Enhancing E-commerce Security through Fake News Detection Using Natural Language Processing and Advanced Feature Engineering Technique

Lama Sameer

doi:https://doi.org/10.54216/JISIoT.150208

International Journal of Neutrosophic Science | 2025

Investigating Workplace Challenges: A Neutrosophic Soft Set Analysis of Female Workers' Problems in Diverse Industries

This research proposes a novel approach to rank the problems faced by female employees in various sectors by utilizing the concept of the bipolar single-valued Neutrosophic soft set-in variable. The feature assessment used an enormous collection of multi-observer information as a basis for examining the issues encountered by women employed in a variety of sectors. An effective method for identifying the Neutrosophic domain's choice-making problem is the Neutrosophic Soft Set. The creation of similar tables has shaped the investigation into classification. In a Neutrosophic setting, grouping objects and persons according to their properties, capacities, the result, etc., is advantageous.

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John Jayaraj J. mail -

I. Paulraj Jayasimman mail -

N. Jose Parvin Praveena mail -

broumi said mail

link https://doi.org/10.54216/IJNS.250434

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

Some New Results about Neutrosophic KU-Module

In this paper, we present new concept namely neutrosophic algebra. Some types of notions such as KU-module, KU-ideal and KU-submodule. We proved that if AI is minimal submodule, then AI ascending (descending) chain condition. On the other hand, more results about Neutrosophic exact sequence and Neutrosophic homomorphism KU-module have been presented.

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Mohammed N. Hamidy mail -

Majid Mohammed Abed mail

link https://doi.org/10.54216/IJNS.250435

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2025

On a convex topological order and neutrosophic continuous sets

In this paper, we employ the classical topological preorder to introduce the concept of topologically bounded sets, in order to relate it to the Collatz conjecture problem. In addition, this preorder allows us to derive some results about topologically convex sets, showing that these form a convex structure. Finally, using this topological preorder, we define the neutrosophic continuous sets and establish the necessary conditions to identify the points that are connected to these sets, which form a topological convex set.

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Elvis Aponte mail -

Jorge Vielma mail -

Jos´e Sanabria mail -

Ennis Rosas mail

link https://doi.org/10.54216/IJNS.250436

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic N-structures on Sheffer stroke UP-algebras

The study defines a neutrosophic N-subalgebra and a level set of a neutrosophic N-structure on Sheffer stroke UP-algebras. It appears that these concepts are integral to understanding the behavior of neutrosophic logic within the framework of Sheffer stroke UP-algebras. The study establishes a relationship between subalgebras and level sets on Sheffer stroke UP-algebras. Specifically, it proves that the level set of neutrosophic Nsubalgebras on this algebra is its subalgebra, and vice versa. This indicates a tight connection between these concepts within the given algebraic structure. It is stated that the family of all neutrosophic N-subalgebras of a Sheffer stroke UP-algebra forms a complete distributive lattice. This suggests that there is a well-defined structure and order among these subalgebras, allowing for systematic analysis. The study describes a neutrosophic N-ideal of a Sheffer stroke UP-algebra and provides some of its properties. Additionally, it is shown that every neutrosophic N-ideal of a Sheffer stroke UP-algebra is also its neutrosophic N-subalgebra, though the inverse is generally not true. This highlights the specific characteristics and behavior of neutrosophic Nideals within the given algebraic context.

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S. R. Vidhya mail -

Aiyared Iampan mail -

Neelamegarajan Rajesh mail

link https://doi.org/10.54216/IJNS.250437

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic Maxwell–Boltzmann Distribution: Properties and Application to Healthcare Data

In this work, we present and analyze new probability distribution by generalizing the classical Maxwell–Boltzmann model to neutrosophic structure. The generalized structure, known as the neutrosophic Maxwell (NMX) model that is designed to analyze data with imprecise or vague information. Closed-form expressions for cumulative distribution functions, probability density functions, survival functions, hazard functions, and moments, moment generating functions, mode, skewness, and kurtosis are derived as part of its detailed mathematical and statistical characteristics. The parameter estimation of the suggested model is carried out employing the maximum likelihood estimation (MLE) technique, and the statistical properties of the estimators are discussed in uncertain environments. The inverse cumulative distribution method is established to generate random samples from the proposed model and to evaluate the efficiency of the MLE method. Eventually, a real-world healthcare data set is used to show the efficacy of the proposed model.  This research provides new knowledge in the field of neutrosophic statistics, laying a foundation for further exploration in this area

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Afrah Al Bossly mail -

Adnan Amin mail

link https://doi.org/10.54216/IJNS.250438

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

Neutrosophic Cordial Labeling on Helm and Closed Helm Graph

The Neutrosophic Cordial Labeling Graph integrates both neutrosophic labeling and Cordial Labeling. Building on our previous work, we have extended our study to include Neutrosophic Cordial Labeling for Helm and Closed Helm Graphs. This extension allows us to explore the application of Neutrosophic Cordial Labeling in more complex graph structures, providing insights into their properties and relationships. One of the key aspects of our research is investigating the relationship between Cordial and Neutrosophic Cordial Labeling. By comparing and contrasting these labeling techniques [4], we aim to uncover similarities, differences, and potential synergies between them. This analysis contributes to a deeper understanding of graph labeling methodologies and their implications in various graph-theoretic applications [18]. Our research contributes to the advancement of graph labeling theory, particularly in the context of Neutrosophic Cordial Labeling and its applications in Helm and Closed Helm Graphs. By exploring these concepts and relationships, we aim to enhance the theoretical foundation and practical utility of graph labeling techniques in diverse domains [16,17].

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Tephilla Joice P. mail -

A. Rajkumar mail

link https://doi.org/10.54216/IJNS.250439

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

Fusion: Practice and Applications | 2025

Optimized Gaussian Convolutional Neural Network Framework for Enhanced Detection of Deepfakes in Digital Media

With the latest developments in computer vision, processing, accurate deepfakes (DF) require powerful tools. Recent research has developed a useful technique for identifying DFs in networks. The inter-frame differences of the gathered media streams, however, are beyond the scope of most methods. In this research, an Optimized Gaussian Convolutional Neural Network Framework for Enhanced Detection of Deepfakes in Digital Media (OGCNN-DDF-DM) is proposed. Initially the input images are gathered using the Face Forensics++ (FF++), and Deep Fake Detection Challenge dataset (DFDC) datasets. Then the Multi-Window Savitzky-Golay Filter (MWSGF) is used to improve quality of the DF images and reduce noise. Afterwards, Simple Contrastive Graph Clustering (SCGC) achieves segmentation. Here, the image's facial regions are segmented. Then, the texture features are extracted using Revised Tunable Q-Factor Wavelet Transform (RTQWT) is introduced. The extracted features are fed to Gaussian Convolutional Neural Network (GCNN) to categorize the image as real or fake. Finally, Gooseneck Barnacle Optimization Algorithm (GBOA) is proposed to improve the GCNN classifier. Performance parameters including accuracy, precision, recall, specificity, ROC, and computation time are examined. The introduced method attained an accuracy of 99.6% and the precision of 98.9% on the FaceForensics++ dataset, and 99.5% and 98.6% on the DFDC dataset, respectively.

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Ahmed Alhussen mail

link https://doi.org/10.54216/FPA.180217

Volume & Issue

Vol. Volume 18 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

The Analysis of Pentagonal Fuzzy Numbers in a Neutrosophic Fuzzy Inventory Management Modelling with Minimal Insufficient Supply Required and Fuzzy Consumption

The fuzzy stock administration demonstrates displayed in this work employments neutrosophic set hypothesis, pentagonal fuzzy numbers, and the Graded mean Integration Representation (GMIR) strategy for defuzzification. Request rates, arrange amounts, utilization rates, holding costs, setup costs, and deficiency costs are all spoken to as fuzzy parameters within the demonstrate to account for the inborn instability and vacillation. To reduce by and large costs, the whole cost work is calculated, taking setup, holding, and shortage costs into consideration. In arrange to speak to the combined impacts of a few fetched components, the overall taken a toll work is rearranged and the ideal arrange amount is built up beneath fuzzy conditions utilizing pentagonal fuzzy parameters. The demonstrate is assessed beneath different degrees of instability through a case-based investigation, advertising an exhaustive system for making choices on stock administration in equivocal and dubious circumstances. The results appear how versatile and capable the show is for improving fetched advancement and stock control.

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Kalaiarasi K. mail -

Nasreen Kausar mail -

Said Broumi mail -

Tonguc Cagin mail

link https://doi.org/10.54216/IJNS.250440

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

Time-Optical Control Strategies for SIR Epidemic Models in Cattle and Neutrosophic Fuzzy Modelling

The utilization of neutrosophic fuzzy logic with machine learning constitutes a revolutionary way of improving epidemic modelling. With the help of Weka, this method solves the problem of uncertainty and vagueness that is characteristic of epidemic processes with the help of neutrosophic equations. These equations enhance the way how indeterminacy of epidemic levels can be modelled, therefore enhancing predictions of complex networks. The effectiveness of the proposed framework is confirmed by extensive evaluations providing extensive tables and visualizations regarding the improvements in the accuracy and reliability of the models. Further, the work explores time-optimal control strategies of SIR epidemic models. It shows exactly how bang-bang controls work avoiding the duration of outbreaks drastically, especially if introduced with delayed interventions. This finding is especially important for controlling the health of livestock since the response to disease outbreaks has to be done as soon as possible because of stringent measures on animal health. Altogether, the analysis presented therein contains strong recommendations that would help to improve the handling of epidemics and better understand the approaches to employ in decision-making under conditions of risk and ambiguity.

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T. Kavitha mail -

P. V. N. Hanumantha Ravi mail -

K. Meenakshi mail -

S. Shunmugapriya mail -

Shrivalli H. Y. mail -

Elangovan Muniyandy mail

link https://doi.org/10.54216/IJNS.250441

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2025

Enhancing E-commerce Security through Fake News Detection Using Natural Language Processing and Advanced Feature Engineering Technique

E-commerce has simplified customers' lives and offered a range of items, but it has also made them vulnerable to frauds. Fake news on e-commerce platforms threatens trust, brand image, and economic stability. Researchers have shown that contemporary Natural Language Processing (NLP) and machine learning can stop bogus news. However, e-commerce companies still struggle to distinguish phony news from real information. Fast knowledge diffusion can cause financial loss, reputation damage, and customer distrust. Thus, e-commerce false news identification requires robust and trustworthy methods. This investigation will successfully recognize and discriminate fake news. High Feature Extraction uses Word2vec and Term Frequency-Inverse Document Frequency (TF-IDF) to extract features. The optimum feature subset is determined via feature selection utilizing the least absolute shrinkage and selector operator (LASSO). The study involves four phases: Extraction, selection, classification, and data processing are the four steps. To remove raw data, data preparation utilizes stemming, lemmatization, and stop word removal. The suggested method averages model outputs to reduce overfitting and improve prediction stability. DIstilBERT with multi-stacked LSTM is tested on WELFake and ranked by F1 score, sensitivity, accuracy, and specificity. The multi-stacked LSTM distiller has 99.77% accuracy, far greater than the others do. We can use it to detect bogus news. It boosts customer confidence and Internet commerce legitimacy by improving accuracy and consistency.

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Lama Sameer Khoshaim mail

link https://doi.org/10.54216/JISIoT.150208

Volume & Issue

Vol. Volume 15 / Iss. Issue 2

Details open_in_new