Working steps and operating algorithm of the developed GSMCS. حسب Abdallah Elshawadfy Elwakeel (19852263)

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. حسب Gursimran Singh (575288)

الموضوعات:

Accuracy and Absolute true of multi-label therapeutic peptides prediction models using different classical ML and DL algorithms on the training set with 5-fold cross-validation. حسب Wenhui Yan (825510)

Performance profiles of these algorithms on the basis of the number of function evaluations. حسب Xianfeng Ding (535904)

Automated sampling and control system for FACS streamlines high-throughput cell sorting workflows. حسب Diane M. Wiener (1956583)

الموضوعات:

Application of the smooth-index to bandwidth-limited matrices (A,B) and to block-diagonal matrices (C,D). حسب Alexander Borst (32619)

الموضوعات:

List of recurrent connections from the single column connectome of Drosophila. حسب Alexander Borst (32619)

الموضوعات:

Steps of data preprocessing. حسب Bernhard Vennemann (7434353)

Multidomain, Automated Photopatterning of DNA-functionalized Hydrogels (MAPDH). حسب Moshe Rubanov (7289156)

"…The algorithm incorporates a wash step between each round of patterning. …"

Objective function trend with static and dynamic step size. حسب Ludovica Adacher (11238189)

<b>Algorithm Pseudocode</b> حسب Yibin Zhao (22425801)

Swarm intelligence algorithms for multi-objective IMP: Step-by-step improvement حسب Francisco Muñoz (9455441)

"…Algorithms implemented on article "<b>A step-by-step solution for the multi-objective influence spread problem</b>". …"

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. حسب Gursimran Singh (575288)

الموضوعات:

Task structure diagram. حسب Honglan Huang (341951)

الموضوعات: "…Cell Biology…"

Second experiment results of the trained model. حسب Honglan Huang (341951)

الموضوعات: "…Cell Biology…"

Flow chart of the analysis steps in this study. حسب Junjie Su (368807)

الموضوعات:

Summary of steps in iterative point set registration for scRNA-seq data. حسب Amir Alavi (9569337)

"…The number of source and/or target cells matched can vary for different matching strategies. 3) Based on the selected pairs, a global transformation function is learned so that source cells in <i>A</i> become closer to their paired cell in <i>B</i>. 4) The learned transformation is next applied to all points in <i>A</i>. 5) This process (steps 2–4) is repeated, iteratively aligning set <i>A</i> onto <i>B</i> until the mean distance between the assigned pairs of cells no longer improves. 6) The final global transformation function is the composition of the functions learned in each iteration at step 3.…"

Comparison of algorithms in two cases. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

Flow of the NSGA-II algorithm. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

Convergence curves for multimodal function test. حسب Qinghe Guo (21519322)