An alternative approach to determination of Covid‑19 personal risk index by using fuzzy logic

COVID-19 disease is an outbreak that seriously affected the whole world, occurred in December 2019, and thus was declared a global epidemic by WHO (World Health Organization). To reduce the impact of the epidemic on humans, it is important to detect the symptoms of the disease in a timely and accurate manner. Recently, several new variants of COVID-19 have been identified in the United Kingdom (UK), South Africa, Brazil and India, and preliminary findings have been suggested that these mutations increase the transmissibility of the virus. Therefore, the aim of this study is to construct a support system based on fuzzy logic for experts to help detect of COVID-19 infection risk in a timely and accurate manner and to get a numerical output on symptoms of the virus from every person. The decision support system consists of three different sub and one main Mamdani type fuzzy inference systems (FIS). Subsystems are Common- Serious symptoms (First), Rare Symptoms (Second) and Personal Information (Third). The first FIS has five inputs, fever-time, cough-time, fatigue-time, shortness of breath and chest pain/dysfunction; the second FIS has four inputs, Loss of Taste/Smell, Body Aches, Conjuctivitis, and Nausea/Vomiting/Diarrhea; and the third FIS has three inputs, Age, Smoke, and Comorbidities. Then, we obtain personal risk index of individual by combining the outputs of these subsystems in a final FIS. The results can be used by health professionals and epidemiologists to make inferences about public health. Numerical output can also be useful for self-control of an individual.No sponso

Optimizing the liver/kidney organ donation waiting list in Antalya using maxsat and graph model

International Conference on Industrial Engineering and Operations Management (2022 : Istanbul, Turkey)Organ transplantation has become an increasing need in the world and in our country. Organ transplantation is completed by taking healthy and matched organs from living or cadaver donors and transplanting them to the recipient. Different approaches are sought for solutions to the organ transplant waiting list and matching problem in the world and in Turkey. The number of people waiting for organs is many times higher than the number of organ donors, and the difference is increasing every year. In this project, we research and learn all the details of the organ transplantation system in Turkey, in particular the computer network where the organ waiting list and matching is processed, coordinated locally at Akdeniz University Prof. Dr. Tuncer KARPUZOĞLU organ transplantation center with the help of its coordinator and Lecturer Nilgün Bilal. We work to identify problems and improve the system when applicable. We apply a new optimization method (MaxSAT method) to the organ waiting list and organ donation matching problem, on which second author worked with Researcher Felip Manyà (UAB-IIIA/CSIC- Spain) at the university in Spain on her Erasmus internship. Alternatively, we also consider approaching the problem using other industrial engineering techniques such as stochastic modeling. We then compare the results in different techniques to improve the system.No sponso