Murat Karabatak

• Fırat University

Obesity, characterized by an excessive increase in body fat, is not only a significant disease but also a condition that serves as the basis for many other illnesses. Therefore, early intervention and necessary precautions for diagnosing and treating obesity are of paramount importance. Classical machine learning algorithms are actively utilized in...

Thanks to the technologies that have become a part of daily life, huge data piles are formed in almost every field. Research on detecting hidden patterns in big data and discovering useful information has gained importance. The amount of data accumulated in the field of education has enabled data mining techniques to come to the fore in this field...

Schizophrenia is a serious chronic mental disorder that significantly affects daily life. Electroencephalography (EEG), a method used to measure mental activities in the brain, is among the techniques employed in the diagnosis of schizophrenia. The symptoms of the disease typically begin in childhood and become more pronounced as one grows older. H...

The advent of deep learning has revolutionized computer vision, enabling real-time analysis crucial for traffic management and vehicle identification. This research introduces a system combining vehicle make and model detection with Automatic Number Plate Recognition (ANPR), achieving a groundbreaking 97.5% accuracy rate. Unlike traditional methods...

Software development processes are continuously evolving and rapidly transforming alongside the rapid changes in technology. Recently, innovations in the field of Artificial Intelligence (AI) have led to significant changes in software development practices. AI tools can greatly enhance traditional software development processes by offering develop...

Software that enables realtime buy and sell transactions in financial markets according to predetermined conditions is called algorithmic trading. When developing algorithmic trading robots, indicators used in technical analysis are generally used. For the strategy selection of the robot, a process called Backtest is performed on the historical tim...

This study aimed to perform a sample educational data mining (EDM) application to draw attention to its EDM predictive power. The data set consisted of the opinions collected from university students. These data set variables were formed by distance education students' academic self-efficacy, sense of community, academic achievement averages, and s...

The electrocardiogram (ECG) is the most common technique used to diagnose heart diseases. The electrical signals produced by the heart are recorded by chest electrodes and by the extremity electrodes placed on the limbs. Many diseases, such as arrhythmia, cardiomyopathy, coronary heart disease, and heart failure, can be diagnosed by examining ECG s...

There are two main benefits of using fundamental analysis for investors and portfolio managers. First, investing in a company with good ratios has lower risks. The second reason is that it is possible to evaluate share prices with internal valuation methods based on ratios. These price valuations can be more meaningful when combined with technical...

The automated segmentation of dental restorations is a critical step in diagnosing dental problems and suggesting the best treatment. Some restorations may be missed during a dental examination, depending on the number of patients, the dentist's experience, and fatigue. Automatic detection of dental restorations based on deep learning has the poten...

Prostate cancer (PCa) is the most common type of cancer among men. Digital rectal examination and prostate-specific antigen (PSA) tests are used to diagnose the PCa accurately. Since PSA is organ-specific and not disease-specific, multiparametric magnetic resonance imaging (mpMRI) is used to reduce unnecessary biopsies. Prostate imaging reporting a...

Today, manual investments in exchanges such as crypto, spot, futures and forex are quickly replaced by algorithmic transactions. Algorithmic transactions automatically send electronic buy/sell commands from the investor's portfolio to the financial stock market when conditions occur, depending on previously developed algorithms. These algorithmic t...

Text analysis is a general term for extracting valuable data from written data. Today, many applications develop approaches based on text analysis for purposes such as customer satisfaction determination, advertising and suggestion system development. Similarly, text analysis can be used in the evaluation of financial investments when the price of...

Hypertension (HTN) is a major risk factor for cardiovascular diseases. At least 45% of deaths due to heart disease and 51% of deaths due to stroke are the result of hypertension. According to research on the prevalence and absolute burden of HTN in India, HTN positively correlated with age and was present in 20.6% of men and 20.9% of women. It was...

Atrial fibrillation (AF) is a common arrhythmia that can lead to stroke, heart failure, and premature death. Manual screening of AF on electrocardiography (ECG) is time-consuming and prone to errors. To overcome these limitations, computer-aided diagnosis systems are developed using artificial intelligence techniques for automated detection of AF....

Background and objective Artificial intelligence‐based analysis of medical images has recently become a trendy field of study. The most significant effect on these systems to produce reliable and high‐performance results is the amount of accessed data. Although whole‐slide images (WSI), one of the current imaging techniques used in histopathology,...

This study aimed to examine the problems experienced by senior students studying at education faculties in the distance Teaching practice (DTP) course, where they participated in practice activities in formal schools due to the Covid-19 pandemic, and the suggestions for solving them. To achieve this aim, the students' opinions, who were determined...

During the pandemic, undergraduate students had to motivate, control, and monitor themselves more than students at other education levels. At this point, the importance of self-directed learning skills that individuals are expected to have has become more evident. For this reason, this research aimed to determine the self-directed learning skill le...

Over the years, there is an increase in the use of artificial intelligence (AI) by digital forensics and cybersecurity professionals to combat cybercrime. Natural Language Processing (NLP) and AI applications for digital forensics and cybersecurity include data mining, knowledge representation, pattern recognition, and expert systems. This research...

Kidney stones are the common complaint worldwide, causing many people to admit to emergency rooms with severe pain. Various imaging techniques are used for the diagnosis of kidney stone disease. Specialists are needed for the interpretation and full diagnosis of these images. Computer-aided diagnosis systems are the practical approaches that can be...

The purpose of this study is to reveal the effects of homework supported distance education on students' academic achievement, academic satisfaction, and attitudes towards distance education. This study was performed with a quantitative paradigm. In this context, repeated measures design was used. The purposeful sampling method was used to determin...

With the growth and increasing sophistication of the Internet and the increasing dependence, it appeared more and more services over the Internet-based database, so it increases the risks facing databases. The number of attacks against these repositories has also increased. A database danger refers to an item, individual or other entity that poses...

The emergence of databases has become one of the most important achievements in the field of software. Databases are at the core of information systems (Online and Offline), and this has fundamentally made them a target for malicious intents because they contain sensitive information. Digital forensics tends to outwit such malicious activities by p...

Advances in artificial intelligence technologies have made it possible to obtain more accurate and reliable results using digital images. Due to the advances in digital histopathological images obtained using whole slide image (WSI) scanners, automated analysis of digital images by computer support systems has become interesting. In particular, dee...

Data generated by computer systems are worthless, because they do not make sense when viewed with the naked eye [1, 2]. When this data is processed for a particular purpose, it starts to make sense. Therefore, it is important to use techniques that can process large amounts of data. Transformation of this raw data into information or meaning can be...

In the last decade, neutrosophic sets (NS), which are defined as the generalization of the interval fuzzy sets, become a hot topic in computer vision and machine learning communities with a numerous of applications. The researchers, who are in the field of computer-vision, have applied NS on various image processing applications. Segmentation is a...

Electroencephalogram (EEG) is a useful tool that measures the change in electrical activity of the human brain. EEGs can be used for identification of the various brain disorders such as epilepsy. Partial epilepsy, which affects some portions of the brain, is called the epileptogenic area. While the epileptogenic area is used for recording of the F...

Data generated by computer systems are worthless, because they do not make sense when viewed with the naked eye (Albayrak & Yılmaz, 2009) (Batan, 2012). When this data is processed for a particular purpose, it starts to make sense. Therefore, it is important to use techniques that can process large amounts of data. Transformation of this raw data i...

Phishing is the learning of personal data (credit card information, passwords, etc.) by illegal means. Fake e-mails or websites are made to steal this data. In this application, the data mining method Apriori Algorithm (AP) was applied to the data of Phishing Websites determined from the UCI database with the support of the WEKA data mining program...

Steganografi kelimesi, “örtülü, gizli veya korumalı” anlamına gelen steganların (στεγανός) ve “yazı” anlamına gelen grapheinin (γράφειν) birleşiminden türetilmiştir. Steganografi çalışmalarının temel amacı, gizli verilerin yetkisiz kişilerce elde edilmesini önlemektir. Steganografi yöntemlerinin temel amacını gerçekleştirmek için, kalıp dosyasında...

Ever since its development in 2005, YouTube has been providing a vital social media platform for video sharing. Unfortunately, YouTube users may have malicious intentions, such as disseminating malware and profanity. One way to do so is using the comment field for this purpose. Although YouTube provides a built-in tool for spam control, yet it is i...

In this letter, a two-stage method for airport detection on remote sensing images is proposed. In the first stage, a new algorithm composed of several line-based processing steps is used for extraction of candidate airport regions. In the second stage, the scale-invariant feature transformation and Fisher vector coding are used for efficient repres...

Breast cancer is known as the most common invasive cancer type among women and automatic breast cancer detection systems are in demand. Thus, various machine learning and pattern recognition techniques have been proposed to detect breast cancer. One of these techniques is the Bayes classifier. Naïve Bayesian (NB) is known to be a simple classifier,...

This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) model for predicting the parameter of dryer system for shelled pistachios. The most important parameter of drying system is drying time because a good drying for good quality product is provided with moisture content 5-7%. Effects of temperatures and air velocities on drying chara...

In this paper, the drying of Siirt pistachios (SSPs) in a newly designed fixed bed dryer system and the prediction of drying characteristics using artificial neural network (ANN) are presented. Drying characteristics of SSPs with initial moisture content (MC) of 42.3% dry basis (db) were studied at different air temperatures (60, 80, and 100 °C) an...

The wavelet domain association rules method is proposed for efficient texture characterization. The concept of association rules to capture the frequently occurring local intensity variation in textures. The frequency of occurrence of these local patterns within a region is used as texture features. Since texture is basically a multi-scale phenomen...

In this work, a rotational invariant image template matching method based on log-polar transform and phase only correlation is presented. The method is composed of two stages. While applying the 2nd Hanning window is formed the first stage, several steps, for phase-based rotational image template matching constitutes the second stage. MATLAB is use...

In this paper, a new feature selection method based on Association Rules (AR) and Neural Network (NN) is presented for the diagnosis of erythemato-squamous diseases. AR is used for reducing the dimension of erythemato-squamous diseases dataset and NN is used for efficient classification. The proposed AR+NN system performance is compared with that o...

This paper presents an automatic diagnosis system for detecting breast cancer based on association rules (AR) and neural network (NN). In this study, AR is used for reducing the dimension of breast cancer database and NN is used for intelligent classification. The proposed AR + NN system performance is compared with NN model. The dimension of input...

This paper presents an expert diagnosis system for detecting breast cancer based on Principle Component Analysis (PCA). In this study, PCA is used for reducing the dimension of breast cancer database and Adaptive Network Based Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) are used for intelligent classification respectively. In...

Texture is an important characteristic for analysis of many types of images that including natural scenes, remotely sensed data and biomedical modalities. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. In this study, multi resolution approaches such as wavelet transf...

Texture can be defined as a local statistical pattern of texture primitives in observer's domain of interest. Texture classification aims to assign texture labels to unknown textures, according to training samples and classification rules. Association rules capture both structural and statistical information, and automatically identify the structur...