Dimensionality reduction techniques like PCA work wonderfully when datasets are linearly separable—but they break down the moment nonlinear patterns appear. That’s exactly what happens with datasets ...
For students enrolled Spring 2026 and beyond. The Big Data and Applied AI option reflects the growing role of artificial intelligence in business decision-making. It provides students with rigorous ...
ABSTRACT: Pyrethrum (Chrysanthemum cinerariaefolium L.) is an industrial crop with complex morphology and diverse physico-mechanical properties that jeopardize the optimal design of precision ...
Abstract: Centralization is indispensable to covariance-based multivariate statistical process monitoring (MSPM) methods, such as principal component analysis (PCA) and canonical correlation analysis ...
Artificial intelligence has developed rapidly in recent years, with tech companies investing billions of dollars in data centers to help train and run AI models. The expansion of data centers has ...
MathWorks, a leading developer of mathematical simulation and computing software, revealed that a ransomware gang stole the data of over 10,000 people after breaching its network in April. The company ...
Background/objectives: Dietary patterns play an important role in regulating serum uric acid (SUA) levels in the body. Recently, compositional data analysis (CoDA) has been proposed as an alternative ...
Database Trends & Applications is excited to bring our community of data professionals together this May 13 - 15 in Boston for 3 days of practical advice, inspiring thought leadership, and in-depth ...
Analyst Insight: The evolving use of data analytics is helping companies achieve supply chain sustainability objectives in the areas of forecasting, transportation and packaging. Sustainability ...
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