Actual autocorrelation function <i>R</i>_<i>ϵϵ</i>(<i>n</i>, <i>k</i>) and sample autocorrelation function estimated online assuming λ = 0.9998 in the case of non-station... by Martin Dodek (20623832)

Results on solving TSS using different evolutionary and greedy algorithms. by Alexander Andreev (16822333)

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Proportion of simulated data with improved likelihood from using multiple restarts (Algorithm 1). by Jesse Wheeler (18462457)

Comparison of the set found when solving IM for <i>k</i> = 19 by the greedy algorithm (left) and the one found by (1 + 1)-WEA for a network with <i>n</i> = 50 vertices. by Alexander Andreev (16822333)

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Parameters of the genetic algorithm. by Jian Ma (170138)

Adding a new function module. by Yukako Yamane (9034133)

Data Sheet 1_Accurate informatic modeling of tooth enamel pellicle interactions by training substitution matrices with Mat4Pep.doc by Jeremy Horst Keeper (20458274)

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

“…Finally, the Inner-DIoU loss function is proposed to optimize bounding box regression. …”

CPU runtime of each algorithm: (a) Running Time Comparison of Different Algorithms on F1-F10 and (b) Running Time Comparison of Different Algorithms on F11-F20. by Ruyi Dong (9038174)

F1-Score of different algorithms for TMD on SHL dataset. by Rui Li (4631)

F1-Score of different algorithms for TMD on HTC dataset. by Rui Li (4631)

STD and STD/mean as a function of <i>N</i>_<i>p</i> for distribution of points with added noise. by Luca Maria Del Bono (20479625)

“…<p>STD (a) and STD/mean (b) as a function of <i>N</i>_<i>p</i> for distribution of points with added noise, before and after GD. …”

Recombinant mapping narrows region of interest to identify a loss-of-function allele of <i>mttp.</i> by McKenna Feltes (11242085)

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Results on solving TSS using (1 + 1)-WEA_v3 with different values of <i>Q.</i> by Alexander Andreev (16822333)

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Performance comparison of YOLOv8n adding different loss functions. by Wenyuan Xu (2553028)

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Graph of YOLOv8n detection results with different loss functions. by Wenyuan Xu (2553028)

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Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

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Table 2_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”

Table 1_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”

Table 3_Uncovering differential gene expression between mtRNA-positive and -negative osteosarcoma cells: implications beyond mitochondrial function.xlsx by Xiaoyuan Meng (22261234)

“…</p>Methods<p>Explore the function of mtRNA in the occurrence and development of osteosarcoma utilizing bioinformatics analysis of the Gene Expression Omnibus (GEO) microarray dataset. …”