Demonstration of the combinatorial Hill functions (A and B), and the regulation function (C and D) under the regulation of an activator and a repressor. by Ruihao Li (2908991)

Comparison before and after the removal of Chl-a data noise. by Li Wang (15202)

Pipeline of the interactor algorithm. by Jose Cleydson F. Silva (8685594)

Comparison of covariates versus brain imaging data in the classification of ASD before and after matching. by Oualid Benkarim (9707986)

Comparison of overall (a) Accuracy and (b) Label request results between ROAL and AOL. by Honglan Huang (341951)

Evolutionary processes on special functions (a) NMO-SARA vs MS-GEP-A (b) GEP vs MS-GEP-I (c) FF-GEP vs MS-GEP. by Jin Ding (11522)

CPU usage of benchmark function: (a) CPU Usage during the Execution of Benchmark Functions F21-F30, (b) CPU Usage during the Execution of Benchmark Functions F31-F40 and (c) CPU Us... by Ruyi Dong (9038174)

Iteration curve of benchmark function: (a) Convergence curves of the average best fitness for functions F21-F30, (b) Convergence curves of the average best fitness for functions F3... by Ruyi Dong (9038174)

SPIRIT diagram showing the schedule of enrollment, allocation, interventions, and assessments of this study. by Reinhard Chun Wang Chau (12733662)

Subjects:

Example of use of the slightly off-axis strategies. by Raul Castañeda (13932971)

Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. by Raul Castañeda (13932971)

Spatiotemporal parameters for patients clusters (before and one year after surgery) and control group. by Xavier Gasparutto (8374578)

Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. by Miray Unlu Yazici (14792680)

Subjects:

Population diversity comparison on all function (a) NMO-SARA vs MS-GEP-A (b) GEP vs MS-GEP-I (c) FF-GEP vs MS-GEP. by Jin Ding (11522)

Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large. by Panfei Li (22379086)

“…<p>Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large.…”

The SSIM for the different algorithms. by Bingbing Li (461702)

“…Unlike traditional threshold functions, the improved threshold function is a continuous function that can avoid the pseudo Gibbs effect after image denoising and improve image quality. …”

Comparison of accuracies before and after clause boundaries. by Sam Tilsen (406665)

The number of core promoter elements and TF binding sites predicted for four promoters with YAPP, GPMiner and ElemeNT algorithms. by Ali Hosseini Rad S. M. (9167497)

Comparison of the test results before and after expanding the data. by Xu Zhang (49484)

Scores of municipalities projected on the first and second functional PC (A), and first and third functional PC (B). by Manuel Ribeiro (17889313)