A SEMI-AUTOMATED POINT CLOUD PROCESSING METHODOLOGY FOR 3D CULTURAL HERITAGE DOCUMENTATION

The preliminary phase in any architectural heritage project is to obtain metric measurements and documentation of the building and its individual elements. On the other hand, conventional measurement techniques require tremendous resources and lengthy project completion times for architectural surveys and 3D model production. Over the past two decades, the widespread use of laser scanning and digital photogrammetry have significantly altered the heritage documentation process. Furthermore, advances in these technologies have enabled robust data collection and reduced user workload for generating various levels of products, from single buildings to expansive cityscapes. More recently, the use of procedural modelling methods and BIM relevant applications for historic building documentation purposes has become an active area of research, however fully automated systems in cultural heritage documentation still remains open. In this paper, we present a semi-automated methodology, for 3D façade modelling of cultural heritage assets based on parametric and procedural modelling techniques and using airborne and terrestrial laser scanning data. We present the contribution of our methodology, which we implemented in an open source software environment using the example project of a 16th century early classical era Ottoman structure, Sinan the Architect’s Şehzade Mosque in Istanbul, Turkey

Immigrant children in Turkey a descriptive study: Determining the depression levels of children who have been exposed to forced migration

Purpose: The aim of this study was to determine the level of depression in children aged 6–17 years who had been subject to forced migration. Design and Method: This study was a descriptive design. The sample included comprised 200 children aged 6–17 years who had experienced forced migration. Findings: About 69.5% of the children who participated in the research migrated from Syria due to war. Participants’ mean Children's Depression Inventory (CDI) score was 13.65 ± 8.58; a CDI score of 19 and higher is considered to indicate depression. Conclusion: It was found that the depression levels of the migrant children were low. Practice Implications: Psychiatric nurses should understand risk factors for depression when providing care to immigrant children