Results 41 to 50 of about 2,973 (161)
Attainment Pairing Effects on Cognitive Conflict in Technology‐enhanced EFL Cooperative Tasks
International Journal of Applied Linguistics, Volume 36, Issue 2, Page 1594-1605, May 2026.ABSTRACT This study examines how attainment pairing (high‐high versus high‐low versus low‐low attainment) impacts English as a Foreign Language (EFL) learner engagement during technology‐enhanced cooperative writing tasks. Seventy‐eight Chinese university learners formed 39 dyads (13 pairs per group) via Tencent Meeting.
Ying Liu, Allen Thurston
wiley +1 more source
Off-policy Maximum Entropy Deep Reinforcement Learning Algorithm Based on RandomlyWeighted Triple Q -Learning [PDF]
, 2022 Reinforcement learning is an important branch of machine learning.With the development of deep learning,deep reinforcement learning research has gradually developed into the focus of reinforcement learning research.Model-free off-policy deep ...
FAN Jing-yu, LIU Quan
core +1 more source
Rare Metals, Volume 45, Issue 2, February 2026.ABSTRACT The high accuracy in surface‐enhanced Raman scattering‐lateral flow immunoassays (SERS–LFIAs) is critical for reliable point‐of‐care testing (POCT) in clinical diagnostics. Conventional approaches are often affected by sampling variability and uneven distribution of immunoprobes, leading to unreliable signal fluctuations.
Shuai Zhao +9 more
wiley +1 more source
Research on optimization of data transmission strategies based on deep reinforcement learning [PDF]
Based on the theoretical framework of deep reinforcement learning, a hierarchical and progressive solution was proposed. Firstly, a heterogeneous data transmission architecture integrating edge computing nodes was constructed, and a multi-dimensional ...
FENG Jun +3 more
core +1 more source
Rare Metals, Volume 45, Issue 1, January 2026.ABSTRACT High‐entropy alloys (HEAs) have emerged as a transformative class of materials distinguished by their complex chemical compositions, unique microstructures, and remarkable mechanical and functional properties. Traditionally, the discovery and optimization of HEAs have relied on conventional methods, including trial‐and‐error experimentation ...
Chrispin Ouko Zamzu +2 more
wiley +1 more source
Research progress of causal inference in reinforcement learning framework(强化学习框架中因果推断研究进展)
Zhejiang Daxue xuebao. Lixue banCausal reasoning has been extensively studied in all fields of science. In recent decades, there have been a number of innovations in the development and implementation of methods aimed at determining causality.
刘华玲(LIU Hualing) +2 more
doaj +1 more source
大数据新闻推荐系统对新媒体新闻传播有着重要作用。提出了一种以深度强化学习为基础的推荐系统，旨在结合神经网络的表征能力和强化学习的策略选择能力来提升新闻推荐效果。使用动态动作掩码加强对用户短期兴趣的判断能力，使用优化缓存机制提升经验缓存的使用效率，通过区域遮蔽性质的奖励设计加快模型训练，从而提高推荐系统在新闻推荐领域的表现。实验表明，所提模型在新闻数据集上的推荐准确率与主流的神经网络推荐方法相当，且在排序性能上优于当前先进的推荐算法。
董相宏, 安俊秀
doaj +1 more source
智能科学与技术学报, 2022 当代系统认知、管理与控制的核心理论、方法与技术已经转移到大数据和人工智能技术上，这导致当前人工智能技术条件局限与复杂系统认知、管理、控制的需求之间形成了一道鸿沟。因此，现实的需求催生了人工智能的一种新型形态——人机混合增强智能形态，即人类智能与机器智能协同贯穿于系统认知、管理、控制等过程的始终，人类的认知和机器智能认知互相混合，形成增强型的智能形态，这种形态是人工智能或机器智能可行的、重要的成长模式。提出了一种物理-数据-知识混合驱动的人机混合增强智能系统管控方法。从可信分布式数据、计算和算法 ...
张俊 +12 more
doaj
International Journal of Urban and Regional Research, Volume 50, Issue 1, Page 191-220, January 2026.Abstract Henry George advocated for capturing land value increases for public ends. The active approach of public authorities organizing and financing land development can help capture higher land value increases, as Hartman and Spit indicate. However, this approach hardly happens in developing countries, where the coalition of private developers and ...
Nannan Xu
wiley +1 more source
Dianxin kexue现有基于深度学习的调制识别在训练阶段需要大量IQ信号样本，而复杂电磁环境中很难获取大量样本，导致基于深度学习的调制识别算法泛化性能下降。针对网络泛化能力差的问题，提出了一种基于信号增强的调制识别（signal enhancement based modulation recognition，SEBMR）算法。首先，设计了捕获IQ信号全局特征的特征提取及重构模块；其次，提出了基于辅助分类生成对抗网络（auxiliary classifier generative adversarial network ...
程风云, 周金
doaj +1 more source