Results 71 to 80 of about 14,306 (259)

What Constitutes an Attractive Product‐as‐a‐Service Offer? Examining Consumer Preferences for (Circular) Business Patterns

Business Strategy and the Environment, EarlyView.
ABSTRACT Little is known about consumer preferences for combinations of circular business model patterns, despite their potential to benefit the design of product services. This study examines consumer preferences for product‐as‐a‐service offers, combined with circular product attributes, across Sweden and the Netherlands.
Steven Sarasini, Aemiro Melkamu Daniel, Katherine Whalen, Nancy Bocken, Agnieszka Hunka, Tarlan Ahmadov   +5 more
wiley   +1 more source

Sustainable and Resilient Supply Networks: Digitalisation, Regulation and Climate Vulnerability in a Global Context

Business Strategy and the Environment, EarlyView.
ABSTRACT The growing frequency of global crises has intensified concerns regarding climate vulnerability and the resilience of global production systems. This study examines the heterogeneous effects of supply chain development and supply chain digitalisation on climate vulnerability across countries, while accounting for institutional and investment ...
Ziwei Li, Zhi Zhan, Kingsley Imandojemu, Romanus Osabohien, Damilola Felix Eluyela   +4 more
wiley   +1 more source

Do Commodity Prices and Energy Markets Drive Asymmetric Volatility in Biodiversity Finance?

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines symmetric and asymmetric volatility spillovers among biodiversity finance, commodity prices, and energy markets using daily data from 2019 to 2025. We apply the Diebold–Yilmaz time–domain connectedness model, Baruník–Křehlík frequency–domain decomposition, and an asymmetric spillover framework.
Ijaz Younis, Maqsood Ahmad, Himani Gupta, Kun Su, Waheed Ullah Shah   +4 more
wiley   +1 more source

Federated multimodal malware classification under non-IID data

Cybersecurity
Malware data in real-world cybersecurity applications are typically distributed across multiple organizations, and privacy, security, and compliance constraints prevent these data from being shared with a central server.
Shaohua Liu, Wenbo Zhang, Tingting Yang, Guanghao Li, Lihua Zhang   +4 more
doaj   +1 more source

Interventional Mitral Valve Edge‐to‐Edge Repair in Patients Above 85 Years of Age

Catheterization and Cardiovascular Interventions, EarlyView.
ABSTRACT Background Mitral valve transcatheter‐edge‐to‐edge repair (M‐TEER) is routinely performed in patients with severe mitral regurgitation (MR) at high operative risk, frequently including elderly patients. Patients ≥ 85 years, however, are frequently excluded in clinical studies.
Florian Jürgens, Florian Schindhelm, Mohammed Abusharekh, Jürgen Kampf, Matthias Totzeck, Fadi Al‐Rashid, Peter Lüdike, Tienush Rassaf, Amir A. Mahabadi   +8 more
wiley   +1 more source

Weighting non-IID batches for out-of-distribution detection

Machine Learning
AbstractA standard network pretrained on in-distribution (ID) samples could make high-confidence predictions on out-of-distribution (OOD) samples, leaving the possibility of failing to distinguish ID and OOD samples in the test phase. To address this over-confidence issue, the existing methods improve the OOD sensitivity from modeling perspectives, i.e.
Zhi-Lin Zhao 0001, Longbing Cao
openaire   +1 more source

Jackknife bias‐corrected variance estimation for the generalized regression estimator

Canadian Journal of Statistics, EarlyView.
Abstract Commonly used variance estimators for the generalized regression estimator (GREG) are based on Taylor linearization and jackknife. Traditionally, a jackknife GREG variance estimator is obtained by jackknifing GREG, which consists of computing GREG from each of several subsamples of the parent sample, and estimating the variance of the parent ...
Marius Stefan, J.N.K Rao
wiley   +1 more source

Pretraining Client Selection Algorithm Based on a Data Distribution Evaluation Model in Federated Learning

IEEE Access
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, Hong Liu, Kexin Li, Wanglei Feng, Wei Qi   +4 more
doaj   +1 more source

Overcoming Forgetting in Federated Learning on Non-IID Data

CoRR, 2019
We tackle the problem of Federated Learning in the non i.i.d. case, in which local models drift apart, inhibiting learning. Building on an analogy with Lifelong Learning, we adapt a solution for catastrophic forgetting to Federated Learning. We add a penalty term to the loss function, compelling all local models to converge to a shared optimum. We show
Neta Shoham, Tomer Avidor, Aviv Keren, Nadav Israel, Daniel Benditkis, Liron Mor-Yosef, Itai Zeitak   +6 more
openaire   +2 more sources

Dynamic survival risk prediction with time‐varying high‐dimensional images

Canadian Journal of Statistics, EarlyView.
Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu, Haolun Shi, Shu Jiang, Liangliang Wang, Da Ma, Mirza Faisal Beg, Jiguo Cao, for the Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source