Results 111 to 120 of about 16,203 (295)

Forecasting of significant wave height using Long Short-Term Memory and Multivariate Variational Mode Decomposition

Journal of Education for Pure Science
 forecasting the height of the significant wave (SWH) accurately and reliably is crucial for maritime and engineering purposes. This work designs a novel deep learning system to forecast the daily significant wave height (SWH).
Hanaa Ibraheem, M. Abdalhadi
semanticscholar   +1 more source

Multivariate phase‐dependent optimization of bioprocesses boosts performance and quality—Why timing (of exposure) matters

Biotechnology Progress, EarlyView.
Abstract Applying a single parameter set to describe complex mammalian kinetics often is too simplistic, as it fails to capture sensitive cell‐to‐environment interactions that may be exploited to optimize production performance. To resolve this time dependency, intra‐experimental parameter shifts as part of design of dynamic experiments (DoDE) can be ...
Samuel Kienzle, Lisa Junghans, Anja Wittmann, Stefan Wieschalka, Ralf Takors, Nicole Erika Radde, Beate Presser, Verena Nold   +7 more
wiley   +1 more source

Early fault diagnosis of transformer windings based on the improved MVMD-ELM

Frontiers in Energy Research
Aiming at the problems of weak early fault characteristics of transformer windings, large noise interference and insufficient accuracy of traditional diagnostic methods, this paper proposes an early fault diagnosis method for transformer windings based ...
Qiuyang Lin, Congwei Wang, Luyi Zhang, Fengping Zhang, Zichi Zhao, Minyi Wei, Jiaqi Liu, Cheng Li   +7 more
doaj   +1 more source

The Use of EEG Signals For Biometric Person Recognition [PDF]

, 2015
This work is devoted to investigating EEG-based biometric recognition systems. One potential advantage of using EEG signals for person recognition is the difficulty in generating artificial signals with biometric characteristics, thus making the spoofing
Yang, Su
core  

Mechanistic deconvolution of BSA size variants by constrained Raman pseudo‐Voigt hard modeling during anion‐exchange chromatography

Biotechnology Progress, EarlyView.
Abstract In biopharmaceutical manufacturing, protein aggregation is a critical quality attribute, necessitating rapid and reliable analytical strategies during downstream processes like anion‐exchange chromatography (AEX). While Raman spectroscopy enables continuous monitoring of protein secondary structure, standard data‐driven regression models ...
Jakob Heyer‐Müller, Robin Schiemer, Lars Robbel, Michael Schmitt, Jürgen Hubbuch   +4 more
wiley   +1 more source

Denoising of CT and MRI Images Using Decomposition-Based Curvelet Thresholding and Classical Filtering Techniques

Applied Sciences
Medical image denoising is crucial for enhancing the diagnostic accuracy of CT and MRI images. This paper presents a modular hybrid framework that combines multiscale decomposition techniques (Empirical Mode Decomposition, Variational Mode Decomposition,
Mahmoud Nasr, Krzysztof Brzostowski, Rafał Obuchowicz, Adam Piórkowski   +3 more
doaj   +1 more source

Sex Prediction From the Clavicle Using Computerized Tomography Images via Traditional and Hybrid Deep Learning Models

Clinical Anatomy, EarlyView.
ABSTRACT The aim of this study is to perform high accuracy sex prediction from clavicle images using proposed hybrid deep learning models and traditional deep learning models. The clavicle of 807 female and 805 male individuals obtained from Computed Tomography were segmented in 3D format and saved in jpeg format as superior–inferior and right–left ...
Yusuf Secgin, Muhammet Cakmak, Deniz Senol, Seren Kaya, Oğuzhan Oztürk, Oğuzhan Harmandaoğlu, Hatice Yenigül, Eslem Yaren Bıyık, Omer Onbaş   +8 more
wiley   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

Carbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao, Fei Wang, Qixuan Cai, Aike Xi, Kangkang Wang, Khaixien Leu, Rufan Zhang   +6 more
wiley   +1 more source

Multiscale Functional Connectivity analysis of episodic memory reconstruction

Frontiers in Cognition
Our ability to share memories constitutes a social foundation of our world. When exposed to another person's memory, individuals can mentally reconstruct the events described, even if they were not present during the related events.
Manuel Morante, Kristian Frølich, Muhammad Shahzaib, Sadia Shakil, Naveed ur Rehman   +4 more
doaj   +1 more source

Engineering Biochar‐Derived Functional Materials for High‐Performance Supercapacitors: Design Principles, Mechanisms, and Scalable Strategies

Carbon Energy, EarlyView.
ABSTRACT Biochar has emerged as a useful and adaptable source of carbon for supercapacitor electrodes. Its value comes from the way biomass chemistry, thermal conversion, and activation conditions shape the resulting pore network, surface groups, and degree of carbon ordering.
Soumen Mandal, Avinash C. Mendhe, Mayna Roy, Neha S. Barse, Taejoon Park, Han‐Seung Lee, Haigun Lee   +6 more
wiley   +1 more source