Results 161 to 170 of about 266,856 (351)

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Wind-Induced Clearances Infringement of Overhead Power Lines [PDF]

, 2014
Ali I. El Gayar, Zulkurnain Abdul‐Malek, Ibtihal Fawzi Elshami   +2 more
openalex   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

OPTIMIZATION OF FAULT INDICATORS SETTING FOR OVERHEAD POWER LINES MONITORING

, 2017
І.В. Блінов, Ievhen V. Parus, Serhii Ie. Tankevych   +2 more
openalex   +2 more sources

DEPLOYMENT CONCEPTS FOR OVERHEAD HIGH VOLTAGE BROADBAND OVER POWER LINES CONNECTIONS WITH TWO-HOP REPEATER SYSTEM: CAPACITY COUNTERMEASURES AGAINST AGGRAVATED TOPOLOGIES AND HIGH NOISE ENVIRONMENTS [PDF]

, 2012
Αθανάσιος Λαζαρόπουλος
openalex   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source

Mitigation of inductive coupling effects on buried pipelines using gradient control conductors of overhead line configuration and hippopotamus optimization algorithm. [PDF]

Sci Rep
Hachani K, Bachir B, Rabah D, Bessedik SA, El-Sehiemy RA.   +4 more
europepmc   +1 more source

Determination of Power Supply System for Low Voltage Single Phase Electric Consumers of Overhead Power Lines 220/380 V

, 2021
Yu. F. Romaniuk, Oleg Solomchak, B. L. Grabchuk, O. I. Savchyn   +3 more
openalex   +2 more sources

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source

Using synthetic data for pretraining partial discharge detection in overhead transmission lines. [PDF]

Sci Rep
Klein L, Fulneček J, Kabot O, Dvorský J, Prokop L.   +4 more
europepmc   +1 more source