Results 61 to 70 of about 13,509 (257)

Assessing the Impact of Promotions on Consumer Purchasing Behavior During Crises

Agribusiness, EarlyView.
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

Price Transmission and Leadership in the Global Poultry Market: Results From Parametric and Nonparametric Approaches

Agribusiness, EarlyView.
ABSTRACT Brazil and the United States account for more than 40% of global poultry exports, with China and South Korea among their major destination markets. This study examines price transmission and market linkages between Brazil and the United States using monthly poultry export price data from January 1990 to December 2024. It also assesses which of
Khondoker Abdul Mottaleb, Shaikh M. Rahman, Syed Imran Ali Meerza   +2 more
wiley   +1 more source

Adding Data Quality to Federated Learning Performance Improvement

IEEE Access
Massive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract relevant and actionable insights. As a result, Federated Learning (FL) allows IoT devices to collaborate in Artificial Intelligence (
Ernesto Gurgel Valente Neto, Solon Alves Peixoto, Valderi Reis Quietinho Leithardt, Juan Francisco de Paz Santana, Julio C. S. Dos Anjos   +4 more
doaj   +1 more source

Is There a Market for Organic Milk in Serbia? Insights From Integrated Choice and Latent Variable Model

Agribusiness, EarlyView.
ABSTRACT Past growth in the global organic market has been concentrated in high‐income countries, while in middle‐income countries such as Serbia the organic market remains nascent and characterized by a sparse assortment of organic products, high retail premia and limited evidence on consumer preferences and their drivers.
Milan Tatic, Sanja Dzever, Bojan Matkovski, Danilo Djokic   +3 more
wiley   +1 more source

The Non-IID Data Quagmire of Decentralized Machine Learning

CoRR, 2019
Many large-scale machine learning (ML) applications need to perform decentralized learning over datasets generated at different devices and locations. Such datasets pose a significant challenge to decentralized learning because their different contexts result in significant data distribution skew across devices/locations.
Kevin Hsieh, Amar Phanishayee, Onur Mutlu, Phillip B. Gibbons   +3 more
openaire   +3 more sources

Consumer Demand and Market Response to Added Sugar Labeling: Evidence From the Updated Nutrition Facts Panel

Agribusiness, EarlyView.
ABSTRACT This paper examines how mandatory disclosure of added sugar content on the updated U.S. Nutrition Facts Panel (NFP) affects consumer demand and market outcomes. Using NielsenIQ Retail Scanner Data (2015–2020) and a random coefficient discrete choice model, we estimate how added sugar labeling influences purchasing behavior in yogurt and cookie
Yuxiang Zhang, Yizao Liu
wiley   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Communication Efficiency and Non-Independent and Identically Distributed Data Challenge in Federated Learning: A Systematic Mapping Study

Applied Sciences
Federated learning has emerged as a promising approach for collaborative model training across distributed devices. Federated learning faces challenges such as Non-Independent and Identically Distributed (non-IID) data and communication challenges.
Basmah Alotaibi, Fakhri Alam Khan, Sajjad Mahmood   +2 more
doaj   +1 more source

Assessing Progression Independent of Relapse Activity in Multiple Sclerosis Using a Patient‐Reported Disability Measure and Self‐Administered Neuroperformance Outcomes

Annals of Neurology, EarlyView.
Objective The objective of this study was to investigate the ability of patient‐reported/administered outcomes to capture disability worsening and progression independent of relapse activity (PIRA) in multiple sclerosis (MS). Methods We included patients from the longitudinal multicenter MS PATHS cohort with ≥3 assessments and >6 months follow‐up. PIRA
Evy M. Reinders, Ariadna Masot‐Llima, Susana Otero‐Romero, René Carvajal, Álvaro Cobo‐Calvo, Pere Carbonell‐Mirabent, Jordina Beltran, Maria Jesús Arévalo, Helena Ariño, Georgina Arrambide, Cristina Auger, Luca Bollo, Joaquín Castilló, Manuel Comabella, Ingrid Galán, Alexis García‐Sarreón, Andrew Goodman, Carrie M. Hersh, Delon La Puma, Le H. Hua, Luciana Midaglia, Neus Mongay‐Ochoa, Ellen M. Mowry, Agustín Pappolla, Breogán Rodríguez‐Acevedo, Jordi Río, Paula Tagliani, Ángela Vidal‐Jordana, Andreu Vilaseca, Ana Zabalza, Deborah Pareto, Carlos Nos, Menno Schoonheim, Eva Strijbis, Jaume Sastre‐Garriga, Madalina Tivarus, Tjalf Ziemssen, Àlex Rovira, Xavier Montalban, Mar Tintoré, Carmen Tur   +40 more
wiley   +1 more source

KL-FedDis: A federated learning approach with distribution information sharing using Kullback-Leibler divergence for non-IID data

Neuroscience Informatics
Data Heterogeneity or Non-IID (non-independent and identically distributed) data identification is one of the prominent challenges in Federated Learning (FL).
Md. Rahad, Ruhan Shabab, Mohd. Sultan Ahammad, Md. Mahfuz Reza, Amit Karmaker, Md. Abir Hossain   +5 more
doaj   +1 more source