Forthcoming and Online First Articles

International Journal of Fuzzy Computation and Modelling

International Journal of Fuzzy Computation and Modelling (IJFCM)

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International Journal of Fuzzy Computation and Modelling (3 papers in press)

Regular Issues

  • Triangular Fuzzy Interpolation Deinterlacing Algorithm Method for Image Edge Detection   Order a copy of this article
    by Jagatheswari Kalimuthu 
    Abstract: Edge detection is the first step in image as it can be applied in the process of feature extraction, segmentation and classification. This study proposes a new fuzzy logic based edge detection method and computationally efficient algorithm based on triangular fuzzy interpolation technique for intra field deinterlacing of images that reduces the loss in image quality at the edges. The proposed algorithm improves image deinterlacing quality with respect to missing pixels in the edge region. When interpolating the missing pixels, characteristics or features of the region around the pixel are interpolated first. The proposed algorithm is tested with five test images which have both uniform surface and edges. The subjective and objective performance of the proposed algorithm shows greater improvement in the edge quality when correlated with the traditional deinterlacing methods. The designed fuzzy rules become an attractive solution for the betterment of the quality of edges as much as possible. The result reveals that the proposed algorithm provides greater robustness to contrast and lighting variations.
    Keywords: triangular fuzzy representation; slope scale; missing pixel; edge detection; edge direction gradient; deinterlacing; fuzzy interpolation; Gaussian gradient; rough interlacing line.
    DOI: 10.1504/IJFCM.2021.10037098
     
  • Response bias in decision making: An application of intuitionistic fuzzy targeting decision uncertainties   Order a copy of this article
    by Arnab Kundu, Tripti Bej, Samirranjan Adhikari 
    Abstract: The human cognitive structure is very uncertain and ever-elusive to arrest. The purpose of this study was to formulate a mathematical model to evade response bias latent in the quantification process in any decision-making by applying intuitionistic fuzzy logic, potent in arresting uncertainties. Following this research aim, a sample problem was adopted from the school setting regarding the election of a class monitor based on an opinion survey among five teachers on a Likert scale. The numerical decision values were converted to intuitionistic fuzzy. Findings revealed a palpable difference between Likert values and their Fuzzified corresponding values wherefrom the authors empirically deduced that fuzzified result is more precise over the quantified Likert values considering respondents biases, uncertainties, inter-rater agreements, or disagreements. Finally, the researchers proposed the intuitionistic fuzzy score function evolved in this study, needs to be investigated with a larger sample size to draw more authentication.
    Keywords: response bias; subjective error; survey; fuzzy; intuitionistic fuzzy; class monitor; decision making; uncertainties.
    DOI: 10.1504/IJFCM.2021.10036917
     
  • On the Borel summability method of rough convergence of triple sequences of Bernstein-Stancu operator of fuzzy numbers   Order a copy of this article
    by A. Esi, Subramanian Nagarajan 
    Abstract: We define the concept of rough limit set of a triple sequence space of Bernstein-Stancu polynomials of Borel summability of fuzzy numbers and obtain the relation between the set of rough limit and the extreme limit points of a triple sequence space of Bernstein-Stancu polynomials of Borel summability method of fuzzy numbers. Finally, we investigate some properties of the rough limit set of Bernstein-Stancu polynomials under which Borel summable sequence of fuzzy numbers are convergent. Also, we give the results for Borel summability method of series of fuzzy numbers.
    Keywords: triple sequences; rough convergence; sequences of fuzzy numbers,Bernstein-Stancu polynomials; Borel summability method.