Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…<div><p>Chest X-ray image classification plays an important role in medical diagnostics. Machine learning algorithms enhanced the performance of these classification algorithms by introducing advance techniques. …"

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... حسب Giacomo Janson (8138517)

3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. حسب Giacomo Janson (8138517)

3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. حسب Giacomo Janson (8138517)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. حسب 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. …"

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. حسب Gursimran Singh (575288)

الموضوعات:

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

Loss functions between PCA-DNN model and PCA-LSTM model. حسب Cihun-Siyong Alex Gong (11874066)

PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. حسب Gursimran Singh (575288)

الموضوعات:

Performance of PCA and Joint Autoencoder (JAE) denoising algorithms. حسب Ege Altan (11768156)

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

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب 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). …"

Testing function diagram of QIMPN-PCA-DC. حسب Jun Zhao (59250)

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"

The loss function of network structures, LPC-DNN, LPC-PCA-DNN, LPC-LSTM, LPC-PCA-LSTM, MFCC-DNN, MFCC-PCA-DNN, MFCC-LSTM and MFCC-PCA-LSTM, as the epoch increases. حسب Cihun-Siyong Alex Gong (11874066)

Functional module diagram. حسب Fan Hongxia (21029673)

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

Illustration of recording paradigm with PyNoetic’s Stimuli generation and recording module. حسب Gursimran Singh (575288)

الموضوعات:

<b>Algorithm Pseudocode</b> حسب Yibin Zhao (22425801)

The structure of the proposed algorithm. حسب Mingbao Yang (14008799)