Completion times for different algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

Simulation settings of rMAPPO algorithm. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Comparison of deconvolution and optimization algorithms on a batch of data. by Ali-Kemal Aydin (10968731)

“…Both experimental data have been resampled at 50ms and used to compute a set of TFs (in orange) either with direct deconvolution approaches (Fourier or Toeplitz methods, middle-upper panel TFs) or with 1-Γ function optimization performed by 3 different algorithms (middle-lower panel TFs). …”

Optimum feature set for classification using both core and margin information utilizing GLCM, GRLM, and GLSZM texture methods and SVM-RBF classification algorithm. by Laurentius O. Osapoetra (9931759)

Reconstruction performance across algorithms, dynamics, cell types, and recording length. by Christian Donner (3663007)

Summary of the contrasts obtained from the normalized images for both inclusions as a function of the host type and the wavelength. by María Victoria Waks-Serra (21578611)

Comparison with the BST algorithm for the AF and CST bundles. by Thomas Durantel (20933812)

The Precision-Recall curve of both the models. by Aastha Vatsyayan (9981916)

Equilibrium membrane displacement as a function of active force. by Kai Liu (159026)

Data_Sheet_1_Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography.docx by Takatsugu Aihara (4433524)

Construction of the PRG score index using integrated machine learning algorithms. by Xiangxin Wu (22320058)

Venn diagrams showing overlap of the total of overrepresented/underrepresented kinases for both cohorts. by Erica A. K. DePasquale (11851483)

Automatic cropping algorithm. by Thomas W Georgi (12427189)

Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)

Comparison of the performance of both models against 13 other models on the independent test dataset. by Aastha Vatsyayan (9981916)

Illustration of the cell detection process. by Adam L. Tyson (10892822)

Data_Sheet_1_Transcranial magnetic stimulation mapping of the motor cortex: comparison of five estimation algorithms.docx by Yuanyuan Chen (165812)