Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

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Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

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Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

“…</p> <p>The study identifies specific variants (L111R, R114C, D123N, G150S, and L243P) in the coding region of the GABRD gene, which are predicted as deleterious by multiple algorithms. …”

Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

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Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 100. by Haiming Du (6691646)

Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 30. by Haiming Du (6691646)

Results of DE algorithms with our scheme and original DE algorithms when function dimensionality is set 50. by Haiming Du (6691646)

Results of proposed algorithms and algorithms in [9] for 18 instances. by Jin Zhang (53297)

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Convergence curves of the voltage profile improvement by using (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

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Convergence curves of voltage stability enhancement based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

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Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

“…In this contribution, we introduce a discrete cosine transformation-based (DCT-based) EIT reconstruction algorithm to demonstrate a way to incorporate the structural prior with the EIT reconstruction process. …”

Algorithm for generating virtual patients. by Adrianne L. Jenner (11133854)

“…<b>2)</b> The model evaluated is then simulated on this parameter set to obtain <i>y</i>(<i>t</i>, <i>p</i>). <b>3)</b> A simulated annealing algorithm is then used to determine a parameter set that optimises the objective function <i>J</i>(<i>p</i>) (<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1009753#ppat.1009753.e059" target="_blank">Eq 17</a>). …”

Convergence curves of total fuel cost minimization based on (a) the HFPSO algorithm and (b) the PSO algorithm. by Abdullah Khan (377292)

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The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Our algorithms process large data sets within a minute. by Manu Aggarwal (15990691)

Predictive Mixing for Density Functional Theory (and Other Fixed-Point Problems) by L. D. Marks (1949689)

“…Density functional theory calculations use a significant fraction of current supercomputing time. …”

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”

Fixed-dimensional multimodal reference functions. by Ruiyu Zhan (21602031)

“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”