Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

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

Subjects: “…evolutionary genetic algorithm…”

Antihypertensive treatment algorithm. by Kira Bang Bove (9607123)

Details of path flows and path travel times by the proposed algorithms. by C. K. Wong (3224922)

Overview of algorithm. by Takayuki Niizato (162226)

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). …”

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

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

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

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

(a) Flow chart for PSO algorithm (b) position and velocity update of particles (c) convergence of PSO. by Waqas Anjum (8415186)

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

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Workflow of algorithm for whole brain flow simulation. by Erlend Hodneland (391541)

Algorithm of the scale-free induced subgroup. by Takayuki Niizato (162226)

Function <i>χ</i>_<i>opt</i> superimposed with the phase-field function indicating the channel geometry. by Martina Bukač (20161460)

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

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

Patient flow chart. by Stephan Ellmann (314565)

Subjects: “…Cell Biology…”

Schematic representation of the edge-cutting algorithm. by Pratik Mullick (12851011)

Subjects:

Pictorial representation of the edge-cutting algorithm. by Pratik Mullick (12851011)

Subjects:

The phase-field function for three different network configurations considered in this work. by Martina Bukač (20161460)