Elektrik - Elektronik Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/202

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    Article
    Citation - WoS: 11
    Citation - Scopus: 14
    Detection of Movement Intention in EEG-Based Brain-Computer Interfaces Using Fourier-Based Synchrosqueezing Transform
    (World Scientific Publ Co Pte Ltd, 2021) Karakullukcu, Nedime; Yilmaz, Bulent; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Karakullukcu, Nedime; Yilmaz, Bülent; 01. Abdullah Gül University
    Patients 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.
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    Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Excitonic Interaction Amongst InP/ZnS Salt Pellets
    (Royal Soc Chemistry, 2017) Altintas, Yemliha; Yazici, Ahmet Faruk; Unlu, Miray; Dadi, Seyma; Genc, Sinan; Mutlugun, Evren; 0000-0002-6909-723X; 0000-0003-2747-7856; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği; 02.07. Malzeme Bilimi ve Nanoteknoloji Mühendisliği; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
    Salt matrix has recently been introduced as a promising robust platform for embedding colloidal quantum dots to provide them with photo stability for versatile applications. This work demonstrates the excitonic interaction amongst high efficiency colloidal InP/ZnS quantum dots embedded in a KCl salt matrix. By varying the donor acceptor ratio within the solid platform, 65% Forster Resonance Energy Transfer (FRET) efficiency was attained. Optimizing the donor : acceptor ratio, we demonstrated the first FRET-enabled Cd-free pellets for white light generation possessing a color rendering index (CRI) of 84.7, correlated color temperature (CCT) of 5347.5 K, and a high luminous efficacy of optical radiation value (LER) of 324.3 lm/W-opt. Our study of excitonic interactions within quantum dot-loaded salt matrices will open new possibilities for future versatile optoelectronic applications.
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    Conference Object
    Fusion and Analysis of PET and CT Images of Patients With Non-Small Cell Lung Cancer
    (Springer, 2016) Ayyildiz, O.; Yilmaz, B.; Karacavus, S.; Kayaalti, O.; Eset, K.; Gazeloglu, C.; Kaya, E.; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Ayyildiz, O.; Yilmaz, Bulent; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 02.05. Elektrik & Elektronik Mühendisliği
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    Prognostic Significance of the Texture Features Determined Using Three Dimensional 18F-FDG PET Images: New Potential Biomarkers
    (Soc Nuclear Medicine inc, 2016) Karacavus, Seyhan; Yilmaz, Bulent; Kayaalti, Omer; Tasdemir, Arzu; Kaya, Eser; Icer, Semra; Asyali, Musa; AGÜ, Mühendislik Fakültesi, Elektrik - Elektronik Mühendisliği Bölümü; Yilmaz, Bulent; Ayyildiz, Oguzhan; 01. Abdullah Gül University