The comparison of serial and parallel runtime (s) for the four sub-functions. by Yongfei Wang (608480)

Cophenetic distances under various <i>L</i>_<i>p</i> norms and contribution functions. by Paweł Górecki (3285255)

Algorithm framework. by Zongjin Li (38031)

RTC-F solar cell: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

PWP201 solar module: (a) <i>I</i>-<i>U</i> and (b) <i>P</i>-<i>U</i> characteristics. by Ziad M. Ali (12516532)

Type-1 membership function for distance. by Seung-Min Ryu (21463891)

Type-1 membership function for speed. by Seung-Min Ryu (21463891)

STD/mean(∞;<i>α</i>) and <i>c</i>(<i>α</i>) coefficients as a function of <i>α</i>. by Luca Maria Del Bono (20479625)

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finit... by Hassan Mehboob (8960273)

Working time of different processes (<i>h</i>). by Dawei Wang (471687)

Types of training algorithms. by Caixia Yan (6647072)

NRPStransformer, an Accurate Adenylation Domain Specificity Prediction Algorithm for Genome Mining of Nonribosomal Peptides by Zhihan Zhang (1403308)

“…Leveraging the sequences within the flavodoxin-like subdomain, we developed a substrate specificity prediction algorithm using a protein language model, achieving 92% overall prediction accuracy for 43 frequently observed amino acids, significantly improving the prediction reliability. …”

MSX-60 module: (a) <i>I</i>-<i>U</i> and (b) <i>P-U</i> characteristics. by Ziad M. Ali (12516532)

<i>I</i>-<i>U</i> characteristics of the experimental PV solar module. by Ziad M. Ali (12516532)

Effectiveness of LSWOA and other SOTA algorithms with <i>D</i>=30, 50 and 100. by Junhao Wei (6816803)

Unraveling the gender-specific molecular landscape of lung squamous cell carcinoma progression by Ayushi Dwivedi (20658343)

Comparison of different algorithms. by Jiandong Qiu (20389944)

Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. by Yuanchen Zhao (12905580)

“…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …”

Membership function of error E1 for tank 1. by Tamiru Demelash Kassie (20678515)

Classification algorithm implemented in SPARTA. by Baptiste Ruiz (20285217)