Results 81 to 90 of about 610,735 (230)

Congestion Control Prediction Model for 5G Environment Based on Supervised and Unsupervised Machine Learning Approach

IEEE Access
With the emergence of 5G technology, congestion control has become a vital challenge to be addressed in order to have efficient communication. There are several congestion control models that have been proposed to control and predict the possible ...
Mohammed B. Alshawki, Ihab Ahmed Najm, Alaa Khalaf Hamoud   +2 more
doaj   +1 more source

Meniscus Pixel Printing for Contact‐Lens Vision Sensing and Robotic Control

Advanced Functional Materials, EarlyView.
A visual‐sensing contact lens is enabled by meniscus pixel printing (MPP), which rapidly patterns a 200 µm perovskite photodetector pixel in 1 s without masks, vacuum processing, or bulky equipment. A deep‐learning‐based super‐resolution reconstructs sparse on‐lens signals into 80 × 80 high‐resolution visual information, while AI‐driven eye‐tracking ...
Byung‐Hoon Gong, Dohyean Kim, Jiyun Jeong, Taekyeong Kim, Soon‐sung Kwon, Junyoung Seo, Il Jeon, Im Doo Jung   +7 more
wiley   +1 more source

Prediction of Creep Rupture Life of 5Cr-0.5Mo Steel Using Machine Learning Models

Metals
The creep rupture life of 5Cr-0.5Mo steels used in high-temperature applications is significantly influenced by factors such as minor alloying elements, hardness, austenite grain size, non-metallic inclusions, service temperature, and applied stress. The
Muhammad Ishtiaq, Hafiz Muhammad Rehan Tariq, Devarapalli Yuva Charan Reddy, Sung-Gyu Kang, Nagireddy Gari Subba Reddy   +4 more
doaj   +1 more source

Amyloidogenic Peptide Fragments Designed From Bacterial Collagen‐like Proteins Form Hydrogel

Advanced Functional Materials, EarlyView.
This study identified amyloidogenic sequence motifs in bacterial collagen‐like proteins and exploited these to design peptides that self‐assemble into β‐sheet fibers and form hydrogels. One hydrogel supported healthy fibroblast growth, showing promise for biocompatible materials. Our work demonstrates that bacterial sequences can be harnessed to create
Vamika Sagar, Xuen J Ng, Lukas Lechel, Ashish Chand Rajwar, Hendrik Bargel, Abhishek A. Jalan   +5 more
wiley   +1 more source

AI without borders: The rise of cross-disciplinary machine learning

Telematics and Informatics Reports
This literature review thoroughly analyzes Machine Learning (ML) algorithms, their applications in many fields, current developments, and interdisciplinary viewpoints.
Aji Prasetya Wibawa, Roni Herdianto, Anik Nur Handayani, Agung Bella Putra Utama, Aripriharta, Felix Andika Dwiyanto, Rafal Drezewski   +6 more
doaj   +1 more source

Engineering Strategies for Stable and Long‐Life Alkaline Zinc‐Based Flow Batteries

Advanced Functional Materials, EarlyView.
Alkaline zinc‐based flow batteries face persistent challenges from unstable zinc deposition, including dendrite growth, passivation, corrosion, and hydrogen evolution, which severely limit cycling stability. Current research addresses these issues through coordinated electrode structuring, electrolyte regulation, and membrane design to control zinc ...
Yuran Bai, Xiaoyu Huo, Xin Long, Enkang Fu, Xusong Gong, Lei Wei, Liang An   +6 more
wiley   +1 more source

ML-NIC: accelerating machine learning inference using smart network interface cards

Frontiers in Computer Science
Low-latency inference for machine learning models is increasingly becoming a necessary requirement, as these models are used in mission-critical applications such as autonomous driving, military defense (e.g., target recognition), and network traffic ...
Raghav Kapoor, David C. Anastasiu, Sean Choi   +2 more
doaj   +1 more source

Single‐ and Dual‐Atom Configurations in Atomically Dispersed Catalysts for Lithium–Sulfur Batteries

Advanced Functional Materials, EarlyView.
Single‐atom and dual‐atom‐based atomically dispersed catalysts (ADCs) effectively address the shuttle effect and sluggish redox kinetics in Li–S batteries. With nearly 100% atomic utilization and tunable coordination environments, ADCs enhance LiPSs adsorption, lower conversion barriers, and accelerate sulfur redox reactions.
Haoyang Xu, Zhenfeng Li, Yue Fei, Ali Mohammadi, Ge Li   +4 more
wiley   +1 more source

Multi‐Scale Interface Engineering of MXenes for Multifunctional Sensory Systems

Advanced Functional Materials, EarlyView.
MXenes, as two‐dimensional transition metal carbides and nitrides, demonstrate remarkable capabilities for multifunctional sensing applications. This review systematically examines multi‐scale interface engineering approaches that enhance sensing performance, enable diverse detection functionalities, and improve system‐level compatibility in MXene ...
Jiaying Liao, Sin‐Yi Pang, Jianhua Hao
wiley   +1 more source

Comparative assessment of rainfall-based water level prediction using machine learning (ML) techniques

Ain Shams Engineering Journal
Machine learning (ML) techniques are rapidly emerging as effective tools in predicting complex hydrological processes. The present study aims to comparatively assess the efficacy of four machine learning algorithms – Multi-Layer Perceptron (MLP), Extreme
Azazkhan Ibrahimkhan Pathan, Lariyah Bte Mohd Sidek, Hidayah Bte Basri, Muhammad Yusuf Hassan, Muhammad Izzat Azhar Bin Khebir, Siti Mariam Binti Allias Omar, Mohd Hazri bin Moh Khambali, Adrián Morales Torres, Ali Najah Ahmed   +8 more
doaj   +1 more source