Results 61 to 70 of about 1,735,174 (276)

A Supervised Machine Learning-Based Approach for Task Workload Prediction in Manufacturing: A Case Study Application

Machines
Predicting workload for tasks in manufacturing is a complex challenge due to the numerous variables involved. In small- and medium-sized enterprises (SMEs), this process is often experience-based, leading to inaccurate predictions that significantly ...
Valentina De Simone, Valentina Di Pasquale, Joanna Calabrese, Salvatore Miranda, Raffaele Iannone   +4 more
doaj   +1 more source

Real-time prediction of short-timescale fluctuations in cognitive workload

Cognitive Research, 2021
Human operators often experience large fluctuations in cognitive workload over seconds timescales that can lead to sub-optimal performance, ranging from overload to neglect.
Udo Boehm, Dora Matzke, Matthew Gretton, Spencer Castro, Joel Cooper, Michael Skinner, David Strayer, Andrew Heathcote   +7 more
doaj   +1 more source

AI‐Assisted Digital Single‐Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo‐Oxidative Damage in High‐Photon‐Flux Enzymology

Advanced Science, EarlyView.
Employing a digital single‐molecule activity tracker (dSMAT), this research demonstrates that high‐photon‐flux irradiation drives progressive oxidative scarring in polymerases. Unlike simple thermal denaturation, real‐time kinetic tracking dynamically visualizes enzymes degrading into multiple impaired subpopulations.
Anran Zheng, Qi Yang, Jinze Li, Fuqiang Ma, Xuefeng Wang, Zhen Guo, Chuanyu Li, Dongshu Li, Jia Yao, Zhiqi Zhang, Wei Zhang, Lianqun Zhou   +11 more
wiley   +1 more source

Multi-task Prediction of Patient Workload

CoRR, 2018
Developing reliable workload predictive models can affect many aspects of clinical decision making procedure. The primary challenge in healthcare systems is handling the demand uncertainty over the time. This issue becomes more critical for the healthcare facilities that provide service for chronic disease treatment because of the need for continuous ...
Mohammad Hessam Olya, Dongxiao Zhu, Kai Yang 0005   +2 more
openaire   +2 more sources

Anisotropic Memristive Switching in NbOCl2 Enabled by Directional Oxygen Ion Migration

Advanced Science, EarlyView.
This study investigates strongly orientation‐dependent memristive switching in anisotropic NbOCl2, observed exclusively along the in‐plane c‐axis. The switching originates from direction‐selective oxygen‐ion migration and vacancy propagation that modulate the Pd/NbOCl2 Schottky barrier, enabling short‐term plasticity.
Caokun Wang, Yun Ji, Sanchali Mitra, Yufei Shi, Haofei Zheng, Yee Sin Ang, Kah‐Wee Ang   +6 more
wiley   +1 more source

VTB-RTRRP: Variable Threshold Based Response Time Reliability Real-Time Prediction

IEEE Access, 2018
To provide high quality of network service, the response time reliability (RTR), the probability that the response time of a service is within the maximum allowable time determined by users, attracts researchers from both academic and industry. For those
Chong Jin, Rui Kang, Ruiying Li
doaj   +1 more source

Hydrogen‐Stabilized Self‐Rectifying Memristor Arrays for Reliable Multilevel Synapses in Transformer‐Based Keyword Spotting

Advanced Science, EarlyView.
A non‐filamentary self‐rectifying HfO2/TiOx resistive random‐access memory integrates H2 annealing with an incremental step pulse with verify algorithm to achieve stable and linear analog conductance modulation. The device enables low‐current 6‐bit multilevel operation while suppressing sneak current in crossbar arrays. Implemented in Transformer‐based
Seonjeong Lee, Seohyeon Ju, Won Joo Lee, Myounggon Kang, Sungjun Kim, Yoon Kim   +5 more
wiley   +1 more source

Deep Learning-Driven Workload Prediction and Optimization for Load Balancing in Cloud Computing Environment

Cybernetics and Information Technologies
Cloud computing revolutionizes as a technology that succeeds in serving large-scale user demands. Workload prediction and scheduling tend to be factors dictating cloud performance.
Karimunnisa Syed, Pachipala Yellamma
doaj   +1 more source

Performance Estimation and Ex Vivo Validation of Untethered Magnetic Robots in Soft Tissue

Advanced Science, EarlyView.
This study presents an empirical model that quantitatively predicts the step‐out frequency of screw‐type untethered magnetic robots (UMRs) in soft viscoelastic environments, including ex vivo brain tissue. By integrating key parameters into a dimensionless framework, the model enables estimation of robot performance across a range of biological ...
Leendert‐Jan W. Ligtenberg, Thijs J. van der Burg, Stijn Y. Kolkman, Santiago Saavedra Castano, David Fernandez Rivas, Anke Klingner, Roger M. L. M. Lomme, Lucas S. Joziasse, Dorothee Wasserberg, H. Remco Liefers, Doron Ben Ami, Udi Sadeh, Oded Shoseyov, Giulio Dagnino, Pascal Jonkheijm, Jurgen J. Fütterer, Stefano Stramigioli, J. Frank W. Nijsen, Michiel C. Warlé, Islam S. M. Khalil   +19 more
wiley   +1 more source

Profit-Efficient Elastic Allocation of Cloud Resources Using Two-Stage Adaptive Workload Prediction

Applied Sciences
Internet services are increasingly being deployed using cloud computing. However, the workload of an Internet service is not constant; therefore, the required cloud computing resources need to be allocated elastically to minimize the associated costs ...
Lei Li, Xue Gao
doaj   +1 more source