Yazar "Sonmez, Yasin" seçeneğine göre listele

Listeleniyor 1 - 2 / 2
  • [ X ]
    Öğe
    Phishing Web Sites Features Classification Based on Extreme Learning Machine
    (Ieee, 2018) Sonmez, Yasin; Tuncer, Turker; Gokal, Huseyin; Avci, Engin
    Phishing are one of the most common and most dangerous attacks among cybercrimes. The aim of these attacks is to steal the information used by individuals and organizations to conduct transactions. Phishing websites contain various hints among their contents and web browser-based information. The purpose of this study is to perform Extreme Learning Machine (ELM) based classification for 30 features including Phishing Websites Data in UC Irvine Machine Learning Repository database. For results assessment, ELM was compared with other machine learning methods such as Support Vector Machine (SVM), Naive Bayes (NB) and detected to have the highest accuracy of 95.34%
  • [ X ]
    Öğe
    Quality of online communication tools at hospitals and their effects on health service consumers' preferences
    (Routledge Journals, Taylor & Francis Ltd, 2020) Gumus, Rojan; Sonmez, Yasin
    The purpose of this study is to determine the quality of online services at hospitals and their effects on consumers' preferences. In the first stage, a survey was administered to 442 individuals living in stanbul, Turkey. In the second stage, based on 442 health consumers' priorities regarding online health services at hospitals, a checklist, including four dimensions (i.e. Ease of Use, Credentials of the Institution, External Activities and Technical Features) and 39 items was created. The findings indicated that, among the top 100 private hospitals in stanbul, 25% received an excellent rating, while 45% and 35% were ranked as good and fair, respectively. In addition, the frequency of Internet usage was positively correlated with education (r=0.121, p<0.05), while the participants that visited the hospitals' webpages were more affected by their organization (r=0.100, p<0.05) and design (r=0.278, p<0.01). Furthermore, a positive correlation was found between the users' hospital ratings and the evaluated scores of the hospitals (r=0.467, p<0.01). The implication of these findings is that online services offered by hospitals can have a significant influence on health consumers' hospital preferences.