Automated Detection of Leadership Qualities Using Textual Data at the Message Level

Autor: Krzysztof Fiok, Waldemar Karwowski, Edgar Gutierrez-Franco, Tameika Liciaga, Alessandro Belmonte, Rocco Capobianco, Maham Saeidi

Publikováno v: IEEE Access, Vol 9, Pp 57141-57148 (2021)

Efficient leadership plays an important role in organizations, with the military being one of the more obvious examples of this statement. In this context, it is not surprising that ensuring a culture of excellence is at the heart of Navy leadership.

Externí odkaz: https://doaj.org/article/655f121bbc8e4e5c8e96f5791c33a90e

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review

Autor: Maham Saeidi, Waldemar Karwowski, Farzad V. Farahani, Krzysztof Fiok, Redha Taiar, P. A. Hancock, Awad Al-Juaid

Publikováno v: Brain Sciences, Vol 11, Iss 11, p 1525 (2021)

Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasing

Externí odkaz: https://doaj.org/article/97d37623d3624809a837fab71e23c18d

A Study of the Effects of the COVID-19 Pandemic on the Experience of Back Pain Reported on Twitter® in the United States: A Natural Language Processing Approach

Autor: Ben D. Sawyer, Awad M. Aljuaid, Edgar Gutierrez, Maham Saeidi, Krzysztof Fiok, Waldemar Karwowski, Mohammad Reza Davahli, Redha Taiar, Tadeusz Marek

Publikováno v: International Journal of Environmental Research and Public Health
Volume 18
Issue 9
International Journal of Environmental Research and Public Health, Vol 18, Iss 4543, p 4543 (2021)
BASE-Bielefeld Academic Search Engine

The COVID-19 pandemic has changed our lifestyles, habits, and daily routine. Some of the impacts of COVID-19 have been widely reported already. However, many effects of the COVID-19 pandemic are still to be discovered. The main objective of this stud

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bb5811a69ff8347102adf8f55829a979

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review

Autor: Redha Taiar, Farzad V. Farahani, Awad M. Aljuaid, Maham Saeidi, Krzysztof Fiok, Waldemar Karwowski, Peter A. Hancock

Publikováno v: Brain Sciences, Vol 11, Iss 1525, p 1525 (2021)
Brain Sciences

Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasing

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f48702669e92fccce1c7f1788c3872c
https://doi.org/10.3390/brainsci11111525

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review.

Autor: Saeidi, Maham¹ (AUTHOR) ffaraha2@jhu.edu, Karwowski, Waldemar¹ (AUTHOR) fiok@ucf.edu, Farahani, Farzad V.^1,2 (AUTHOR), Fiok, Krzysztof¹ (AUTHOR), Taiar, Redha³ (AUTHOR) redha.taiar@univ-reims.fr, Hancock, P. A.⁴ (AUTHOR) peter.hancock@ucf.edu, Al-Juaid, Awad⁵ (AUTHOR) amjuaid@tu.edu.sa

Publikováno v: Brain Sciences (2076-3425). Nov2021, Vol. 11 Issue 11, p1525. 1p.