Results 171 to 180 of about 8,736,056 (314)
Enhancing Supply Chain Efficiency: Demand Forecasting Using Deep Learning Techniques
reservedDemand forecasting is a critical component of supply chain management, essential for optimizing inventory levels, reducing costs, and enhancing customer satisfaction .This study tries to enhance the efficiency of supply chain by accurate demand ...
AHMADIESLAMLOO, ELAHEH
core
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
Patients improve, patterns persist: longitudinal stability of RA joint involvement patterns
Objective Rheumatoid arthritis is a heterogeneous disease. Data‐driven approaches, from synovial histology to joint involvement patterns (JIPs), have sought to define clinically meaningful subgroups. Whether these subgroups represent stable phenotypes or transient disease states remains unclear.
Tjardo Maarseveen +24 more
wiley +1 more source
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck +10 more
wiley +1 more source
Deep learning approaches for preprocessing and analysis of neuroimaging data
openIn the last decade, human neuroscience has been profoundly impacted by the appearance of large, publicly available databases comprising neuroimaging data of hundreds to thousands of participants.
WATHTHE LIYANAGE, WAGEESHA WIDURANGA
core
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +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
Audio Signal Analysis using Deep Learning
reservedGoal of the work is to develop and improve a tool for automated Transcription of Audiosignals using deep learning techniques. Approaches should be used which restrict the output to a predefined vocabulary.
HOETH, MAX HENNING
core
Relationship of Physical Activity Type, Nutrition, and Bone Mineral Density in Korean Adolescents
Bone density reaches its peak in the mid-20s, and it manifests as osteoporosis and osteopenia with aging. Bone density is affected by body mass index, muscle mass, nutritional calcium and vitamin D, various lifestyles, physical activity level, and high ...
Yong Hwan Kim +2 more
doaj
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source

