The influence of different materials of scatterers on the sound absorption. حسب Xiaogang Li (299205)

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Data for Figs 3–9. حسب Xiaogang Li (299205)

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The solid material attributes. حسب Xiaogang Li (299205)

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Sound absorption spectrum calculated by TMM (dots) and FEM (solid lines). حسب Xiaogang Li (299205)

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Fig 6 - حسب Xiaogang Li (299205)

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Simulation sample. حسب Xiaogang Li (299205)

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Fig 7 - حسب Xiaogang Li (299205)

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The normalized acoustic resistance (blue lines) and reactance (red dotted lines) of the optimization case in Fig 7. حسب Xiaogang Li (299205)

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Cross section of the metagrating and the distribution of effective homogeneous layers. حسب Xiaogang Li (299205)

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Model’s measure methods. حسب Songsong Wang (8088293)

"…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…"

DataSheet1_Applying neural network algorithms to ascertain reported experiences of violence in routine mental healthcare records and distributions of reports by diagnosis.pdf حسب Ava J. C. Mason (19571008)

"…Introduction<p>Experiences of violence are important risk factors for worse outcome in people with mental health conditions; however, they are not routinely collected be mental health services, so their ascertainment depends on extraction from text fields with natural language processing (NLP) algorithms.</p>Methods<p>Applying previously developed neural network algorithms to routine mental healthcare records, we sought to describe the distribution of recorded violence victimisation by demographic and diagnostic characteristics. …"

Data pre-processing and identification of DEGs. حسب Ziyang Liu (242055)

<b>Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</b> حسب Yize Wang (19535173)

"…<p dir="ltr">The farm-level yaw control optimization algorithm Codes for "Fatigue analysis of wind turbine and load reduction through wind-farm-level yaw control"</p>…"

Accuracy of different electrical and optical neural networks for various input noise levels. حسب Reyhane Ahmadi (14857363)

Elements: Multiparticle collision dynamics simulations of mesoscale hydrodynamic interactions in complex soft materials and environments حسب Michael Howard (19421473)

Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx حسب Pan Zhang (206408)

"…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …"

Computation time as a function of the sample size on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). حسب Tomokaze Shiratori (9635271)

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Computation time as a function of the sample size on the random graph dataset. حسب Tomokaze Shiratori (9635271)

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F1 score of edges selected through cross-validation on the chain graph dataset. حسب Tomokaze Shiratori (9635271)

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