Optimizing photovoltaic power prediction at extreme altitudes using stacking metamodels and dimensionality reduction. [PDF]
Huaquipaco S +9 more
europepmc +1 more source
Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling +4 more
wiley +1 more source
Benchmarking of dimensionality reduction methods to capture drug response in transcriptome data. [PDF]
Kwon Y, Park S, Park S, Lee H.
europepmc +1 more source
Objective Our objective was to describe the social networks of Black individuals with rheumatic and musculoskeletal conditions and understand the clustering of health‐related behaviors to inform future community‐based, peer‐led interventions. Methods We used an adapted Personal Network Survey for Clinical Research (PERSNET) to map the personal social ...
Taussia Boadi +27 more
wiley +1 more source
Evaluating Dimensionality Reduction for Patient-Reported Outcome-Based Survival Modeling in Patients With Head and Neck Cancer. [PDF]
Anyimadu EA +6 more
europepmc +1 more source
Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane +3 more
wiley +1 more source
EncoderMap III: A Dimensionality Reduction Package for Feature Exploration in Molecular Simulations. [PDF]
Sawade K, Lemke T, Peter C.
europepmc +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Dimensionality reduction of COSMO-RS molecular descriptor using functional principal component analysis (FPCA) for organic solvent mapping. [PDF]
Ramirez Cardenas LE +4 more
europepmc +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source

