Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/7

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  • Article
    Assessment of Artificial Lighting Conditions in Sunlight-Deprived Classrooms
    (Gazi Univ, Fac Engineering Architecture, 2025) Duyan, Fazila; Kaplan, Elif
    Numerous studies on classroom lighting emphasize a close and significant relationship between students' concentration, comprehension of course content, and the efficiency of activities such as drawing, writing, and practices, with the lighting conditions. In this context, it is particularly important to properly design both the physical and psychological effects of artificial lighting, especially in sunlight-deprived classrooms. This study examines the artificial lighting conditions of a classroom located in the basement of a university building, which has no visual connection to the outdoors. The classroom is utilized by students from the departments of Architecture, Interior Architecture, and Industrial Design. The study investigates the effects of current artificial lighting on students, focusing on aspects such as visual perception satisfaction, light colour, illuminance level, glare, and the temporal light modulation effect. To assess students' perception of the existing lighting conditions, an online questionnaire was administered, and a total of 104 students (65 female, 39 male) who had previous experience with the classroom participated in the study. Technical measurements of the existing luminaires were conducted, and the classroom was digitally modelled using the DIALux Evo lighting software. The collected data were analysed using the SPSS statistical analysis program. The findings of the study indicate that students perceived the artificial lighting conditions as inadequate in terms of visual comfort. Moreover, based on technical measurements, simulations, and user evaluations, it was determined that the existing luminaires caused glare and temporal light modulation effects, negatively affecting the classroom environment.
  • Conference Object
    Sts: AI-Driven Smart Test Scenario Generation Tool
    (IEEE, 2025) Baglum, Cem; Yayan, Ugur
    One of the most critical steps in the software testing lifecycle, test scenario generation, reduces process efficiency due to its high time and resource requirements. As an innovative solution to this issue, the Smart Test Scenario Tool (STS) has been developed. Smart Test Scenario Tool (STS) enhances contextual accuracy and automation in test scenario generation by analyzing documents in xlsx, py, cpp, txt, and docx formats using large language models. This approach minimizes time loss, and the risk of errors encountered in traditional manual testing processes while transforming test procedures into a context-driven and systematic framework, offering an innovative contribution to the literature. Strengthened with a Streamlit interface, MongoDB-supported database management, and Ollama integration, the system enables the test scenario generation process, a critical component of the software testing cycle, to be conducted more efficiently and reliably. The validity of the study was confirmed through two distinct projects, the first implemented in Python and the second in C++.