Staffing & Scheduling

Multilayer redox-based HfO/AlO/TiO memristive structures for neuromorphic computing.

Redox-based memristive devices have shown great potential for application in neuromorphic computing ...

The gate injection-based field-effect synapse transistor with linear conductance update for online training.

Neuromorphic computing, an alternative for von Neumann architecture, requires synapse devices where ...

Orientation-Preserving Rewards' Balancing in Reinforcement Learning.

Auxiliary rewards are widely used in complex reinforcement learning tasks. However, previous work ca...

FAPNET: Feature Fusion with Adaptive Patch for Flood-Water Detection and Monitoring.

In satellite remote sensing applications, waterbody segmentation plays an essential role in mapping ...

Automation of generative adversarial network-based synthetic data-augmentation for maximizing the diagnostic performance with paranasal imaging.

Thus far, there have been no reported specific rules for systematically determining the appropriate ...

Editorial for "Gradual Self-Training via Confidence and Volume Based Domain Adaptation for Multi Dataset Deep Learning-Based Brain Metastases Detection Using Nonlocal Networks on MRI Images".

AI technologies: guidelines set out training requirements for NHS staff.

Learning Transferable Parameters for Unsupervised Domain Adaptation.

Unsupervised domain adaptation (UDA) enables a learning machine to adapt from a labeled source domai...

Association of artificial intelligence use and the retention of elderly caregivers: A cross-sectional study based on empowerment theory.

AIM: The purpose of this study is to investigate how the use of artificial intelligence is associate...

Conformal prediction under feedback covariate shift for biomolecular design.

Many applications of machine-learning methods involve an iterative protocol in which data are collec...

Towards Online Ageing Detection in Transformer Oil: A Review.

Transformers play an essential role in power networks, ensuring that generated power gets to consume...

Switchgear Digitalization-Research Path, Status, and Future Work.

To keep pace with global energy efficiency trends and, in particular, emission reduction targets in ...

Fast Explainable Recommendation Model by Combining Fine-Grained Sentiment in Review Data.

With the rapid development of e-commerce, recommendation system has become one of the main tools tha...

Virtual classroom proficiency-based progression for robotic surgery training (VROBOT): a randomised, prospective, cross-over, effectiveness study.

Robotic surgery training has lacked evidence-based standardisation. We aimed to determine the effect...

Emerging Computational Methods in Mass Spectrometry Imaging.

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds o...

sEMG-Based Gain-Tuned Compliance Control for the Lower Limb Rehabilitation Robot during Passive Training.

The lower limb rehabilitation robot is a typical man-machine coupling system. Aiming at the problems...

Data Center Traffic Prediction Algorithms and Resource Scheduling.

This paper uses intelligent methods such as a time recurrent neural network to predict network traff...

Training recurrent neural networks as generative neural networks for molecular structures: how does it impact drug discovery?

INTRODUCTION: Deep learning approaches have become popular in recent years in de novo drug design. G...

Acceleration of Deep Neural Network Training Using Field Programmable Gate Arrays.

Convolutional neural network (CNN) training often necessitates a considerable amount of computationa...

Legged locomotion over irregular terrains: state of the art of human and robot performance.

Legged robotic technologies have moved out of the lab to operate in real environments, characterized...

A deep-learning approach for automatically detecting gait-events based on foot-marker kinematics in children with cerebral palsy-Which markers work best for which gait patterns?

Neuromotor pathologies often cause motor deficits and deviations from typical locomotion, reducing t...