Results 41 to 50 of about 2,097 (259)
Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
Support Resistance Levels towards Profitability in Intelligent Algorithmic Trading Models
Past studies showed that more advanced model architectures and techniques are being developed for intelligent algorithm trading, but the input features of the models across these studies are very similar.
Jireh Yi-Le Chan +3 more
doaj +1 more source
Global Rather Than Vertical‐Selective Saccadic Abnormalities in Progressive Supranuclear Palsy
ABSTRACT Objective To test whether vertical saccades are preferentially affected in Progressive Supranuclear Palsy (PSP). Methods PSP patients (n = 24) were compared to age‐matched controls (n = 94) and two degenerative groups (Alzheimer's disease, n = 20; Lewy body disease, n = 50).
Duy Duan Nguyen +6 more
wiley +1 more source
This study investigates the integration of machine learning techniques with multi-indicator strategies in algorithmic trading to overcome the limitations of traditional trading methods.
Narongsak Sukma, Chakkrit Snae Namahoot
doaj +1 more source
From trading to technical trading, algorithmic trading and HFT trading
Let us go back a little bit and try to look at this phenomenon in the context of the current situation. Financial markets, particularly stock markets, stimulate buying and selling of financial instruments - contracts that give a right for a gradual withdrawal of funds. Different players can be involved in these markets at different times.
openaire +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
Applying Deep Reinforcement Learning to Algorithmic Trading
At the moment, there is a large volume of literature on exchange trading. Obviously, every year the mathematical base of work is becoming more complicated along with an increase in computing power, machines can process more metrics from year to year and ...
Petr Nikitin +3 more
doaj +1 more source
Data Science in Finance: Challenges and Opportunities
Data science has become increasingly popular due to emerging technologies, including generative AI, big data, deep learning, etc. It can provide insights from data that are hard to determine from a human perspective.
Xianrong Zheng +4 more
doaj +1 more source
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
Algorithmic setups for trading popular U.S. ETFs
In this research, we test whether common trading oscillators can outperform the buy-and-hold strategy (B&H) using six popular ETFs for the period of the last 20 years.
Gil Cohen
doaj +1 more source

