TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/4
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Article Observing Conductance Quantization by a Novel Magnetic Control System(Gazi Univ, 2024-06-01) Ozturk, Yavuz; Çiğdem, Dila; Karakaya, Bilge Toprak; Değimli, Duru; Çelikoğlu, Meltem Gönülol; Gonulol, MeltemIn this study, a novel magnetic system that allows observing quantized conductance for undergraduate and graduate laboratories is presented. Bending of a magnetic cylindrical beam, like a cantilever, is controlled by an electromagnet to provide contact between needle type electrode and a plane of conductor. It is shown that by using the beam bending, it is possible to displace an object on the beam in nanometer and micrometer scale. The measured quantized conductance results prove that the designed system can be used for demonstration of the quantized conductance.Article Citation - WoS: 18Citation - Scopus: 34Modelling AI in Architectural Education(Gazi Univ, 2022-12-01) Başarır, LaleThis work displays an outlook on major questions concerning the integration of Artificial Intelligence (AI) in Architectural education. Gradually, part of the domain knowledge and hard skills become either irrelevant or insufficient by the time the students graduate. This paper suggests that integrating AI in the architectural design curriculum is beneficial for raising designers’ awareness of all areas of architectural design, in the form of input, process, and output. The study views consecutive learning experiences in a continuum and explores the potentials of integrating AI applications and techniques in architectural education, and how architectural design practice may benefit from it. Consequently, it provides insights into how architectural design education may transform itself considering the future impact of AI on the Architecture Engineering Construction (AEC) industry.Article Citation - WoS: 1Minimization of Number of Tool Switching Instants in Automated Manufacturing Systems(Gazi Univ, 2022-03-01) Gokgur, Burak; Özpeynirci, SelinThis study addresses the problem of minimizing tool switching instants in automated manufacturing systems. There exist a single machine and a group of jobs to be processed on it. Each job requires a set of tools, and due to limited tool magazine capacity, and because it is not possible to load all available tools on the machine, tools must be switched. The ultimate goal, in this framework, is to minimize the total number of tool switching instants. We provide a mathematical programming model and two constraint programming models for the problem. Because the problem is proven to be NP-hard, we develop two heuristic approaches, and compare their performance with methods described in the literature. Our analysis indicates that our constraint programming models perform relatively well in solution quality and execution time in small-sized problem instances. The performance of our greedy approach shows potential, reaching the optimal solution in 82.5% of instances. We also statistically demonstrate that the search algorithm enhances the quality of the solution obtained by the greedy heuristic, particularly in large sets. Hence, the solution approach, i.e., the greedy heuristic and the search algorithm proposed in this study is able to quickly reach near-optimal solutions, showing that the method is appropriate for manufacturing settings requiring sudden adjustments.