Results 81 to 90 of about 129,562 (262)

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

Fairness-Aware Hyperparameter Optimization

, 2020
In recent years, increased usage of machine learning algorithms has been accompanied by several reports of machine bias in areas from recidivism assessment, to job-applicant screening tools, and estimating mortgage default risk. Additionally, recent advances in machine learning have prominently featured so-called "black-box" models (e.g.
openaire   +2 more sources

Adaptive Optimizer for Automated Hyperparameter Optimization Problem

, 2022
The choices of hyperparameters have critical effects on the performance of machine learning models. In this paper, we present a general framework that is able to construct an adaptive optimizer, which automatically adjust the appropriate algorithm and parameters in the process of optimization.
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

Liquid Metal Sensors for Soft Robots

Advanced Robotics Research, EarlyView.
This review thoroughly reviews liquid metal sensors in soft robots. Their unique material properties like high conductivity and good biocompatibility are analyzed. Working principles are classified, and applications in environmental perception, motion detection, and human—robot interaction are introduced.
Qi Zhang, Nan Li, Yujia Song, Chen Hua, Tangzhen Guan, Yibing Ma, Cai Cheng, Jing Liu   +7 more
wiley   +1 more source

MTMEGPS: An R package for multi-trait and multi-environment genomic and phenomic selection using deep learning

Frontiers in Plant Science
Genomic and phenomic selection have transformed modern breeding by enabling data-driven prediction of complex traits. Deep learning (DL) can further enhance predictive ability by capturing nonlinear patterns that classical and Bayesian approaches often ...
Freddy Mora-Poblete, Javiera Valenzuela-Herrera, Matías Balach, Claudio J. Martínez-Araya, Carlos Maldonado   +4 more
doaj   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Hyperparameters optimization of evolving spiking neural network using artificial bee colony for unsupervised anomaly detection

Journal of Intelligent Systems
Nowadays, anomaly detection in streaming data has gained considerable attention due to the exponential growth in the data gathered by Internet of Things applications. Analyzing and processing vast data volumes requires a system capable of working in real-
Rehan Rabie, Sahran Shahnorbanun, Alyasseri Zaid Abdi Alkareem, Sani Nor Samsiah, Al-Betar Mohammed Azmi   +4 more
doaj   +1 more source

Multi-Task Multicriteria Hyperparameter Optimization

, 2020
We present a new method for searching optimal hyperparameters among several tasks and several criteria. Multi-Task Multi Criteria method (MTMC) provides several Pareto-optimal solutions, among which one solution is selected with given criteria significance coefficients.
Akhmetzyanov, Kirill, Yuzhakov, Alexander   +1 more
openaire   +2 more sources

HPN: Personalized Federated Hyperparameter Optimization

, 2023
Numerous research studies in the field of federated learning (FL) have attempted to use personalization to address the heterogeneity among clients, one of FL's most crucial and challenging problems. However, existing works predominantly focus on tailoring models.
Cheng, Anda, Wang, Zhen, Li, Yaliang, Cheng, Jian   +3 more
openaire   +2 more sources