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)

Data_Sheet_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.PDF by Shakiru A. Alaka (9302864)

“…<p>Background and Purpose: Stroke-related functional risk scores are used to predict patients' functional outcomes following a stroke event. …”

Data_Sheet_1_SDA: a data-driven algorithm that detects functional states applied to the EEG of Guhyasamaja meditation.docx by Ekaterina Mikhaylets (17865407)

“…<p>The study presents a novel approach designed to detect time-continuous states in time-series data, called the State-Detecting Algorithm (SDA). …”

Experiment 1b: Evaluating modularity-based consensus clustering pipelines on the algorithm design datasets as a function of the mixing parameter. by Yasamin Tabatabaee (18095491)

Function <i>wVL</i> for evaluation of resettable bistability. by Takashi Naka (272391)

Improved Ant Colony Algorithm by AOBEI ZHANG (17657703)

“…To achieve this, we integrate the hyperbolic tangent function, fine-tuning the ACO algorithm's behavior to adaptively adjust its search strategy across iterations.(2) Recognizing the tendency of heuristic algorithms to converge prematurely into local optima, we devise a max-min ant colony strategy. …”

Output groupings of the 3 algorithms for a linear degradation chain of <i>N</i> = 3 metabolites. by Yuanchen Zhao (12905580)

Visual depiction of the MSA algorithm. by Kayson Fakhar (12890364)

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

“…To address this issue, this paper proposes FCMI-YOLO, a real-time fire detection algorithm optimized for edge devices. …”

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

Running memory of the algorithms. by Yanju Zhang (437336)

a) FO Function, b) FI function. by Huang Jiexian (17060975)

“…The SRL32 primitive (Reconfigurable Look up Tables—RLUTs) and DPR (Dynamic Partial Reconfiguration) are employed to reconfigure single round MISTY1 / KASUMI algorithms on the run-time. The RLUT based architecture attains dynamic logic functionality without extra hardware resources by internally modifying the LUT contents. …”

Summary of results of naïve Bayes algorithms. by Christopher E. Niemczak (8586861)

Subjects:

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. by Alexis M. Thornton (11068403)

“…Impactful mutations are then tested for their directional impact of gain-of-function (GOF) or loss-of-function (LOF). For non-impactful mutations, a “power test” determines whether the two signatures are similar to one another due to a real signal or due to noise. …”

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)

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

“…However, our algorithm was 1000 times faster than pyROSETTA (both algorithms have been parallelized on a per-structure basis using the Python package joblib [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010531#pcbi.1010531.ref069" target="_blank">69</a>]).…”

Convergent curves of EOSA and related optimization algorithms benchmark functions over 1, 50, 100, 200, 300, 400 and 500 epochs. by Tehnan I. A. Mohamed (16846175)

“…<p>Convergent curves of EOSA and related optimization algorithms benchmark functions over 1, 50, 100, 200, 300, 400 and 500 epochs.…”

Model optimization flow by MFO algorithm. by Ruoqi Wang (14958062)

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)

Two equivalent switching functions and their switching circuits. by Alrik Thiem (4008182)