Results 81 to 90 of about 96,144 (271)

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Accelerating Fair Federated Learning: Adaptive Federated Adam

IEEE Transactions on Machine Learning in Communications and Networking
Federated learning is a distributed and privacy-preserving approach to train a statistical model collaboratively from decentralized data held by different parties. However, when the datasets are not independent and identically distributed, models trained
Li Ju, Tianru Zhang, Salman Toor, Andreas Hellander   +3 more
doaj   +1 more source

Sustainable Productivity Growth in Agriculture: The Role of Shifts in R&D Investments and Technology

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT The objective of the paper is to evaluate the long‐term prospects of sustainable productivity growth linked to plausible assumptions on public agricultural R&D investments as the key productivity driver. Second, it investigates the role of changing R&D focus from yield maximization to input saving technologies (fertilizers and pesticides). The
Zuzana Smeets Křístková, Michiel van Dijk, Robert M'Barek, Hans van Meijl, Tomas Ratinger   +4 more
wiley   +1 more source

An Watermarking Framework of Active Protection Model for Secure Federated Learning [PDF]

Jisuanji gongcheng
As a new paradigm in deep learning, federated learning allows multiple parties to jointly train deep learning models while ensuring that data remains on the clients' local devices.
CHEN Xianyi, DING Sizhe, WANG Kang, YAN Leiming, FU Zhangjie
doaj   +1 more source

Federated Neural Architecture Search

, 2020
To preserve user privacy while enabling mobile intelligence, techniques have been proposed to train deep neural networks on decentralized data. However, training over decentralized data makes the design of neural architecture quite difficult as it ...
Bian, Kaigui, Huang, Gang, Liu, Xuanzhe, Mei, Qiaozhu, Xu, Mengwei, Zhao, Yuxin   +5 more
core  

Disentangling the relationships between denomination of origin regulatory councils activities and Spanish wineries' export performance

Agribusiness, EarlyView.
Abstract World markets for quality differentiated agri‐food products are highly competitive, presenting significant challenges for firms aiming to compete effectively. Government agencies and business organizations often implement various export promotion policies to address these challenges.
Nicolás Depetris‐Chauvin, Marta Fernández‐Olmos   +1 more
wiley   +1 more source

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

Advanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen, Patrick W. V. Butler, Jesper R. Pedersen, Nis Fisker‐Bødker, Tejs Vegge, Jin Hyun Chang, Ivano E. Castelli   +6 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +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

FedADC: Federated Average Knowledge Distilled Mutual Conditional Learning (FedADC) for Waste Classification

IEEE Access
Federated learning presents a potent avenue for addressing challenges in waste classification, where diverse datasets are distributed across sources.
Ananya Ghosh, Parthiban Krishnamoorthy
doaj   +1 more source