Kulaç, Oray

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https://gcris.yasar.edu.tr/handle/123456789/12806
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Öğrt.Gör.
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Main Affiliation
01. Yaşar Üniversitesi
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Former Staff
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ORCID ID
0000-0003-3734-5785
Scopus Author ID
57821084100
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pzo7tBIAAAAJ
WoS Researcher ID
LZF-9332-2025

Sustainable Development Goals

NO POVERTY1
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ZERO HUNGER2
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GOOD HEALTH AND WELL-BEING3
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QUALITY EDUCATION4
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GENDER EQUALITY5
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
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REDUCED INEQUALITIES10
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SUSTAINABLE CITIES AND COMMUNITIES11
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
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CLIMATE ACTION13
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LIFE BELOW WATER14
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LIFE ON LAND15
LIFE ON LAND
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
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PARTNERSHIPS FOR THE GOALS17
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Computers in Biology and Medicine1
International Conference on Intelligent and Fuzzy Systems INFUS 20221
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    Citation - Scopus: 2
    Intelligent Supply Chains Through Implementation of Digital Twins
    (Springer Science and Business Media Deutschland GmbH, 2022) Oray Kulaç; Banu Yetkin Yetkin Ekren; Ayhan Özgür Toy; Toy, A. Ozgur; Kulac, Oray; Ekren, Banu Y.; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
    Data-driven decision-making process can be defined to be the sequential activities of real-time data collection data analytics optimization and decision making. Developments in Industry 4.0 technologies have made it possible to realize that new quality decision-making process. When that decision-making process is performed under the simulation model of a system developed on real-time data-based and end-to-end connection manner to prevent the disruption risks and to improve resilience in a system then it constitutes a digital twin (DT). A DT is a virtual representation of an object or system that can help organizations monitor operations perform predictive analytics and improve processes. For instance a DT could provide a digital replica of the operations of a factory communications network or the flow of goods through a supply chain system. In this work we focus on DT implementations in supply chain networks. We present state of the art implementation of DTs in supply chains and their prospective utilizations towards creating intelligent supply chains. © 2022 Elsevier B.V. All rights reserved.
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    Article
    Citation - Scopus: 2
    Analysis of inoculation strategies during COVID-19 pandemic with an agent-based simulation approach
    (Elsevier Ltd, 2025) Oray Kulaç; Ayhan Özgür Toy; Kamil Erkan Kabak; Toy, Ayhan Özgür; Kabak, Kamil Erkan; Kulaç, Oray
    Background: The severity of recent Coronavirus (COVID-19) pandemics has revealed the importance of development of inoculation strategies in case of limited vaccine availability. Authorities have implemented inoculation strategies based on perceived risk factors such as age and existence of other chronic health conditions for survivability from the disease. However various other factors can be considered for identifying the preferred inoculation strategies depending on the vaccine availability and disease spread levels. This study explores the effectiveness of inoculating different groups of population in case of various vaccine availabilities and disease spread levels by means of some performance metrics namely: Attack Rate (AR) Death Rate (DR) and Hospitalization Rate (HR). Method: In this study we have implemented a highly detailed Agent-Based Simulation (ABS) model that extends classical SEIR Model by including five more additional states: Asymptomatic (A) Quarantine (Q) Hospitalized (H) Dead (D) and Immune (M) which can be used as a decision support tool to prioritize the groups of the population inoculated. The approach employs the modelling of daily mobility of individuals their interactions and transmission of virus among individuals. The population is heterogeneously clustered according to age family size work status transportation and leisure preferences with 17 different groups in order to find the most appropriate one to inoculate. Three different Disease Spread Levels (DSL) (low mid high) are experimented with four different Vaccine Available Percentages (VAP) (25% 50% 75% and 85%) with a total of 84 scenarios. Results: As the benchmark under the No Vaccine case Attack Rate Hospitalization Rate and Death Rate goes as high as 99.53% 16.96% and 1.38% respectively. Corresponding highest performance metrics (rates) are 72.33% 15.95% and 1.35% for VAP = 25%, 50.25% 9.55% and 0.94% for VAP = 50%, 24.53% 2.62% and 0.25% for VAP = 75%, and 11.51% 0.002% and 0.08% for VAP = 85%. The results of our study shows that the common practice of inoculation based on the age of individual does not yield the best outcome in terms of performance metrics across all DSL and VAP values. The groups containing workers and students that represent highly interactive individuals i.e. Group (9 10) Group (9 11 10‾) and Group (9 10 11 12‾) emerge as a commonly recommended choice for inoculation in the majority of cases. As expected we observe that the higher is the VAP levels the more is the number of alternative inoculation groups. Conclusions: Findings of this study present that: (i) inoculation considerably decreases the number of infected individuals the number of deaths and the number of hospitalized individuals due to the disease (ii) the best inoculation group/groups with respect to performance metrics varies depending on the vaccine availability percentages and disease spread levels (iii) simultaneous implementation of both inoculation and precautions like lock-down social distances and quarantines yields a stronger impact on disease spread and its consequences. © 2025 Elsevier B.V. All rights reserved.