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Jing Liu, Xuesong Hai and Keqin Li
Massive amounts of data drive the performance of deep learning models, but in practice, data resources are often highly dispersed and bound by data privacy and security concerns, making it difficult for multiple data sources to share their local data dir...
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Songlin Tian, Ying Yang and Lei Yang
Business intelligence (BI), as a system for business data integration, processing, and analysis, is receiving increasing attention from enterprises. Data visualization is an important feature of BI, which allows users to visually observe the distribution...
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Aikaterini Kasimati, George Papadopoulos, Valentina Manstretta, Marianthi Giannakopoulou, George Adamides, Damianos Neocleous, Vassilis Vassiliou, Savvas Savvides and Andreas Stylianou
Addressing the urgent sustainability challenges in the wine industry, this study explores the efficacy of sustainability-oriented innovations (SOIs) and smart farming technologies (SFTs) across wine value chains in Cyprus and Italy. Utilising a mixed-met...
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Andreas Giannakoulopoulos, Minas Pergantis and Aristeidis Lamprogeorgos
The present study focuses on using qualitative and quantitative data to evaluate the functionality, user experience (UX), and aesthetic approach offered by an academic multi-site Web ecosystem consisting of multiple interconnected websites. Large entitie...
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Lijun Zu, Wenyu Qi, Hongyi Li, Xiaohua Men, Zhihui Lu, Jiawei Ye and Liang Zhang
The digital transformation of banks has led to a paradigm shift, promoting the open sharing of data and services with third-party providers through APIs, SDKs, and other technological means. While data sharing brings personalized, convenient, and enriche...
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Jose A. Montenegro and Antonio Muñoz
In this manuscript, we present EventGeoScout, an innovative framework for collaborative geographic information management, tailored to meet the needs of the dynamically changing landscape of geographic data integration and quality enhancement. EventGeoSc...
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Alya Alshammari and Khalil El Hindi
The combination of collaborative deep learning and Cyber-Physical Systems (CPSs) has the potential to improve decision-making, adaptability, and efficiency in dynamic and distributed environments. However, it brings privacy, communication, and resource r...
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Thanda Shwe and Masayoshi Aritsugi
Intelligent applications in several areas increasingly rely on big data solutions to improve their efficiency, but the processing and management of big data incur high costs. Although cloud-computing-based big data management and processing offer a promi...
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Hanyue Xu, Kah Phooi Seng, Jeremy Smith and Li Minn Ang
In the context of smart cities, the integration of artificial intelligence (AI) and the Internet of Things (IoT) has led to the proliferation of AIoT systems, which handle vast amounts of data to enhance urban infrastructure and services. However, the co...
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Mikael Sabuhi, Petr Musilek and Cor-Paul Bezemer
As the number of machine learning applications increases, growing concerns about data privacy expose the limitations of traditional cloud-based machine learning methods that rely on centralized data collection and processing. Federated learning emerges a...
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