 56.87 meV at specific k-points, particularly pronounced in the antiparallel magnetization configuration. This finding marks a significant advancement in spintronics, highlighting the potential of our spin valve prototype to contribute to the development of cutting-edge electronic device technologies. © 2024, CC BY.

关键词： Spintronics

How (not) to Build Quantum PKE in Minicrypt

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Li, Longcheng Li, Qian Li, Xingjian Liu, Qipeng State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences China Shenzhen International Center For Industrial And Applied Mathematics Shenzhen Research Institute of Big Data China Tsinghua University China University of California San Diego United States

The seminal work by Impagliazzo and Rudich (STOC’89) demonstrated the impossibility of constructing classical public key encryption (PKE) from one-way functions (OWF) in a black-box manner. Quantum information has the potential to bypass classical limitations, enabling the realization of seemingly impossible tasks such as quantum money, copy protection for software, and commitment without one-way functions. However, the question remains: can quantum PKE (QPKE) be constructed from quantumly secure OWF? A recent line of work has shown that it is indeed possible to build QPKE from OWF, but with one caveat. These constructions necessitate public keys being quantum and unclonable, diminishing the practicality of such "public" encryption schemes — public keys cannot be authenticated and reused. In this work, we re-examine the possibility of perfect complete QPKE in the quantum random oracle model (QROM), where OWF exists. Our first main result: QPKE with classical public keys, secret keys and ciphertext, does not exist in the QROM, if the key generation only makes classical queries. Therefore, a necessary condition for constructing such QPKE from OWF is to have the key generation classically "un-simulatable". Previous results (Austrin et al. CRYPTO’22) on the impossibility of QPKE from OWF rely on a seemingly strong conjecture. Our work makes a significant step towards a complete and unconditional quantization of Impagliazzo and Rudich’s results. Our second main result extends to QPKE with quantum public keys. The second main result: QPKE with quantum public keys, classical secret keys and ciphertext, does not exist in the QROM, if the key generation only makes classical queries and the quantum public key is either pure or "efficiently clonable". The result is tight due to these existing QPKEs with quantum public keys, classical secret keys, quantum/classical ciphertext and classical-query key generation require the public key to be mixed instead of pure;or require quantu

关键词： Reusability

The Macroscopic Finite-Difference Scheme and Modified Equations of the General Propagation Multiple-Relaxation-Time Lattice Boltzmann Model

学校读者我要写书评

暂无评论

SSRN

SSRN 2023年

作者： Chen, Ying Chai, Zhenhua Liu, Xi Shi, Baochang School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Institute of Interdisciplinary Research for Mathematics and Applied Science Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

In this paper, we first present the general propagation multiple-relaxation-time lattice Boltzmann (GPMRT-LB) model and obtain the corresponding macroscopic finite-difference (GPMFD) scheme on conservative moments. Then based on the Maxwell iteration method, we conduct the analysis on the truncation errors and modified equations (MEs) of the GPMRT-LB model and GPMFD scheme at both diffusive and acoustic scalings. For the nonlinear anisotropic convection-diffusion equation (NACDE) and Navier-Stokes equations (NSEs), we also derive the first- and second-order MEs of the GPMRT-LB model and GPMFD scheme. In particular, for the one-dimensional convection-diffusion equation (CDE) with the constant velocity and diffusion coefficient, we can develop a fourth-order GPMRT-LB (F-GPMRT-LB) model and the corresponding fourth-order GPMFD (F-GPMFD) scheme at the diffusive scaling. Finally, two benchmark problems, Gauss hill problem and Poiseuille flow in two-dimensional space, are used to test the GPMRT-LB model and GPMFD scheme, and it is found that the numerical results are not only in good agreement with corresponding analytical solutions, but also have a second-order convergence rate in space. Additionally, a numerical study on one-dimensional CDE also demonstrates that the F-GPMRT-LB model and F-GPMFD scheme can achieve a fourth-order accuracy in space, which is consistent with our theoretical analysis. © 2023, The Authors. All rights reserved.

关键词： Navier Stokes equations

Perceptions of AI in Education: A New AI-Based Model Towards Innovative Learning 24

学校读者我要写书评

暂无评论

Perceptions of AI in Education: A New AI-Based Model Towards...

Proceedings of the 2024 the 12th International Conference on Information technology (ICIT)

作者： Ahmed Al-Hunaiyyan Salah Al-Sharhan Fawaz S Al-Anzi Shaikhah Alainati Computing Department College of Business Studies. Public Authority for Applied Education and Training Kuwait Kuwait and Abdullah Al Salem University Khalidiya Kuwait Computer Engineering International University of Science and Technology in Kuwait Kuwait Kuwait Computer Engineering Kuwait University Kuwait Kuwait Management Department College of Business Studies. Public Authority for Applied Education and Training Kuwait Kuwait

ISBN: (纸本)9798400717376

Understanding the incorporation of artificial intelligence (AI) in educational institutions is essential, considering Kuwait’s dedication to innovation and academic success. This study investigates the different perspectives and barriers related to the integration of artificial intelligence (AI) in higher education in Kuwait. Using quantitative analysis, the research examines students’ views, experiences, and the challenges they face in the adoption of AI technologies in their academic environments. The study reveals a nuanced viewpoint among participants concerning the opportunities and challenges related to the integration of AI in education. Nonetheless, the investigation yielded results that directly contradicted the research hypothesis. The findings indicate that there is no substantial variation between genders about the level of significance. These findings along with reviewing literature allowed the authors to propose a new model towards innovative learning in order to offer valuable perspectives for policymakers and educators in Kuwait, facilitating the efficient incorporation of AI into the education system.

关键词： Artificial intelligence

A thermodynamically consistent and conservative diffuse-interface model for gas-liquid-solid multiphase flows

学校读者我要写书评

暂无评论

arXiv 2023年

In this work, a thermodynamically consistent and conservative diffuse-interface model for gas-liquid-solid multiphase flows is proposed. In this model, a novel free energy for the gas-liquid-solid multiphase flows is established according to a ternary phase-field model, and it not only contains the standard bulk and interface free energies for two-phase flows, but also includes some additional terms to reflect the penalty in the solid phase and the wettability on the solid surface. Furthermore, a smooth indicator function of the solid phase is also introduced in the consistent Navier-Stokes equations to achieve a high viscosity in the solid phase and preserve the velocity boundary conditions on the solid surface. Based on the proposed diffuse-interface model, the fluid interface dynamics, the fluid-structure interaction, and the wetting property of the solid surface can be described simply and efficiently. Additionally, the total energy is also proved to be dissipative for the two-phase flows in the stationary geometries. To test the present diffuse-interface model, we develop a consistent and conservative lattice Boltzmann method and conduct some simulations. The numerical results also confirm the energy dissipation and good capability of the proposed diffuse-interface model in the study of two-phase flows in complex geometries and gas-liquid-particle multiphase flows. © 2023, CC BY.

关键词： Energy dissipation

Advanced Energy Management in Smart Grids using Lyrebird Optimization Algorithm

学校读者我要写书评

暂无评论

Advanced Energy Management in Smart Grids using Lyrebird Opt...

Trends in Material Science and Inventive Materials (ICTMIM), International Conference on

作者： Mahmoud Z. Mistarihi Putchakayala Yanna Reddy A.Senthilnathan R. Bagavathi Subbi Naidu Bora Prasad Yadav Kurikyala Mechanical and Industrial Engineering Department Faculty of Engineering and Computing Liwa College Abu Dhabi UAE Hijjawi Faculty for Engineering Technology Yarmouk University Jordan Department of EEE Bharat Institute of Engineering and Technology Department of EEE Dr.N.G.P Institute of Technology Coimbatore India Department of Mathematics Rathinam Technical Campus Coimbatore Rajiv Gandhi University of Knowledge Technologies Nuzvid Andhra Pradesh Department of Engineering and Technology University of Technology and Applied Sciences Ibri Oman

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Integration of a hybrid wind turbine (HWT) and a battery energy system (BES) is expected to take place under the framework of a Smart Grid (SG) to optimize energy generation, storage, and distribution and enhance stability and efficiency. One aspect of such systems is a challenge concerning the effective management of Renewable Energy (RE) fluctuation to achieve balanced operation among renewable generation and energy demand. This paper proposes a Lyrebird Optimization Algorithm (LOA) to optimize energy demand forecasting and management within the hybrid system. The LOA is used to minimize Mean Absolute Percentage Error (MAPE) in energy demand forecasting within the SG system. By optimizing energy demand forecasting, the LOA effectively improves accuracy in energy management and forecasting within the SG. Its adaptive optimization ensures that forecasting errors are minimized across various operating conditions, enhancing overall efficiency of the energy distribution system. By then the proposed LOA method is implemented on the MATLAB platform, and its performance is evaluated by comparing it with existing optimization techniques such as Improved Grey Wolf Optimization (IGWO), Multi-Objective Optimization (MOO), Multi-Objective Wind Driven Optimization (MOWDO), and Coati Optimization Algorithm (COA). The results show that the proposed LOA method provides superior performance in minimizing MAPE, achieving the lowest MAPE value of 2.90%, indicating its enhanced accuracy in energy demand forecasting and optimization.

关键词： Energy consumption Renewable energy sources Accuracy Scalability Real-time systems Smart grids Wind turbines Batteries Forecasting Optimization