Flowchart of software workflow. حسب Gavrielle R. Untracht (11820311)

Automated Discovery and Optimization of 3D Topological Photonic Crystals حسب Samuel Kim (1682104)

الموضوعات:

Table1_Fine tuning a logical model of cancer cells to predict drug synergies: combining manual curation and automated parameterization.DOCX حسب Åsmund Flobak (789984)

Validation of image processing steps and metric results using images of a microfluidic device. حسب Gavrielle R. Untracht (11820311)

Study workflow overview. حسب Janne J. Luppi (17804327)

tUbenet Foundation Model Weights حسب Natalie Holroyd (7099391)

Diagram illustrating the MEM method applied to the HMR RRAS 12, in São Paulo state; A: The data input contains the number of cases per week per year, needed to describe the disease... حسب Ayrton Sena Gouveia (21587635)

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment حسب Jianfang Cao (1881379)

"…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …"

Overview of study assessments of the trial. حسب Tan Boon Toh (1348143)

"…Established PDOs will be subject to QPOP analyses to determine their therapeutic sensitivities to specific panels of drugs. A QPOP-guided treatment selection algorithm will then be used to select the most appropriate drug combination. …"

Experimental observation of gastruloids and shape quantification using LOCO-EFA. حسب Martijn A. de Jong (17896732)

Supplementary file 1_Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field.pdf حسب Shuangshuang Zhang (701020)

"…Aiming at this problem, this paper establishes a set of dynamic and static integrated classification model of tight sandstone gas wells in Sulige based on XGBoost algorithm. After comparison and verification, it is proved to be accurate and reliable. …"

Fig 3 - حسب Ali Ahmed (2567584)

Establishment of MPM. حسب Amir Abbas Navidinia (21656136)

Sample image for illustration. حسب Indhumathi S. (19173013)

"…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …"

Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential حسب Fengyang Han (14613218)

"…This information is useful to guide the construction of libraries for shape-based virtual screening and to improve the docking algorithm to efficiently sample bound conformations.…"

Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential حسب Fengyang Han (14613218)

"…This information is useful to guide the construction of libraries for shape-based virtual screening and to improve the docking algorithm to efficiently sample bound conformations.…"

Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

"…The results demonstrate that CBFD achieves a average precision of 0.97 for the test image, outperforming Superpoint, Directional Intensified Tertiary Filtering (DITF), Binary Robust Independent Elementary Features (BRIEF), Binary Robust Invariant Scalable Keypoints (BRISK), Speeded Up Robust Features (SURF), and Scale Invariant Feature Transform (SIFT), which achieve scores of 0.95, 0.92, 0.72, 0.66, 0.63 and 0.50 respectively. …"

Steps in the extraction of 14 coordinates from the CT slices for the curved MPR. حسب Linus Woitke (22783534)

"…The image is then cleaned in c) using morphological filtering with an <i>opening</i> operation to remove small-scale noise. …"

Image1_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)

Image3_Applying the Hubbard-Stratonovich Transformation to Solve Scheduling Problems Under Inequality Constraints With Quantum Annealing.TIF حسب Sizhuo Yu (11429743)