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Efficiency of deep neural networks for joint angle modeling in digital gait assessment 

Alcaraz, Javier Conte; Moghaddamnia, Sanam; Peissig, Jürgen (Springer Open, 2021)
Reliability and user compliance of the applied sensor system are two key issues of digital healthcare and biomedical informatics. For gait assessment applications, accurate joint angle measurements are important. Inertial ...
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Monitoring the rehabilitation progress using a DCNN and kinematic data for digital healthcare 

Alcaraz, Javier Conte; Moghaddamnia, Sanam; Penner, Maxim; Peissig, Jürgen (Institute of Electrical and Electronics Engineers, 2021)
Monitoring the progress of patients during the rehabilitation process after an operation is beneficial for adjusting care and medical treatment in order to improve the patient's quality of life. The supervised methods used ...

Classification of brain electrophysiological changes in response to colour stimuli 

Göksel Duru, Dilek; Alobaidi, May (Springer, 2021)
In this study, the classification of ongoing brain activity occurring as a response to colour stimuli was managed and reported. Until now, the classification of the seen colour from brain electrical signals has not been ...
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Optimum design of cylindrical walls using ensemble learning methods 

Bekdaş, Gebrail; Çakıroğlu, Celal; Islam, Kamrul; Kim, Sanghun; Geem, Zong Woo (MDPI-Multidisciplinary Digital Publishing Institute, 2022)
The optimum cost of the structure design is one of the major goals of structural engineers. The availability of large datasets with preoptimized structural configurations can facilitate the process of optimum design ...

Challenges and limitations in the studies of glycoproteins: A computational chemist's perspective 

Ballı, Öykü İrem; Uversky, Vladimir N.; Durdağı, Serdar; Weber, Orkide Coşkuner (WILEY, 2021)
Experimenters face challenges and limitations while analyzing glycoproteins due to their high flexibility, stereochemistry, anisotropic effects, and hydration phenomena. Computational studies complement experiments and ...
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Optimal dimensioning of retaining walls using explainable ensemble learning algorithms 

Bekdaş, Gebrail; Çakıroğlu, Celal; Kim, Sanghun; Geem, Zong Woo (MDPI-Multidisciplinary Digital Publishing Institute, 2022)
This paper develops predictive models for optimal dimensions that minimize the construction cost associated with reinforced concrete retaining walls. Random Forest, Extreme Gradient Boosting (XGBoost), Categorical Gradient ...



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AuthorAlcaraz, Javier Conte (2)Bekdaş, Gebrail (2)Geem, Zong Woo (2)Kim, Sanghun (2)Moghaddamnia, Sanam (2)Peissig, Jürgen (2)Çakıroğlu, Celal (2)Alobaidi, May (1)Ballı, Öykü İrem (1)Durdağı, Serdar (1)... View MoreSubjectMachine Learning (6)
Maschinelles Lernen (6)
Makine Öğrenimi (2)Optimierung (2)Optimizasyon (2)Optimization (2)Classical Molecular Simulations (1)Classification (1)Colour Stimuli (1)Deep Neural Network (1)... View MoreDate Issued2021 (4)2022 (2)Has File(s)Yes (4)No (2)

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