Step-function plots of longitudinal dose changes for propranolol separated by cluster assignment analyzed using 2, 3, and 4 clusters. by Mary-Carty Pittman (21161824)

Step-function plots of longitudinal dose changes for captopril separated by cluster assignment analyzed using 2, 3, and 4 clusters. by Mary-Carty Pittman (21161824)

Node matching step 1. by Shuwen Wang (457921)

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3D visualization of the Rastrigin function from the CEC 2019 benchmark test functions. by Mahmood A. Jumaah (22272371)

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This appendix presents the flowchart used in the development of the particle swarm optimization algorithm for determining the optimal PID controller gain values. by Rafael Mendes Faria (18886798)

Count comparison of all output steps based on time performance. by Zhiqun Lin (1429501)

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Benchmark test function results. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Reward function related parameters. by Honglei Pang (22693724)

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The network lifetime as a function of number of sensor nodes. by Zhou He (10330007)

Delivered packets as a function of number of sensor nodes. by Zhou He (10330007)

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data by Anthony S. Barente (14035175)

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Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

IRBMO vs. meta-heuristic algorithms boxplot. by Chenyi Zhu (9383370)

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IRBMO vs. feature selection algorithm boxplot. by Chenyi Zhu (9383370)

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Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…Hierarchical clustering was computed using the scikit learn module in Python. C) Dendrogram of averaged functional connectivity from healthy subjects. …”

Wavelet transform and scaling function. by Menaa Nawaz (14304920)

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning by Bernhard Vennemann (7434353)

“…In this article, we describe how unsupervised novelty detection algorithms can be used to automate the interpretation of blood flow data to improve outcomes through early detection of adverse cardiovascular events without requiring repeated check-ups in a clinical environment. …”

The case of LLSKSO with the value of the weight coefficient <i>w</i> in steps of 0.1. by Ruyi Dong (9038174)

Subjects: “…effective optimization algorithm…”

Step by step workflow for PRLF model training and data scoring. by John Prindle (10774286)

Rules of the proposed fuzzy inference system for the objective function in CCR. by Zhou He (10330007)