Search

• Propose an IoMT security defense method based on blockchain and fuzzy set theory. • Propose DFCM algorithm to solve the clustering problem of balanced data. • Use FSVM model to classify data points far from the sample center. • Use the combination of DFCM and FSVM in IoT attack detection. This work aims to improve the stability and efficiency of the Internet of Medical Things (IoMT), strengthen the security and privacy of personal information, and create a healthy and safe network environment. First, art therapy in the current medical environment is discussed, and the security defenses of the IoMT supporting art therapy are studied. Then, a security defense method for IoMT is proposed by combining basic Blockchain knowledge with the Fuzzy Sets Theory. Specifically, a Density-awarded Fuzzy C-means (DFCM) algorithm is developed to solve the clustering issue of unbalanced data sets. Besides, the Fuzzy Support Vector Machine (FSVM) model is used to classify data points far from the sample center to increase classification accuracy. In the simulation experiment, the DFCM algorithm achieves a pleasing clustering effect on the four data sets, involving the data sets with density changes and imbalanced sample points within the cluster. Moreover, the combination of DFCM and FSVM (DFCM-FSVM) for attack detection in the Internet of Things (IoT) realizes the optimal accuracy in the detection of different behaviors compared with similar algorithms; the detection accuracy of normal behavior, scheduled attack, gray hole attack, and black hole attack is 99.8%, 89.8%, 99.4%, and 91.5%, respectively. This work creatively proposes a hybrid intrusion detection method based on fuzzy theory. As the second line of defense in security protection, it plays a critical role and is suitable for the network environment of the perception layer. In conclusion, the attack detection method based on Blockchain combined with the Fuzzy Sets Theory can precisely identify potential attacks in abnormal data, which has important practical value for maintaining data security and the regular operation of the IoMT. [ABSTRACT FROM AUTHOR]

Abstract: This study proposes a framework based on the concept of fuzzy sets theory and the VIKOR method to provide a rational, scientific and systematic process for evaluating the hospital service quality under a fuzzy environment where the uncertainty, subjectivity and vagueness are addressed with linguistic variables parameterized by triangular fuzzy numbers. This study applies the fuzzy multi-criteria decision making approach to determine the importance weights of evaluation criteria and the VIKOR method is taken to consolidate the service quality performance ratings of the feasible alternatives. An empirical case involving 33 evaluation criteria, 2 public and 3 private medical centres in Taiwan assessed by 18 evaluators from various fields of medical industry is solicited to demonstrate the proposed approach. The analysis result reveals that the service quality of private hospitals is better than public hospitals because the private hospitals are rarely subsidized by governmental agencies. These private hospitals have to fend themselves to retain existing patients or attract new patients to ensue sustainable survival. [Copyright &y& Elsevier]

Abstract: The recent economic recession has added more uncertainty to industries’ decision processes regarding production quantity. Moreover, due to the nature of ambiguous information, manufacturers often fail to achieve precise assessments of the parameters of market demand, production cost functions, etc. This paper develops the Cournot production game with multiple firms in an ambiguous decision environment, where the form of ambiguity is described by a set of fuzzy parameters. Our model applies the weighted center of gravity method (WCoG) to defuzzify the fuzzy profit function considering firms’ control parameters. The resulting outcomes are in the form of matrix representations. We also analyze the effect of firms’ control parameters on outcomes. The results indicate that a firm’s fuzzy profit function plays an important role in economic interpretation. To investigate the effect of parameter perturbations on firms’ outcomes, we also conduct the sensitivity analysis. [Copyright &y& Elsevier]

Abstract: This study develops a forecasting framework based on the fuzzy multi-criteria decision making (FMCDM) approach to help organizations build awareness of the critical influential factors on the success of knowledge management (KM) implementation, measure the success possibility of knowledge management projects, as well as identify the necessary actions prior to embarking on conducting knowledge management. Subjectivity, uncertainty and vagueness within the prediction process are dealt with using linguistic variables parameterized by triangular fuzzy numbers. By multiplying the importance weights of influential factors and the possible rating of success (failure), predicted success (failure) values are determined to enable organizations to decide whether to initiate knowledge management, inhibit adoption or undertake remedial improvements to increase the possibility of successful knowledge management project. The proposed approach is demonstrated using a real case involving a Taiwanese semiconductor engineering corporation. [Copyright &y& Elsevier]