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Saeed Samadianfard, Salar Jarhan, Ely Salwana, Amir Mosavi, Shahaboddin Shamshirband and Shatirah Akib
Advancement in river flow prediction systems can greatly empower the operational river management to make better decisions, practices, and policies. Machine learning methods recently have shown promising results in building accurate models for river flow...
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Jasna Soldic-Aleksic, Biljana Chroneos Krasavac, Ema Karamata
Research question: In the last decade, the concept of Business analytics (BA) has gone through revolutionary changes. It has gained a lot in popularity and attracted immense interest both in academic and commercial communities. Accepting this reality, th...
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Narasimha Rao Vajjhala, Ervin Ramollari
Pág. 129 - 137
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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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Kenneth David Strang
A critical worldwide problem is that ransomware cyberattacks can be costly to organizations. Moreover, accidental employee cybercrime risk can be challenging to prevent, even by leveraging advanced computer science techniques. This exploratory project us...
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Wei-Ling Hsu, Yi-Jheng Chang, Lin Mou, Juan-Wen Huang and Hsin-Lung Liu
Historic urban areas are the foundations of urban development. Due to rapid urbanization, the sustainable development of historic urban areas has become challenging for many cities. Elements of tourism and tourism service facilities play an important rol...
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Marwa Salah Farhan, Amira Youssef and Laila Abdelhamid
Traditional data warehouses (DWs) have played a key role in business intelligence and decision support systems. However, the rapid growth of the data generated by the current applications requires new data warehousing systems. In big data, it is importan...
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Thoralf Reis, Lukas Dumberger, Sebastian Bruchhaus, Thomas Krause, Verena Schreyer, Marco X. Bornschlegl and Matthias L. Hemmje
Manual labeling and categorization are extremely time-consuming and, thus, costly. AI and ML-supported information systems can bridge this gap and support labor-intensive digital activities. Since it requires categorization, coding-based analysis, such a...
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Eleni Vlachou, Aristeidis Karras, Christos Karras, Leonidas Theodorakopoulos, Constantinos Halkiopoulos and Spyros Sioutas
In this work, we present a Distributed Bayesian Inference Classifier for Large-Scale Systems, where we assess its performance and scalability on distributed environments such as PySpark. The presented classifier consistently showcases efficient inference...
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Aristeidis Karras, Anastasios Giannaros, Christos Karras, Leonidas Theodorakopoulos, Constantinos S. Mammassis, George A. Krimpas and Spyros Sioutas
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices. Our study introduces ...
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