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    Article
    Factors Affecting Dentists' Intention To Adopt Artificial Intelligence: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model
    (Emerald Group Publishing Ltd, 2025) Alqaifi, Faten; Tengilimoglu, Dilaver
    PurposeAdvancements in science and technology have integrated artificial intelligence (AI) into dentistry, improving treatment processes, operational efficiency, and clinical outcomes. However, AI adoption among dentists remains underexplored, hindering progress in oral healthcare. This study aims to identify key barriers to AI adoption and examine factors influencing dentists' intention to use AI.Design/methodology/approachA quantitative cross-sectional approach was employed, utilizing self-administered questionnaires distributed online and across various dental clinics and hospitals in Ankara, Turkey. A total of 440 dentists participated in the study. Data analysis was conducted using SPSS and SmartPLS.FindingsThe study found that AI-anxiety negatively affects the intention to adopt AI in dentistry, showing a medium (almost large) effect that is stronger than other UTAUT factors such as performance expectancy, effort expectancy, and social influence, which demonstrated only small effects. Dentists with higher anxiety about learning and sociotechnical blindness are less likely to adopt AI, while concerns about job replacement and AI-configuration have less but still significant impact.Research limitations/implicationsThese results contribute to the growing body of knowledge on technology adoption in oral healthcare and provide practical implications for technology developers, policymakers, and other stakeholders seeking to facilitate AI integration in dentistry.Originality/valueThis study provides novel insights into AI adoption in dentistry, offering guidance for future development and integration, and addressing a critical research gap in a growing field-particularly in Turkey, where implementation is still in its early stages.
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    Master Thesis
    Yapay Zeka Teknikleri Kullanılarak Bor Nitrür Kaplamalarının Modellenmesi
    (2025) Küçüköztaş, Korcan; Turhan, Çiğdem; Kaftanoğlu, Bilgin
    Bor nitrür (BN), yüksek ısıl iletkenlik, düşük sürtünme katsayısı ve yüksek sertlik gibi mükemmel özelliklere sahip bir seramik malzemedir. Ancak, BN kaplamalarının Fiziksel Buhar Biriktirme (FBB) süreci ile Magnetron Saçtırma (MS) tekniği kullanılarak uygulanması, süreç parametreleri ile kaplama özellikleri arasındaki karmaşık etkileşimler nedeniyle zorludur. Bu tez, altı gelişmiş makine öğrenmesi tekniğinden yararlanan Yapay Zeka (YZ) tabanlı bir çerçeve kullanılarak BN kaplama sürecinin modellenmesi ve optimizasyonuna yönelik yenilikçi bir yaklaşım sunmaktadır. Çelik numuneler, farklı kaplama parametreleri ile kaplanmış ve yüksek hassasiyetli ekipmanlarla karakterize edilmiştir. Verileri tanıyabilmek amacıyla, keşifsel veri analizi gerçekleştirilmiştir. Üç farklı kaplama özelliğini tahmin etmek üzere altı farklı mimari kullanılarak makine öğrenmesi modelleri geliştirilmiş ve regresyon değerlendirme metrikleri ile karşılaştırılmıştır. Son olarak, en başarılı modeller, yeni veri setleri üzerinde tahminlerde bulunmak amacıyla kullanılmış ve sonuçlar görselleştirilmiştir. YZ tabanlı yaklaşım, karar verme süresini azaltarak istenilen özelliklere göre en uygun parametrelerinin belirlenmesini sağlamaktadır.
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    Article
    An Empirical Study of the Technoparks in Turkey in Investigating the Challenges and Potential of Designing Intelligent Spaces
    (Mdpi, 2023) Erisen, Serdar
    The use of innovative technologies in workspaces, such as the Internet of Things (IoT) and smart systems, has been increasing, yet it remains in the minority of the total number of smart system applications. However, universities and technopoles are part of open innovation that can encourage experimental IoT and smart system projects in places. This research considers the challenges and advantages of developing intelligent environments with smart systems in the Technology Development Zones (TDZs) of Turkey. The growth of Silicon Valley has inspired many technopoles in different countries. Thus, the article includes first a comprehensive survey of the story of Silicon Valley and the emerging technological potential of open and responsible innovation for intelligent spaces and technoparks with rising innovative interest. The study then conducts empirical research in inspecting the performance of TDZs in Turkey. In the research, machine learning and Artificial Intelligence (AI) models are applied in the analyses of critical performance indicators for encouraging incentives and investments in innovative attempts and productivity in TDZs; the challenges, potential, and need for intelligent spaces are evaluated accordingly. This article also reports on the minority of the design staff and the lack of innovation in developing intelligent spaces in the organization of the creative class in Turkey. Consequently, the research proposes a set of implementations for deploying intelligent spaces to be practiced in new and existing TDZs by considering their potential for sustainable and responsible innovation.