Results 111 to 120 of about 434,301 (280)

A novel caputo fractional model for english language learning: Analysis and simulation with bayesian regularization approach

MethodsX
In this paper, a new Caputo discrete fractional model is introduced to capture the dynamics of English language learning. This model creates a strong foundation for examining language acquisition behaviors by including the learning process within the ...
Maria, Aqsa Zafar Abbasi, Muhammad Asif Zahoor Raja, Kottakkaran Sooppy Nisar, Muhammad Shoaib   +4 more
doaj   +1 more source

The Bayesian iterated learning model

Abstract The Bayesian iterated learning model (BILM) provides a computational and mathematical solution to the problem of how learners’ biases causally affect the evolution of culturally transmitted information. Early simulations of language evolution found that learning biases could affect the evolution of linguistic structure, however,
openaire   +1 more source

Design of Single‐Atom Nanozymes for Precision Treatment of Erectile Dysfunction with Integrated Single‐Cell RNA Sequencing and Machine Learning

Advanced Science, EarlyView.
It is innovatively utilized single‐cell RNA sequencing to explore the underlying causes of diabetes mellitus‐induced erectile dysfunction, followed by machine learning‐driven design of a single‐atom nanozyme (Fe‐DMOF) for precision treatment of erectile dysfunction.
Xiang Zhou, Xi Zhang, Sihan Chen, Mengchi Yu, Yilan Hu, Chi Gan, Xianghu Meng, Long Li, Ninghong Song   +8 more
wiley   +1 more source

Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches

Scientific Reports
Deep learning-based medical image analysis has shown strong potential in disease categorization, segmentation, detection, and even prediction. However, in high-stakes and complex domains like healthcare, the opaque nature of these models makes it ...
Mohsin Akram, Muhammad Adnan, Syed Farooq Ali, Jameel Ahmad, Amr Yousef, Tagrid Abdullah N. Alshalali, Zaffar Ahmed Shaikh   +6 more
doaj   +1 more source

Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design

Advanced Science, EarlyView.
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang, Depeng Kong, Zhiao He, Jikai Liang, Yuyao Lu, Zikang Deng, Honghe Li, Mengke Wang, M. Jamal Deen, Zhiqiu Ye, Shuyao Zhou, Huayong Yang, Honghao Lyu, Jun Chen, Kaichen Xu, Geng Yang   +15 more
wiley   +1 more source

Emulating clinician-assigned diagnostic patterns of Alzheimer's disease in a tertiary neurology hospital using interpretable Bayesian machine learning

Journal of Alzheimer's Disease Reports
Background Accurate differentiation of Alzheimer's disease (AD) from other causes of cognitive impairment remains a major challenge, particularly in low- and middle-income countries where access to advanced biomarkers such as positron emission tomography
Ehsan Ahmed, Azizur Rahman, Abdullah Yusuf, Mohammad Sayeed Hassan, Adneen Moureen, Mohammad Nur Uddin, Maliha Hakim   +6 more
doaj   +1 more source

Sustainable Materials Design With Multi‐Modal Artificial Intelligence

Advanced Science, EarlyView.
Critical mineral scarcity, high embodied carbon, and persistent pollution from materials processing intensify the need for sustainable materials design. This review frames the problem as multi‐objective optimization under heterogeneous, high‐dimensional evidence and highlights multi‐modal AI as an enabling pathway.
Tianyi Xu, Tianshuo Wei, Yan Ge, Bo Peng, Yue Li, Maolin Wang, Peng Wen, Chao Yang, Ye Wei   +8 more
wiley   +1 more source

In Situ Polymerized Composite Electrolytes for High‐Performance Solid‐State Lithium Batteries: A Review

Advanced Science, EarlyView.
This review systematically explores the recent advances in in situ polymerized composite polymer electrolytes (CPEs) for solid‐state lithium batteries. It covers the fundamentals of reaction mechanisms, monomer chemistry, and their impact on interfacial stability, ionic conductivity, and electrochemical performance.
Jialin Li, Yufen Yan, Xiaoju Wang, Yuhui Huang, Zhen Huang, Lingjie Zhang, Ningzhong Bao, Zijian Hong, Yongjun Wu, Dali Ji   +9 more
wiley   +1 more source

Comparative evaluation of score criteria for dynamic Bayesian Network structure learning.

PLoS ONE
Dynamic Bayesian Networks (DBNs) are probabilistic models with a directional structure employed to model temporal processes. Three approaches to DBN structure learning are constraint-based, score-based, and hybrid.
Aslı Yaman, Mehmet Ali Cengiz
doaj   +1 more source

STAID: A Self‐Refining Deep Learning Framework for Spatial Cell‐Type Deconvolution with Biologically Informed Modeling

Advanced Science, EarlyView.
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu, Shuli Sun, Zhengliang Lv, Xinyu Liu, Yihua Wang, Bingqiang Liu   +5 more
wiley   +1 more source