Results 51 to 60 of about 11,209 (254)

An Efficient Index Building Algorithm for Selection of Aggregator Nodes in Wireless Sensor Networks

International Journal of Distributed Sensor Networks, 2014
In wireless sensor networks (WSNs), aggregator nodes perform the data aggregation process. Thus, careful selection of the aggregator nodes is needed to reduce network traffic in data aggregation process and prolong overall lifetime of the network.
Sun-Young Ihm, Aziz Nasridinov, Young-Ho Park   +2 more
doaj   +1 more source

Degradation Mechanism of Phosphate‐Based Li‐NASICON Conductors in Alkaline Environment

Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.
The presence of water in the cathode of a Li‐air battery shifts reactions to produce LiOH, creating a corrosive, alkaline environment. This study investigates the alkaline stability of the common Li‐NASICON solid‐state conductor chemistries through a systematic experimental study combined with computational modeling to understand the degradation ...
Benjamin X. Lam, Zhuohan Li, Tara P. Mishra, Gerbrand Ceder   +3 more
wiley   +1 more source

Design for Copying Grouser and Bionic Convex Hull Patterns on Track Surfaces of Crawler Combine Harvesters

Agriculture
In the rainy season, which often has uncertain rainfall, crawler combine harvesters have difficulty traversing wet and soft rice fields. A large amount of clay is often accumulated on the track surfaces, resulting in frequent slipping and sinking, which ...
Lulu Yuan, Zhong Tang, Sifan Liu, Ting Wang, Zhao Ding   +4 more
doaj   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Deephullnet: a deep learning approach for solving the convex hull and concave hull problems with transformer

International Journal of Digital Earth
Convex and concave hulls originating from computational geometry are widely applied in practice. For instance, to determine the boundaries of a geographical area within a group of cities, convex hulls can represent the approximate boundaries of the areas.
Haojian Liang, Shaohua Wang, Song Gao, Huilai Li, Cheng Su, Hao Lu, Xueyan Zhang, Xi Chen, Yinan Chen   +8 more
doaj   +1 more source

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

Advanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi, Kateryna Andriienkova, Tetyana Goldanova, Ezgi Antmen, Thibaut Soubrie, Nihal Engin Vrana   +5 more
wiley   +1 more source

Optimizing convex hull discovery: Introducing a quintuple-region algorithm with enhanced computational efficiency

Engineering Science and Technology, an International Journal
This paper introduces a novel algorithm for computing the convex hull of a finite set of points in two-dimensional space. Unlike traditional methods, this algorithm strategically partitions the input set into five distinct regions, isolating interior ...
Fidan Nuriyeva, Hakan Kutucu
doaj   +1 more source

A Fast and Robust Support Vector Machine With Anti-Noise Convex Hull and its Application in Large-Scale ncRNA Data Classification

IEEE Access, 2019
Support vector machine (SVM) achieves successful classification performance with the application in non-coding RNA (ncRNA) data. With the rapid increase of the species and sizes of ncRNA sequences, several fast SVM methods based on data distribution and ...
Xiaoqing Gu, Tongguang Ni, Yiqing Fan
doaj   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source