Introduction to Restricted Neutrosophic Set and Its Application

Somen

doi:https://doi.org/10.54216/IJNS.180206

Journal of Cybersecurity and Information Management | 2022

A Framework for creating a Safety and Security Management System (SSMS)

Safety and security risks to critical infrastructure organizations are well known, and incidents in both fields have taken place. To help critical infrastructure organizations manage these areas, safety and security standards have been created.  The main aim of this paper is to present a framework that has been created to manage both safety and security by providing guidance on how to create a Safety and Security Management System (SSMS).   The framework identifies and remediates conflicts and issues between IT, OT, safety, and security. While also creating processes that can combine safety and security compliance to standards to reduce duplication of work and allow one process to manage both areas. A survey was carried out to understand if the framework would be of use to organizations and to better understand the issues users have with managing safety and security and how they manage conflicts that can occur.  The survey showed key areas of concern for organizations and how the framework can be of use to them.  It identified six themes from the research and identified improvements opportunities for the framework that can be implemented. 

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Robert Kemp mail -

Richard Smith mail

link https://doi.org/10.54216/JCIM.090201

Volume & Issue

Vol. Volume 9 / Iss. Issue 2

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Journal of Cybersecurity and Information Management | 2022

Trust Aware Aquila Optimizer based Secure Data Transmission for Information Management in Wireless Sensor Networks

The province of wireless sensor network (WSN) is increasing continuously because of wide-ranging applications, namely, monitoring environmental conditions, military, and many other fields. But trust management in the WSN is the main objective as trust was utilized once cooperation among nodes becomes crucial to attaining reliable transmission. Thus, a new trust-based routing protocol is introduced to initiate secure routing. This study focuses on the design of Trust Aware Aquila Optimizer based Secure Data Transmission for Information Management (TAAO-SDTIM) in WSN. The presented TAAO-SDTIM model mainly intends to achieve maximum security and information management in WSN. The presented TAAO-SDTIM model determines optimum set of routes to base station (BS) utilizing a fitness function involving three parameters like residual energy (RE), distance to BS (DBS), and trust level (TL). The incorporation of the trust level of the nodes in the route selection process aids in appropriately selecting highly secure nodes in the data transmission procedure. For ensuring the enhanced performance of the TAAO-SDTIM model, a wide range of experiments are executed and the results pointed out the improved outcomes of the TAAO-SDTIM model over the other recent approaches. 

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Abedallah Zaid Abualkishik mail -

Ali A. Alwan mail

link https://doi.org/10.54216/JCIM.090104

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

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Fusion: Practice and Applications | 2022

Earthworm Optimization with Deep Transfer Learning Enabled Aerial Image Classification Model in IoT Enabled UAV Networks

Unmanned aerial vehicles (UAVs) can be placed effectively in offering high-quality services for Internet of Things (IoT) networks. It finds use in several applications such as smart city, smart healthcare, surveillance, environment monitoring, disaster management, etc. Classification of images captured by UAV networks, i.e., aerial image classification is a challenging task and can be solved by the design of artificial intelligence (AI) techniques. Therefore, this article presents an Earthworm Optimization with Deep Transfer Learning Enabled Aerial Image Classification (EWODTL-AIC) model in IoT enabled UAV networks. The major intention of the EWODTL-AIC technique is to effectually categorize different classes of aerial images captured by UAVs. The EWODTL-AIC technique initially employs AlexNet model as feature extractor for producing optimal feature vectors. Followed by, the hyperparameter values of the AlexNet model are decided by the utilization of earthworm optimization (EWO) algorithm. At last, the extreme gradient boosting (XGBoost) model is employed for the classification of aerial images. The experimental validation of the EWODTL-AIC model is performed using benchmark dataset. The extensive comparative analysis reported the better outcomes of the EWODTL-AIC technique over the other existing techniques. 

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Dr.R.PANDI SELVAM mail

link https://doi.org/10.54216/FPA.070104

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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Fusion: Practice and Applications | 2022

Support System Based Computer-Aided Detection for Skin Cancer: A Review

According to the American Society of Clinical Oncology, Computer-Aided Diagnosis (CAD) techniques have the tremendous possibility for the screening and early identification of melanoma. They are evaluated in terms of their current state-of-the-art, as well as current practices, challenges, and prospects in the areas of image screening, pre-processing of an image, segmentation of Region of Interest (ROI), feature extraction, feature selection, and classification of dermoscopic images. It is stated in this study that statistical information and outcomes from the most major implementations that have been reported to date are presented. We investigated the evaluation performance of many classifiers that had been developed specifically for the diagnosis of skin cancer. The fundamental aim of this paper is to develop a framework that will serve as a complete guideline for choosing relevant techniques for various elements of an automatic detection technique.

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Nechirvan Asaad Zebari mail -

Mehmet Emin Tenekeci mail

link https://doi.org/10.54216/FPA.070103

Volume & Issue

Vol. Volume 7 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2022

Neutrosophic set with Adaptive Neuro-Fuzzy Inference System for Liver Tumor Segmentation and Classification Model

Lung cancer is the abnormal development of cells in the lung causes serious risk to the health since lung has an interconnected system of blood vessel and lymphatic channel exposed to metastasis. The survival rate of lung cancer depends greatly on the earlier diagnosis and staging of the lung cancer. Computed Tomography (CT) image is commonly employed for lung cancer diagnosis since they offer data regarding distinct portions of the lung. The exactness of finding tumor location, volume and shape acting a major role in positive treatment and diagnosis of tumor. This article designs a novel neutrosophic set with adaptive neuro-fuzzy inference system for liver tumor segmentation and classification (NSANFIS-LTSC) model. The presented NSANFIS-LTSC model aims to identify and classify the presence of liver tumor from medical images. The presented NSANFIS-LTSC model primarily undergoes pre-processing to eradicate the noise. Followed by, the neutrosophic set (NS) based segmentation is applied to identify the affected tumor regions in the CT images. Besides, DenseNet-169 model is utilized to create feature vectors and dragonfly algorithm (DFA) is applied to tune the hyper parameters of the DenseNet-169 model. Finally, ANFIS classifier is exploited for the occurrence and classification of liver tumor. The simulation analysis of the NSANFIS-LTSC model is experimented using benchmark dataset and the results are investigated under several aspects. The simulation outcome reported the betterment of the NSANFIS-LTSC model over the recent methodologies. 

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Mohammed I. Alghamdi mail

link https://doi.org/10.54216/IJNS.180202

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

Network user interest mining method based on Neutrosophic cluster analysis

These days’ user interests have become more critical for companies and firms to introduce their content due to the growth in networks and the internet. So this method used neutrosophic sets for network user interest. In this paper, we proposed five main criteria and seventeen sub-criteria to show user interest in the network. The multi-criteria decision-making (MCDM) method is used to deal with various criteria and sub-criteria. So the Analytical Hierarchal Process (AHP) is used to show weights of criteria and sub-criteria to present the user interest in the network. An illustrative example provides to show calculations of the proposed method.

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Abedallah Zaid Abualkishik mail -

Anqi Li mail

link https://doi.org/10.54216/IJNS.180203

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

Neutrosophic Infi-Semi-Open Set via Neutrosophic Infi-Topological Spaces

In this article an attempt is made to introduce the notion of neutrosophic infi-topological space as an extension of infi-topological space and fuzzy infi-topological space. Besides, we define some open sets, namely, neutrosophic infi-open set, neutrosophic infi-semi-open set, neutrosophic infi-pre-open set, neutrosophic infi-b-open set. Then, we define some continuous functions namely, neutrosophic infi-continuous function, neutrosophic infi-semi-continuous function, neutrosophic infi-pre-continuous function, neutrosophic infi-b-continuous function via neutrosophic infi-topological space. Further, we formulate several interesting results on them via neutrosophic infi-topological spaces.

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Suman Das mail -

Rakhal Das mail -

Surapati Pramanik mail -

Binod Chandra Tripathy mail

link https://doi.org/10.54216/IJNS.180204

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

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American Journal of Business and Operations Research |

The Fuzziness, Similarity And The Symmetry Properties On The Neutrosophic Interval Probability

Abstract The neutrosophic interval statistical number (NISN) has been known to be very useful in expressing the interval values under indeterminate environments. One of the essential and so important useful as tools for measuring the degree of similarity between sets of given objects is the similarity measure . In this paper, neutrosophic numbers as well as the generalized Dice similarity measure for neutrosophic numbers for two sets are defined after which the axioms of fuzziness similarity and symmetry satisfying the NISN the properties were proved.

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International Journal of Neutrosophic Science | 2022

Graded Mean Integral Distance Measure and VIKOR Strategy Based MCDM Skill in Trapezoidal Neutrosophic Number

This article exceedingly induces a completely new impression of graded mean integral representation in trapezoidal neutrosophic number domain corresponding to each membership function. Furthermore employing these integral representations, a new fangled graded mean integral distance measure is produced between two trapezoidal neutrosophic numbers. Notably, a numerical business economy based Multi Criteria Decision Making (MCDM) problem is fabricated along with the explication of neutrosophic theory to authenticate our suggested course of action in the decision making policy with the prominent solution scheme of VlseKriterijumska Optimizcija I Kaompromisno Resenje (VIKOR) technique for recognising the best alternative from a finite set. Lastly, the comparison work acts as an additional encouragement of our proposed scheme.

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Avishek Chakraborty mail -

Baisakhi Banik mail -

Said Broumi mail -

Soheil Salahshour mail

link https://doi.org/10.54216/IJNS.180205

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2022

Introduction to Restricted Neutrosophic Set and Its Application

This paper is devoted to introduce a novel concept known as restricted neutrosophic set (RNS) as another subclass of neutrosophic set (NS). The purpose of introducing the notion of RNS is to give a new mathematical theory that is more promising and purposeful than the existing fuzzy-centric theories to solve the uncertainty based real-world problems in a lucid manner. From decision-makers point of view, the new mathematical tool can be viewed as a direct extension of Pythagorean neutrosophic set (PNS). The PNS has its own inherent limitation for which the decision-makers can’t answer a certain type of problem. For example, in a certain problem, if we consider the degree of truth-membership =0.8, degree of indeterminate-membership , and the degree of falsity-membership =0.8, then it gives an absurd result under PNS. To remove such kind of absurdity, there is a demand to introduce another superior set-theoretical concept that provides more information for the decision-makers. This gives rise to the introduction of RNS. In RNS, we choose any value belongs to for the three membership degrees so that their product always limited to 1. So, the beauty of RNS is that it can accommodate more information within small range with relaxed membership values i.e under RNS we can consider the maximum membership triplet as . Undoubtedly the RNS gives more compact set-theoretical model to describe imprecise knowledge with ease. Finally, a decision-making approach based algorithm is introduced and applied to solve medical diagnosis problem.

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Somen Debnath mail

link https://doi.org/10.54216/IJNS.180206

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

Details open_in_new