Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

A University of Houston professor has taken on the global challenge of reducing the staggering amount of heat generated in artificial intelligence data centers. Hadi Ghasemi, J. Willard Gibbs ...

Sophelio Introduces the Data Fusion Labeler (dFL) for Multimodal Time-Series Data - The only labeling and harmonization studio built for multimodal time-series with full provenance you can replay “dFL ...

This study utilized hyperspectral technology in conjunction with chemometric methods for the non-destructive assessment of chilled meat quality. Average spectra were extracted from regions of interest ...

Abstract: Flow cytometry is an advanced technique for analyzing cellular heterogeneity in biomedical research and clinical diagnostics. Its ability to generate multiparametric data has facilitated ...

Maritime cargo capacity serves as a critical indicator of port efficiency and regional economic impact, yet reliable data remain constrained by operational and commercial complexities. This study ...

The adoption of analytical techniques is revolutionizing operations, especially in enhancing efficiency and reducing costs.

The world as we know it has been transformed by AI, but perhaps no field has been more profoundly affected than analytics and data science. While traditional data science practices have paved the way ...

Abstract: Preprocessing methods are important in enhancing prediction performance for time-series administrative data. This study underscores the importance of preprocessing methods by comparing two ...