Results 51 to 60 of about 11,273 (224)
Hadoop Cluster Deployment: A Methodological Approach
For a long time, data has been treated as a general problem because it just represents fractions of an event without any relevant purpose. However, the last decade has been just about information and how to get it.
Ronaldo Celso Messias Correia +5 more
doaj +1 more source
This study presents an integrated framework linking six foundational elements of water resources management: watershed modeling, surrogate modeling, optimization, artificial intelligence, decision support systems, and monitoring. The synthesis highlights how connecting these traditionally separate domains fosters smarter, adaptive, and data‐driven ...
Hoda S. Razavi +5 more
wiley +1 more source
"Big data" has become a major area of research and associated funding, as well as a focus of utopian thinking. In the still growing research community, one of the favourite optimistic analogies for data processing is that of the oil refinery, extracting ...
Eerke A. Boiten, Boiten, Eerke Albert
core +1 more source
ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed +2 more
wiley +1 more source
Hadoop Configuration Tuning With Ensemble Modeling and Metaheuristic Optimization
MapReduce is a popular programming model for big data processing. Although the distributed processing framework Hadoop greatly reduced the development complexity of MapReduce applications, fine tuning of the Hadoop systems for optimal performance remains
Xingcheng Hua +2 more
doaj +1 more source
An Overview of Deep Learning Techniques for Big Data IoT Applications
Reviews deep learning integration with cloud, fog, and edge computing in IoT architectures. Examines model suitability across IoT applications, key challenges, and emerging trends Provides a comparative analysis to guide future deep learning research in IoT environments.
Gagandeep Kaur +2 more
wiley +1 more source
Modern web applications are deployed in cloud computing systems because they support unlimited storage and computing power. One of the main back-end storage components of this cloud computing system is the distributed file system which allows massive ...
Anusha Nalajala +2 more
doaj +1 more source
AI‐driven perception management and political soft power: Insights from expert interviews
Abstract This study explores the role of artificial intelligence (AI) in perception management as an emerging tool of political soft power. Drawing on the theoretical frameworks of social psychology, strategic communication, and political communication, the research investigates how AI‐assisted strategies influence public perception, image, and trust ...
Özkul Haraç, Ayhan Dolunay
wiley +1 more source
A sliding window-based dynamic load balancing for heterogeneous Hadoop clusters
At present MapReduce computing model‐based Hadoop framework has gradually become the most famous distributed computing framework because of its remarkable features such as scalability, fault tolerance, data security, and powerful IO ability.
Xiang, Y. +4 more
core +1 more source
A Multi‐Layered Analysis of Energy Consumption in Spark
ABSTRACT Although energy has become a major concern in data processing systems, it is usually hard to get a deep understanding of how performance and energy consumption relate to each other when planning how to configure a computing environment to execute a specific data‐oriented workload.
Nestor D. O. Volpini +2 more
wiley +1 more source

