Results 141 to 150 of about 16,046 (295)

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Application of GAN–CNN in Risk Assessment of Pipeline Failures in Multiphase Pipeline With Image Information Encoding Approach

Energy Science &Engineering, EarlyView.
Field data from multiphase pipelines are transformed into grayscale images via Image Information Encoding, preserving feature values and interparameter relationships. A GAN–CNN model generates synthetic images that are decoded to expand the original database.
Sihang Chen, Na Zhang, Biyuan Shui
wiley   +1 more source

Do generative models learn rare generative factors?

Frontiers in Artificial Intelligence
Generative models are becoming a promising tool in AI alongside discriminative learning. Several models have been proposed to learn in an unsupervised fashion the corresponding generative factors, namely the latent variables critical for capturing the ...
Fasih Haider, Edward Moroshko, Yuyang Xue, Sotirios A. Tsaftaris   +3 more
doaj   +1 more source

A Review of Overcurrent Protection in Smart Grids Under Cyber‐Physical Threats With a Cyber‐Physical Evaluation Framework

Energy Science &Engineering, EarlyView.
By manipulating current and voltage measurements, an assailant can induce unwanted relay action while attempting to avoid detection. Detecting advanced cyber intrusions in power protection environments requires specialised data analysis and anomaly detection methods.
Feras Alasali, Anas AlMajali, Naser Naily, Hassen Loukil, Salah AbuGhalyon, William Holderbaum, Abdelaziz Salah Saidi   +6 more
wiley   +1 more source

Identifying Venous Insufficiency in Head and Neck Reconstruction Flaps Using Machine Learning and Deep Learning Methods

Head &Neck, EarlyView.
ABSTRACT Background Venous insufficiency is a major cause of flap failure in head and neck reconstruction. AI provides a reliable, convenient solution for early detection. Methods Clinical data and postoperative flap photos of head and neck cancer patients (2018–2024) at our center were retrospectively collected, categorized into normal and venous ...
Yurong He, Jugao Fang, Lizhen Hou, Zufei Li, Shizhi He, Yanming Zhao, Qijia Li, Rongjia Li, Xiaoyu Shi, Jiayi Yang, Qi Zhong   +10 more
wiley   +1 more source

Evaluating the impact of generative adversarial models on the performance of anomaly intrusion detection

IET Networks
With the increasing rate and types of cyber attacks against information systems and communication infrastructures, many tools are needed to detect and mitigate against such attacks, for example, Intrusion Detection Systems (IDSs).
Mohammad Arafah, Iain Phillips, Asma Adnane   +2 more
doaj   +1 more source

Progress of metabolomics‐centric multi‐omics research in medicine

iMetaOmics, EarlyView.
The graphical abstract illustrates a holistic roadmap for metabolomics‐centric multi‐omics integration in medical research. The upper panel depicts the technological transition from traditional bulk analysis to high‐resolution single‐cell and spatial methodologies, specifically addressing inherent challenges such as molecular complexity and dynamic ...
Ziyi Wang, Shiwen Deng, Xiaoxu Wang, Xiao Chang, Na Guo, Peng Chen, Hongjun Yang   +6 more
wiley   +1 more source

Optimizing Generative Adversarial Networks for Low Resolution Image Enhancement

, 2020
Our research focuses on optimizing the performance of Generative Adversarial Networks to increase image resolution through various methods and approaches.
Gonzalez, Maria, Hall, Justin
core  

Polymer informatics: Integrating data‐driven strategies, advanced machine learning, and automated synthesis for next‐generation polymer design

InfoScience, EarlyView.
Designing new polymers for applications such as sustainable plastics, biomaterials, and 3D printing has traditionally been slow and expensive, relying heavily on trial‐and‐error experiments. This review shows how polymer informatics—the integration of large polymer databases, machine‐learning models, and automated robotic synthesis—enables fast ...
Md. Saiful Islam, Tamanna Hoque, Junied Islam Shuvo, Sheta Roy Tori, Sadit Bihongo Malitha, Md. Zahangir Alam, A. M. Sarwaruddin Chowdhury   +6 more
wiley   +1 more source

Deep learning‐based prediction of cervical lymph node metastasis and genetic alterations from whole‐slide images of thyroid cancer frozen sections

Interdisciplinary Medicine, EarlyView.
Deep learning models accurately predict cervical lymph node metastasis and key genetic mutations (BRAF/TERT) directly from thyroid cancer frozen sections. This AI‐driven pipeline provides a rapid real‐time tool to guide intraoperative surgical decisions, helping to optimize surgical extent and prevent both over‐ and under‐treatment without the need for
Mingxing Qiu, Jinbang Li, Shujing Guo, Danyi Li, Chengyu Lu, Chenglong Zhao, Jiankun He, Hanxi Wang, Qiao Bai, Aihetaimu Aimaier, Zhijian Cen, Rui Mao, Zimo Ye, Jiaxue Zang, Zhining Zhuo, Lijuan Qu, Yueping Liu, Jing Cui, Xiaohong Yao, Xiuwu Bian, Li Liang   +20 more
wiley   +1 more source