WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
Browse
2 results
Search Results
Article Citation - WoS: 3Citation - Scopus: 3The Angular Electronic Band Structure and Free Particle Model of Aromatic Molecules: High-Frequency Photon-Induced Ring Current(World Scientific Publ Co Pte Ltd, 2017-03) Oncan, Mehmet; Koc, Fatih; Sahin, Mehmet; Koksal, KorayThis work introduces an analysis of the relationship of first-principles calculations based on DFT method with the results of free particle model for ring-shaped aromatic molecules. However, the main aim of the study is to reveal the angular electronic band structure of the ring-shaped molecules. As in the case of spherical molecules such as fullerene, it is possible to observe a parabolic dispersion of electronic states with the variation of angular quantum number in the planar ring-shaped molecules. This work also discusses the transition probabilities between the occupied and virtual states by analyzing the angular electronic band structure and the possibility of ring currents in the case of spin angular momentum (SAM) or orbital angular momentum (OAM) carrying light. Current study focuses on the benzene molecule to obtain its angular electronic band structure. The obtained electronic band structure can be considered as a useful tool to see the transition probabilities between the electronic states and possible contribution of the states to the ring currents. The photoinduced current due to the transfer of SAM into the benzene molecule has been investigated by using analytical calculations within the frame of time-dependent perturbation theory.Article Citation - WoS: 11Citation - Scopus: 14Detection of Movement Intention in EEG-Based Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform(World Scientific Publ Co Pte Ltd, 2021) Karakullukcu, Nedime; Yilmaz, BulentPatients with motor impairments need caregivers' help to initiate the operation of brain-computer interfaces (BCI). This study aims to identify and characterize movement intention using multichannel electroencephalography (EEG) signals as a means to initiate BCI systems without extra accessories/methodologies. We propose to discriminate the resting and motor imagery (MI) states with high accuracy using Fourier-based synchrosqueezing transform (FSST) as a feature extractor. FSST has been investigated and compared with other popular approaches in 28 healthy subjects for a total of 6657 trials. The accuracy and f-measure values were obtained as 99.8% and 0.99, respectively, when FSST was used as the feature extractor and singular value decomposition (SVD) as the feature selection method and support vector machines as the classifier. Moreover, this study investigated the use of data that contain certain amount of noise without any preprocessing in addition to the clean counterparts. Furthermore, the statistical analysis of EEG channels with the best discrimination (of resting and MI states) characteristics demonstrated that F4-Fz-C3-Cz-C4-Pz channels and several statistical features had statistical significance levels, p, less than 0.05. This study showed that the preparation of the movement can be detected in real-time employing FSST-SVD combination and several channels with minimal pre-processing effort.