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International Journal of Neutrosophic Science | 2019

A Contribution to Neutrosophic Groups

The objective of this paper is to define some  new substructures (AH-substructures) in a neutrosophic group. Also, it deals with some elementary properties of AH-subgroups, AH-normality, AH-homomorphisms, AH-quotients and AH-direct products.

groups
Mohammad Abobala mail -
Ahmed Hatip mail -
Riad K. Alhamido mail
link https://doi.org/10.54216/IJNS.000202

Volume & Issue

Vol. Volume 0 - 2019 / Iss. Issue II- Vol 0

Details open_in_new
International Journal of Neutrosophic Science | 2019

Star Neutrosophic Fuzzy Topological Space

In this paper, we aim to develop a new type of neutrosophic fuzzy set called the star neutrosophic fuzzy set as a generalization to star neutrosophic crisp set defined in by Salama et al.[8], and study some of its properties. Adedd to, we introduce the notion of star neutrosophic fuzzy topological space as a generalization to some topological consepts as star neutrosophic fuzzy closure, and star neutrosophic fuzzy interior. Finally, we  extend the concepts of  fuzzy topological  space, and intuitionistic fuzzy  topological  space to  the  case  of  star neutrosophic fuzzy sets.  

groups
A.A.Salama mail -
Hewayda ElGhawalby mail -
A.M.Nasr mail
link https://doi.org/10.54216/IJNS.000203

Volume & Issue

Vol. Volume 0 - 2019 / Iss. Issue II- Vol 0

Details open_in_new
International Journal of Neutrosophic Science | 2019

Neutrosophic Quotient Algebra

The algebraic properties of neutrosphic ideals over algebra, isomorphism properties of neutrosophic ideal and neutrosophic modules over algebra are discussed in this paper. Some of the charactrisations of Neutrosophic quotient algebra are derived and the role of algebraic structures is studied in the context of neutrosophic set.  This paper expands the definition of quotient algebra within the context of neutrosophical set.

groups
Binu R mail
link https://doi.org/10.54216/IJNS.000204

Volume & Issue

Vol. Volume 0 - 2019 / Iss. Issue II- Vol 0

Details open_in_new
International Journal of Neutrosophic Science | 2019

Neutrosophic Crisp B-Functions

  The purpose of the present paper is to introduce and study the concept of B-continuous function and B-open function in neutrosophic crisp topological spaces. Finally, some characterizations concerning neutrosophic crisp functions are presented and one obtains several properties.  

groups
A. A. Salama mail
link https://doi.org/10.54216/IJNS.000205

Volume & Issue

Vol. Volume 0 - 2019 / Iss. Issue II- Vol 0

Details open_in_new
Journal of Cybersecurity and Information Management | 2020

Survey on Deep Learning Approaches for Aspect Level Opinion Mining

The the task of Aspect-based opinion mining (AbOM) is an emeraging research area, where aspects are mined, the corresponding opinion are scrutinized and sentiments are continuously changed, is gaining increased attention with growing feedback of clients and community across various social media streams. The gigantic improvements of deep learning (DL) techniques in natural language processing (NLP) tasks motivated research community to introduce  a novel DL models and for AbSA, each investigate a diverse research points from different perspective, that cope with imminent problems and composite circumstances of AbOM. Consequently, in this survey paper, we concentrate on the limitations of the current studies and challenges relevant to mining of various aspects and their pertinent opinion, interrelationship delineations among different aspects, interactions, dependencies and contextual-semantic associations among various entities for enhanced opinion precision, and estimation of the automaticity of opinion polrity development. A laborious investigation of the later  advancement is discussed depending on their contribution in the direction of spotlighting and alleviating the shortcomings related to Aspect Extraction (AE), AbOM, opinion progression (OP). The reported performance for each scrutinized study of Aspect Extraction and Aspect opinion Analysis is also given, revealing the numeriacal evaluation of the presented approach. Future research trends are introduce and delibrated by critically analysing the existing recent approaches, that will be supportive for researchers and advantageous for refining aspect based opinion classification.

groups
AHMED R. ABAS mail -
IBRAHIM EL-HENAWY mail -
AMR ABDELLATIF mail -
HOSSAM MOHAMED mail
link https://doi.org/10.54216/JCIM.040104

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2020

Detection and Classification of Alcoholics Using Electroencephalogram Signal and Support Vector Machine

Alcoholism may be recognized with the use of (EEG) analyzing signals. None-the-less, the analysis of the multi-channel signals of EEG is a complicated issue that usually needs performing complex computation operations and takes quite a long time to execute. The presented research will propose 13 optimal channel to feature extraction. In this research, an innovative horizontal visibility graph entropy (HVGE) method has been proposed for evaluating signals of EEG from controlled drinkers and alcoholic subjects and comparing against an approach of sample entropy (SaE). Values of HVGE and SaE have been obtained from 1200 records of bio-medical signals.  While  in classification step using SVM as classifier.

groups
Shaymaa Adnan Abdulrahman mail -
Rafah Amer Jaafar mail
link https://doi.org/10.54216/FPA.020103

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

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International Journal of Neutrosophic Science | 2020

A Note on Neutrosophic Polynomials and Some of Its Properties

The purpose of this article is to study Neutrosophic polynomials i.e. polynomials which are Neutrosophic in nature and study its properties with the help of Neutrosophic numbers. Apart from this we discuss different types of neutrosophic polynomials with concrete examples and establish some theorems and results which will be useful for the further study. We also give a solution method to find the approximate roots of a Neutrosophic polynomial equation.

groups
somendebnath mail
link

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International Journal of Neutrosophic Science | 2020

Plithogenic Cognitive Maps in Decision Making

Plithogenic sets introduced by Smarandache (2018) have disclosed new research vistas and this paper introduces the novel concept of plithogenic cognitive maps (PCM) and its applications in decision making. The new approach of defining instantaneous state neutrosophic vector with the confinement of indeterminacy to (0,1] is proposed to quantify the degree of indeterminacy. The resultant vector is obtained by applying instantaneous state vector through the connection matrix together with plithogenic operators comprising the contradiction degrees. The connection matrix is represented as fuzzy matrix and neutrosophic matrix and the resultant vector is determined by applying plithogenic fuzzy operators and plithogenic neutrosophic operators respectively. The obtained results are highly feasible in making the decision as it incorporates the contradiction degree of the conceptual nodes with respect to the dominant node. This research work will certainly pave the way for developing new approaches in decision making using PCM.

groups
Nivetha Martin mail -
Florentin Smarandache mail
link https://doi.org/10.54216/IJNS.090101

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new
Fusion: Practice and Applications | 2020

Ensemble Learning for Facial Expression Recognition

Facial expressions are the translation of the emotions such as anger, sadness, happiness, disgust felt by a person. Facial expression recognition, classification of expressions which has application in various industries such as hospitality, medical to name a few. There are various datasets available for facial expression recognition, we used FER 2013 dataset to build a classification algorithm. This algorithm classifies the emotions into seven categories namely, angry, disgust, happy, sad, fear, surprise and neutral. In traditional convolutional neural network algorithm the computing time is very large, ensemble learning significantly reduced the computing time and offered a promising accuracy. Features of images were extracted using the convolutional neural network, further these features were implemented using XGBoost and Random Forest to build classification algorithms and an accuracy of 77% and 74% was obtained. This was comparable to the accuracy obtained by traditional convolutional neural network which was 75% also with very less computing time.

groups
Anjali Raghav mail -
Monika Gupta mail
link https://doi.org/10.54216/FPA.020104

Volume & Issue

Vol. Volume 2 / Iss. Issue 1

Details open_in_new