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    An application of fuzzy soft sets to a real-life problem: Classification of wood materials to prevent fire-related injuries and deaths
    (Elsevier, 2023) Korkmaz, Esra; Özcan, Cemal; Korkmaz, Mustafa
    A variety of methods are used to determine the health and life-threatening consequences of wood combustion. However, these methods suffer from some limitations. They analyze the data obtained during combustion individually rather than evaluating them together. Furthermore, they do not take into account the fact that some of the parameters that influence the process can be positive, while others can be negative, or that they may not be of equal importance. In this study, we present a fuzzy soft set-based algorithm to handle such issues. The proposed algorithm can also deal with problems arising when the membership values of the objects are close together. It also contributes a novel approach to the literature regarding the selection of wood materials that are suitable for use in fireprone areas. In order to demonstrate the applicability of our approach we performed an experiment and analyzed wood materials, which are frequently used in wooden structures, according to parameters that may affect human life and health. We also highlight how the present work contributes to the state-of-the-art by interpreting our results using a method that already exists in the literature. (c) 2022 Elsevier B.V. All rights reserved.
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    A novel approach to fuzzy N-soft sets and its application for identifying and sanctioning cyber harassment on social media platforms
    (Springer, 2024) Korkmaz, Esra; Riaz, Muhammad; Deveci, Muhammet; Kadry, Seifedine
    This study proposes a novel approach to fuzzy N-soft sets for handling cases where membership degree and grade are not related. In the standard model of fuzzy N-soft sets, membership degree and grade are assumed to be directly proportional. This assumption may not hold true in real-world situations, so a more flexible and nuanced approach is necessary. The proposed approach includes two novel algorithms for decision-making problems involving fuzzy N-soft sets. As a result, it is able to be adaptable and sensitive when addressing uncertainties in real-world scenarios, with a particular focus on identifying and sanctioning cyber harassment on social media platforms. Additionally, an innovative perspective and approach to decision-making problems involving fuzzy N-soft sets is introduced by extending an established selection process that prioritizes the dominant parameter, resulting in more precise and dependable outcomes. Our study offers an effective tool for decision-making in various fields, including e-commerce, social media, and product reviews.