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Max Schrötter, Andreas Niemann and Bettina Schnor
Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusi...
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Liang Liu, Tianbin Li and Chunchi Ma
Three-dimensional (3D) models provide the most intuitive representation of geological conditions. Traditional modeling methods heavily depend on technicians? expertise and lack ease of updating. In this study, we introduce a deep learning-based method fo...
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Nils Hütten, Miguel Alves Gomes, Florian Hölken, Karlo Andricevic, Richard Meyes and Tobias Meisen
Quality assessment in industrial applications is often carried out through visual inspection, usually performed or supported by human domain experts. However, the manual visual inspection of processes and products is error-prone and expensive. It is ther...
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Styliani Tassiopoulou, Georgia Koukiou and Vassilis Anastassopoulos
In the ever-evolving landscape of tomographic imaging algorithms, this literature review explores a diverse array of themes shaping the field?s progress. It encompasses foundational principles, special innovative approaches, tomographic implementation al...
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Abdul Majeed, Abdullah M. Alnajim, Athar Waseem, Aleem Khaliq, Aqdas Naveed, Shabana Habib, Muhammad Islam and Sheroz Khan
In fifth Generation (5G) networks, protection from internal attacks, external breaches, violation of confidentiality, and misuse of network vulnerabilities is a challenging task. Various approaches, especially deep-learning (DL) prototypes, have been ado...
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Filippo Poltronieri, Cesare Stefanelli, Mauro Tortonesi and Mattia Zaccarini
Modern computing environments, thanks to the advent of enabling technologies such as Multi-access Edge Computing (MEC), effectively represent a Cloud Continuum, a capillary network of computing resources that extend from the Edge of the network to the Cl...
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Fadwa Alrowais, Saud S. Alotaibi, Anwer Mustafa Hilal, Radwa Marzouk, Heba Mohsen, Azza Elneil Osman, Amani A. Alneil and Mohamed I. Eldesouki
Big Data analytics is a technique for researching huge and varied datasets and it is designed to uncover hidden patterns, trends, and correlations, and therefore, it can be applied for making superior decisions in healthcare. Drug?drug interactions (DDIs...
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Imad Janbain, Abderrahim Jardani, Julien Deloffre and Nicolas Massei
Water quality monitoring is essential for managing water resources and ensuring human and environmental health. However, obtaining reliable data can be challenging and costly, especially in complex systems such as estuaries. To address this problem, we p...
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Saidur R. Pavel and Yimin D. Zhang
Massive multiple-input multiple-output (MIMO) technology, which is characterized by the use of a large number of antennas, is a key enabler for the next-generation wireless communication and beyond. Despite its potential for high performance, implementin...
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Sebastian C. Ibañez and Christopher P. Monterola
Accurate prediction of crop production is essential in effectively managing the food security and economic resilience of agricultural countries. This study evaluates the performance of statistical and machine learning-based methods for large-scale crop p...
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