Results of the Kherson Area Visual Assessment. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Work flow chart. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Experimental data. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Results of the PY area visual assessment. حسب YueSheng Jiang (19267984)

"…To overcome these limitations, this paper developed a simple and fast adaptive remote sensing image Spatio-Temporal fusion method based on Fit-FC, called Adapt Lasso-Fit-FC (AL-FF). Firstly, the sparse characteristics of time phase change between images are explored, and a time phase change estimation model based on sparse regression is constructed, which overcomes the fuzzy problem of fusion image caused by the failure of linear regression to capture complex nonlinear time phase transition in the weighted Function method, making the algorithm better at capturing details. …"

Comparison of the improved LRM and RM results. حسب YueSheng Jiang (19267984)

Result charts for different window sizes. حسب YueSheng Jiang (19267984)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... حسب Hector Torres (11708207)

Overview of our study for sampling candidate aptamer sequences using the API classifiers and MCTS. حسب Gwangho Lee (11027565)

"…<p>(A) shows the process of choosing the best model from the random forest classifier trained by the API classification benchmark dataset. (B) illustrates our iterative forward sampling algorithm to obtain the candidate aptamer sequences that bind to the given target protein. …"

Reliability of the optimized frequency parameters and sFC matrix edges in the high-dimensional cases as well as of the GoF. حسب Kevin J. Wischnewski (21354521)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data حسب Jean-Christophe Lachance (6619307)

"…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …"

Main parameters of braking system. حسب Honglei Pang (22693724)

الموضوعات:

Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... حسب Honglei Pang (22693724)

الموضوعات:

EMB and SBW system structure. حسب Honglei Pang (22693724)

الموضوعات:

Raw data. حسب Honglei Pang (22693724)

الموضوعات:

Braking performance and lateral stability on low-adhesion road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle s... حسب Honglei Pang (22693724)

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Code program. حسب Honglei Pang (22693724)

الموضوعات:

The HIL simulation data flowchart. حسب Honglei Pang (22693724)

الموضوعات:

Braking performance and lateral stability on curved road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sidesli... حسب Honglei Pang (22693724)

الموضوعات:

Steering system model. حسب Honglei Pang (22693724)

الموضوعات:

Braking performance and lateral stability on split-μ road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sidesl... حسب Honglei Pang (22693724)

الموضوعات: