Flowchart of OP-ZOA algorithm. by Tengfei Ma (597633)

“…During experimental evaluation, the efficiency of OP-ZOA was verified using the CEC2017 test functions, demonstrating superior performance compared to seven recently proposed meta-heuristic algorithms (Bloodsucking Leech Algorithm (BSLO), Parrot Optimization Algorithm (PO), Polar Lights Algorithm (PLO), Red-tailed Hawk Optimization Algorithm (RTH), Bitterling Fish Optimization Algorithm (BFO), Spider Wasp Optimization Algorithm (SWO) and Zebra Optimization Algorithm (ZOA)). …”

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

Data Sheet 1_Non-negative connectivity causes bow-tie architecture in neural circuits.pdf by Zhaofan Liu (327486)

Comparison with the BST algorithm for the AF and CST bundles. by Thomas Durantel (20933812)

Fitness function parameters. by Ankita Sharma (3183054)

It includes raw data extracted from graphical experimental data sets presented in [22,23] for both P2X receptors and used in the fitting process. by Alireza Poshtkohi (11632250)

Local topological scales of hierarchical community organization in structural and functional brain graphs. by Arian Ashourvan (6685232)

Multi-scale detection of hierarchical community architecture in structural and functional brain networks by Arian Ashourvan (6685232)

“…Finally, we build an explicitly multimodal multiplex graph that combines both structural and functional connectivity in a single model, and we identify the topological scales where resting state functional connectivity and underlying structural connectivity show similar <i>versus</i> unique hierarchical community architecture. …”

Occurrence probabilities of behavioral switching in multi-agent predator–prey interactions when both <i>D</i>_<i>w</i> and <i>D</i>_<i>s</i> are 2. by Hiroyuki Ichijo (13891153)

A flow diagram to explain the algorithm named 2BDP (Biomarker Discovery Process at Binomial Decision Point) that we used to find the best fitting model to predict RRiF. by Nabarun Chakraborty (535772)

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…”

Main parameters of braking system. by Honglei Pang (22693724)

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Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... by Honglei Pang (22693724)

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EMB and SBW system structure. by Honglei Pang (22693724)

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Raw data. by Honglei Pang (22693724)

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Braking performance and lateral stability on low-adhesion road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle s... by Honglei Pang (22693724)

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Code program. by Honglei Pang (22693724)

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The HIL simulation data flowchart. by Honglei Pang (22693724)

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Braking performance and lateral stability on curved road surfaces: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sidesli... by Honglei Pang (22693724)

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Steering system model. by Honglei Pang (22693724)

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