AZoM on MSN

Imaging silicon defects using Raman and PL multivariate imaging

PCA and K-means clustering applied to Raman and PL imaging reveal structural defects in silicon wafers, enhancing understanding of optoelectronic performance.
Open Heart

Artificial intelligence-based clustering to identify functional risk phenotypes in heart failure

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
IEEE

Frequency hopping patterns design based on objective optimization algorithm

Abstract: Frequency hopping (FH) is a classical anti-jamming technique widely used in military and civil communication. Differential FH and cognitive FH ensure communication reliability by the ...
GitHub

Fashion-MNIST Unsupervised Clustering

PCA + MiniBatch KMeans offers a strong trade-off between performance and computational cost. SAE + DBSCAN produces high-quality clusters but requires significantly more training time. Visual ...
IEEE

Investigation on PCA and LDA Feature Extraction Algorithms with KNN Classifier Targetting to Improve Diagnostic Accuracy into Detection of Breast Cancer Malignancy

Abstract: This work aims to compare two different Feature Extraction Algorithms (FEAs) viz. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), using a K-Nearest Neighbor (KNN) ...
Searchenginejournal.com

Google Begins Rolling Out March Core Algorithm Update

Google has officially begun rolling out its March 2025 core algorithm update, according to an announcement posted to the Google Search Status Dashboard today. The update commenced at 9:23 AM PDT and ...
Scientific Research Publishing

Lin, J. and He, J. (2022) Parallel Random Forest Prediction Algorithm Based on PCA Stratified Sampling in the Big Data Environment. China Management Informationization, 25, 172 ...

ABSTRACT: To improve the efficiency of air quality analysis and the accuracy of predictions, this paper proposes a composite method based on Vector Autoregressive (VAR) and Random Forest (RF) models.
Frontiers

Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models

Our findings suggest that, while PD is generally associated with a larger DAT deficit in specific brain structures of the neostriatum, it exhibits intrinsic heterogeneity across individuals, which may ...