Testing performance comparison for different algorithms. by Roberto Bárcenas (13924220)

Training performance comparison for different algorithms. by Roberto Bárcenas (13924220)

Algorithm used in the model to automatically estimate the parameters of LD pharmacodynamics, via minimization of a cost function. by Mauro Ursino (144905)

Working steps and operating algorithm of the developed GSMCS. by Abdallah Elshawadfy Elwakeel (19852263)

An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

“…<p><i>(a)</i> Noninvadable states by definition can only exist in the region Ω of resource space where the growth rate <i>dN</i>_<i>i</i>/<i>dt</i> of each species <i>i</i> is zero or negative. …”

Wav2DDK: An automated DDK estimation algorithm (Kadambi et al., 2023) by Prad Kadambi (16680635)

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Supporting data for "Personalized Electromyography Based Control Algorithm Development and Training System for Hand Prosthesis" for HKU Libraries by Xiaojun Wang (9067289)

Reward function related parameters. by Honglei Pang (22693724)

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DataSheet1_Sensor-based outcomes to monitor everyday life motor activities of children and adolescents with neuromotor impairments: A survey with health professionals.pdf by Fabian Marcel Rast (13945515)

Subjects: “…Animal Structure and Function…”

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

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)

Comparison between the non-sensory motor and sensory–motor algorithms. by Hiroyuki Ichijo (13891153)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

Generation of simulated datasets. by Ege Altan (11768156)

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Noise decrease rate comparison. by Xianlin Ren (22783589)

“…This research initially proposes an adaptive variational mode decomposition approach based on dung beetle optimization algorithm to decompose and extract signals. At the same time, a composite optimization indicator function based on Tanimoto coefficient, permutation entropy and kurtosis are presented as the fitness function of decomposition to increase the flexibility and robustness of the technique. …”

HIL test results of curved road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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HIL test results of low-adhesion road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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HIL test results of split-μ road: (a)Vehicle velocity; (b) Braking distance; (c) Lateral displacement; (d) Lateral acceleration; (e)Vehicle sideslip angle; (f) Yaw rate. by Honglei Pang (22693724)

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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

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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