Demographic and clinical characteristics of participants included in the BNA neuromarker. by Sharon Hassin-Baer (420354)

Subjects:

Results of the cognitive tasks performance. by Sharon Hassin-Baer (420354)

Subjects:

Correlation between the BNA neuromarker linear scores and the mUPDRS scores. by Sharon Hassin-Baer (420354)

Subjects:

Progress toward national and global TB targets for (a) TB mortality and (b) new TB infections in the 15–64 age group, under 2015 and optimised allocations of national TB spending.... by Lara Goscé (11485929)

Subjects:

<b>The Application of the Optimized Genetic Algorithm in SerDes Circuit Design</b> by Xuan Wei (18564826)

Flowchart of system algorithm. by Syed Zahurul Islam (9635163)

Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures. by Kevin Sawade (16726527)

“…Our ISA algorithm correlates with the much more sophisticated ROSETTA algorithm with a Pearson correlation coefficient of 0.88 (B). …”

Type-I (<i>α</i>) and Type-II (<i>β</i>) errors, and accuracies for different clinical stages (a) Stage 1, (b) Stage 2, (c) Stage 3, and (d) Stage 4. by Mario A. Quiroz-Juárez (11457140)

Distribution of the average embeddings. by Yiming Kuang (22120458)

Subjects:

Proposed algorithm flowchart. by Fadhil Mukhlif (8411451)

Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

“…This program implements the “modeling by satisfaction of spatial restraints” strategy and its core algorithm has not been altered significantly since the early 1990s. …”

Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms. by Ruyi Dong (9038174)

“…<p>Iteration curve of each algorithm: (a) Convergence curves of the average best fitness for functions F1-F10, (b) Convergence curves of the average best fitness for functions F11-F20 and (c) Correspondence between curve colors and algorithms.…”

Performance comparison in CP-EE model (a) SVR model (b) BPNN model (c) RF model (d) MS-GEP model. by Jin Ding (11522)

Convergence curve of others functions compared with the PSO family algorithms. by Yong Gao (29929)

Convergence curve of unimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

Convergence curve of unimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Convergence curve of others functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Convergence curve of multimodal functions compared with the meta-heuristic algorithms. by Yong Gao (29929)

Convergence curve of multimodal functions compared with the PSO family algorithms. by Yong Gao (29929)

The execution times (nano seconds) per particle are measured for four different algorithms [47], (A: first algorithm, B: second algorithm, C: third algorithm: and D: fourth algorit... by Abedalmuhdi Almomany (18547669)