Results 101 to 110 of about 9,950,038 (297)
ABSTRACT This paper explores Swedish consumers' protein preferences by estimating the willingness‐to‐pay (WTP) for minced meat and plant‐based proteins in pasta sauce from an in‐store experiment (n = 206) and an online discrete choice experiment (n = 517). On average, the WTP was highest for minced meat.
Emilia Mattsson +3 more
wiley +1 more source
On the nonuniform Berry--Esseen bound [PDF]
Due to the effort of a number of authors, the value c_u of the absolute constant factor in the uniform Berry--Esseen (BE) bound for sums of independent random variables has been gradually reduced to 0.4748 in the iid case and 0.5600 in the general case ...
Pinelis, Iosif
core
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data [PDF]
Federated learning achieves effective performance in modeling decentralized data. In practice, client data are not well-labeled, which makes it potential for federated unsupervised learning (FUSL) with non-IID data.
Xinting Liao +9 more
semanticscholar +1 more source
Assessing the Impact of Promotions on Consumer Purchasing Behavior During Crises
ABSTRACT Understanding how households modify their food expenditure decisions during times of crisis is essential because consumer purchasing behavior frequently changes during these times. This study looks at these behavioral shifts during the COVID‐19 pandemic, concentrating on how price sensitivity and response to sales promotions changed over the ...
Wafa Mehaba, José María Gil
wiley +1 more source
Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren +6 more
wiley +1 more source
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
Federated Learning (FL) allows task initiators (servers) to utilize data from task participants (clients) to train machine learning models while protecting data privacy.
Chang Xu +4 more
doaj +1 more source
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong +4 more
wiley +1 more source
Distributed denial of service (DDoS) is an awful cyber threat, becoming more prevalent with mature heterogeneous IoT (HetIoT) applications like intelligent agriculture, wearables, and self-driving cars. Developing intelligent intrusion detection systems (
Shalaka S. Mahadik +2 more
doaj +1 more source
Genomic Structural Variations Provide Insights Into Litter Size and Teat Number Traits in Hu Sheep
Here, we conducted whole genome sequencing on 300 Hu sheep with an average depth of 16.51X. Two candidate genes associated with litter size and teat number traits were identified, namely MAST2 and AFDN. ABSTRACT Litter size and the teat number are important economic indicators in sheep production.
Xin Xiang +3 more
wiley +1 more source

