De-Noising and Segmentation of Medical Images using Neutrophilic Sets

C. S.; V. D. Ambeth; G.; R.; N. Senthil

doi:https://doi.org/10.54216/FPA.110208

International Journal of Advances in Applied Computational Intelligence | 2022

Intelligent systems and AI techniques: Recent advances and Future directions

In recent years, Intelligent systems and AI techniques have advanced significantly, thanks to breakthroughs in deep learning, reinforcement learning, and related fields. These advancements have led to the development of more efficient and accurate systems, including computer vision, natural language processing, and autonomous systems. The future of intelligent systems and AI techniques involves further improvements in deep learning, explainable AI, transfer learning, and human-AI collaboration. As these systems continue to be adopted, they have the potential to revolutionize our lives and create new opportunities for progress. However, ethical concerns such as bias and privacy must be addressed, and future research should focus on developing more secure systems and integrating these technologies with emerging technologies like quantum computing and blockchain. Overall, the field of intelligent systems and AI techniques is primed for continued growth and innovation, offering exciting possibilities for solving some of the most pressing challenges of our time.

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Ismail Eyad Samara mail

link https://doi.org/10.54216/IJAACI.010202

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Vol. Volume 1 / Iss. Issue 2

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Journal of Neutrosophic and Fuzzy Systems | 2023

Bipolar neutrosophic soft continuity mappings

In this article, we have introduced a bipolar neutrosophic soft point and investigated some of the properties with appropriate examples. Further, we have defined bipolar neutrosophic soft continuous mapping through bipolar neutrosophic soft points. Some results have been produced as theorems and examples. Further, we have discussed the relationship between the proposed mapping with the various existing mappings.

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P. Arulpandy mail

link https://doi.org/10.54216/JNFS.060104

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Vol. Volume 6 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2023

Neutrosophic-Operational and Multi-Decision Analysis Study for Meeting the Demands of FinTech Education Marketing

FinTech marketing education poses unique challenges that require new research directions. The constantly-evolving nature of the industry, coupled with the need to keep pace with technological advancements, demands an innovative approach to curriculum design and evaluation. Traditional education methods may not be sufficient to prepare students for careers in FinTech marketing, emphasizing the need for a multi-dimensional evaluation framework that considers business requirements, market trends, and customer needs. A Neutrosophic-Operational and Multi-Decision Analysis approach can provide a new direction for research, enabling educators to meet the evolving needs of the industry and better prepare students for successful careers in FinTech marketing. Throughout this article, we demonstrate a hybrid application of the Neutrosophic-AHP and the Multi-Criteria Decision Analysis technique for determining and assessing the most important characteristics of e-learning systems in the field of sustainability science education. Sustainability, scientific education, e-learning, and technological criterion are some of the most important to consider in order to reach this stated objective. The participative neutrosophic AHP method examined sixteen sub-criteria in terms of the value and calculation of coefficients within the framework of impact and evaluation. The most crucial factors for the ultimate choice issue are gathered. Therefore, techniques such as neutrosophic-operational and multi-decision analysis, as well as expert surveys, may be used to identify the most important criteria for e-learning in the field of sustainability science, which can then be employed to develop adaptable and relevant decision features.

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Noura Metawa mail -

Reneh Abokhoza mail -

Ahmed Aziz mail

link https://doi.org/10.54216/IJNS.200416

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Vol. Volume 20 / Iss. Issue 4

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Journal of Neutrosophic and Fuzzy Systems | 2023

A Multi Objective Epq Model with Uniform Demand and Productıon Rate Along Wıth Shortages Under Intuitioistic Fuzzy Programmıng Approach

In this paper we have described a multi-objective economic production quantity (EPQ) model with uniform demand rate as well as shortages. In this model we have considered the production rate as finite. Due to uncertainty in the various cost parameters, most of the costs parameters are taken as pentagonal fuzzy number. The model has been solved by Fuzzy Non-Linear Programming Problem (FNLP), Fuzzy Additive Goal Programming Problem (FAGP) and Intuitionistic fuzzy programming approach (IFP).To demonstrate the validity of this model some numerical examples have been given lastly. The sensitivity analysis for some cost parameters has also been given.

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Kausik Das mail -

Sahidul Islam mail

link https://doi.org/10.54216/JNFS.060105

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Vol. Volume 6 / Iss. Issue 1

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American Journal of Business and Operations Research | 2023

Assessment of the relationship between sustainability and resilience in supply chain management using α-D MCDM

Several research on the topic of supply chain resilience and sustainability have been done in recent years. However, they make clear that there are various points of view when it comes to the sustainability-resilience relationship. To adapt supply chains (SC) to the needs of contemporary manufacturing processes, new trends and approaches in environmental protection and social welfare have been put into place. Even though sustainability and resilience have each been extensively examined separately, there aren't many concepts that combine them to determine supply chain performance. Therefore, this study is displaying the aspects of supply chain resilience and how it may affect sustainability triple bottom line. Moreover, this study presents an extension of analytic hierarchy process (AHP), α-Discounting multi-criteria decision-making (α-D MCDM) to evaluate the resilience aspects in more consistent manner. This study proposes an idea of utilization of α-D MCDM in different manner to solve several supply chain evaluation issues.  

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Rehab Mohamed mail -

Mahmoud Ismail mail

link https://doi.org/10.54216/AJBOR.100201

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Vol. Volume 10 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2023

Neutrosophic G* -Closed Sets in Neutrosophic Topological Spaces

A neutrosophic set is a mathematical approach that helps with challenges involving data that is indeterminate, imprecise, or inconsistent. The goal of this manuscript is to present the notion of neutrosophic g*-closed sets and neutrosophic g*-open sets. In this situation, we prove various neutrosophic generalized theorems. The findings support previous methodologies in the literature and are backed up by various examples and an application.

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Wadei Faris AL-Omeri mail

link https://doi.org/10.54216/IJNS.200417

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Vol. Volume 20 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2023

Application of Neutrosophic Filters in Lattice Implication Algebra

Neutrosophic set theory is applied to lattice implication algebra, and the concept of neutrosophic filters and neutrosophic lattice filters in lattice implication algebra are introduced. Several properties are investigated.  Characterizations of a neutrosophic filter are discussed. Finally, we proved that every neutrosophic filter is a neutrosophic lattice filter, but the converse is invalid.

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V. S. Naga Malleswari mail -

Kiran kumar mail -

K. Bhagya Lakshmi mail -

G. Luka mail -

T. Srinivasa Rao mail

link https://doi.org/10.54216/IJNS.200418

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Vol. Volume 20 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2023

A Study on various Pentapartitioned Neutrosophic generalized closed sets

The purpose of this paper is to introduce the concept of various Pentapartitioned neutrosophic generalized closed sets such as PNg-closed set, PNω-closed set, PNgb-closed set in Pentapartitioned Neutrosophic Topological spaces. We also study some of their properties with counter examples.  

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Subasree R. mail -

Basari Kodi K. mail -

Sathikala L. mail -

Subramanian K. mail

link https://doi.org/10.54216/IJNS.200419

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Vol. Volume 20 / Iss. Issue 4

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Fusion: Practice and Applications | 2023

Relevance Mapping based CNN model with OSR-FCA Technique for Multi-label DR Classification

In computer vision, multi-label classification (MLC) is especially important for medical picture analysis. We use MLC to classify diverse stages of diabetic retinopathy (DR) using colour fundus pictures of varying brightness and contrast. As a result, ophthalmologists can now identify the early warning symptoms of DR and the varying stages of DR, allowing them to begin therapy sooner and prevent further difficulties. Using the outlier-based shallow regularization fuzzy clustering approach (OSR-FCA), for classification we present a deep learning method in this paper's picture segmentation task. The fundamental feature of the proposed system is the ability to identify and analyse different degenerative changes in the retina that occur alongside the progression of DR without requiring the patient to undergo costly diagnostic procedures like dye injections. Photographs are first resized, converted to grayscale, cleaned of noise, and the contrast increased by the use of histogram equalization adopting the CLAHE method. The clipping limit of CLAHE is optimized by the help of the rat optimization algorithm, which is applied throughout the histogram process. In addition, a Gaussian metric regularization to the objective function in OSR-FCA is a great way to enhance clustering approaches that use fuzzy membership with sparseness which is based on neutrosophic set. This research proposes a new approach called "Relevance Mapping on Multi-Class Label" (RMMCL) for locating and viewing regions of interest (ROI) inside a segmented picture. These representations give better explanations for the predictions of the DL model founded on a convolutional neural network-(CNN). The validation of two ML datasets showed the projected model outperformed the existing models by achieving an average correctness of 97.27 percent over five stages of the IDRID dataset.

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S. Hemamalini mail -

V. D. Ambeth Kumar mail -

R. Venkatesan mail -

S. Malathi mail

link https://doi.org/10.54216/FPA.110207

Volume & Issue

Vol. Volume 11 / Iss. Issue 2

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Fusion: Practice and Applications | 2023

De-Noising and Segmentation of Medical Images using Neutrophilic Sets

Medical diagnosis and prognosis are challenging tasks due to subjectivity and inherent uncertainty in medical images. Inconsistencies in expert opinions can result in incorrect diagnoses. Neutrosophic theory, a mathematical framework that deals with imprecise or incomplete data, has shown promise in addressing the challenges posed by medical image processing. A neutrosophic theory approach is explored in this paper for de-noising and segmenting medical images. Neutrosophic theory has been utilized to represent the different degrees of truth in each piece of information, resulting in better performance in de-noising and segmentation tasks. Neutosophic theory presents a promising avenue for future investigation in medical image processing as shown in this study.

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C. S. Manigandaa mail -

V. D. Ambeth Kumar mail -

G. Ragunath mail -

R. Venkatesan mail -

N. Senthil Kumar mail

link https://doi.org/10.54216/FPA.110208

Volume & Issue

Vol. Volume 11 / Iss. Issue 2

Details open_in_new