WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 2Citation - Scopus: 2Charting the Landscape of Design Cognition: Bridging the Gap Between Design Cognition and Cognitive Science(Taylor & Francis Ltd, 2025) Ata, F. Zeynep; Dogan, FehmiThis study examines the trajectory of cognitive studies on design processes (DesCog), charting its scientific landscape and interactions with cognitive science (CogSci). First, the study delineates the boundaries of DesCog within all published scholarly works. The analysis indicates that DesCog is a focused field with lesser impact on other fields, showing divergent bibliographic positions and connections for 'design cognition' and 'design thinking'. Second, the longitudinal evolution of DesCog is identified as gradually becoming more diverse and more connected. Third, DesCog's foundational connections to CogSci demonstrate that the relationship is spontaneous rather than following 'generalising interdisciplinarity' aims. The analysis indicates a unidirectional flow from CogSci to DesCog, with occasional reciprocal interactions. The volume and diversity of CogSci literature cited by DesCog appear narrow, and most cited publications are based on the information-processing theory of cognition. Fourth, the study identifies common themes at the intersection of two fields, demonstrating that creativity has been a focal theme for both since earlier studies. Finally, the individual impact of CogSci researchers on DesCog highlights the significance of Simon and Newell's influence. The study contributes to reflections on DesCog's knowledge production, underlining unidirectional knowledge flows from CogSci to DesCog and partial theoretical connections within the field.Conference Object Decoding and Predicting the Attributes of Urban Public Spaces With Soft Computing Models and Space Syntax Approaches(Ecaade-education & Research Computer Aided Architectural design Europe, 2023) Yonder, Veli Mustafa; Dogan, Fehmi; Cavka, Hasan Burak; Tayfur, Gokmen; Dulgeroglu, OzumPeople spend a considerable amount of time in public spaces for a variety of reasons, albeit at various times of the day and during season. Therefore, it is of utmost importance for both urban designers and local authorities to try to gain an understanding of the architectural qualities of these spaces. Within the scope of this study, squares and green parks in Izmir, the third largest city in Turkey, were analyzed in terms of their dimensions, landscape characteristics, the quality of their semi-open spaces, their landmarks, accessibility, and overall aesthetic quality. Using linear predictor, general regression neural networks, multilayer feed-forward neural networks (2-3-4-5-6 nodes), and genetic algorithms, soft computing models were trained in accordance with the results of the conducted analyses. Meanwhile, using space syntax methodologies, a visibility graph analysis and axial map analysis were conducted. The training results (i.e., root mean square error, mean absolute error, bad prediction rates for testing and training phases, and standard deviation of absolute error) were obtained in a comparative table based on training times and root mean square error values. According to the benchmarking table, the network that most accurately predicts the aesthetic score is the 2-node MLFNN, whereas the 6-node MLFN network is the least successful network.Article Citation - WoS: 1Citation - Scopus: 1Socio-Economic and Development Disparities Over the Long-Run: Exploring Spatial Heterogeneities in the Case of Turkey(Hungarian Central Statistical Office, 2024) Duran, Hasan Engin; Cifci, Burcu Degerli; Karabakan, Berfin; Dogan, FehmiThe aim of this paper is to explore the evolution of socioeconomic development and income disparities and convergence patterns across Turkish provinces, emphasizing the impact of spatial heterogeneities. We propose two types of contributions to the literature. First, most of the studies that apply the 13- convergence method presume a unique 13 parameter, assuming that all regions homogenously converge to the steady state at the same pace. However, we argue that relaxing this assumption by way of considering spatial heterogeneities might be more informative. Second, we provide a simple solution to a severe problem: The neoclassical model assumes a monotonic saddle path along which economic fluctuations are not considered, which might be particularly influential with regard to convergence when the time span is too short to capture long-term evolution. Many empirical studies cover only short periods, which may be easily dominated by recessions or expansions, significantly biasing the results. To overcome this problem, we look into two datasets covering long periods (1963-2017 and 1975-2021). Having applied various empirical methods, such as spatial regressions, GWR and nonparametric regressions, we obtain several results. First, at the country level, there is empirical evidence of regional convergence and decreasing development inequalities. Second, however, this convergence process is not valid in all areas. We conclude that there is nonnegligible spatial heterogeneity that should be taken into account in such analyses.Conference Object Citation - Scopus: 2Multi-Disciplinarity and Collaboration in Computational Design Teams(Ecaade-Education & Research Computer Aided Architectural Design Europe, 2022) Altintas, Livanur Erbil; Kasali, Altug; Dogan, FehmiThis study reports cases involving computational practices in architectural design to understand how a distributed cognitive system supports multidisciplinary collaboration in design teams. In particular, we look into the role of coding languages in collaborative practices within interdisciplinary design teams. By providing an analysis on the distributed nature of the design process, this research aims to explain collaboration involving team participants with different skills in representation.