4 results
Search Results
Now showing 1 - 4 of 4
Article Citation - WoS: 4Citation - Scopus: 3Role of E-government in Reducing Disasters(Uikten - Assoc information Communication Technology Education & Science, 2019) Ibrahim, Thaer; Mishra, Alok; Bostan, AtilaDisasters affect three-quarters of the world, they cause huge losses of life and property every year. Information and communication technology (ICT) - as the backbone of e-government is one of the factors that reduce the damage caused by these disasters. This paper discusses the impact of demographic factors on citizens' readiness towards ICTs and disaster management, by conducting a questionnaire form that tests the readiness of the Iraqi citizen and the extent of their interest in this technology being threatened by disaster.Article Citation - WoS: 6Citation - Scopus: 7Impact of Education on Security Practices in Ict(Univ Osijek, Tech Fac, 2015) Bostan, Atila; Akman, IbrahimIn assuring the security in information technology, user awareness and acquired-user habits are inevitable components, yet they may be qualified as the feeblest ones. As the information technology tries to put its best in providing maximum security, user awareness plays a key-role. Additionally, although the literature provides studies on approaches for teaching information security, there are not many evidences on the impact of education level. Therefore, this study investigates the impact of the education level on user security awareness in using the Information and Communication Technology (ICT) products. For this purpose, a survey was conducted among 433 citizens from different layers of the society. Interestingly, the results indicated that education level has significant impact on all security issues included in the analysis regarding computer usage, web usage and e-mail usage.Article Citation - WoS: 2Citation - Scopus: 3Implicit Learning With Certificate Warning Messages on Ssl Web Pages: What Are They Teaching?(Wiley-hindawi, 2016) Bostan, AtilaSSL-based web services are the most common technology in secure transactions on the Internet today. The security level of these services is inevitably related with that of digital certificates and user awareness. With the high number of nonconforming digital certificate usage, which eventually invokes warning messages on the Internet, users are implicitly forced to develop unsecure usage habits. In this study, we have studied the implicit learning effect of certificate warning messages on the SSL web pages. We have conducted two different experimental studies on university students and on instructors in IT departments. The results point to acquired indifference towards these warnings in users. Copyright (C) 2016 John Wiley & Sons, Ltd.Article Crack Detection on Asphalt Runway Using Unmanned Aerial Vehicle Data with Non-Crack Object Removal and Deep Learning Methods(Pontificia Univ Catolica Chile, Escuela Construccion Civil, 2025) Tapkin, Serkan; Tercan, Emre; Bostan, Atila; Sengul, GokhanUnmanned aerial vehicles are extensively utilized for image acquisition in a cheap, fast, and effective way. In this study, an automatic crack detection method with non-crack object removal and deep learning-based approaches are developed and tested on images captured by unmanned aerial vehicle. The motivation of this study is to detect either a crack exists or not in the asphalt-runway. The novelty of this study lies in integrating a non-crack artifact removal process with six classical edge detectors and comparing the resulting performance with four lightweight CNN models on the same UAV-acquired runway image dataset, enabling a unified evaluation of classical and learning-based approaches. For deep learning-based approach, four lightweight CNN models, namely GoogleNet, SqueezeNet, MobileNetv2, and ShuffleNet, are trained and the best accuracy of %87.9 is obtained whenever GoogleNet model is used. For the non-crack object removal approach, exclusion of non-crack objects from the images is the first step, where crack-detection which makes use of edge-detection techniques is the latter. In the study, Sobel, Prewitt, Canny, Laplacian of Gaussian, Roberts and Zero Cross edge detection algorithms are examined and their success rates in detecting cracks are comparatively presented. With sensitivity=0.981, specificity=0.744, accuracy=0.917, precision=0.912 and F-score=0.945 values Canny algorithm performs significantly better than others in detecting the cracks. This study provides enough evidence for the practicability of automated crack detection on unprocessed digital photographs by the results of the study conducted on asphalt runway.
