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Article Citation - WoS: 2Citation - Scopus: 3A Hybrid Approach for Semantic Image Annotation(Ieee-inst Electrical Electronics Engineers inc, 2021) Sezen, Arda; Turhan, Cigdem; Sengul, GokhanIn this study, a framework that generates natural language descriptions of images within a controlled environment is proposed. Previous work on neural networks mostly focused on choosing the right labels and/or increasing the number of related labels to depict an image. However, creating a textual description of an image is a completely different phenomenon, structurally, syntactically, and semantically. The proposed semantic image annotation framework presents a novel combination of deep learning models and aligned annotation results derived from the instances of the ontology classes to generate sentential descriptions of images. Our hybrid approach benefits from the unique combination of deep learning and semantic web technologies. We detect objects from unlabeled sports images using a deep learning model based on a residual network and a feature pyramid network, with the focal loss technique to obtain predictions with high probability. The proposed framework not only produces probabilistically labeled images, but also the contextual results obtained from a knowledge base exploiting the relationship between the objects. The framework's object detection and prediction performances are tested with two datasets where the first one includes individual instances of images containing everyday scenes of common objects and the second custom dataset contains sports images collected from the web. Moreover, a sample image set is created to obtain annotation result data by applying all framework layers. Experimental results show that the framework is effective in this controlled environment and can be used with other applications via web services within the supported sports domain.Article Citation - WoS: 3Citation - Scopus: 4Sector Diversity among IT Professionals in the Timing of Blockchain Adoption: an Attitudinal Perspective(Kaunas Univ Technol, 2022) Akman, Ibrahim; Turhan, CigdemBlockchain technology has the potential to reshape the conventional ways of processes and transactions on digital platforms. Much of the attention surrounding blockchain is mainly focused on the technical and organizational aspects. Comparatively, little effort has been targeted towards understanding the attitudinal issues in blockchain adoption. This study aims to explore the role of attitudinal forms behind the intended timing of IT professionals' blockchain adoption, with an emphasis on the differences between the public and private sectors. A survey method was used where the data was collected from 208 IT professionals from public and private sector establishments in order to investigate how the different attitudes of the participants as well as the differences in their work sectors affect their intention to adopt blockchain. The data collected was analysed with ordinal logistic regression and the results indicate that the participants' affective, normative and pessimistic attitudes have a significant effect on the timing of blockchain adoption, and that these effects show differences among the IT professionals from the public and private sector. The findings are believed to provide valuable information to researchers and strategists in forecasting the future evolution of the blockchain technology in terms of individual utilization. The results also will provide feedback to managers of different sectors in making decisions regarding blockchain adoption, developers of blockchain services, as well as individuals who are interested in using blockchain.Conference Object Citation - WoS: 15Mobile Technology Applications in the Healthcare Industry for Disease Management and Wellness(Elsevier Science Bv, 2015) Kalem, Guler; Turhan, CigdemTechnology is an unavoidable fact of today's life. Attractive advantages of wireless technology accelerated the rapid development of mobile applications. With the increase of the usage of mobile devices in the recent years, new solutions come to mind including mobile technologies to fulfill requirements or suggest better solutions in the vast area of medical informatics to the existing ones. Augmentation in the area of wireless technology positively affects the medical applications. In the healthcare industry, mobile applications provide better personalized health care, disease management and services to patients and their relatives, as well as a better and flexible way of communicating with physicians, patients and medical suppliers. It is obvious that the applications using mobile technologies has the potential to bring better conditions both for the patients for their disease management and for the humanity for checking their self wellness. In this paper, the current mobile technology utilized in healthcare such as relapse prevention in schizophrenia, aged people's care and wellness, diagnosis and management of attention-deficit etc. is reviewed in detail outlining the current mobile technologies and wireless revolution of today and examining some of the outstanding applications using these technologies in the clinical area. The results of this study can provide clues to researchers to further the mobile technology in healthcare. (C) 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).Article Citation - WoS: 13Citation - Scopus: 24A Combined Approach for Customer Profiling in Video on Demand Services Using Clustering and Association Rule Mining(Ieee-inst Electrical Electronics Engineers inc, 2020) Guney, Sinem; Peker, Serhat; Turhan, CigdemThe purpose of this paper is to propose a combined data mining approach for analyzing and profiling customers in video on demand (VoD) services. The proposed approach integrates clustering and association rule mining. For customer segmentation, the LRFMP model is employed alongside the k-means and Apriori algorithms to generate association rules between the identified customer groups and content genres. The applicability of the proposed approach is demonstrated on real-world data obtained from an Internet protocol television (IPTV) operator. In this way, four main customer groups are identified: "high consuming-valuable subscribers", "less consuming subscribers","less consuming-loyal subscribers" and "disloyal subscribers". In detail, for each group of customers, a different marketing strategy or action is proposed, mainly campaigns, special-day promotions, discounted materials, offering favorite content, etc. Further, genres preferred by these customer segments are extracted using the Apriori algorithm. The results obtained from this case study also show that the proposed approach provides an efficient tool to form different customer segments with specific content rental characteristics, and to generate useful association rules for these distinct groups. The proposed combined approach in this research would be beneficial for IPTV service providers to implement effective CRM and customer-based marketing strategies.Article The Individual Readiness and Risk-Related Concerns of It Professionals for Blockchain Adoption(Elsevier, 2025) Turhan, Cigdem; Akman, IbrahimBlockchain has gained remarkable momentum since its introduction in 2008, drawing the attention of industries, individuals, and governments on a global scale. This technology has been studied in the literature, with a focus on technical aspects, application areas, and emerging research challenges. However, few studies address individuals' perceptions of and concerns with respect to blockchain adoption. This study aims to investigate the attributes affecting blockchain adoption intention. A sample of IT professionals was used for this purpose since they are expected to have earlier and greater awareness of new digital technologies. The perceptions of this group of users regarding attributes such as innovativeness, self-efficacy, social pressure, and awareness, as well as their perceptions of privacy, security, and complexity, were examined through a survey of 208 responses. The results indicate that among the individual attributes, personal innovativeness, awareness, and social pressure positively affect blockchain acceptance, whereas security and privacy concerns fuel the reluctance to adopt blockchain. The findings hopefully provide insight for developers and management of enterprises to ensure a smooth transition into blockchain and present evidence to forecast its future.
