Deep learning enables a novel magnetic resonance imaging contrast that unveils chemical and microstructural brain tissue changes through nondipolar larmor frequency shifts. - In: Biomedical engineering, ISSN 1862-278X, Bd. 68 (2023), S. 160
https://doi.org/10.1515/bmte-2023-2001
Mapping the anisotropy of tissue magnetic susceptibility from single-orientation magnetic resonance imaging. - In: Biomedical engineering, ISSN 1862-278X, Bd. 68 (2023), S. 156
https://doi.org/10.1515/bmte-2023-2001
Real-time smartphone-assisted EEG electrode localization and augmented reality application. - In: Biomedical engineering, ISSN 1862-278X, Bd. 68 (2023), S. 153
https://doi.org/10.1515/bmte-2023-2001
Cobalt ferrite nanoparticles as thermal markers on lateral flow assays. - In: Biomedical engineering, ISSN 1862-278X, Bd. 68 (2023), S. 126
https://doi.org/10.1515/bmte-2023-2001
Comparison of a 3D co-culture and a mini organ culture by testing barium sulphate and titanium dioxide nanoparticle aerosols. - In: Naunyn-Schmiedeberg's archives of pharmacology, ISSN 1432-1912, Bd. 396 (2023), 1, P055, S. S37
https://doi.org/10.1007/s00210-023-02397-6
Novel MRI technique reveals subtypes of paramagnetic rim lesions and predicts 5-year rim disappearance. - In: Multiple sclerosis journal, ISSN 1477-0970, Bd. 29 (2023), 2, P031
https://doi.org/10.1177/13524585231169437
Enhanced fuzzy-MFC-based traction control system for electric vehicles. - In: IEEE Xplore digital library, ISSN 2473-2001, (2023), insges. 6 S.
Modern vehicles require the installation of motion control systems to ensure driving safety. In electric vehicles, these systems are convenient to be developed and applied due to the better response of the electric motor compared to the internal combustion engine. Therefore, the development of traction control systems for electric vehicles is of great interest to many researchers. In this study, a wheel slip control algorithm for electric vehicles is proposed by considering the vehicle as an equivalent inertial system. Based on the monotonicity of the algorithm, a fuzzy controller is also incorporated in the study so that the wheel slip control can adapt to the actual road conditions. Its performance is verified by comparative simulations with baseline anti-slip methods for different road conditions and vehicle velocities.
https://doi.org/10.1109/VPPC60535.2023.10403162
Fast fictitious surface charge method for calculation of torso surface potentials. - In: IEEE Xplore digital library, ISSN 2473-2001, (2023), insges. 4 S.
Well-established forward modeling methods in electrocardiography (ECG) require fine meshes to calculate the electric scalar potential at the body surface with high accuracy. We introduce a fast fictitious surface charge method (FSCM) with local mesh refinement and smart calculations of elements interactions which improves the accuracy of the calculations and, at the same time, preserves the performance speed.
https://doi.org/10.1109/COMPUMAG56388.2023.10411804
Applicability study of model-free reinforcement learning towards an automated design space exploration framework. - In: 2023 IEEE Symposium Series on Computational Intelligence (SSCI), (2023), S. 525-532
Design space exploration is a crucial aspect of engineering and optimization, focused on identifying optimal design configurations for complex systems with a high degree of freedom in the actor set. It involves systematic exploration while considering various constraints and requirements. One of the key challenges in design space exploration is the need for a control strategy tailored to the particular design. In this context, reinforcement learning has emerged as a promising solution approach for automatically inferring control strategies, thereby enabling efficient comparison of different designs. However, learning the optimal policy is computationally intensive, as the agent determines the optimal policy through trial and error. The focus of this study is on learning a single strategy for a given design and scenario, enabling the evaluation of numerous architectures within a limited time frame. The study also highlights the importance of plant modeling considering different modeling approaches to effectively capture the system complexity on the example of vehicle dynamics. In addition, a careful selection of an appropriate hyperparameter set for the reinforcement learning algorithm is emphasized to improve the overall performance and optimization process.
https://doi.org/10.1109/SSCI52147.2023.10371864
Linear versus quadratic detrending in analyzing simultaneous changes in DC-EEG and transcutaneous pCO2. - In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Conference (EMBC), (2023), insges. 4 S.
Physiological direct current (DC) potential shifts in electroencephalography (EEG) can be masked by artifacts such as slow electrode drifts. To reduce the influence of these artifacts, linear detrending has been proposed as a pre-processing step. We considered quadratic detrending, which has hardly been addressed for ultralow frequency components in EEG. We compared the performance of linear and quadratic detrending in simultaneously acquired DC-EEG and transcutaneous partial pressure of carbon dioxide during two activation methods: hyperventilation (HV) and apnea (AP). Quadratic detrending performed significantly better than linear detrending in HV, while for AP, our analysis was inconclusive with no statistical significance. We conclude that quadratic detrending should be considered for DC-EEG preprocessing.
https://doi.org/10.1109/EMBC40787.2023.10340855