• EEG channel selection using differential evolution algorithm and particle swarm optimization for classification of odorant-stimulated records 

  Şeker, Mesut; Özerdem, Mehmet Siraç (INESEG Yayıncılık, 2021)

  A significant advancement has been made in the evolutionary computing and swarm intelligence methods in past decades. These methods have been commonly used to calculate well optimized solutions. Methods select the best ...

• Statistical analysis and modeling of charging time in radio frequency energy harvesting systems 

  Cansız, Mustafa (Springer, 2022)

  In this study, charging time in RF energy harvesting systems is measured and statistically analyzed. The measurement system is carried out using an RF energy harvesting circuit, transmitters as RF sources, a patch antenna ...

• A deep learning approach in automated detection of schizophrenia using scalogram images of EEG signals 

  Aslan, Zülfikar; Akın, Mehmet (Springer, 2022)

  This study presents a method with high accuracy performance that aims to automatically detect schizophrenia (SZ) from electroencephalography (EEG) records. Unlike related literature studies using traditional machine learning ...

• Determining optimal SVC location for voltage stability using multi-criteria decision making based solution: Analytic hierarchy process (AHP) approach 

  Aydın, Faruk; Gümüş, Bilal (IEEE-Institute of Electrical Electronics Engineers INC., 2021)

  Due to latest blackouts in the world, voltage instability and voltage collapse have become the main issues studied in electrical power systems. For this purpose, various Flexible AC Transmission Systems (FACTS) devices ...

• Detection of eccentricity fault based on vibration in the PMSM 

  Çıra, Ferhat (Elsevier B.V., 2018)

  This paper presents how to diagnose faults in static and dynamic eccentricity of a rotor by observing the vibration of permanent magnet synchronous motor. The radial electromagnetic force density of the permanent magnet ...

• I-PD controller design based on analytical rules for stable processes with inverse response 

  Kaya, İbrahim (Balkan Yayın, 2020)

  Inverse response characteristic makes the control of a process more challenging. In this study, simple and analytical expressions have been obtained to evaluate optimum settings of I-PD controllers for controlling open ...

• Aşırı öğrenme makinası yöntemi ile sürekli mıknatıslı senkron motorun moment verileri kullanılarak sargı izolasyonu arızasının tespiti 

  Çıra, Ferhat (TMMOB Elektrik Mühendisleri Odası, 2019)

  Elektrik makinalarının arızalarının erken tespitinin yapılmaması, felaketle sonuçlanabilecek arızalara neden olduğu bilinmektedir. Endüstride en çok kullanılan motorların asenkron motorlar olması sebebiyle durum izleme ve ...

• Şizofrenik ve sağlıklı EEG zaman serilerinin sınıflandırılması ve istatistiksel analizi 

  Şeker, Delal; Özerdem, Mehmet Siraç (IEEE-Institute of Electrical Electronics Engineers INC., 2020)

  Bu çalışmada sağlıklı ve şizofrenik EEG zaman serilerinin lineer öznitelikler kullanılarak farklı sınıflandırma yöntemleri ile ayırt edilmesi amaçlanmıştır. Bu amaçla 39 şizofreni hastası ve 39 sağlıklı kişiden 16 kanallı ...

• Şizofreni teşhisinde bir nöro-isaretçi olarak EEG uyumluluğu 

  Şeker, Mesut; Özerdem, Mehmet Siraç (IEEE-Institute of Electrical Electronics Engineers INC., 2020)

  Bu deneysel çalışmada, şizofreni (sch) hastalığı tespitinde EEG uyumluluk tabanlı bir yaklaşım önerilmiştir. Bu bağlamda 16 kanallı EEG sisteminde 6 inter-hemisferik, 3 sol ve 3 sağ intra-hemisferik elektrot çiftleri ...

• Hilbert dönüşümü kullanılarak EEG işaretlerinden kanal bazlı şizofren hastalığının tespiti 

  Türk, Ömer; Özerdem, Mehmet Siraç; Şeker, Mesut (Türkiye Bilişim Vakfı, 2020)

  Elektroensefalografi (EEG) nörolojik hastalıkların tespitinde sahip olduğu çok kanallı ve yüksek zaman çözünürlüklü yapısı ile çalışmalarda etkili bir görüntüleme aracı olarak popülerliğini korumaktadır. Bu çalışmada, ...

• Derin transfer öğrenimi yaklaşımı ile kamusal alanda medikal maske kullanımının otomatik kontrolü 

  Polat, Hasan; Özerdem, Mehmet Siraç (Bingöl Üniversitesi Fen Bilimleri Enstitüsü, 2021)

  Uluslararası kamu sağlığı acil durumu olan COVID-19 hastalığının başlıca bulaşma yolları, solunum damlacıkları ve fiziksel temastır. Hastalığın yayılımını önlemek ve salgınla mücadele etmenin kapsamlı stratejilerinden biri ...

• Spherical plasma focus operated with nitrogen and neon gases for soft x-rays (bremsstrahlung radiation, line radiation, and radiative recombination) 

  Ay, Yaşar (IOP Publishing Ltd., 2021)

  X-ray emissions (bremsstrahlung radiation, line radiation, and radiative recombination) from spherical plasma focus (SPF) device are investigated with the developed spherical MHD model for nitrogen (N) and neon (Ne) gases ...

• The convolutional neural network approach from electroencephalogram signals in emotional detection 

  Türk, Ömer; Özerdem, Mehmet Siraç (Wiley, 2021)

  Although brain-computer interfaces (BCI) progress rapidly, the desired success has not been achieved yet. One of these BCI is to detect emotional states in humans. An emotional state is a brain activity consisting of ...

• Extreme learning machine (ELM)-based classification of benign and malignant cells in breast cancer 

  Toprak, Abdullah (International Scientific Information, Inc., 2018)

  Background: Breast cancer is one of the most common cancer types in the world and is a serious threat to health. This type of cancer is complex; it is a hereditary disease and does not result from a single cause. The ...

• Automatic detection of cursor movements from the EEG signals via deep learning approach 

  Polat, Hasan; Özerdem, Mehmet Siraç (IEEE-Institute of Electrical Electronics Engineers INC., 2020)

  The classification of motor imagery (MI) tasks is one of the key objectives of EEC-based brain-computer interface (BC!) systems. To ensure successful classification performance to BCI systems, researchers endeavor to extract ...

• Fault detection in photovoltaic arrays via sparse representation classifier 

  Kılıç, Heybet; Khaki, Behnam; Gümüş, Bilal; Yılmaz, Musa; Palensky, Peter (IEEE-Institute of Electrical Electronics Engineers INC., 2020)

  In recent years, there has been an increasing interest in the integration of photovoltaic (PV) systems in the power grids. Although PV systems provide the grid with clean and renewable energy, their unsafe and inefficient ...

• Analysis of epileptic iEEG data by applying convolutional neural networks to low-frequency scalograms 

  Bayram, Muhittin; Arserim, Muhammet Ali (IEEE-Institute of Electrical Electronics Engineers INC., 2021)

  In this paper, Convolutional Neural Networks (CNN) method was applied to low frequency scalograms in order to contribute to the development of diagnostic and early diagnosis systems of epileptic intracranial EEG (iEEG) ...

• Empirical mode decomposition and convolutional neural network-based approach for diagnosing psychotic disorders from eeg signals 

  Aslan, Zülfikar; Akın, Mehmet (Springer, 2022)

  Psychotic disorders are mental disorders that negatively affect human life. Diagnosis of psychotic patients is usually done in consultation with the patient, and this is a time-consuming process. In this study, a Computer ...

• Determining similarities of COVID-19-lung cancer drugs and affinity binding mode analysis by graph neural network-based GEFA method 

  Budak, Cafer; Mençik, Vasfiye; Gider, Veysel (Taylor & Francis, 2021)

  COVID-19 is a worldwide health crisis seriously endangering the arsenal of antiviral and antibiotic drugs. It is urgent to find an effective antiviral drug against pandemic caused by the severe acute respiratory syndrome ...

• Epilepsy detection by using scalogram based convolutional neural network from eeg signals 

  Türk, Ömer; Özerdem, Mehmet Siraç (MDPI AG, 2019)

  The studies implemented with Electroencephalogram (EEG) signals are progressing veryrapidly and brain computer interfaces (BCI) and disease determinations are carried out at certainsuccess rates thanks to new methods ...

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