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A Second-Order Semi-Implicit Method for the Inertial Landau-Lifshitz-Gilbert Equation

Numerical Mathematics(Theory,Methods and Applications) 2023年第1期16卷 182-203页

作者： Panchi Li Lei Yang Jin Lan Rui Du Jingrun Chen School of Mathematical Sciences Soochow UniversitySuzhou 215006China School of Computer Science and Engineering Macao University of Science and TechnologyMacao SARChina Center for Joint Quantum Studies and Department of Physics School of ScienceTianjin University92 Weijin RoadTianjin 300072China Mathematical Center for Interdisciplinary Research Soochow UniversitySuzhou 215006China Suzhou Institute for Advanced Research University of Science and Technology of ChinaSuzhouJiangsu 215123China School of Mathematical Sciences University of Science and Technology of ChinaHefeiAnhui 230026China

Electron spins in magnetic materials have preferred orientations collectively and generate the macroscopic *** dynamics spans over a wide range of timescales from femtosecond to picosecond,and then to *** Landau-Lifshitz-Gilbert(LLG)equation has been widely used in micromagnetics simulations over *** theoretical and experimental advances have shown that the inertia of magnetization emerges at sub-picosecond timescales and contributes significantly to the ultrafast magnetization dynamics,which cannot be captured intrinsically by the LLG ***,as a generalization,the inertial LLG(iLLG)equation is proposed to model the ultrafast magnetization ***,the LLG equation is a nonlinear system of parabolic type with(possible)***,the iLLG equation is a nonlinear system of mixed hyperbolic-parabolic type with degeneracy,and exhibits more complicated *** behaves as a hyperbolic system at sub-picosecond timescales,while behaves as a parabolic system at larger timescales spanning from picosecond to *** hybrid behaviors impose additional difficulties on designing efficient numerical methods for the iLLG *** this work,we propose a second-order semiimplicit scheme to solve the iLLG *** second-order temporal derivative of magnetization is approximated by the standard centered difference scheme,and the first-order temporal derivative is approximated by the midpoint scheme involving three time *** nonlinear terms are treated semi-implicitly using one-sided interpolation with second-order *** each time step,the unconditionally unique solvability of the unsymmetric linear system is proved with detailed discussions on the condition ***,the second-order accuracy of the proposed method in both time and space is *** sub-picosecond timescales,the inertial effect of ferromagnetics is observed in micromagnetics simulations,in consistency wi

关键词： Inertial Landau-Lifshitz-Gilbert equation semi-implicit scheme second-order accuracy micromagnetics simulations

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A Deep Learning based Approach to Stock Market Price Prediction using Technical indicators

A Deep Learning based Approach to Stock Market Price Predict...

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Advances in Intelligent Computing and Applications (AICAPS), International Conference on

作者： Nirupama Parida Bunil Kumar Balabantaray Rajashree Nayak Jitendra Kumar Rout Computer Science and Engineering National Institute of Technology Meghalaya Shillong India JIS Institute of Advanced Studies and Research(JISIASR) Kolkata India Computer Science and Engineering National Institute of Technology Raipur India

Prediction of stock market data is difficult because of its complex and highly volatile nature. In this work the historical data as well as the technical indicators are implemented for the purpose of prediction. Different features are extracted using the CNN technique and further the prediction is performed using the dropout based LSTM technique. The basic aim of this study is optimization of the prediction accuracy of the stock price. Different technical indicators and historical data are taken as input data. The sub max layer is substituted with KELM (Kernel Based Extreme Learning Machine). This paper shows a CNN based hybrid system applied on a variety of sources comprising of different stock market. Various matrices are used for observing the accurateness of the proposed model. Two different stock market data are considered for this purpose. The extracted features shows more accurate result. Further it is observed that the proposed model outrun different other methods discussed in this paper

关键词： Deep learning Extreme learning machines Computational modeling Predictive models Feature extraction Matrices Stock markets

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Correction to: Performance study and analysis of Al2O3 Nanofluid under different flow conditions

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Interactions 2024年第1期245卷 1-2页

作者： Sivakumar, V. Visagavel, K. Kumaraswamy, J. Balaji, E. Khalkar, V. Gnanavel, C. Kalyana Chakravarthy, P. R. Baskar, S. Vijayan, V. Department of Mechanical Engineering Knowledge Institute of Technology Salem India Department of Mechanical Engineering R. L. Jalappa Institute of Technology (Visvesvararaya Technological University Belagavi) Doddaballapur India Department of Mechanical Engineering Vel Tech Multi Tech Dr Rangarajan Dr Sakunthala Engineering College Chennai India Department of Mechanical Engineering Gharda Institute of Technology Ratnagiri India School of Engineering Vels Institute of Science Technology and Advanced Studies Chennai India Department of Mechanical Engineering K.Ramakrishnan College of Technology Tiruchirappalli India

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Implementation of an Improved Phasor Approximation Technique for Compensating the CCTV Transient Effect 1

Implementation of an Improved Phasor Approximation Technique...

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1st International Conference on Advances in Electrical, Electronics and Computational Intelligence, ICAEECI 2023

作者： Karthik, Mamidala Vijay Reddy, M Pala Prasad Rao, G Madhusudhana Bindu, A. Hima Rubini, B. Satyanarayana, Vanam CMR Engineering College EEE Dept Hyderabad India Inst. of Aeronautical Engg. EEE Dept Hyderabad India OP Jindal University EE Department Raigarh India Annamacharya Institute of Technology and Sciences EEE Dept Rajampet India Vels Institute of Science Technology and Advanced Studies EEE Dept Chennai India Vaagdevi College of Engineering EEE Dept Telangana Warangal India

ISBN: (纸本)9798350342796

This paper proposes an improved phasor estimation technique based on intrinsic time decomposition which enhances the distance relay performance during coupling capacitor voltage transformer (CCVT) subsidence transient. The proposed logic utilizes voltage and current signals at relay point and decomposes it's in to corresponding baseline and residual signals. Then, the decaying dc component is calculated and removed from the signals. Finally, the phasor of corresponding signals are evaluated using discrete Fourier transform to evaluate the performance of the distance relay. The proposed integrated phasor estimation based distance relaying algorithm is tested for different worst scenarios such as different source impedance ratio and different CCVT burden. The simulation has been performed on 60 Hz, 500 kV CCVT power system modeled using EMTDC/PSCAD. Results obtained using proposed phasor estimation scheme enhances the distance relay for correctly discriminating the in-zone faults from out-zone faults. Finally, assessment of transient estimation technique proves the superiority of the proposed method in distance relaying application. © 2023 IEEE.

关键词： Coupling Capacitor Voltage Transformer Distribution Systems FACTS Devices Relays Transient Estimation Zonal Faults

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System-level time computation and representation in the suprachiasmatic nucleus revealed by large-scale calcium imaging and machine learning

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细胞研究（英文版） 2024年第7期34卷 493-503页

作者： Ziehen Wang Jing Yu Muyue Zhai Zehua Wang Kaiwen Sheng Yu Zhu Tianyu Wang Mianzhi Liu Lu Wang Miao Yan Jue Zhang Ying Xu Xianhua Wang Lei Ma Wei Hu Heping Cheng National Biomedical Imaging Center State Key Laboratory of Membrane BiologyInstitute of Molecular MedicinePeking-Tsinghua Center for Life SciencesCollege of Future TechnologyPeking UniversityBeijingChina Research Unit of Mitochondria in Brain Diseases Chinese Academy of Medical SciencesPKU-Nanjing Institute of Translational MedicineNanjingJiangsuChina National Biomedical Imaging Center State Key Laboratory of Membrane BiologyInstitute of Molecular MedicinePeking-Tsinghua Center for Life SciencesCollege of Future TechnologyPeking UniversityBeijingChina Wangxuan Institute of Computer Technology Peking UniversityBeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina Beijing Academy of Artificial Intelligence BeijingChina Department of Bioengineering Stanford UniversityStanfordCAUSA Beijing Academy of Artificial Intelligence BeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina College of Engineering Peking UniversityBeijingChina Jiangsu Key Laboratory of Neuropsychiatric Diseases and Cambridge-Su Genomic Resource Center Medical School of Soochow UniversitySuzhouJiangsuChina National Biomedical Imaging Center State Key Laboratory of Membrane BiologyInstitute of Molecular MedicinePeking-Tsinghua Center for Life SciencesCollege of Future TechnologyPeking UniversityBeijingChina Beijing Academy of Artificial Intelligence BeijingChina Wangxuan Institute of Computer Technology Peking UniversityBeijingChina

The suprachiasmatic nucleus(SCN)is the mammalian central circadian pacemaker with heterogeneous neurons acting in concert while each neuron harbors a self-sustained molecular ***,how system-level SCN signals encode time of the day remains *** we show that population-level Ca2+signals predict hourly time,via a group decision-making mechanism coupled with a spatially modular time feature representation in the ***,we developed a high-speed dual-view two-photon microscope for volumetric Ca2+imaging of up to 9000 GABAergic neurons in adult SCN slices,and leveraged machine learning methods to capture emergent properties from multiscale Ca2+signals as a *** achieved hourly time prediction by polling random cohorts of SCN neurons,reaching 99.0％accuracy at a cohort size of ***,we revealed that functional neuron subtypes identified by contrastive learning tend to aggregate separately in the SCN space,giving rise to bilaterally symmetrical ripple-like modular *** modules represent distinctive time features,such that a module-specifically learned time predictor can also accurately decode hourly time from random polling of the same *** findings open a new paradigm in deciphering the design principle of the biological clock at the system level.

关键词： representation nucleus learning imaging time calcium computation large-scale machine revealed

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Mechanical characterization of soft silicone gels via spherical nanoindentation for applications in mechanobiology

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Acta Mechanica Sinica 2021年第4期37卷 554-561,I0001页

作者： Yajun Zhang Xiaoning Yang Chunyang Xiong Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China Jiangsu Key Laboratory of Medical Optics Suzhou Institute of Biomedical Engineering and TechnologyChinese Academy of SciencesSuzhou 215163China

As a biocompatible material,soft silicone gels like CY52-276 have been applied to many engineering fields associated with interactions between mammalian cells and extracellular matrices/substrates,due to its nontoxicity,ease of preparation,optical transparency and tunable mechanical *** quantification of mechanical properties of silicone gels is crucial for quantitatively investigating mechanical responses of cells to *** the material with high surface energy,we design a new strategy for the nanoindentation technique to reduce or even eliminate the effect of interfacial adhesions with the aid of some specified ***,we dissect the dependence of its Young’s modulus on the ratios of monomers and crosslinkers and curing conditions,and therefore identify a dose-response relationship between its moduli and the corresponding prepolymer *** the non-linear large deformation nanoindentation tests,we further showed that the two-parameter Mooney-Rivlin model may well characterize the hyperelastic deformations of the materials with different composition *** pave the way for more precise exploration of the interaction between cells and extracellular matrix and the underlying mechanotransduction pathways in mechanobiology.

关键词： Silicone gel Young's modulus Nanoindentation Mechanobiology

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Multi Parametric Optimization of Dry Turning of Titanium Alloy (Ti6Al4V Graded 5) using Coated Carbide Insert: A Novel Hybrid RSM-Artificial Gorilla Troop Optimization and Dingo Optimization Algorithm 2nd

Multi Parametric Optimization of Dry Turning of Titanium All...

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2nd International Conference on Functional Material, Manufacturing and Performances, ICFMMP 2021

作者： Bagal, Dilip Kumar Jeet, Siddharth Barua, Abhishek Pradhan, Swastik Rath, Arati Sahu, Saujanya Kumar Department of Mechanical Engineering Government College of Engineering Kalahandi Odisha Bhawanipatna India Department of Mechanical Engineering Centre for Advanced Post Graduate Studies BPUT Odisha Rourkela India School of Mechanical Engineering Lovely Professional University Punjab Phagwara India School of Computer Engineering Kalinga Institute of Industrial Technology Odisha Bhubaneswar India Department of Civil Engineering Government College of Engineering Kalahandi Odisha Bhawanipatna India

ISBN: (纸本)9789811941467

The present research piloted dry turning of titanium alloys (Ti-6Al-4V Grade 5) utilizing modern titanium carbonitrides chemical vapor deposition (MT-CVD) coated carbide tool inserts. The impacts of cutting parameters such as feed rate, cutting speed, and depth of cut on output responses such as cutting forces, flank wear, and surface roughness were investigated using a Box-Behnken design based on response surface methodology (RSM). To find the optimum cutting condition, a newly developed hybrid optimization method, namely RSM-linked Artificial Gorilla Troop Optimization Algorithm and Dingo Optimization Algorithm, was utilized. The flank wear along with cutting force was recorded when the depth of cut was less while better surface finish was achieved with lower cutting speed. Additionally, analysis of variance was used to determine the most important component in each of the three responses, followed by a confirmatory test that revealed a high degree of agreement between anticipated and experimental results. As per the analysis of variance (ANOVA) results, the depth of cut was determined to be the most crucial component in attaining the lowest cutting force, flank wear, and surface roughness responses. The results obtained using the artificial gorilla optimization algorithm and the dingo optimization algorithm are found to be more precise than those obtained using the RSM-designed experimentation of dry turning operations, as cutting force, surface roughness, and flank wear have been minimized by utilizing the factor settings achieved using both the artificial gorilla optimization algorithm and the dingo optimization algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Surface roughness

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Spatiotemporally controlled emergence of nanoparticle microvortices under electric field

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Aggregate 2024年第2期5卷 290-300页

作者： Qi Pan Xijian Lin Shiyuan Wei Jinghong Su Hansen Zhao Xiaojie Duan Guoqing Hu Yan He Department of Chemistry Key Laboratory of Bioorganic Phosphorus Chemistry and Chemical Biology(Ministry of Education)Tsinghua UniversityBeijingChina Department of Biomedical Engineering College of Future TechnologyPeking UniversityBeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina The State Key Laboratory of Nonlinear Mechanics Institute of MechanicsChinese Academy of SciencesBeijingChina School of Engineering Science University of Chinese Academy of SciencesBeijingChina Department of Engineering Mechanics State Key Laboratory of Fluid Power and Mechatronic SystemsZhejiang UniversityHangzhouChina

Controlled assembly of nanoparticles(NPs)has garnered much interest over the past two *** established techniques,new methods utilizing local short-range or large-scale long-range interactions remain to be explored to achieve diverse micro-and nanoscale ***,we report the controlled emergence of vortex-pair arrays within monodispersed gold nanorods by applying a direct current electric field across a pair of sawtooth *** employing in situ darkfield microscopy and particle collective analysis,we elucidate the mechanism behind the formation and stabilization of the NP vortices,attributing it to the combined effects of the electrode shape,high NP density,and high solution *** further explore the controllability of the vortex-pair arrays and obtain multiple complex vortice *** findings will facilitate the investigation of efficient and controlled dynamic assembly of NPs under external fields and help manufacture next-generation optoelectronic functional materials.

关键词： dynamic assembly electric field gold nanoparticles sawtooth electrodes vortex

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Bibliometric Analysis of Friction Stir Spot Welded Joints using SCOPUS Database 2nd

Bibliometric Analysis of Friction Stir Spot Welded Joints us...

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2nd International Conference on Functional Material, Manufacturing and Performances, ICFMMP 2021

作者： Bagal, Dilip Kumar Jeet, Siddharth Barua, Abhishek Pradhan, Swastik Panda, Surya Narayan Sahu, Saujanya Kumar Department of Mechanical Engineering Government College of Engineering Kalahandi Odisha Bhawanipatna India Department of Mechanical Engineering Centre for Advanced Post Graduate Studies BPUT Odisha Rourkela India School of Mechanical Engineering Lovely Professional University Punjab Phagwara India Department of Production Engineering Birsa Institute of Technology Sindri Jharkhand Dhanbad India Department of Civil Engineering Government College of Engineering Kalahandi Odisha Bhawanipatna India

ISBN: (纸本)9789811941467

Friction stir spot welding (FSSW) is an eco-friendly high efficient welding technique in the field of solid-state welding. Using this technique dissimilar metal lap joints can be done such as aluminum alloy with the copper alloy. Moreover, bibliometric research is an essential method of statistical analysis of publications in a certain research field. This commonly used technique categorizes the information using different variables such as active journals, countries, and authors. In this paper, a systematic review of the research carried out in the area of FSSW process is presented by use of bibliometric research indicators thus recognizing the most influential research in this field. The SCOPUS repository is used to retrieve the research published regarding the FSSW since 1960. The paper is divided into several analysis sections that focus on the most influential years, journals, authors, affiliations, countries, document type, subject area, and keywords that have contributed to the field of FSSW. The aim of this study is to be informative regarding FSSW and use the bibliometric indicators to highlight the vital research conducted in the field of FSSW. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Copper alloys

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Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

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Computers, Materials & Continua 2024年第8期80卷 2081-2098页

作者： Atif Mehmood Zhonglong Zheng Rizwan Khan Ahmad Al Smadi Farah Shahid Shahid Iqbal Mutasem K.Alsmadi Yazeed Yasin Ghadi Syed Aziz Shah Mostafa M.Ibrahim Department of Computer Science and Technology Zhejiang Normal UniversityJinhua321002China Zhejiang Institute of Photoelectronics&Zhejiang Institute for Advanced Light Source Zhejiang Normal UniversityJinhua321004China Department of Data Science and Artificial Intelligence Zarqa UniversityZarqa13100Jordan School of Chemical and Environmental Engineering College of ChemistryChemical Engineering andMaterials ScienceSoochow UniversitySuzhou215123China Department of Management Information Systems College of Applied Studies and Community ServiceImam Abdulrahman Bin Faisal UniversityDammam32244Saudi Arabia Department of Computer Science Al Ain UniversityAbu Dhabi999041United Arab Emirates Department of Electrical Engineering Faculty of EngineeringMinia UniversityMinia61519Egypt Healthcare Technology and Innovation Theme Faculty Research Centre for Intelligent HealthcareCoventry UniversityCoventryCV48BWUK

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and ***,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)*** paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and *** improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized *** performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed *** experimental results demonstrate superior performance in classifying the three binary classification tasks:NC ***,NC ***,and MCI ***,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,*** study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM *** findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

关键词： Alzheimer’s disease mild cognitive impairment normal control transfer learning classification augmentation

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