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Yayın Pros and cons of using building information modeling in the AEC industry(ASCE-AMER Soc Civil Engineers, 2019-08-01) Seyis Kazazoğlu, SenemAlthough a plethora of studies on building information modeling (BIM) have been conducted in the last decade, none of the previous studies collate and/or prioritize the benefits, risks, and challenges of BIM based on the data collected from a comprehensive literature review and subject matter experts (SMEs). In order to allow architecture, engineering, and construction (AEC) professionals and academics see the true potential of BIM in a wider context and help them understand its multiorganizational and multidisciplinary functions, there is an obvious necessity for identifying, classifying, and prioritizing the pros and cons of BIM; however, such a study is still currently absent in the AEC literature. The aim of this study is to identify, classify, and rank the pros and cons of BIM that address the benefits, challenges, and risks of BIM in the transition from computer-aided design (CAD). A literature review was performed and face-to-face semistructured interviews with SMEs on BIM were conducted for identification and classification purposes. A total of 41 types of benefits, 11 types of risks, and 13 types of challenges of BIM were identified via triangulation of literature review and face-to-face semistructured interviews with SMEs. The Delphi method was performed for prioritizing the benefits of BIM in terms of time, cost, and sustainability as well as the risks and challenges of BIM encountered in the transition process from CAD to BIM. The interrater agreement and significance-level statistics were performed to analyze and validate the consensus reached by the Delphi panel experts. This paper contributes to the existing body of knowledge on BIM by providing comprehensive identification and classification of the benefits, challenges, and risks of BIM, and prioritization of the benefits for BIM in terms of time, cost, and sustainability as well as the risks and challenges of BIM. The priority rankings of benefits, risks, and challenges of BIM ensure successful completion of projects and create additional value by allowing professionals to make well-informed decisions that support decreasing time and cost-related waste in the transition process from CAD to BIM.Yayın Quality assessment of 3D building data(Wiley-Blackwell Publishing, 2010-12) Akça, Mehmet Devrim; Freeman, Mark; Sargent, Isabel; Gruen, Armin W.Three-dimensional building models are often now produced from lidar and photogrammetric data. The quality control of these models is a relevant issue both from the scientific and practical points of view. This work presents a method for the quality control of such models. The input model (3D building data) is co-registered to the verification data using a 3D surface matching method. The 3D surface matching evaluates the Euclidean distances between the verification and input data-sets. The Euclidean distances give appropriate metrics for the 3D model quality. This metric is independent of the method of data capture. The proposed method can favourably address the reference system accuracy, positional accuracy and completeness. Three practical examples of the method are provided for demonstration.Yayın Disaster damage assessment for buildings using self-similarity descriptor(Institute of Electrical and Electronics Engineers Inc, 2015) Kahraman, Fatih; İmamoğlu, Mümin; Ateş, Hasan FehmiAssessment of damage caused by an earthquake is significant for coordinating emergency response teams and planning emergency aid. In this study, a robust method is proposed for detecting damaged buildings using pre- and post-event satellite images and building footprints. The method uses local self-similarity descriptor for change detection in buildings, which is shown to be robust against variations in illumination and small local deformations. The use of building footprints helps reduce the false alarms due to changes in non-building areas. The 2010 Haiti earthquake is analyzed with the suggested method and 72% true positive rate and 29% false positive rate are obtained for detection of collapsed buildings with respect to the ground truth data of UNITAR/UNOSAT.Yayın Development of an indoor navigation system using NFC technology(IEEE, 2011) Özdenizci Köse, Büşra; Ok, Kerem; Coşkun, Vedat; Aydın, Mehmet NafizExisting indoor navigation systems face with many different technical and usability problems. In this paper we present a Near Field Communication (NFC) based indoor navigation system called NFC Internal in order to eliminate the current indoor navigation problems. NFC Internal enables an easy data transfer for indoor navigation systems just by touching tags spread over a building or a complex. The proposed system has several benefits and has potential to increase the usability of these systems. We discuss the system requirements and explain the phases of NFC Internal through use cases.Yayın Battle damage assessment based on self-similarity and contextual modeling of buildings in dense urban areas(IEEE, 2016) Kahraman, Fatih; İmamoğlu, Mümin; Ateş, Hasan FehmiAssessment of battle damages is significant both for tactical planning and for after-war relief efforts. In this study damaged buildings are detected using self-similarity descriptor in pre- and post-war satellite images. Detection accuracy is improved by the use of a contextual model that describes the building neighborhoods. Building footprints are utilized for accurate assessment of building-level changes and for the formation of neighborhood context. The Gaza Strip after 2014 Israel-Palestine conflict is analyzed with the suggested method and 84% true positive rate and 19% false positive rate are obtained on the average for detection of damaged buildings with respect to the ground truth data of UNOSAT.Yayın Uzaktan algılanan görüntülerde bina yoğunluğu kestirimi için derin öğrenme(Institute of Electrical and Electronics Engineers Inc., 2019-09) Süberk, Nilay Tuğçe; Ateş, Hasan FehmiBu bildiri, derin öğrenme yöntemleri uygulayarak uzaktan algılamalı optik görüntülerde bina yoğunluğunun noktasal olarak kestirilmesi ile ilgilidir. Bu çalışma kapsamında, evrişimsel sinir ağına (ESA) dayalı derin öğrenme yöntemlerine başvurulmuştur. Önceden eğitilmiş, VGG-16 ve FCN-8s derin mimarileri bu probleme uyarlanmış ve ince ayar verilerek eğitilmiştir. Kestirilen değerler yerleşim bölgelerinde bina yoğunluk haritası oluşturmak için kullanılmıştır. Her iki mimarinin karşılaştırmalı benzetim sonuçları, güdümlü eğitim için binaları gösteren detaylı haritalara ihtiyaç duyulmadan hassas yoğunluk kestirimi yapılabileceğini göstermektedir.
