Ticari Bilimler Fakültesi / Faculty of Commercial Science

Permanent URI for this collectionhttps://hdl.handle.net/11727/2074

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The Impact of Developed Energy Efficiency Model on Vessel Valuation
(2018) Koray, Murat; Sogut, M. Ziya; Uysal, Murat Pasa; Karakoc, T. Hikmet; 0000-0002-8349-9403; 0000-0002-9782-7885; 0000-0002-8349-9403; 0000-0001-8182-8667; GQQ-0222-2022; T-2601-2017; GQQ-0222-2022; AAA-1363-2021
An Integrated Research for Architecture-Based Energy Management in Sustainable Airports
(2017) Uysal, Murat Pasa; Sogut, M. Ziya; 0000-0002-8349-9403; 0000-0002-9782-7885; GQQ-0222-2022; T-2601-2017
Energy Management (EM) has become crucial and much more complicated for airports with the introduction of various energy sources, technologies and different comfort requirements. Regarding the aviation industry as one of the major sources of global warming and air pollution, this situation becomes highly critical. However, the review of literature on Energy Management Information Systems (EMIS) for airports shows that the proposed solutions are usually domain-specific, platform-depended and away from suggesting complete solutions and architectures. Therefore, the main argument of this study is that a holistic and integrated approach should be adopted for EM in airports and we claim the notion of sustainability through the use of Enterprise Architecture (EA)-based EM. In this paper, we present the results of a two-faced research study. Action Research (AR) and Design Science Research (DSR) methods are combined to adopt an integrated approach. At the first phase, an EA is developed and evaluated, and then, this is followed by the second phase with three cases to find the potential energy savings in Istanbul Airport. Along with the findings, the primary and secondary contributions of this research brought to the EM knowledge domain are presented. Consequently, there is an important potential for energy saving in the terminal buildings, which would be approximately 70% of the total airport energy consumption. There is also a nearly 250.000 $/year potential saving, and also 121397 $/year for the daylight time and period. This research can be seen as an initial attempt to the enhancement of sustainable airports, and therefore, it has showed the potential for using EAs as a means to improve EM in airports. We hope that this study may help researchers to obtain an overview of existing and possible approaches to sustainability through the use of EAs for EM practices. (C) 2017 Elsevier Ltd. All rights reserved.
Machine learning-enabled healthcare information systems in view of Industrial Information Integration Engineering
(2022) Uysal, Murat Pasa; 0000-0002-8349-9403
Recent studies on Machine learning (ML) and its industrial applications report that ML-enabled systems may be at a high risk of failure or they can easily fall short of business objectives. Cutting-edge developments in this field have increased complexity and also brought new challenges for enterprise information integration. This situation can even get worse when considering the vital importance of ML-enabled healthcare information systems (HEIS). Therefore, the main argument of this paper is that we need to adopt the principles of Industrial Information Integration Engineering (IIIE) for the design, development, and deployment processes of ML-enabled systems. A mixed research paradigm is adopted, and therefore, this study is conducted by following the guidelines and principles of Action Research, Design Science Research, and IIIE. The contributions of this study are two-fold: (a) to draw researchers' and practitioners' attention to the integration problems of ML-enabled systems and discuss them in view of IIIE, and (b) to propose an enterprise integration architecture for ML-enabled HEIS of a uni-versity hospital, which is designed and developed by following the guidelines and principles of IIIE.