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Journal articles on the topic 'Multiscale strategy'

Author: Grafiati

Published: 23 November 2024

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1

Favela, Luis H. "Journal of Multiscale Neuroscience." Journal of Multiscale Neuroscience 2, no. 1 (April 28, 2023): 240–51. http://dx.doi.org/10.56280/1567939485.

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Neuroscience has become a big data enterprise. This is due in large part to the rapidly growing quantity and quality of data and increased appreciation of non-neuronal physiology and environments in explaining behavior, cognition, and consciousness. One way neuroscience is dealing with this embarrassment of riches is by appealing to investigative frameworks that put the multiscale nature of neural systems at the forefront. The current work offers one such approach: Nested dynamical modeling, a strategy for creating models of phenomena comprised of multiple spatial and/or temporal scales for purposes of exploration, explanation, and understanding. Building from dynamical systems theory and synergetics, nested dynamical modeling applies a methodological approach aimed at nesting models at one scale of inquiry within models at other scales without compromising biological realism. This strategy is demonstrated via a proof of concept. Some consequences this approach has for the epistemological and theoretical commitments of neuroscience are discussed.

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Yan-Bo, SUN, YANG Bin, AN Zhe, YU Chun-Lei, XUE Yao-Hong, and LIU Hong. "Multiscale Simulation Strategy for Preparing Polyurethane." Acta Physico-Chimica Sinica 30, no. 11 (2014): 2035–42. http://dx.doi.org/10.3866/pku.whxb201409111.

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Krishnan, Arun, and Karlene A. Hoo. "A Multiscale Model Predictive Control Strategy." Industrial & Engineering Chemistry Research 38, no. 5 (May 1999): 1973–86. http://dx.doi.org/10.1021/ie980658+.

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4

Boucard, P. A., S. Buytet, and P. A. Guidault. "A multiscale strategy for structural optimization." International Journal for Numerical Methods in Engineering 78, no. 1 (April 2, 2009): 101–26. http://dx.doi.org/10.1002/nme.2484.

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5

Wang, Zhuang, Martina G. Vijver, and Willie J. G. M. Peijnenburg. "Multiscale Coupling Strategy for Nano Ecotoxicology Prediction." Environmental Science & Technology 52, no. 14 (June 27, 2018): 7598–600. http://dx.doi.org/10.1021/acs.est.8b02895.

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Heidebrecht, Peter, Matthias Pfafferodt, and Kai Sundmacher. "Multiscale modelling strategy for structured catalytic reactors." Chemical Engineering Science 66, no. 19 (October 2011): 4389–402. http://dx.doi.org/10.1016/j.ces.2011.03.052.

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Raynal, L., A. Gomez, B. Caillat, and Y. Haroun. "CO2Capture Cost Reduction: Use of a Multiscale Simulations Strategy for a Multiscale Issue." Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 68, no. 6 (September 12, 2013): 1093–108. http://dx.doi.org/10.2516/ogst/2012104.

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Hajibeygi, H., and H. A. A. Tchelepi. "Compositional Multiscale Finite-Volume Formulation." SPE Journal 19, no. 02 (November 20, 2013): 316–26. http://dx.doi.org/10.2118/163664-pa.

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Summary The multiscale finite-volume (MSFV) method is extended to include compositional processes in heterogeneous porous media, which require accurate modeling of the mass transfer and associated phase behaviors. A sequential-implicit strategy is used to deal with the coupling of the flow (pressure) and transport (component overall concentration) problems. In this compositional formulation, the overall continuity equation is used to formulate the pressure equation. The resulting pressure equation conserves total mass by construction and depends weakly on the distributions of the phase compositions. The transport equations are expressed in terms of the overall composition; hence, phase-appearance and -disappearance effects do not appear explicitly in these expressions. The details of the MSFV strategy for the pressure equation are described. The only source of error in this MSFV framework is the localization assumption. No additional assumptions related to the complex physics are used. For 1D problems, the sequential strategy is validated against solutions obtained by a fully implicit simulator. The accuracy of the MSFV method for compositional simulations is then illustrated for different test cases.

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Popov, Andrey M., Irina V. Lebedeva, Sergey A. Vyrko, and Nikolai A. Poklonski. "Multiscale modeling strategy to solve fullerene formation mystery." Fullerenes, Nanotubes and Carbon Nanostructures 29, no. 10 (March 22, 2021): 755–66. http://dx.doi.org/10.1080/1536383x.2021.1900124.

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Yan, Minghan, Jian Zhou, Cong Luo, Tingfa Xu, and Xiaoxue Xing. "Multiscale Joint Optimization Strategy for Retinal Vascular Segmentation." Sensors 22, no. 3 (February 7, 2022): 1258. http://dx.doi.org/10.3390/s22031258.

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The accurate segmentation of retinal vascular is of great significance for the diagnosis of diseases such as diabetes, hypertension, microaneurysms and arteriosclerosis. In order to segment more deep and small blood vessels and provide more information to doctors, a multi-scale joint optimization strategy for retinal vascular segmentation is presented in this paper. Firstly, the Multi-Scale Retinex (MSR) algorithm is used to improve the uneven illumination of fundus images. Then, the multi-scale Gaussian matched filtering method is used to enhance the contrast of the retinal images. Optimized by the Particle Swarm Optimization (PSO) algorithm, Otsu algorithm (OTSU) multi-threshold segmentation is utilized to segment the retinal image extracted by the multi-scale matched filtering method. Finally, the image is post-processed, including binarization, morphological operation and edge-contour removal. The test experiments are implemented on the DRIVE and STARE datasets to evaluate the effectiveness and practicability of the proposed method. Compared with other existing methods, it can be concluded that the proposed method can segment more small blood vessels while ensuring the integrity of vascular structure and has a higher performance. The proposed method has more obvious targets, a higher contrast, more plentiful detailed information, and local features. The qualitative and quantitative analysis results show that the presented method is superior to the other advanced methods.

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Zimmermann, Wolfram-Hubertus. "Multiscale Strategy to Resolve Stroma–Cardiac Fibroblast Interactions." Circulation Research 128, no. 1 (January 8, 2021): 39–41. http://dx.doi.org/10.1161/circresaha.120.318494.

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Krishnan, A., and K. A. Hoo. "Comments on “A Multiscale Model Predictive Control Strategy”." Industrial & Engineering Chemistry Research 38, no. 11 (November 1999): 4520. http://dx.doi.org/10.1021/ie991071d.

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E, Weinan, Weiqing Ren, and Eric Vanden-Eijnden. "A general strategy for designing seamless multiscale methods." Journal of Computational Physics 228, no. 15 (August 2009): 5437–53. http://dx.doi.org/10.1016/j.jcp.2009.04.030.

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Kaczmarczyk, Łukasz, Chris J. Pearce, Nenad Bićanić, and Eduardo de Souza Neto. "Numerical multiscale solution strategy for fracturing heterogeneous materials." Computer Methods in Applied Mechanics and Engineering 199, no. 17-20 (March 2010): 1100–1113. http://dx.doi.org/10.1016/j.cma.2009.11.018.

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Karimi-Rouzbahani, Hamid. "Evidence for Multiscale Multiplexed Representation of Visual Features in EEG." Neural Computation 36, no. 3 (February 16, 2024): 412–36. http://dx.doi.org/10.1162/neco_a_01649.

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Abstract Distinct neural processes such as sensory and memory processes are often encoded over distinct timescales of neural activations. Animal studies have shown that this multiscale coding strategy is also implemented for individual components of a single process, such as individual features of a multifeature stimulus in sensory coding. However, the generalizability of this encoding strategy to the human brain has remained unclear. We asked if individual features of visual stimuli were encoded over distinct timescales. We applied a multiscale time-resolved decoding method to electroencephalography (EEG) collected from human subjects presented with grating visual stimuli to estimate the timescale of individual stimulus features. We observed that the orientation and color of the stimuli were encoded in shorter timescales, whereas spatial frequency and the contrast of the same stimuli were encoded in longer timescales. The stimulus features appeared in temporally overlapping windows along the trial supporting a multiplexed coding strategy. These results provide evidence for a multiplexed, multiscale coding strategy in the human visual system.

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Tian, Shuang, Qikai Lu, and Lifei Wei. "Multiscale Superpixel-Based Fine Classification of Crops in the UAV-Manned Hyperspectral Imagery." Remote Sensing 14, no. 14 (July 8, 2022): 3292. http://dx.doi.org/10.3390/rs14143292.

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As an effective approach to obtaining agricultural information, the remote sensing technique has been applied in the classification of crop types. The unmanned aerial vehicle (UAV)-manned hyperspectral sensors provide imagery with high spatial and high spectral resolutions. Moreover, the detailed spatial information, as well as abundant spectral properties of UAV-manned hyperspectral imagery, opens a new avenue to the fine classification of crops. In this manuscript, multiscale superpixel-based approaches are proposed for the fine identification of crops in the UAV-manned hyperspectral imagery. Specifically, the multiscale superpixel segmentation is performed and a series of superpixel maps can be obtained. Then, the multiscale information is integrated into image classification by two strategies, namely pre-processing and post-processing. For the pre-processing strategy, the superpixel is regarded as the minimum unit for image classification, whose feature is obtained by using the average of spectral values of pixels within it. At each scale, the classification is performed on the basis of the superpixel. Then, the multiscale classification results are combined to generate the final map. For the post-processing strategy, the pixel-wise classification is implemented to obtain the label and posterior probabilities of each pixel. Subsequently, the superpixel-based voting is conducted at each scale, and these obtained voting results are fused to generate the multiscale voting result. To evaluate the effectiveness of the proposed approaches, three open-sourced hyperspectral UAV-manned datasets are employed in the experiments. Meanwhile, seven training sets with different numbers of labeled samples and two classifiers are taken into account for further analysis. The results demonstrate that the multiscale superpixel-based approaches outperform the single-scale approaches. Meanwhile, the post-processing strategy is superior to the pre-processing strategy in terms of higher classification accuracies in all the datasets.

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Su, Tung-Huan, Szu-Jui Huang, Jimmy Gaspard Jean, and Chuin-Shan Chen. "Multiscale computational solid mechanics: data and machine learning." Journal of Mechanics 38 (2022): 568–85. http://dx.doi.org/10.1093/jom/ufac037.

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Abstract Multiscale computational solid mechanics concurrently connects complex material physics and macroscopic structural analysis to accelerate the application of advanced materials in the industry rather than resorting to empirical constitutive models. The rise of data-driven multiscale material modeling opens a major paradigm shift in multiscale computational solid mechanics in the era of material big data. This paper reviews state-of-the-art data-driven methods for multiscale simulation, focusing on data-driven multiscale finite element method (data-driven FE2) and data-driven multiscale finite element-deep material network method (data-driven FE-DMN). Both types of data-driven multiscale methods aim to resolve the past challenge of concurrent multiscale simulation. Numerical examples are designed to demonstrate the effectiveness of data-driven multiscale simulation methods. Future research directions are discussed, including data sampling strategy and data generation technique for the data-driven FE2 method and generalization of data-driven FE-DMN method.

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Hunter, Peter, and Poul Nielsen. "A Strategy for Integrative Computational Physiology." Physiology 20, no. 5 (October 2005): 316–25. http://dx.doi.org/10.1152/physiol.00022.2005.

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Organ function (the heart beat for example) can only be understood through knowledge of molecular and cellular processes within the constraints of structure-function relations at the tissue level. A quantitative modeling framework that can deal with these multiscale issues is described here under the banner of the International Union of Physiological Sciences Physiome Project.

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Aliyu, Ohunene Hafsa. "Computational Schemes in the Design of Novel Materials for Energy Savings." Nigerian Journal of Technological Development 17, no. 1 (April 22, 2020): 55–61. http://dx.doi.org/10.4314/njtd.v17i1.8.

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The current demand for lightweight energy efficient materials in industries to help in addressing the current challenges faced in reducing green house gas emissions is one of the motivations behind innovative material design. This paper has tried to review in particular the importance of the hierarchical multiscale modelling strategy in the design of novel lightweight materials. It also highlights on one of the hierarchical multiscale modelling methodologies from ab-initio level to macro level in predicting macroscopic material behaviour and the impact this simulation strategy will have on the development of innovative materials. It highlights on the limitations of this modelling strategy such as: the unreasonable computational time associated with the relaxation of polymeric chains or entanglements as well as scale bridging approaches between low level and high level models which are areas of current research interest. Keywords: Multiscale modelling, lightweight materials, energy-efficiency, scale bridging, length scale.

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Yang, Hongqi, and Bing Zhou. "A Multilevel Iteration Method for Solving a Coupled Integral Equation Model in Image Restoration." Mathematics 8, no. 3 (March 4, 2020): 346. http://dx.doi.org/10.3390/math8030346.

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The problem of out-of-focus image restoration can be modeled as an ill-posed integral equation, which can be regularized as a second kind of equation using the Tikhonov method. The multiscale collocation method with the compression strategy has already been developed to discretize this well-posed equation. However, the integral computation and solution of the large multiscale collocation integral equation are two time-consuming processes. To overcome these difficulties, we propose a fully discrete multiscale collocation method using an integral approximation strategy to compute the integral, which efficiently converts the integral operation to the matrix operation and reduces costs. In addition, we also propose a multilevel iteration method (MIM) to solve the fully discrete integral equation obtained from the integral approximation strategy. Herein, the stopping criterion and the computation complexity that correspond to the MIM are shown. Furthermore, a posteriori parameter choice strategy is developed for this method, and the final convergence order is evaluated. We present three numerical experiments to display the performance and computation efficiency of our proposed methods.

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Du, Yongzhao, Yuling Fan, Xiaofang Liu, Yanmin Luo, Jianeng Tang, and Peizhong Liu. "Multiscale Cooperative Differential Evolution Algorithm." Computational Intelligence and Neuroscience 2019 (December 17, 2019): 1–17. http://dx.doi.org/10.1155/2019/5259129.

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A multiscale cooperative differential evolution algorithm is proposed to solve the problems of narrow search range at the early stage and slow convergence at the later stage in the performance of the traditional differential evolution algorithms. Firstly, the population structure of multipopulation mechanism is adopted so that each subpopulation is combined with a corresponding mutation strategy to ensure the individual diversity during evolution. Then, the covariance learning among populations is developed to establish a suitable rotating coordinate system for cross operation. Meanwhile, an adaptive parameter adjustment strategy is introduced to balance the population survey and convergence. Finally, the proposed algorithm is tested on the CEC 2005 benchmark function and compared with other state-of-the-art evolutionary algorithms. The experiment results showed that the proposed algorithm has better performance in solving global optimization problems than other compared algorithms.

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Xiong, Fen Fen, Gao Rong Sun, and Liang Yu Zhao. "Robust Multiscale Design Using PATC and WSRSM." Advanced Materials Research 148-149 (October 2010): 1075–78. http://dx.doi.org/10.4028/www.scientific.net/amr.148-149.1075.

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Multiscale design dealing with 2-scale material and product system is implemented by employing probabilistic analytical target cascading (PATC) and weighted stochastic response surface method (WSRSM) in this paper. PATC allows design autonomy at each scale subsystem by formulating the multiscale design system as a multilevel structure. WSRSM ensures uncertainties to be propagated within and across each scale accurately and efficiently. Comparative study on a multiscale bracket design problem shows that the results obtained by our strategy are very close to the reference values. It is demonstrated that PATC and WSRSM are highly effective and applicable on multiscale design.

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Kou, Jisheng, Shuyu Sun, and Bo Yu. "Multiscale Time-Splitting Strategy for Multiscale Multiphysics Processes of Two-Phase Flow in Fractured Media." Journal of Applied Mathematics 2011 (2011): 1–24. http://dx.doi.org/10.1155/2011/861905.

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The temporal discretization scheme is one important ingredient of efficient simulator for two-phase flow in the fractured porous media. The application of single-scale temporal scheme is restricted by the rapid changes of the pressure and saturation in the fractured system with capillarity. In this paper, we propose a multi-scale time splitting strategy to simulate multi-scale multi-physics processes of two-phase flow in fractured porous media. We use the multi-scale time schemes for both the pressure and saturation equations; that is, a large time-step size is employed for the matrix domain, along with a small time-step size being applied in the fractures. The total time interval is partitioned into four temporal levels: the first level is used for the pressure in the entire domain, the second level matching rapid changes of the pressure in the fractures, the third level treating the response gap between the pressure and the saturation, and the fourth level applied for the saturation in the fractures. This method can reduce the computational cost arisen from the implicit solution of the pressure equation. Numerical examples are provided to demonstrate the efficiency of the proposed method.

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Ngo, Son Ich, and Young-Il Lim. "Multiscale Eulerian CFD of Chemical Processes: A Review." ChemEngineering 4, no. 2 (March 31, 2020): 23. http://dx.doi.org/10.3390/chemengineering4020023.

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This review covers the scope of multiscale computational fluid dynamics (CFD), laying the framework for studying hydrodynamics with and without chemical reactions in single and multiple phases regarded as continuum fluids. The molecular, coarse-grained particle, and meso-scale dynamics at the individual scale are excluded in this review. Scoping single-scale Eulerian CFD approaches, the necessity of multiscale CFD is highlighted. First, the Eulerian CFD theory, including the governing and turbulence equations, is described for single and multiple phases. The Reynolds-averaged Navier–Stokes (RANS)-based turbulence model such as the standard k-ε equation is briefly presented, which is commonly used for industrial flow conditions. Following the general CFD theories based on the first-principle laws, a multiscale CFD strategy interacting between micro- and macroscale domains is introduced. Next, the applications of single-scale CFD are presented for chemical and biological processes such as gas distributors, combustors, gas storage tanks, bioreactors, fuel cells, random- and structured-packing columns, gas-liquid bubble columns, and gas-solid and gas-liquid-solid fluidized beds. Several multiscale simulations coupled with Eulerian CFD are reported, focusing on the coupling strategy between two scales. Finally, challenges to multiscale CFD simulations are discussed. The need for experimental validation of CFD results is also presented to lay the groundwork for digital twins supported by CFD. This review culminates in conclusions and perspectives of multiscale CFD.

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Yin, Jingbo, Huangping Yan, Gesang Dunzhu, Rui Wang, Shengzhu Cao, Rui Zhou, and Yuanzhe Li. "General Strategy toward Laser Single-Step Generation of Multiscale Anti-Reflection Structures by Marangoni Effect." Micromachines 13, no. 9 (September 8, 2022): 1491. http://dx.doi.org/10.3390/mi13091491.

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The anti-reflection of transparent material surfaces has attracted great attention due to its potential applications. In this paper, a single-step controllable method based on an infrared femtosecond laser is proposed for self-generation multiscale anti-reflection structures on glass. The multiscale composite structure with ridge structures and laser-induced nano-textures is generated by the Marangoni effect. By optimizing the laser parameters, multiscale structure with broadband anti-reflection enhancement is achieved. Meanwhile, the sample exhibits good anti-glare performance under strong light. The results show that the average reflectance of the laser-textured glass in the 300–800 nm band is reduced by 45.5% compared with the unprocessed glass. This work provides a simple and general strategy for fabricating anti-reflection structures and expands the potential applications of laser-textured glass in various optical components, display devices, and anti-glare glasses.

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Parno, Matthew, Tarek Moselhy, and Youssef Marzouk. "A Multiscale Strategy for Bayesian Inference Using Transport Maps." SIAM/ASA Journal on Uncertainty Quantification 4, no. 1 (January 2016): 1160–90. http://dx.doi.org/10.1137/15m1032478.

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Zhou, Qiang, Shi-Min Cai, and Yi-Cheng Zhang. "Multiscale community estimation based on temporary local balancing strategy." International Journal of Modern Physics C 31, no. 04 (February 12, 2020): 2050056. http://dx.doi.org/10.1142/s0129183120500564.

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Community division in complex networks has become one of the hot topics in the field of network science. Most of the methods developed based on network topology ignore the dynamic characteristics underlying the structure. By exploring the diffusion process in the network based on random walk, this paper sums up the general rule with temporal characteristics as a temporary local balancing strategy which can be used in the community division. The strategy divides the network into different communities according to the duration of a stable local balancing state in the diffusion process. The longer the duration, the more stable the structure of the community in that state. Applying the strategy to computer-generated and real-world networks, respectively, it is proved that these temporary local balancing states existing in the diffusion process can reveal the internal community structure of the network. In addition, the modular structure appears at different time scales of diffusion process, similar to the hierarchical organization, and also provides a new perspective for multiscale network community detection.

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Kong, Wei-Bin, Hou-Xing Zhou, Wei-Dong Li, Guang Hua, and Wei Hong. "The MLFMA Equipped with a Hybrid Tree Structure for the Multiscale EM Scattering." International Journal of Antennas and Propagation 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/281303.

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We present an efficient strategy for reducing the memory requirement for the near-field matrix in the multilevel fast multipole algorithm (MLFMA) for solving multiscale electromagnetic (EM) scattering problems. A multiscale problem can obviously lower the storage efficiency of the MLFMA for the near-field matrix. This paper focuses on overcoming this shortcoming to a certain extent. A hybrid tree structure for the MLFMA that possesses two kinds of bottom-layer boxes with different edge sizes will be built to significantly reduce the memory requirement for the near-field matrix in the multiscale case compared with the single-tree-structure technique. Several numerical examples are provided to demonstrate the efficiency of the proposed scheme in the multiscale EM scattering.

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Kang, Emily L., and John Harlim. "Filtering Partially Observed Multiscale Systems with Heterogeneous Multiscale Methods–Based Reduced Climate Models." Monthly Weather Review 140, no. 3 (February 1, 2012): 860–73. http://dx.doi.org/10.1175/mwr-d-10-05067.1.

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Abstract This paper presents a fast reduced filtering strategy for assimilating multiscale systems in the presence of observations of only the macroscopic (or large scale) variables. This reduced filtering strategy introduces model errors in estimating the prior forecast statistics through the (heterogeneous multiscale methods) HMM-based reduced climate model as an alternative to the standard expensive (direct numerical simulation) DNS-based fully resolved model. More importantly, this approach is not restricted to any analysis (or Bayesian updating) step from various ensemble-based filters. In a regime where there is a distinctive separation of scales, high filtering skill is obtained through applying the HMM alone with any desirable analysis step from ensemble Kalman filters. When separation of scales is not apparent as typically observed in geophysical turbulent systems, an additional procedure is proposed to reinitialize the microscopic variables to statistically reflect pseudo-observations that are constructed based on the unbiased estimates of the macroscopic variables. Specifically, these pseudo-observations are constructed offline from the conditional distributions of the microscopic forcing to the macroscopic dynamics given the macroscopic variables with the method-of-moments estimator. This HMM-based filter is comparable to the more expensive standard DNS-based filter on a stringent test bed, the two-layer Lorenz’96 model, in various regimes of scale gap, including the not so apparent one. This high filtering skill is robust in the presence of additional model errors through inconsistent pseudo-observations and even when macroscopic observations are spatially incomplete.

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Yang, Jie, Zhijun Xu, and Xiaoning Yang. "Multiscale molecular simulations on interfacial adsorption and permeation of nanoporous graphynes." Physical Chemistry Chemical Physics 19, no. 32 (2017): 21481–89. http://dx.doi.org/10.1039/c7cp04236a.

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Sun, Gao Rong. "Application of Probabilistic Distribution Matching PATC on Robust Multi-Scale Design." Advanced Materials Research 479-481 (February 2012): 1665–69. http://dx.doi.org/10.4028/www.scientific.net/amr.479-481.1665.

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Multiscale design dealing with a 2-scale material and product system is implemented by employing the probabilistic distribution matching probabilistic analytical target cascading method (PATC-PCE) in this paper. PATC-PCE allows design autonomy at each scale subsystem by formulating the multiscale design system as a multilevel design structure. The probabilistic distribution matching strategy in PATC-PCE can quantify the stochastic interrelated responses accurately enough. Comparative study on a multiscale bracket design problem shows that the results obtained by our method are very close to the benchmark values. PATC-PCE is demonstrated to be highly effective and applicable on multi-scale design.

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Macaluso, Veronica, Lorenzo Cupellini, Giacomo Salvadori, Filippo Lipparini, and Benedetta Mennucci. "Elucidating the role of structural fluctuations, and intermolecular and vibronic interactions in the spectroscopic response of a bacteriophytochrome." Physical Chemistry Chemical Physics 22, no. 16 (2020): 8585–94. http://dx.doi.org/10.1039/d0cp00372g.

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Zheng, Xiaoyan, Dong Wang, Wenhan Xu, Siqin Cao, Qian Peng, and Ben Zhong Tang. "Charge control of fluorescent probes to selectively target the cell membrane or mitochondria: theoretical prediction and experimental validation." Materials Horizons 6, no. 10 (2019): 2016–23. http://dx.doi.org/10.1039/c9mh00906j.

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Zhao, Peiyao, Ziming Cai, Lingling Chen, Longwen Wu, Yu Huan, Limin Guo, Longtu Li, Hong Wang, and Xiaohui Wang. "Ultra-high energy storage performance in lead-free multilayer ceramic capacitors via a multiscale optimization strategy." Energy & Environmental Science 13, no. 12 (2020): 4882–90. http://dx.doi.org/10.1039/d0ee03094e.

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Yu, Xiaole, Yudong Hou, Mupeng Zheng, and Mankang Zhu. "Multiscale Heterogeneity Strategy in Piezoceramics for Enhanced Energy Harvesting Performances." ACS Applied Materials & Interfaces 13, no. 15 (April 7, 2021): 17800–17808. http://dx.doi.org/10.1021/acsami.1c01409.

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Målqvist, Axel, and Barbara Verfürth. "An offline-online strategy for multiscale problems with random defects." ESAIM: Mathematical Modelling and Numerical Analysis 56, no. 1 (January 2022): 237–60. http://dx.doi.org/10.1051/m2an/2022006.

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In this paper, we propose an offline-online strategy based on the Localized Orthogonal Decomposition (LOD) method for elliptic multiscale problems with randomly perturbed diffusion coefficient. We consider a periodic deterministic coefficient with local defects that occur with probability p. The offline phase pre-computes entries to global LOD stiffness matrices on a single reference element (exploiting the periodicity) for a selection of defect configurations. Given a sample of the perturbed diffusion the corresponding LOD stiffness matrix is then computed by taking linear combinations of the pre-computed entries, in the online phase. Our computable error estimates show that this yields a good approximation of the solution for small p, which is illustrated by extensive numerical experiments. This makes the proposed technique attractive already for moderate sample sizes in a Monte Carlo simulation.

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Malavasi, G., M. C. Menziani, A. Pedone, B. Civalleri, M. Corno, and P. Ugliengo. "A computational multiscale strategy to the study of amorphous materials." Theoretical Chemistry Accounts 117, no. 5-6 (February 28, 2007): 933–42. http://dx.doi.org/10.1007/s00214-006-0214-1.

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Ricci, Francesco, Renato Vacondio, and Angelantonio Tafuni. "Multiscale Smoothed Particle Hydrodynamics based on a domain-decomposition strategy." Computer Methods in Applied Mechanics and Engineering 418 (January 2024): 116500. http://dx.doi.org/10.1016/j.cma.2023.116500.

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Pratikakis, Ioannis, Christian Barillot, Pierre Hellier, and Etienne Memin. "Robust Multiscale Deformable Registration of 3D Ultrasound Images." International Journal of Image and Graphics 03, no. 04 (October 2003): 547–65. http://dx.doi.org/10.1142/s0219467803001184.

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In this paper, we embed the minimization scheme of an automatic 3D non-rigid registration method in a multiscale framework. The initial model formulation was expressed as a robust multiresolution and multigrid minimization scheme. At the finest level of the multiresolution pyramid, we introduce a focusing strategy from coarse-to-fine scales which leads to an improvement in the accuracy of the registration process. A focusing strategy has been tested for a linear and a non-linear scale-space. Results on real 3D ultrasound images are discussed.

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Chen, Yuqing, Zongcai Feng, Lei Fu, Abdullah AlTheyab, Shihang Feng, and Gerard Schuster. "Multiscale reflection phase inversion with migration deconvolution." GEOPHYSICS 85, no. 1 (January 1, 2020): R55—R73. http://dx.doi.org/10.1190/geo2018-0751.1.

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Reflection full-waveform inversion (RFWI) can recover the low-wavenumber components of the velocity model along with the reflection wavepaths. However, this requires an expensive least-squares reverse time migration (LSRTM) to construct the perturbation image that can still suffer from cycle-skipping problems. As an inexpensive alternative to LSRTM, we use migration deconvolution (MD) with RFWI. To mitigate cycle-skipping problems, we develop a multiscale reflection phase inversion (MRPI) strategy that boosts the low-frequency data and should only explain the phase information in the recorded data, not its magnitude spectrum. We also use the rolling-offset strategy that gradually extends the offset range of data with an increasing number of iterations. Numerical results indicate that the MRPI + MD method can efficiently recover the low-wavenumber components of the velocity model and is less prone to getting stuck in local minima compared to conventional RFWI.

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Zhang, Hong, Lixing Chen, Yong Qu, Guo Zhao, and Zhenwei Guo. "Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/835791.

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The purpose of this paper is to investigate the short-term wind power forecasting. STWPF is a typically complex issue, because it is affected by many factors such as wind speed, wind direction, and humidity. This paper attempts to provide a reference strategy for STWPF and to solve the problems in existence. The two main contributions of this paper are as follows. (1) In data preprocessing, each encountered problem of employed real data such as irrelevant, outliers, missing value, and noisy data has been taken into account, the corresponding reasonable processing has been given, and the input variable selection and order estimation are investigated by Partial least squares technique. (2) STWPF is investigated by multiscale support vector regression (SVR) technique, and the parameters associated with SVR are optimized based on Grid-search method. In order to investigate the performance of proposed strategy, forecasting results comparison between two different forecasting models, multiscale SVR and multilayer perceptron neural network applied for power forecasts, are presented. In addition, the error evaluation demonstrates that the multiscale SVR is a robust, precise, and effective approach.

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Cho, Seok-Kyu, Sung-Ju Cho, Seong-Sun Lee, Keun-Ho Choi, and Sang-Young Lee. "DNA-directed amphiphilic self-assembly as a chemifunctional/multiscale-structuring strategy for high-performance Li–S batteries." Journal of Materials Chemistry A 7, no. 8 (2019): 4084–92. http://dx.doi.org/10.1039/c8ta11398j.

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Wu, Heng, Wenyu Yuan, Yingxin Zhao, Daoyang Han, Xiaowen Yuan, and Laifei Cheng. "B, N-dual doped sisal-based multiscale porous carbon for high-rate supercapacitors." RSC Advances 9, no. 3 (2019): 1476–86. http://dx.doi.org/10.1039/c8ra09663e.

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Wang, Fei, and Yalu Ying. "Evaluation of Students’ Innovation and Entrepreneurship Ability Based on ResNet Network." Mobile Information Systems 2022 (February 22, 2022): 1–11. http://dx.doi.org/10.1155/2022/7772415.

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As the country’s high-quality talents, college students are an important force in national construction. Evaluating the innovative and entrepreneurial abilities for Chinese students will help promote innovation and entrepreneurship education system and improve the reform of educational system and mechanism of colleges, thereby enhancing the innovation and entrepreneurship abilities of college students and then pushing the country into the ranks of a strong country in human resources and a strong country in talents. This work designs a ResNet-based evaluation method to college innovation and entrepreneurship abilities; the main contributions are as follows. (1) When ResNet performs feature extraction, there are problems of bloated network structure and feature loss. A feature extraction backbone network based on ResNet is proposed. To solve the issue of loss for shallow features in process of feature extraction, a skip architecture is added to fuse the shallow details and spatial information with the deep semantic information. To solve the problem of weak model generalization ability caused by the shallow network, a network stacking strategy is proposed to deepen the network structure. (2) Aiming at the problem that ResNet using single-scale feature prediction cannot effectively utilize multiscale features in the network, a multiscale feature prediction is designed. According to idea of feature pyramid, multiple feature maps with different scales are selected for the improved residual network. It designed a multiscale feature fusion strategy for fusing the selected multiscale feature maps into a feature map and evaluated the innovation and entrepreneurship abilities on the fused feature maps. Finally, comparative experiment proves that the improved feature extraction backbone network and multiscale feature scheme can improve performance accuracy on constructed dataset.

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Wang, Ronghan, Tao Liu, Junwei Lu, and Yuwei Zhou. "Interpretable Optimization Training Strategy-Based DCNN and Its Application on CT Image Recognition." Mathematical Problems in Engineering 2022 (March 16, 2022): 1–13. http://dx.doi.org/10.1155/2022/2170596.

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The theoretical basis of the discrete random sample batch classification is not clear and the sample division is not scientific during the process of Deep Convolutional Neural Network (DCNN) model training. Aiming at the problems above, starting from the DCNN detection recognition mechanism, the theory of random discrete samples is given and proved, and a scientific quantitative batch of sample input method is proposed. Combined with image preprocessing, based on the strategy of random dispersion of samples, and scientifically quantified sample input batches, the DCNN model is trained with limited label samples, and then the CT image recognition of pulmonary nodules is carried out. Experimental results based on the LIDC-ID-RI public dataset show that the sensitivity, specificity, and accuracy of the proposed method have reached 96.40%, 95.60%, and 96.00%, respectively. Compared with the multiscale convolutional neural network method and the multiscale multimode image fusion method, the recognition accuracy of the proposed method is improved by 1.6 and 3.49 percentage points, respectively.

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Pan, Ming, Eric F. Wood, Dennis B. McLaughlin, Dara Entekhabi, and Lifeng Luo. "A Multiscale Ensemble Filtering System for Hydrologic Data Assimilation. Part I: Implementation and Synthetic Experiment." Journal of Hydrometeorology 10, no. 3 (June 1, 2009): 794–806. http://dx.doi.org/10.1175/2009jhm1088.1.

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Abstract The multiscale autoregressive (MAR) framework was introduced in the last decade to process signals that exhibit multiscale features. It provides the method for identifying the multiscale structure in signals and a filtering procedure, and thus is an efficient way to solve the optimal estimation problem for many high-dimensional dynamic systems. Later, an ensemble version of this multiscale filtering procedure, the ensemble multiscale filter (EnMSF), was developed for estimation systems that rely on Monte Carlo samples, making this technique suitable for a range of applications in geosciences. Following the prototype study that introduced EnMSF, a strategy is devised here to implement the multiscale method in a hydrologic data assimilation system, which runs a land surface model. Assimilation experiments are carried out over the Arkansas–Red River basin, located in the central United States (∼645 000 km2), using the Variable Infiltration Capacity (VIC) model with a computing grid of 1062 pixels. A synthetic data assimilation experiment is performed, driven by meteorological forcing fields downscaled from the ensemble forecasts made by the NOAA/National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS). The classic full-rank ensemble Kalman filter is used as the benchmark to evaluate the multiscale filter performance, and comparisons are also made with a horizontally uncoupled filter. It is demonstrated that the multiscale filter is able to closely approximate the full-rank solution with a low computational cost (∼1/20 of the full-rank filter) in an experiment in which the top-layer soil moisture is assimilated, whereas the horizontally uncoupled filter fails to approximate the full-rank solution.

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Lei, Qi, Jiankang He, and Dichen Li. "Electrohydrodynamic 3D printing of layer-specifically oriented, multiscale conductive scaffolds for cardiac tissue engineering." Nanoscale 11, no. 32 (2019): 15195–205. http://dx.doi.org/10.1039/c9nr04989d.

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Here a novel strategy was presented to fabricate multiscale conductive scaffolds with layer-specific fiber orientations for cardiac tissue engineering by combining solution-based and melt-based electrohydrodynamic (EHD) printing techniques.

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Zhao, Chunhui, Boao Qin, Shou Feng, and Wenxiang Zhu. "Multiple Superpixel Graphs Learning Based on Adaptive Multiscale Segmentation for Hyperspectral Image Classification." Remote Sensing 14, no. 3 (January 31, 2022): 681. http://dx.doi.org/10.3390/rs14030681.

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Hyperspectral image classification (HSIC) methods usually require more training samples for better classification performance. However, a large number of labeled samples are difficult to obtain because it is cost- and time-consuming to label an HSI in a pixel-wise way. Therefore, how to overcome the problem of insufficient accuracy and stability under the condition of small labeled training sample size (SLTSS) is still a challenge for HSIC. In this paper, we proposed a novel multiple superpixel graphs learning method based on adaptive multiscale segmentation (MSGLAMS) for HSI classification to address this problem. First, the multiscale-superpixel-based framework can reduce the adverse effect of improper selection of a superpixel segmentation scale on the classification accuracy while saving the cost to manually seek a suitable segmentation scale. To make full use of the superpixel-level spatial information of different segmentation scales, a novel two-steps multiscale selection strategy is designed to adaptively select a group of complementary scales (multiscale). To fix the bias and instability of a single model, multiple superpixel-based graphical models obatined by constructing superpixel contracted graph of fusion scales are developed to jointly predict the final results via a pixel-level fusion strategy. Experimental results show that the proposed MSGLAMS has better performance when compared with other state-of-the-art algorithms. Specifically, its overall accuracy achieves 94.312%, 99.217%, 98.373% and 92.693% on Indian Pines, Salinas and University of Pavia, and the more challenging dataset Houston2013, respectively.

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Xu, Jun, Han Zhou, Kaiyu Shi, Runyu Yan, Yiwen Tang, Jian Liu, Jinhua Ye, Di Zhang, and Tongxiang Fan. "Bio-directed morphology engineering towards hierarchical 1D to 3D macro/meso/nanoscopic morph-tunable carbon nitride assemblies for enhanced artificial photosynthesis." Journal of Materials Chemistry A 5, no. 5 (2017): 2195–203. http://dx.doi.org/10.1039/c6ta08691h.

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Jurinovich, Sandro, Gennaro Pescitelli, Lorenzo Di Bari, and Benedetta Mennucci. "A TDDFT/MMPol/PCM model for the simulation of exciton-coupled circular dichroism spectra." Phys. Chem. Chem. Phys. 16, no. 31 (2014): 16407–18. http://dx.doi.org/10.1039/c3cp55428g.

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A multiscale strategy is presented to simulate electronic CD spectra of multichromophoric systems using an excitonic approach in which all components are calculated self-consistently through a fully polarizable QM/MM/PCM method.

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