International Journal of Fuzzy Systems and Advanced Applications
E-ISSN: 2313-0512
Volume 7, 2020
Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of NAUN Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.
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Volume 7, 2020
Title of the Paper: Prime Fuzzy Bi-Ideals in Near-Subtraction Semigroups
Authors: K. Mumtha, V. Mahalakshmi, S. Usha Devi
Pages: 24-28
http://doi.org/10.46300/91017.2020.7.5
Abstract: A study on fuzzy prime ideals in near-subtraction semigroups is already known. We have to expand the concept of prime fuzzy bi-ideals in near-subtraction semigroups and analyse some of its properties to characterize it. This will lead to learn a new type of fuzzy ideal and to develope the researcher to made their research.
Title of the Paper: Detection of Glaucoma in Retinal Fundus Images using Fast Fuzzy C Mean Clustering
Authors: Law Kumar Singh, Pooja, Hitendra Garg
Pages: 16-23
http://doi.org/10.46300/91017.2020.7.4
Abstract: Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is a disease in the eye where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from fundus images. The proposed method suggest automatic detect the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 91.91%, 90.49% and 90.17% when tested on DRIONS, DRIVE and STARE on publicly available databases of fundus images.
Title of the Paper: Meteorological Risk Assessment for Ships with Fuzzy Logic Designer
Authors: Ismail Karaca, Ridvan Saracoglu, Omer Soner
Pages: 12-15
http://doi.org/10.46300/91017.2020.7.3
Abstract: Fuzzy Logic, an advanced method to supportdecision-making, is used by various scientists in many disciplines.Fuzzy programming is a product of fuzzy logic, fuzzy rules, andimplication. In marine science, fuzzy programming for ships isdramatically increasing together with autonomous ship studies. Inthis paper, a program to support the decision-making process for shipnavigation has been designed. The program is produced in fuzzylogic and rules, by taking the marine accidents and expert opinionsinto account. After the program was designed, the program was testedby 46 ship accidents reported by the Transportation SafetyInvestigation Center of Turkey. Wind speed, sea condition, visibility,day/night ratio have been used as input data. They have beenconverted into a risk factor within the Fuzzy Logic Designerapplication and fuzzy rules set by marine experts. Finally, the expert'smeteorological risk factor for each accident is compared with theprogram's risk factor, and the error rate was calculated. The mainobjective of this study is to improve the navigational safety of ships,by using the advance decision support model. According to the studyresult, fuzzy programming is a robust model that supports safenavigation.
Title of the Paper: Some New Properties of Fuzzy Maximal Regular Open Sets
Authors: Mohammed M. Ali Al-Shamiri, Khaled A. Alzobydi
Pages: 8-11
http://doi.org/10.46300/91017.2020.7.2
Abstract: A proper nonempty open subset of a fuzzy topological space is said to be a fuzzy maximal regular open set , if any regular open set which contains is or . The purpose of this paper is to study some new fundamental properties of fuzzy maximal regular open sets. The decomposition theorems for a fuzzy maximal regular open set are investigated. Notion and basic properties of radical of fuzzy maximal regular open sets are established, such as the law of fuzzy radical closure. Some new properties and characterization theorems of fuzzy maximal regular open set are achieved.
Title of the Paper: Fuzzy Variable Frame analysis for Speech Recognition
Authors: Vani H. Y. , Anusuya M. A.
Pages: 1-7
http://doi.org/10.46300/91017.2020.7.1
Abstract: Recent works in machine learning has focused on models such as Support Vector Machine(SVM), Artificial Neural Network(ANN) and Long Short Term Memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure has been modified in the framing phase to reduce the number of noisy frames using thresholding at two level local maxima procedures. A comparative results of various classifiers like SVM with kernel function, ANN and LSTM are tabulated for recognition accuracies. A fuzzy interpretation at the framing level to calculate optimal frames has been presented in this paper. In the proposed work 20% of unwanted processing of frames is reduced that equally produces the accuracies obtained by fixed frame analysis. An investigation shows that the obtained features with LSTM decrease word error rate still by 1% as increasing the recognition accuracy from 98 to 99% . approach.
