4 results for “Transitional Area”
Research Article
Open Access Exploring Integrity in Javanese Islamic Sites Through Archival Study and the Lens of the HUL Paradigm
Karina Tucunan, Tucunan K
7th International Symposium on Innovation in Architecture, Planning and Design 2025 https://doi.org/10.36287/setsci.23.31.001
This paper explores the role of archival study in exploring site integrity within the Historic Urban Landscape (HUL) framework, using the case of Islamic heritage sites in Java, Indonesia. In contexts where material traces have been lost or obscured, archival …
Research Article
Open Access Amasya Kent Merkezinde Fiziksel Zarar Görebilirlik Düzeylerinin Mekânsal Analizi: CBS Tabanlı Bir Yaklaşım
Harun Ceylan, Ceylan H, Rabia Karamustafa, Karamustafa R, Süleyman Tuğrul Kılıç, Kılıç S, Aslı Altanlar, Altanlar A
7th International Symposium on Innovation in Architecture, Planning and Design 2025 https://doi.org/10.36287/setsci.23.83.001
Afet risklerinin azaltılmasında, fiziksel zarar görebilirlik düzeylerinin mekânsal olarak belirlenmesi ve görselleştirilmesi, kentsel dayanıklılığın artırılması açısından kritik bir öneme sahiptir. Bu çalışma, Amasya kent merkezinde afet kaynaklı fiziksel kırı…
Research Article
Open Access Investigation of Rammed Earth Research in the Context of Sustainable Building Materials with Performance Analysis
Yahya Melikoğlu, Melikoğlu Y, Fatma Şebnem Kuloğlu Yüksel, Kuloğlu Yüksel F, Sevilay Akalp, Akalp S
7th International Symposium on Innovation in Architecture, Planning and Design 2025 https://doi.org/10.36287/setsci.23.102.001
Throughout history, earth as one of the most basic building materials of architecture, has stood out as a culturally and environmentally sustainable resource thanks to its local availability, compatibility with natural cycles and renewability. Increasing envir…
Research Article
Open Access XAI-Powered Comparative Diabetes Prediction with XGBoost, SVM and Artificial Neural Networks
Furkan Sefa Demirci, Demirci F, Remzi Yıldırım, Yıldırım R
International Symposium on AI-Driven Engineering Systems 2025 https://doi.org/10.36287/setsci.22.30.001
In this study, diabetes prediction was conducted using XGBoost, Support Vector Machines (SVM), and a Multilayer Artificial Neural Network (ANN). Attributes that cannot be biologically ‘0’ (e.g. glucose, BMI) were first marked as NaN. After filling the missing …
