Browsing by Author "Akan, A."

Now showing 1 - 5 of 5

Citation - WoS: 5
Citation - Scopus: 7
Classification of Alzheimer’s Dementia Eeg Signals Using Deep Learning
(SAGE Publications Ltd, 2025) Sen, S.Y.; Cura, O.K.; Yilmaz, G.C.; Akan, A.
Alzheimer’s dementia (AD) is a predominant neurological disorder arising from corruptions in brain functions and is characterized by a chronic or progressive nature. While the precise etiology of dementia remains incompletely elucidated, its manifestation is frequently associated with discernible structural and chemical alterations in the brain. Living with dementia significantly impacts individuals’ daily lives due to the resultant loss of cognitive functions. This study presents a novel method to monitor and detect AD using advanced signal processing applied to electroencephalography (EEG) signals. The intrinsic time-scale decomposition (ITD) algorithm is employed to extract proper rotation components (PRCs) from EEG signals, utilizing a 5-second EEG segment duration. The proposed method is compared with the detection of 5-second raw EEG segments using a custom one-dimensional convolutional neural network (1D CNN). Additionally, four different quartiles (Quartile 1 (Q1), Q2, Q3, and Q4) of EEG signals are considered to identify the most significant contributor to AD. Experimental results demonstrate that the ITD-based approach yields better detection performance compared to using raw EEG signals. The most promising result is achieved by the EEG-PRCs method in Q1, with an accuracy of 94.00%, sensitivity of 93.50%, and specificity of 93.90%. In contrast, the highest-performing result of the raw EEG segments method is in Q2, with an accuracy of 88.40%, sensitivity of 89.10%, and specificity of 87.60% in terms of detecting AD. © The Author(s) 2024.
Classification of Attention Deficit Hyperactivity Disorder (ADHD) by Using Statistical Features of Mr Images
(Institute of Physics Publishing, 2020) Cicek, G.; Akan, A.
The aim of this study is to minimize the human effort in the diagnosis of ADHD, and to develop an objective and reliable tool that can help physicians. Towards this direction, a model has been proposed by utilizing MRI data obtained from NPIstanbul Hospital. © IOP Publishing Ltd 2020.
Citation - WoS: 5
Citation - Scopus: 7
Detection of Olfactory Stimulus in Electroencephalogram Signals Using Machine and Deep Learning Methods
(Istanbul University, 2024) Akbuğday, Burak; Akbugday, S.P.; Sadikzade, R.; Akan, A.; Unal, S.
The investigation of olfactory stimuli has become more prominent in the context of neuromarketing research over the last couple of years. Although a few studies suggest that olfactory stimuli are linked with consumer behavior and can be observed in various ways, such as via electroencephalogram (EEG), a universal method for the detection of olfactory stimuli has not been established yet. In this study, 14-channel EEG signals acquired from participants while they were presented with 2 identical boxes, scented and unscented, were processed to extract several linear and nonlinear features. Two approaches are presented for the classification of scented and unscented cases: i) using machine learning (ML) methods utilizing extracted features; ii) using deep learning (DL) methods utilizing relative sub-band power topographic heat map images. Experimental results suggest that the olfactory stimulus can be successfully detected with up to 92% accuracy by the proposed method. Furthermore, it is shown that topographic heat maps can accurately depict the response of the brain to olfactory stimuli. © 2024 Istanbul University. All rights reserved.
Influence of Machine-Side Converter Diode Selection on the Lifetime of Type-4 Wind Turbine Power Converters
(VDE Verlag GmbH, 2024) Alişar, İ.; Demirok, E.; Akan, A.
Type-4 wind turbine power converters provide better grid compliance performance that is essential for effectively integrating more renewable energy sources into the electrical network. The lifetime of the converters should be concerned during the design and operation phases as well as efficiency of the system. In this study, a lifetime enhancement method is proposed for back-to-back connected power converters of Type-4 wind turbines. The technique is to place Si or SiC diodes with partial current ratings in parallel to existing Si diodes of IGBT modules within MSCs (machine side converters). The lifetime of back-to-back connected power converters is mostly determined by the MSC, and especially by the diodes. Therefore, any precaution which limits or decreases the diode junction temperatures will contribute to improve the lifetime of the converter system. In the study, Si and SiC devices have been evaluated and the results are benchmarked with the case having only existing Si diode of IGBT modules. The proposed method is developed and tested in PSCAD (wind turbine and converter model development) and MATLAB (thermal model development and lifetime calculations) tools. The results reveal the effectiveness of the proposed method. © VDE VERLAG GMBH · Berlin · Offenbach
Political Polarisation and the Covid-19 Crisis in Turkey
(Springer International Publishing, 2024) Akan, A.
Following the tenets and tools of Multimodal Critical Discourse Studies, this chapter investigates the discourses disseminated in two major Turkish media outlets during the COVID-19 pandemic. The chapter focuses on the controversial governmental ‘We are self-sufficient, my Turkey’ fundraising campaign and shows how the official narrative—based on Islam and the values of the Ottoman Empire—was disseminated with the help of the media outlet Sabah, ideologically close to the Islamic nationalist positions of President Erdoğan. This narrative was countered in the daily Sözcü (more akin to the Westernising stance of the political opposition) mainly by giving voice to political figures who denounced and exposed the corrupt strategies of a regime that only benefits the few. The chapter evidences the high mediatic and political polarisation of the country, the strength gained by President Erdoğan and the resistance mounted by his opponents.