Hacer (Uke) Karacan

Gazi University · Department of Computer Engineering

Background/Objectives: Attention-Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivity. Traditional diagnostic methods, which depend on subjective assessments, often lack precision. This study evaluates the validity and reliability of a newly developed diagnosti...

In an era in which cardiovascular disease has become the main cause of death all over the world, diagnostic accuracy in identifying blood vessels has become particularly important. Vascular stenosis causes serious health risks by affecting blood flow, leading to conditions like heart attacks and strokes. Traditional diagnostic methods face challeng...

Hamilelik döneminde kadınlar, oluşabilecek komplikasyonlar açısından yüksek risk altında bulunur. Bu riskler birçok zaman düşük ve ölümle sonuçlanmaktadır. Bu yüzden de hamilelik boyunca ve hamilelikten önce kadın sağlığı hem anne hem çocuk için önemli rol oynamaktadır. Doğumdan önce ve sonra, anne ve bebeğin sağlık takibi, oluşabilecek riskleri en...

In the field of unmanned systems, the combination of artificial intelligence with self-operating functionalities is becoming increasingly important. This study introduces a new method for autonomously detecting humans in indoor environments using unmanned aerial vehicles, utilizing the advanced techniques of a deep learning framework commonly known...

Users' personality traits can provide different clues about them in the Internet environment. Some areas where these clues can be used are law enforcement, advertising agencies, recruitment processes, and e-commerce applications. In this study, it is aimed to create a dataset and a prediction model for predicting the personality traits of Internet...

Reviews and reputation scores of sellers play an important role in decision-making process of potential buyers in an e-commerce system. A trustworthy and reliable reputation system is a crucial component in the e-commerce ecosystem, as buyers rely on it to make informed decisions. In this work, we propose a privacy-preserving decentralized reputati...

Günümüz gelişen teknolojisiyle birlikte yapay zekâ kullanımı artmıştır. Bu durumun çoğunlukla faydaları üzerine konuşulsa da kişisel veri mahremiyetine ve güvenliğine olumsuz etkisi göz ardı edilmemelidir. Çünkü yapay zekâ için ham madde olan veriler, kişilerin mahremiyet haklarına aykırı durumlara neden olabilmektedir. Bu doğrultuda ilgili çalışma...

E-ticaret işlemlerinde satıcı firmaların sunduğu ticari kimlik, sertifika, ruhsat, akreditasyon belgesi, kalite belgesi gibi belgelerin doğruluğunun kanıtlanmasındaki zorluklar, e-ticaret ile yapılan alışverişlerde güven sorununa yol açmaktadır. Dijital ortamda sunulan bu belgeler, genellikle kağıt ortamında alınmış olan fiziksel belgelerin görsell...

Detecting web attacks is a major challenge, and it is observed that the use of simple models leads to low sensitivity or high false positive problems. In this study, we aim to develop a robust two-stage deep learning based stacked ensemble web application firewall. Normal and abnormal classification is carried out in the first stage of the proposed...

There is a need to obtain more information about target audiences in many areas such as law enforcement agencies, institutions, human resources, and advertising agencies. In this context, in addition to the information provided by individuals, their personal characteristics are also important. In particular, the predictability of personality traits...

Solunum sistemine etki eden ve ileri vakalarda ölüme neden olan korona virüs salgını yaklaşık iki yıldır devam etmektedir. Her ülkenin salgın ile mücadele yöntemi farklı olmasına rağmen ortak izlenen metot ise hastalığın tespiti ve izolasyonudur. Tespit ve izolasyon için en kritik adım ise COVID-19 tanısının doğru ve hızlı konulmasıdır. Akciğer X-R...

Web applications are often exposed to attacks because of the critical information and valuable assets they host. In this study, Bi-LSTM based web application security models were developed in order to detect web attacks and classify them into binary or multiple classes using HTTP requests. A novel data augmentation technique based on the self-adapt...

The COVID-19 pandemic, which emerged at the end of 2019, continues to be effective. Although various vaccines have been developed, uncertainties remain over vaccine sharing, supply, storage and effect. The tendency of some countries to keep the developed vaccines only for their own citizens and using them as a political leverage shows that the pand...

Recommendation systems (RSs) are tools for interacting with large and complex information spaces. They provide a personalized view of such spaces, prioritizing items likely to be of interest to the user. The main objective of RSs is to tool up users with desired items that meet their preferences. A major problem in RSs is called: “cold-start”; it i...

Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems by alleviating RSs drawbacks. The most common limitations are sparsity and the cold-start problem. This article proposes two models to mitigate the effects of these limitations. The propos...

Matlab code of our article entitled "Kd-tree and adaptive radius (KD-AR Stream) based real-time data stream clustering".

The development of Web 2.0 and the rapid growth of available data have led to the development of systems, such as recommendation systems (RSs), that can handle the information overload. However, RS performance is severely limited by sparsity and cold-start problems. Thus, this paper aims to alleviate these problems. To realize this objective, a new...

Data stream clustering is one of the most popular topics of today's world where the amount of data reaches incredible levels in parallel with technological developments. The most important problems encountered in data stream clustering approaches are the fact that most of the approaches consists of an online and offline phases, the definition of th...

Sliding window based data summarization which is a quantity based summarization is commonly used in data stream clustering area in which the recent data is more important. In this data summarization method, w which is a predefined variable, of the most recent data is taken as the summary each time a new data arrives and the window slides one by one...

Databases are very important sources for storing huge size of data. Today, yearly produced information is expressed as multiple size of the amount that produced before. Retrieving correct data is as important as storing it. At this point, querying becomes more important. Classical SQL queries return a record only if the database has a record which...

In parallel with the development of today's technology, the amount of data that has been transferred to the computer environment has reached incredible dimensions and is increasing day by day. For this reason, the methods of data processing are also changing. In classical data clustering approaches, data is static. However, in today's technology in...

The increasing number of malicious web sites and attacks, along with the increase in the usage rate of web applications, cause severe damage to the end user. One of these attacks aimed at stealing personal and sensitive information is the Phishing Attack. In the published security reports, it is stated that in recent years there has been millions o...

In this paper, a new method proposed for extracting and matching the Search Result Record (SRR) data items from different search engines. The method first detects SRRs for a given Web search result. Afterwards, an SRR simplification algorithm is devised to deal with complexity of SRR Document Object Model (DOM) Trees. SRRs and their data items (or...

As a result of the continuously increasing amount of important data, the demand for information security increases daily. Steganographic techniques can play a considerable role in solving this issue, since they can hide the necessary data. Generally, audio and image files have been utilized as hiding media in this area. However, because of their li...

Recommendation Systems (RSs) are used to provide users useful and effective suggestions. Effectiveness of RSs is depend on the quality of the suggestions. In this study, a new RS based on decision tree (DT) using implicit relevance feedback have been developed for movies. User behavior as implied relevance feedback is modeled by clickstreams. The D...

In this paper, a new method proposed for finding and extracting the SRRs. The method first detects content dense nodes on HTML DOM and then extracts SRRs to suggest a list of candidate HTML DOM nodes for a given single research result Web page instance. Afterwards an evaluation algorithm has been applied to the candidate list to find the best solut...

Nowadays, the amount of stored data is constantly growing because of the increasing internet usage and the developments in magnetic medium technology. It has been more complex to analyze this increasing amount of data, therefore new methods and technologies are needed. Today, data mining, is used for solving some of these problems and making future...

The introduction of the Semantic Web in 2001 lead the way to many new ideas and technologies in computing. Data handling and sharing gained a semantic level rather than structural, facilitating the development of innovative and more helpful end-user applications. Semantics of Web information is formally defined in ontologies, making it possible for...

İnternet dolandırıcılığı, hızla gelişen ve milyonlarca kişiyi mağdur eden, milyarlarca dolarlık da bir pazar haline gelen bir suç ortamıdır. İnternet ortamı, saldırganın çok kolay bir şekilde ve arkada hemen hemen hiç iz bırakmadan kaybolabilmesini sağlayan bir ortam olduğu için bu ortamda gerçekleşen saldırılar günden güne artmaktadır. Bu sal...

Due to the software and hardware inconsistencies and security requirements during the transition between IPv4 and IPv6 protocols, an additional cost will be formed and this cost varies depending on the IPv6 support level of IT infrastructure for each country. Therefore while determining the transition strategies a cost analysis should be done for e...

Many techniques that have different intended uses are available in data mining. One of the techniques used frequently in recent years is the agglomerative hierarchical clustering analysis. In this study, an object oriented agglomerative hierarchical clustering model has been developed. Users have used the system interface easily through the interac...

In this study, we examined the mechanisms that control attention in natural scenes. We asked whether familiarity with the environment makes subjects more sensitive to changes or novel events in the scene. Previous investigation of this issue has been based on viewing 2-D images of simple objects or of natural scenes, a situation that does not accur...

An Experimental Study on the Usability of the Turkish Consumer Portal Türkiye’de yaşayan tüketicilerin, tüketici hakları konusunda bilgilendirilmesi ve çevrimiçi şikâyette bulunmalarının sağlanması amacı ile tasarlanan Türkiye Tüketici Portalı (TTP) geniş bir kullanıcı kitlesine hitap etmesi sebebiyle kullanılabilirlik seviyesi yüksek bir uygulama...

In this work, effects of stereoscopic view on object recognition and navigation performance of the participants are examined in an indoor desktop virtual reality environment, which is a two-floor virtual museum having different floor plans and 3D object models inside. This environment is used in two different experimental settings: 1) color-multipl...