Results 121 to 130 of about 279,520 (289)

A Method of Semi-Supervised Learning using Siamese Neural Network for Disaster Monitoring on Philippine Social Media [PDF]

Philippine E-Journal for Applied Research and Development, 2019
Studies have shown the potential of social media as a valuable source of real-time information for disaster monitoring through machine learning. However, the scarcity of labeled data used for training, especially during the onset of a disaster event ...
Andrew T. Marges, Jaime M. Samaniego
doaj  

Atomic Layer Deposition in Transistors and Monolithic 3D Integration

Advanced Functional Materials, EarlyView.
Transistors are fundamental building blocks of modern electronics. This review summarizes recent progress in atomic layer deposition (ALD) for the synthesis of two‐dimensional (2D) metal oxides and transition‐metal dichalcogenides (TMDCs), with particular emphasis on their enabling role in monolithic three‐dimensional (M3D) integration for next ...
Yue Liu, Taoyu Zou, Cheng‐Yan Xu, Liang Zhen, Yang Li, Yong‐Young Noh   +5 more
wiley   +1 more source

SMS Spam Classifier Using Machine Learning

, 2023
The purpose of this research paper is to examine how machine learning techniques are used to identify whether a SMS is spam or not. The growth of mobile users has led to a dramatic increase in SMS and messages. Despite the fact that our idea of information channels are currently seen as spotless and reliable in many parts of the world on going data ...
openaire   +1 more source

Bioprinting Organs—Science or Fiction?—A Review From Students to Students

Advanced Healthcare Materials, EarlyView.
Bioprinting artificial organs has the potential to revolutionize the medical field. This is a comprehensive review of the bioprinting workflow delving into the latest advancements in bioinks, materials and bioprinting techniques, exploring the critical stages of tissue maturation and functionality.
Nicoletta Murenu, Camilla Mussoni, Mateo S. Andrade Mier, Paula Buettner, Nathaly Chicaiza‐Cabezas, Yi‐Yu Robin Dai, Jessica Faber, Maren Fiedler, Zan Lamberger, Xuen Jen Ng, Vanessa Moessler, Anna Rederer, Jonas Roeder, Sabrina Stecher, Katinka Theis, Jeanette Weigelt, Silvia Budday, Gregor Lang, Natascha Schaefer   +18 more
wiley   +1 more source

Computational Modeling Meets 3D Bioprinting: Emerging Synergies in Cardiovascular Disease Modeling

Advanced Healthcare Materials, EarlyView.
Emerging advances in three‐dimensional bioprinting and computational modeling are reshaping cardiovascular (CV) research by enabling more realistic, patient‐specific tissue platforms. This review surveys cutting‐edge approaches that merge biomimetic CV constructs with computational simulations to overcome the limitations of traditional models, improve ...
Tanmay Mukherjee, Mehdi Salar Amoli, Sarah Rezapourdamanab, Lama Rita El Shammas, Martin L. Tomov, Emilio A. Mendiola, Vahid Serpooshan, Reza Avazmohammadi   +7 more
wiley   +1 more source

Laser‐Assisted Processing and Modification of Bioactive Glasses: A Review

Advanced Healthcare Materials, EarlyView.
Laser technologies provide powerful tools to process and transform bioactive glasses for advanced biomedical applications. This review discusses laser‐matter interaction mechanisms, laser surface engineering, and laser‐assisted fabrication of scaffolds and nanofibers.
Antonio Riveiro, Mario González‐Quintas, Mónica Fernández‐Arias, Jesús del Val, Félix Quintero, Rafael Comesaña, Fernando Lusquiños, Julian R. Jones, Juan Pou   +8 more
wiley   +1 more source

Smart Catheters for Diagnosis, Monitoring, and Therapy

Advanced Healthcare Materials, EarlyView.
This study presents a comprehensive review of smart catheters, an emerging class of medical devices that integrate embedded sensors, robotics, and communication systems, offering increased functionality and complexity to enable real‐time health monitoring, diagnostics, and treatment. Abstract This review explores smart catheters as an emerging class of
Azra Yaprak Tarman, Samiha Ahmed, Majed Othman Althumayri, Megan Guy, Darlenne Chavez Lugo, Frances S. Ligler, George T. Ligler, Rahmi Oklu, Hiroshi Kawahira, Michael J. McShane, Jun Kameoka, Jonathan Bova, Hatice Ceylan Koydemir   +12 more
wiley   +1 more source

Redefining Therapies for Drug‐Resistant Tuberculosis: Synergistic Effects of Antimicrobial Peptides, Nanotechnology, and Computational Design

Advanced Healthcare Materials, EarlyView.
Antimicrobial peptide (AMP)‐loaded nanocarriers provide a multifunctional strategy to combat drug‐resistant Mycobacterium tuberculosis. By enhancing intracellular delivery, bypassing efflux pumps, and disrupting bacterial membranes, this platform restores phagolysosome fusion and macrophage function.
Christian S. Carnero Canales, Jessica Ingrid Marquez Cazorla, Renzo Marianito Marquez Cazorla, Aline Martins dos Santos, Jonatas Lobato Duarte, Letícia Oliveira Catarin Nunes, Túlio Custódio Reis, Lara Cerazi Salvador, Norival Alves Santos‐Filho, Rafael Miguel Sábio, Hélder A. Santos, Fernando Rogério Pavan   +11 more
wiley   +1 more source

Machine learning-based discovery of informative SNPs for population assignment through whole genome sequencing

BMC Genomics
Background Whole-genome sequencing (WGS) data contain a large proportion of genetic information for farm animals, while machine learning algorithms offer a powerful approach for discovering population-informative genetic markers for population assignment.
Hui Liang, Yugang He, Jingfang Si, Xin Su, Xue Wang, Huaming Mao, Yi Zhang   +6 more
doaj   +1 more source

Classifying astronomical sources with machine learning

, 2022
More than 4 million astronomical sources extracted from the Sloan Digital Sky Survey catalog have been used to train a set of machine learning models, selected with a benchmarking program, in order to identify the best basic classifier of astronomical sources for future observations. We have also applied different filters to our dataset that modify its
openaire   +1 more source