Results 211 to 220 of about 25,210 (289)

Characteristics of Pulsed-Laser-Induced Layers with Cracks Prepared for SiC Grinding Processes. [PDF]

Materials (Basel)
Li H, Jiang Y, Yang Y, Yang J, Zhu L.
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Comparative evaluation of dry, wet, and minimum quantity lubrication (MQL) cooling strategies in the machining of GTD-450 martensitic stainless steel. [PDF]

Sci Rep
Dastgerdi HM, Bakhshayesh AM, Saberi M, Hajaliakbari A, Davoodi B, Niknam SA.   +5 more
europepmc   +1 more source

Multitarget Recognition of Flower Images Based on Lightweight Deep Neural Network and Transfer Learning

Advanced Intelligent Systems, EarlyView.
This article proposes a lightweight YOLOv4‐based detection model using MobileNetV3 or CSPDarknet53_tiny, achieving 30+ FPS and higher mAP. It also presents a ShuffleNet‐based classification model with transfer learning and GAN‐augmented images, improving generalization and accuracy.
Qingyang Liu, Yanrong Hu, Hongjiu Liu
wiley   +1 more source

Cross‐Modal Characterization of Thin‐Film MoS2 Using Generative Models

Advanced Intelligent Systems, EarlyView.
Cross‐modal learning is evaluated using atomic force microscopy (AFM), Raman spectroscopy, and photoluminescence spectroscopy (PL) through unsupervised learning, regression, and autoencoder models. Autoencoder models are used to generate spectroscopy data from the microscopy images.
Isaiah A. Moses, Chen Chen, Joan M. Redwing, Wesley F. Reinhart   +3 more
wiley   +1 more source

Multi-criteria decision analysis approach on parametric optimization of abrasive waterjet pocket milling in Ti-6Al-4V alloy. [PDF]

Sci Rep
Naresh Raj KL, Jayavelu S, Kumar MS, Kumar A, Swarna B.   +4 more
europepmc   +1 more source

Real‐Time, Label‐Free Classification of Cell Death Pathways via Holotomography‐Based Deep Learning Framework

Advanced Intelligent Systems, EarlyView.
A 3D holotomography system coupled with a deep learning model distinguishes how cells die—apoptosis, necroptosis or necrosis—without any fluorescent labels. Training on refractive index maps of HeLa cells yields 97% accuracy and flags necroptosis hours before chemical dyes.
Minwook Kim, Wei Sun Park, Geon Kim, Sanggeun Oh, Jaephil Do, Juyeon Park, Jihwan Yu, Won Do Heo, YongKeun Park   +8 more
wiley   +1 more source

The Influence of Operating Pressure Oscillations on the Machined Surface Topography in Abrasive Water Jet Machining. [PDF]

Materials (Basel)
Veljković DŽ, Baralić J, Janković P, Dučić N, Savković B, Jovičić A.   +5 more
europepmc   +1 more source

A Generalizable Transformer Framework for Gene Regulatory Network Inference from Single‐Cell Transcriptomes

Advanced Intelligent Systems, EarlyView.
FTGRN introduces an LLM‐enhanced framework for gene regulatory network inference through a two‐stage workflow. It combines a Transformer‐based model, pretrained on GPT‐4 derived gene embeddings and regulatory knowledge, with a fine‐tuning stage utilizing single‐cell RNA‐seq data.
Guangzheng Weng, Hyobin Kim, Patrick Martin, Junil Kim, Tae‐Hyung Kim, Gi‐Hoon Nam, Dongha Kim, Kyoung Jae Won   +7 more
wiley   +1 more source

A Multi-Response Investigation of Abrasive Waterjet Machining Parameters on the Surface Integrity of Twinning-Induced Plasticity (TWIP) Steel. [PDF]

Materials (Basel)
Cavusoglu O.
europepmc   +1 more source