Results 131 to 140 of about 969,371 (282)

Machine learning for multi-omics data integration in crop improvement: a systematic review. [PDF]

BMC Bioinformatics
Tsega A, Mullualem D.
europepmc   +1 more source

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

Machine Learning Prediction of BCS Superconductors without BCS Theory. [PDF]

ACS Omega
Rhone TD, Sheils D, Krockenberger Y.
europepmc   +1 more source

Game Theory Meets Computational Learning Theory (Dagstuhl Seminar 17251)

, 2017
his report documents the program and the outcomes of Dagstuhl Seminar 17251 "Game Theory Meets Computational Learning Theory". While there have been many Dagstuhl seminars on various aspects of Algorithmic Game Theory, this was the first one to focus on the emerging field of its intersection with computational learning theory.
Goldberg, Paul W., Mansour, Yishay, Dütting, Paul   +2 more
openaire   +2 more sources

Microfluidic Hydroporation Platform for Effective Allogeneic CAR‐T Cell Production and Subsequent Functional Cytotoxicity Analysis

Advanced Materials Technologies, EarlyView.
The hydroporator platform employs controlled hydrodynamic deformation for efficient mRNA and CRISPR/Cas9 delivery into primary human T cells, enabling allogeneic CAR‐T cell manufacturing. It preserves cell functionality and drives potent gene editing, CAR expression, and tumor cytotoxicity, while feature‐based analysis links these functional outcomes ...
Soohyun Jeon, Sein Kim, Hyun‐Young Kim, Duck Cho, Sungsu Park, Seohyun Kim, Aram J. Chung   +6 more
wiley   +1 more source

Stable approach based diagonal recurrent quantum neural networks for identification of nonlinear systems. [PDF]

Sci Rep
Khalil H, Elshazly O, Shaheen O.
europepmc   +1 more source

Introduction: Special issue on computational learning theory [PDF]

Machine Learning, 1990
openaire   +2 more sources

Recent Advances of Slip Sensors for Smart Robotics

Advanced Materials Technologies, EarlyView.
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang, Liao Wu, Shuai He, Zhao Sha, Yuwan Huang, Shuying Wu, Dewei Chu, Chun H. Wang, Shuhua Peng   +8 more
wiley   +1 more source

Interpretable deep learning reveals distinct spectral and temporal drivers of perceived musical emotion. [PDF]

Sci Rep
Gu Y, Shao C, Li J, Fan Y.
europepmc   +1 more source

Fabric‐Based Wearable Robotic Exoskeleton Gloves: Advancements and Challenges

Advanced Materials Technologies, EarlyView.
This review highlights interdisciplinary technological advances in fabric‐based robotic gloves, focusing on progress in design, fabrication, actuation, sensing, control, and power and energy requirements. It also addresses performance testing and validation, including biomechanical, strength, functional, user experience, and durability assessments, to ...
Ayse Feyza Yilmaz, Gökhan Ince, Ozgur Atalay   +2 more
wiley   +1 more source