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An Approach for Cardiac Coronary Detection of Heart Signal Based on Harris Hawks Optimization and Multichannel Deep Convolutional Learning

Cevat Rahebi

Automatic diagnosis of arrhythmia by electrocardiogram has a significant role to play in preventing and detecting cardiovascular disease at an early stage. In this study, a deep neural network model based on Harris hawks optimization is presented to arrive at a temporal and spatial fusion of information from ECG signals. Compared with the initial model of the multichannel deep neural network mechanism, the proposed model of this research has a flexible input length; the number of parameters is halved and it has a more than 50% reduction in computations in real-time processing. The results of t ...Daha fazlası

Makale 2022 Computational Intelligence And Neuroscience2022 ( 1 ) 183 Görüntülenme

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Examination on the current conduction mechanisms of Au/n-Si diodes with ZnO-PVP and ZnO/Ag2WO4 -PVP interfacial layers

İlke Taşçıoğlu

This study reports a comparative characterization of Au/n-Si Schottky diodes/contacts (SDs) with hydrothermally synthesized ZnO-PVP and ZnO/Ag2WO4-PVP interfacial layers, which outperforms conventional metal-semiconductor Schottky diode structures. This characterization is important because these structures outperform traditional metal-semiconductor Schottky diodes due to the presence of an interfacial layer, allowing barrier height control, surface passivation, and leakage current reduction. Based on the thermionic emission (TE) theory assumed to be the dominant current mechanism across, SDs ...Daha fazlası

Makale 2023 Journal Of Sol-Gel Science And Technology107 ( 3 ) , pp. 5 - 547 20 Görüntülenme

Süresiz Ambargo

A local-holistic graph-based descriptor for facial recognition

Metin Zontul

Face recognition remains critical and up-to-date due to its undeniable contribution to security. Many descriptors, the most vital figures used for face discrimination, have been proposed and continue to be done. This article presents a novel and highly discriminative identifier that can maintain high recognition performance, even under high noise, varying illumination, and expression exposure. By evolving the image into a graph, the feature set is extracted from the resulting graph rather than making inferences directly on the image pixels as done conventionally. The adjacency matrix is create ...Daha fazlası

Makale 2022 MULTIMEDIA TOOLS AND APPLICATIONS82 ( 13 ) , pp. 1 - 19298 179 Görüntülenme Süresiz Ambargo

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TÜRKİYE DEVLET TAHVİL PİYASASININ EKONOMİK BÜYÜME ÜZERİNDEKİ ETKİSİ

Aref Yelghı

Günümüze gelindiğinde devletlerin finansal gereksinimlerinin giderilmesi içinbaşvurdukları önemli yollardan biri tahvil ihracıdır. Türkiye’de tahvil piyasasındanen çok devletin yararlandığı görülmektedir. Literatürde ekonomik büyüme ile hissesenedi piyasası ve kredi arasında birçok çalışma bulunurken tahvil piyasası ile ilgilioldukça az çalışma yapılmıştır. Finansal piyasalarında tahvil piyasası önemli payalması ve ekonomik büyümesinde etkisi ne ölçüde oluğu merak edilmektedir. Sondönemlerde tahvil piyasasının gelişimi hem ulusal hem uluslararası piyasada hızkazanmıştır. Bu çalışmada Türkiye t ...Daha fazlası

Makale 2021 Doğuş Üniversitesi Dergisi 86 Görüntülenme

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Face Recognition System using Histograms of Oriented Gradients and Convolutional Neural Network based on with Particle Swarm Optimization

Cevat Rahebi

In this paper, Histograms of Oriented Gradients dependent on the strong point of convolutional neural organization which is new methodology for evenness face data set, is introduced. A proposed face acknowledgment framework was created to be utilized for various purposes. We utilized Gabor wavelet change for include extraction of evenness face preparing information and afterward we utilized profound learning technique for acknowledgment. We executed and assessed the proposed strategy on ORL and YALE data sets with Matlab 2020b. Besides, similar trials were directed applying Particle Swarm Opti ...Daha fazlası

Bildiri 2021 Institute of Electrical and Electronics Engineers Inc. 147 Görüntülenme

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Estimation single output with a hybrid of ANFIS and MOPSO_HS

Aref Yelghı

Adaptive Neuro-Fuzzy Inference System (ANFIS) has gained popularity in recent years due to its predictive capabilities. Proper adjustment of ANFIS parameters is an optimization problem but integrating it with traditional optimization techniques has led to challenges such as local minima and slow convergence, resulting in obstacles to its prediction. Additionally, some researchers focusing on incorporating single-objective optimization often face issues with reliability and stability in parameter adjustment. This study, focused on multi-objective optimization, presents an algorithm that integra ...Daha fazlası

Makale 2024 Sakarya Universit7 ( 1 ) , pp. 1 - 126 14 Görüntülenme

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Harris Hawks Optimization (HHO) Algorithm based on Artificial Neural Network for Heart Disease Diagnosis

Cevat Rahebi

Signal processing methods usually diagnose heart disease, and the diagnosis of this type of disease by signal processing sometimes encounters many difficulties. To reduce diagnostic problems, careful feature selection and training are needed to analyze these signals. In this study, an attempt has been made to combine machine learning skills, such as neural network learning, with the Harris Hawks Optimization method to diagnose heart disease. In this paper, the heart disease diagnosis is analyzed with the feature selection method. For feature selection, the Harris Hawks Optimization Algorithm b ...Daha fazlası

Bildiri 2021 IEEE 305 Görüntülenme Süresiz Ambargo

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Parametrized hyperbolic tangent based Banach space valued multivariate multi layer neural network approximations

Seda Karateke

Here we examine the multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or R N , N ∈ N, by the multivariate normalized, quasi-interpolation, Kantorovich type and quadrature type neural network operators. We research also the case of approximation by iterated operators of the last four types, that is multi hidden layer approximations. These approximations are achieved by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high order Fr´echet derivatives. Our ...Daha fazlası

Makale 2023 Journal of Computational Analysis and Applications31 ( 4 ) , pp. 4 - 519 127 Görüntülenme

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Some New Results on Bicomplex Bernstein Polynomials

Seda Karateke

The aim of this work is to consider bicomplex Bernstein polynomials attached to analytic functions on a compact C2-disk and to present some approximation properties extending known approximation results for the complex Bernstein polynomials. Furthermore, we obtain and present quantitative estimate inequalities and the Voronovskaja-type result for analytic functions by bicomplex Bernstein polynomials.

Makale 2021 Mathematıcs9 ( 21 ) 165 Görüntülenme

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Brain magnetic resonance image (MRI) segmentation using multimodal optimization

Taymaz Akan

One of the highly focused areas in the medical science community is segmenting tumors from brain magnetic resonance imaging (MRI). The diagnosis of malignant tumors at an early stage is necessary to provide treatment for patients. The patient’s prognosis will improve if it is detected early. Medical experts use a manual method of segmentation when making a diagnosis of brain tumors. This study proposes a new approach to simplify and automate this process. In recent research, multi-level segmentation has been widely used in medical image analysis, and the effectiveness and precision of the segm ...Daha fazlası

Makale 2024 Multimedia Tools and Applications 2 Görüntülenme

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Vector quantization using whale optimization algorithm for digital image compression

Cevat Rahebi

Today, much of the information is storing in images. To transfer information in the form of images, image compression is required. Compressing images reduces the size of images and sends them faster over the network. One of the most methods of image compression is the vector quantization. For vector quantization compression, the codebook is using in cryptography and decryption. The vector quantization compression method typically uses codebooks that are not optimized, which reduces the compression quality of the images. Choosing the optimal codebook makes compression of images with higher qual ...Daha fazlası

Makale 2022 Multimedia Tools And Applications81 ( 14 ) , pp. 2 - 20103 77 Görüntülenme Süresiz Ambargo

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Health-Care Monitoring of Patient using CNN based Model in Internet of Things

Cevat Rahebi

There is rising public concern about exposure to radiofrequency (RF) electromagnetic fields (EMF) as more and more wireless communications become concentrated in everyday living surroundings. There are a number of obstacles, primarily originating from infrastructure expenses, but recent technology breakthroughs are shifting attention to Internet of Things (IoT) devices that enable automatic and continuous realtime EMF monitoring. The Internet of Things (IoT) has made the world a better place by expanding the capabilities of telemedicine and allowing for more precise remote monitoring of patie ...Daha fazlası

Konferans Kağıdı 2023 IEEE Xplore 20 Görüntülenme Süresiz Ambargo