Results 161 to 170 of about 708,932 (315)
Representing functional data in reproducing Kernel Hilbert Spaces with applications to clustering and classification [PDF]
Functional data are difficult to manage for many traditional statistical techniques given their very high (or intrinsically infinite) dimensionality. The reason is that functional data are essentially functions and most algorithms are designed to work ...
Alberto Muñoz, Javier González
core
AMINO ACID DIGESTIBILITIES OF PALM KERNEL MEAL IN POULTRY [PDF]
, 2008 Palm kernel meal (PKM) is produced in large quantities in many parts of the world. Problems associated with PKM are due to their high fibre content, imbalanced amino acid ratios, the possibility of Maillard products and their own physical ...
Kumar, A, Dingle, J, Sundu, B
core
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Kernel-Based Learning of Hierarchical Multilabel Classification Models [PDF]
, 2006 We present a kernel-based algorithm for hierarchical text classification where the documents are allowed to belong to more than one category at a time.
Szedmak, S. +3 more
core
Advanced Science, EarlyView.High‐throughput single‐cell analysis of resuscitating bacteria reveals a starvation‐history‐dependent transiently tolerant subpopulation that survives β$\beta$‐lactam exposure by temporarily reducing growth. Distinct from classical persisters, these actively growing yet dynamically modulated cells dominate survival across clinically relevant antibiotic
Kieran Abbott +5 more
wiley +1 more source
Sparse Kernel feature extraction [PDF]
, 2008 The presence of irrelevant features in training data is a significant obstacle for many machine learning tasks, since it can decrease accuracy, make it harder to understand the learned model and increase computational and memory requirements.
Dhanjal, Charanpal
core
Advanced Science, EarlyView.This review explains how chronic liver injury progresses toward hepatocellular carcinoma through interconnected changes in gut microbes, metabolism, immunity, fibrosis, and diet. It highlights microbial metabolites, bile‐acid signaling, immune dysfunction, and nutritional or microbiome‐based interventions as opportunities to identify risk earlier ...
Yi Hu +5 more
wiley +1 more source
VALUE OF INCREASING KERNEL UNIFORMITY [PDF]
Kernel uniformity is an important quality attribute that can now be measured at low cost. This study analyzes the profitability of sorting to increase wheat kernel uniformity.
Yoon, Byung-Sam +2 more
core +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
SERS Facemask for Rapid and Portable Sensing Mycobacterium Tuberculosis Antigens for TB Screening
Advanced Science, EarlyView.Our study introduced an Au─Ag embedded covalent organic framework (U@COF) ‐mediated facemask for sensing TB antigen ESAT‐6/CFP‐10 complex in clinical droplet samples toward TB screening. Practical analysis of clinical samples demonstrated the availability of our facemask, which is capable of identifying the TB subjects (N = 17) from healthy candidates (
Lingzhi Chen +20 more
wiley +1 more source