Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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_id	ascaad2021_142
id	ascaad2021_142
authors	Bakir, Ramy; Sara Alsaadani, Sherif Abdelmohsen
year	2021
title	Student Experiences of Online Design Education Post COVID-19: A Mixed Methods Study
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 142-155
summary	This paper presents findings of a survey conducted to assess students’ experiences within the online instruction stage of their architectural education during the lockdown period caused by the COVID-19 pandemic between March and June 2020. The study was conducted in two departments of architecture in both Cairo branches of the Arab Academy for Science, Technology & Maritime Transport (AASTMT), Egypt, with special focus on courses involving a CAAD component. The objective of this exploratory study was to understand students’ learning experiences within the online period, and to investigate challenges facing architectural education. A mixed methods study was used, where a questionnaire-based survey was developed to gather qualitative and quantitative data based on the opinions of a sample of students from both departments. Findings focus on the qualitative component to describe students’ experiences, with quantitative data used for triangulation purposes. Results underline students’ positive learning experiences and challenges faced. Insights regarding digital tool preferences were also revealed. Findings are not only significant in understanding an important event that caused remote architectural education in Egypt but may also serve as an important stepping-stone towards the future of design education in light of newly-introduced disruptive online learning technologies made necessary in response to lockdowns worldwide
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ascaad2021_041
id	ascaad2021_041
authors	Taºdelen, Sümeyye; Leman Gül
year	2021
title	Social Network Analysis of Digital Design Actors: Exploratory Study Covering the Journal Architectural Design
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 280-292
summary	This research asks the question of how the design knowledge production mechanism is processed differentiates digital design actors from each other in the social media/professional and academic fields of architecture. Due to the broad nature of the research question, the study focuses on academia and academia-related media through prominent architect-authors and subject titles in the literature. Bourdieu’s concept of capital is introduced, in which cultural and symbolic capital are considered part of the production values of digital design actors. Digital design actors use image-based social media tools such as Instagram effectively. The paper uses two methods: the first is a bibliographical analysis of author-texts, and the second is a social network analysis. By employing the keyword-based search from the Web of Science database, this study has managed to extract papers with full records (citations, keywords, and abstracts), with the journal Architectural Design having most publications. Considering that both academicians and professionals contribute to publications in Architectural Design, we selected all its publications between 2010-2020 for bibliometric analysis. These analysis techniques include the bibliometric network analyses and social network analysis with the focus on visualizing the algorithms and statistical calculations of well-established metrics. The research reveals the most critical nodes of the bibliometric network by calculating the appropriate central metrics. The network formed by the selected Instagram accounts of digital design actors are shown to be a small-scale network group, while the hashtags of digital design concepts are more numerous than the digital design actors.
series	ASCAAD
email
last changed	2021/08/09 13:11

_id	acadia20_426
id	acadia20_426
authors	Zohier, Islam; EL Antably, Ahmed; S. Madani, Ahmed
year	2020
title	An AI Lens on Historic Cairo
doi	https://doi.org/10.52842/conf.acadia.2020.1.426
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 426-434.
summary	Reports show that numerous heritage sites are in danger due to conflicts and heritage mismanagement in many parts of the world. Experts have resorted to digital tools to attempt to conserve and preserve endangered and damaged sites. To that end, in this applied research, we aim to develop a deep learning framework applied to the decaying tangible heritage of Historic Cairo, known as “The City of a Thousand Minarets.” The proposed framework targets Cairo’s historic minaret styles as a test case study for the broader applications of deep learning in digital heritage. It comprises recognition and segmentation tasks, which use a deep learning semantic segmentation model trained on two data sets representing the two most dominant minaret styles in the city, Mamluk (1250–1517 CE) and Ottoman (1517–1952 CE). The proposed framework aims to classify these two types using images. It can help create a multidimensional model from just a photograph of a historic building, which can quickly catalog and document a historic building or element. The study also sheds light on the obstacles preventing the exploration and implementation of deep learning techniques in digital heritage. The research presented in this paper is a work-in-progress of a larger applied research concerned with implementing deep learning techniques in the digital heritage domain.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

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