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Tim Hulsen
Artificial Intelligence (AI) describes computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Examples of AI techniques are machine learni...
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Francisco Florez-Revuelta
This paper presents a new evolutionary approach, EvoSplit, for the distribution of multi-label data sets into disjoint subsets for supervised machine learning. Currently, data set providers either divide a data set randomly or using iterative stratificat...
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Íñigo Manuel Iglesias-Sanfeliz Cubero, Andrés Meana-Fernández, Juan Carlos Ríos-Fernández, Thomas Ackermann and Antonio José Gutiérrez-Trashorras
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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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Mateusz Zareba, Hubert Dlugosz, Tomasz Danek and Elzbieta Weglinska
Air pollution is an important problem for public health. The spatiotemporal analysis is a crucial step for understanding the complex characteristics of air pollution. Using many sensors and high-resolution time-step observations makes this task a big dat...
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Roman Khotyachuk and Klaus Johannsen
In this study, the numerical solutions to the Elder problem are analyzed using Big Data technologies and data-driven approaches. The steady-state solutions to the Elder problem are investigated with regard to Rayleigh numbers (????
R
a
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Muhammad Shoaib Arif, Aiman Mukheimer and Daniyal Asif
Clinical decision-making in chronic disorder prognosis is often hampered by high variance, leading to uncertainty and negative outcomes, especially in cases such as chronic kidney disease (CKD). Machine learning (ML) techniques have emerged as valuable t...
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Rogério Xavier de Azambuja, A. Jorge Morais and Vítor Filipe
In the current technological scenario of artificial intelligence growth, especially using machine learning, large datasets are necessary. Recommender systems appear with increasing frequency with different techniques for information filtering. Few large ...
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Fabrizio Marozzo and Domenico Talia
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Nisrine Berros, Fatna El Mendili, Youness Filaly and Younes El Bouzekri El Idrissi
Medicine is constantly generating new imaging data, including data from basic research, clinical research, and epidemiology, from health administration and insurance organizations, public health services, and non-conventional data sources such as social ...
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Aristeidis Karras, Christos Karras, Nikolaos Schizas, Markos Avlonitis and Spyros Sioutas
The field of automated machine learning (AutoML) has gained significant attention in recent years due to its ability to automate the process of building and optimizing machine learning models. However, the increasing amount of big data being generated ha...
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Rohit Gupta and Krishna Teerth Chaturvedi
The smart grid (SG) ensures the flow of electricity and data between suppliers and consumers. The reliability and security of data also play an important role in the overall management. This can be achieved with the help of adaptive energy management (AE...
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Zhang Yiming, Xie Fang, Olena Hordiichuk-Bublivska, Halyna Beshley and Mykola Beshley
The digitalization of production in smart grids entails challenges related to data collection, coordination, privacy protection, and anomaly detection. Machine learning techniques offer effective tools for processing Big Data, but identifying critical sy...
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Hugo Silva and Jorge Bernardino
Decision support systems with machine learning can help organizations improve operations and lower costs with more precision and efficiency. This work presents a review of state-of-the-art machine learning algorithms for binary classification and makes a...
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Changwon Yoo, Efrain Gonzalez, Zhenghua Gong and Deodutta Roy
Every year, biomedical data is increasing at an alarming rate and is being collected from many different sources, such as hospitals (clinical Big Data), laboratories (genomic and proteomic Big Data), and the internet (online Big Data). This article prese...
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Khalid Alfalqi and Martine Bellaiche
Emergency events arise when a serious, unexpected, and often dangerous threat affects normal life. Hence, knowing what is occurring during and after emergency events is critical to mitigate the effect of the incident on humans? life, on the environment a...
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Yunus Dogan, Feristah Dalkiliç, Alp Kut, Kemal Can Kara and Uygar Takazoglu
Large numbers of job postings with complex content can be found on the Internet at present. Therefore, analysis through natural language processing and machine learning techniques plays an important role in the evaluation of job postings. In this study, ...
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Xinjie Zhao, Shiyun Wang and Hao Wang
This study aims to give an insight into the development trends and patterns of social organizations (SOs) in China from the perspective of network science integrating geography and public policy information embedded in the network structure. Firstly, we ...
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Galina Ilieva, Tania Yankova, Stanislava Klisarova-Belcheva and Svetlana Ivanova
The risk of COVID-19 in higher education has affected all its degrees and forms of training. To assess the impact of the pandemic on the learning of university students, a new reference framework for educational data processing was proposed. The framewor...
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Gema Hernández-Moral, Sofía Mulero-Palencia, Víctor Iván Serna-González, Carla Rodríguez-Alonso, Roberto Sanz-Jimeno, Vangelis Marinakis, Nikos Dimitropoulos, Zoi Mylona, Daniele Antonucci and Haris Doukas
Current climate change threats and increasing CO2 emissions, especially from the building stock, represent a context where action is required. It is necessary to provide efficient manners to manage energy demand in buildings and contribute to a decarboni...
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