An important measure in various stages of oil sand mining is particle size distribution (PSD) of oil sand particles. Currently PSD is found by time consuming manual inspection. An effective automation ...

PCA(Principle Component Analysis) For Wine dataset in ML. Requirements. import numpy as np. import pandas as pd. import matplotlib.pyplot as plt. sklearn. Wine dataset. This Program is About Principal ...

An end point detection algorithm for small area etching was developed using the modified principal component analysis. Because the traditional end point detection techniques used a few manually ...

Principal Component Analysis (PCA) is a dimensionality reduction technique that is used to extract important features from high-dimensional datasets. PCA works by identifying the principal components ...

ABSTRACT. Objective: There were many constraints produced by training time and joint injury to analyze the influence of the training intensity on the elbow and knee joints of athletes during the ...

In other words, cryptanalysts and quantum researchers have not been able to devise an efficient quantum algorithm capable of solving the LWE problem and, hence, FrodoKEM. In cryptography, absolute ...

In addition, we applied principal component analysis (PCA) as an input to the algorithms to address multidriver dependency of FCH4 and reduce the internal complexity of the algorithmic structures. We ...