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Erişime Açık

Richards’s curve induced Banach space valued multivariate neural network approximation

Seda Karateke

Here, we present multivariate quantitative approximations of Banach space valued continuous multivariate functions on a box or RN , N ∈ N, by the multivariate normalized, quasi-interpolation, Kantorovichtype and quadrature-type neural network operators. We examine also the case of approximation by iterated operators of the last four types. These approximations are achieved by establishing multidimensional Jackson type inequalities involving the multivariate modulus of continuity of the engaged function or its high-order Fréchet derivatives. Our multivariate operators are defined using a multid ...Daha fazlası

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A novel seismic vulnerability assessment for the urban roadway by using interval valued fermatean fuzzy analytical hierarchy process

Bahar Yalçın Kavuş | Tolga Kudret Karaca

Seismic activity poses significant challenges to urban road infrastructure, often resulting in road closures due to the combined effects of damaged buildings and affected road networks. In contrast, the resilience of roads is crucially important for all kinds of relief activities after an earthquake in this context, this study outlines a methodological framework for assessing the vulnerability of urban road infrastructure to seismic activity. By integrating various criteria within an Interval-valued Fermatean fuzzy Analytic Hierarchy Process framework, the approach offers a comprehensive analy ...Daha fazlası

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A cyber defense system against phishing attacks with deep learning game theory and LSTM-CNN with African vulture optimization algorithm (AVOA)

Cevat Rahebi

Phishing attacks pose a significant threat to online security, utilizing fake websites to steal sensitive user information. Deep learning techniques, particularly convolutional neural networks (CNNs), have emerged as promising tools for detecting phishing attacks. However, traditional CNN-based image classification methods face limitations in effectively identifying fake pages. To address this challenge, we propose an image-based coding approach for detecting phishing attacks using a CNN-LSTM hybrid model. This approach combines SMOTE, an enhanced GAN based on the Autoencoder network, and swar ...Daha fazlası

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Battle royale optimizer for multilevel image thresholding

Taymaz Akan

Image segmentation, the process of partitioning an image into meaningful regions, is a fundamental step in image processing, crucial for applications like computer vision, medical imaging, and object recognition. Image segmentation is an essential step of image processing that directly affects its success. Among the methods used for image segmentation, histogram-based thresholding is prevalent. Two well-known approaches to histogram-based thresholding are Otsu’s and Kapur’s methods in gray images that maximize the between-class variance and the entropy measure, respectively. Both techniques we ...Daha fazlası

Süresiz Ambargo

Human retinal optic disc detection with grasshopper optimization algorithm

Cevat Rahebi

A growing number of qualified ophthalmologists are promoting the need to use computer-based retinal eye processing image recognition technologies. There are differ- ent methods and algorithms in retinal images for detecting optic discs. Much attention has been paid in recent years using intelligent algorithms. In this paper, in the human retinal images, we used the Grasshopper optimization algorithm to implement a new automated method for detecting an optic disc. The clever algorithm is influenced by the social nature of the grasshopper, the intelligent Grasshopper algorithm. Include this algo ...Daha fazlası

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Patient privacy in smart cities by blockchain technology and feature selection with Harris Hawks Optimization (HHO) algorithm and machine learning

Haedar Al-Safi | Jorge Munilla | Cevat Rahebi

A medical center in the smart cities of the future needs data security and confidentiality to treat patients accurately. One mechanism for sending medical data is to send information to other medical centers without preserving confidentiality. This method is not impressive because in treating people, the privacy of medical information is a principle. In the proposed framework, the opinion of experts from other medical centers for the treatment of patients is received and consider the best therapy. The proposed method has two layers. In the first layer, data transmission uses blockchain. In the ...Daha fazlası

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Normalization of masseter VEMP and comparison with cervical VEMP in normal individuals

Betül Taşcı

ObjectiveThe objective of this study is to obtain normative data of the masseter vestibular-evoked myogenic potential (mVEMP) test in healthy individuals without hearing loss and dizziness and to compare the responses with the cVEMP test.MethodsTwenty healthy individuals (10 males and 10 females) aged 20-30 years without auditory and vestibular disorders participated in the study. First, mVEMP and then cVEMP tests were applied to the individuals who voluntarily participated in the study.ResultsLatency values of the air-conducted mVEMP were 15.90 +/- 1.68 ms for P1 and 25.86 +/- 1.48 ms for N1 ...Daha fazlası

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A data-driven analysis of renewable energy management: a case study of wind energy technology

Fatma Altuntaş

Renewable energy management is critical for obtaining a significant number of practical benefits. Wind energy is one of the most important sources of renewable energy. It is extremely valuable to manage this type of energy well and monitor its development. Data-driven analysis of wind energy technology provides essential clues for energy management. Patent documents are extensively used to follow technology development and find exciting patterns. Patent analysis is an excellent way to conduct a data-driven analysis of the technology under concern. This study aims to define concepts related to ...Daha fazlası

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Compression of images with a mathematical approach based on sine and cosine equations and vector quantization (VQ)

Cevat Rahebi

Compressing the image causes less memory to be used to store the images. Compressing images increases the transmission speed of compressed images in the network. Vector quantization (VQ) is one of the image compression methods. The challenge of the vector quantization method for compression is the non-optimization of the codebooks. Codebook optimization increases the quality of compressed images and reduces the volume of compressed images. Various methods of swarm intelligence and meta-heuristics are used to improve the vector quantization algorithm, but using meta-heuristic methods based on m ...Daha fazlası

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The Ideal Grandparent Scale: Validation in a Turkish Young Adults Population

Zerrin Çiğdem

Aim: The aim of this study is to examine the psychometric properties of the Turkish version of The Ideal Grandparent Scale(IGS). Method: Content and construct validity were evaluated for the psychometric measurements of the scale. In addition, language validity and reliability analyzes were performed. Results: The language and content validity of the scale was evaluated as appropriate. In the analyzes made for construct validity, item loads, variance and fit values of the scale were found to be appropriate. In addition, in the analyzes for reliability, it was determined that the cronbach alpha ...Daha fazlası

Süresiz Ambargo

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

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