Yazar "Kurt, Muhammed B." seçeneğine göre listele

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    The ANN-based computing of drowsy level
    (Pergamon-Elsevier Science Ltd, 2009) Kurt, Muhammed B.; Sezgin, Necmettin; Akin, Mehmet; Kirbas, Gokhan; Bayram, Muhittin
    We have developed a new method for automatic estimation of vigilance level by using electroencephalogram (EEG), electromyogram (EMG) and eye movement (EOG) signals recorded during transition from wakefulness to sleep. In the previous studies, EEG signals and EEG signals with EMG signals were used for estimating vigilance levels. In the present study, it was aimed to estimate vigilance levels by using EEG, EMG and EOG signals. The changes in EEG, EMG and EOG were diagnosed while transiting from wakefulness to sleep by using wavelet transform and developed artificial neural network (ANN). EEG signals were separated to its subbands using wavelet transform, LEOG (Left EOG), REOG (Right EOG) and chin EMG was used in ANN process for increasing the accuracy of the estimation rate by evaluating their tonic levels and also used in data preparation stage to verify and eliminate the movement artifacts. Then, training and testing data sets consist of the EEG subbands (delta, theta, alpha and beta); LEOG, REOG and EMG signals were applied to the ANN for training and testing the system which gives three Situations for the vigilance level of the subject: Awake, drowsy, and sleep. The accuracy of estimation is about 97-98% while the accuracy of the previous study which used only EEG was 95-96% and the study which used EEG with EMG was 98-99%. The reason of decreasing the percentage of present study according to the last study is because of the increase of the input data. (C) 2008 Elsevier Ltd. All rights reserved.
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    Development of a High Gain, Dual-Band and Two-Layer Miniaturized Microstrip Antenna for 5.8 GHz ISM and 10 GHz X-Band Applications
    (Applied Computational Electromagnetics Soc, 2019) Atas, Isa; Abbasov, Teymuraz; Kurt, Muhammed B.
    In this study, it is explained how to increase the gain of a two-layer stacked miniaturized microstrip patch antenna (MPA) operating at 5.8 GHz and 10 GHz step by step by combining several different methods used in the literature for performance improvement of MPAs. A commonly used FR4 substrate material was preferred to design and produce the antenna. For electromagnetic modeling of the prototype structure, numerical analysis, and optimization, ANSYS HFSS was used. The performance of the proposed antenna was evaluated in terms of return loss (RL), surface current distribution, radiation patterns and gain/directivity. To confirm the study, the simulation results were compared with the measurements taken over the antenna prototype and good agreement has been achieved. The peak gain values of the proposed antenna at 5.8 GHz and 10 GHz are obtained as 4.11 dBi and 7.15 dBi, respectively.
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    Estimating vigilance level by using EEG and EMG signals
    (Springer London Ltd, 2008) Akin, Mehmet; Kurt, Muhammed B.; Sezgin, Necmettin; Bayram, Muhittin
    We developed a new method for estimation of vigilance level by using both EEG and EMG signals recorded during transition from wakefulness to sleep. Previous studies used only EEG signals for estimating the vigilance levels. In this study, it was aimed to estimate vigilance level by using both EEG and EMG signals for increasing the accuracy of the estimation rate. In our work, EEG and EMG signals were obtained from 30 subjects. In data preparation stage, EEG signals were separated to its subbands using wavelet transform for efficient discrimination, and chin EMG was used to verify and eliminate the movement artifacts. The changes in EEG and EMG were diagnosed while transition from wakefulness to sleep by using developed artificial neural network (ANN). Training and testing data sets consist of the subbanded components of EEG and power density of EMG signals were applied to the ANN for training and testing the system which gives three situations for the vigilance level of the subject: awake, drowsy, and sleep. The accuracy of estimation was about 98-99% while the accuracy of the previous study, which uses only EEG, was 95-96%.
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    An Experimental Performance Investigation of an Ultra-Wideband Directional Antenna in the Microwave Imaging of Breast Cancer Tumor
    (Applied Computational Electromagnetics Soc, 2019) Celik, Ali R.; Kurt, Muhammed B.; Helhel, Selcuk
    The purpose of this study is testing the performance and success of a compact-sized, ultrawide-band and directional printed circular monopole antenna proposed in a previous study for detection of the small breast cancer tumors. For this aim, simple but basic experimental studies of the radar based ultra-wideband microwave measurement system are presented. In the measurements, different breast phantoms that have low dielectric constant materials representing the fat tissue and high dielectric constant object representing the tumor are formed and used. The object is located at different positions and the reflected signals are observed. The mono-static system which uses the same antenna to perform both the transmitting and receiving task of the signals is preferred in the study. According to the measured frequency domain signals, the reflected energy increases when the tumor is present. According to the amplitude and phase of the time domain signals, the presence, position and size of the tumor are inferenced. In order to provide more clear information about the tumor, a sample image is also created by implementing delay-and-sum algorithm. Furthermore, specific absorption rate of the breast is discussed. In summary, the performance of the antenna is valid for using in the radar-based ultra-wideband microwave imaging with respect to its features of the size, bandwidth, directivity, and beamwidth.