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On The 3-Cyclic Refined Neutrosophic Real Roots of Unity and Their Algebraic Classification

The objective of this paper is to find all formulas that describe the 3-cyclic refined neutrosophic real solutions of the equation 𝑋𝑛=1 which are called 3-cyclic refined real roots of unity. Also, we classify the algebraic group represented by these solutions as a direct product of some familiar finite abelian groups. On the other hand, we illustrate many examples to clarify the validity of our work.

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Agnes Osagie mail
link https://doi.org/10.54216/JNFS.090105

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new

Solving of First Order Initial Value Problem Using Fuzzy Kamal Transform in Neutrosophic Environment

This manuscript presents a novel approach for solving first-order initial value problems by leveraging the Fuzzy Kamal Transform within a Neutrosophic framework. By integrating fuzzy logic with Neutrosophic set theory, the method adeptly addresses uncertainties inherent in differential equations. The efficacy of this method is demonstrated through the exposition of various illustrative examples.

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Azal J. Mera mail -
Huda A. Hadi mail -
Sahar M. Jabbar mail
link https://doi.org/10.54216/IJNS.250323

Volume & Issue

Vol. Volume 25 / Iss. Issue 3

Details open_in_new

The Zariski topology on the graded second spectrum of a graded module

Let R be a G-graded ring and M be a G-graded R-module. The graded second spectrum of M, denoted by Specs G(M), is the set of all graded second submodules of M. In this paper, we define a topology on Specs G(M) which is analogous to that for SpecG(R), and investigate several topological properties of this topology.

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Saif Salam mail -
Khaldoun Al-Zoubi mail
link https://doi.org/10.54216/IJNS.250324

Volume & Issue

Vol. Volume 25 / Iss. Issue 3

Details open_in_new

Integrating Neutrosophic Theory for Improved Decision-Making in Wireless Body Area Networks: Enhancing Accuracy and Efficiency in Health Monitoring

Wireless Body Area Networks (WBANs) play a pivotal role in modern healthcare by enabling continuous monitoring of physiological data through sensors placed on or around the human body. Despite their significant benefits, WBANs face challenges such as data uncertainty, complex decision-making processes, and dynamic network conditions. These challenges can lead to inaccuracies and inefficiencies in health monitoring and diagnostics. The paper's main aim is to incorporate neutrosophic theory into Wireless Body Area Networks to provide enhancements in decision-making. In modern healthcare, the use of WBANs for monitoring physiological data by sensors, which are attached to or around the human body, can be continuous. Despite huge advantages, the main challenges that WBANs face are the uncertainties in data, complex decision-making processes, and dynamic network conditions, making health monitoring and diagnostics inaccurate and inefficient. In this paper, authors propose a robust framework to map sensor data into the neutrosophic domain and apply neutrosophic logic for enhanced accuracy and reliability of decision-making. In this paper, a Neutrosophic Decision-Making Algorithm is proposed, and its performance is compared with other decision-making techniques in terms of accuracy, response time, energy efficiency, and reliability. Experimental results show major improvements of around 95.3% in accuracy and a reduction of up to 25% in response time and energy consumption. Results underline the potential of neutrosophic theory for revolutionizing decision-making processes within WBANs to ensure more reliable and efficient health monitoring. This approach enables not only operational life but also improves patient outcome, avoiding a wrong diagnosis, during long-term health monitoring applications using WBAN devices.

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Intisar A.M. Al Sayed mail -
Bourair Al-Attar mail -
Lateef Abd Zaid Qudr mail -
Azmi Shawkat Abdulbaqi mail -
Jamal Fadhil Tawfeq mail -
Ravi Sekhar mail -
Pritesh Shah mail -
Marshiana Devaerakkam mail
link https://doi.org/10.54216/IJNS.250325

Volume & Issue

Vol. Volume 25 / Iss. Issue 3

Details open_in_new

On the Nature of Solutions of Discrete Time Lyapunov Equations

This paper provides a method to solve the discrete time Lyapunov equation. Identified and discussed. If the equation takes the following form: D (λy+μz) = λDy+ μDz , 𝑦,z∈ y; λ ,μ ∈𝐹 . If ∃ a constant e∈∞ ∋ ||Dy|| ≤ e ||y||, y ∀Y. and D is bounded, then D is called a linear operator equation. In particular, (Lyapunov and Sylvester operator equations) are very important in differential equations, integral equations and many other branches of mathematics. The study of solutions and of the above equestion We also discussed operator equations and special kinds of operators and studied some elementary operators. These operators are generalizations of operators τ𝐴𝐷:𝐷(𝐻)→𝐷(𝐻) τ𝐴𝐷:𝜏𝐴𝐷(𝑦)=𝐴𝑦−𝑦𝐷, 𝑦∈𝐷(𝐻)

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Mohammed Noori Joudah mail -
Emad Farhood Muhi mail
link https://doi.org/10.54216/PMTCS.040203

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Accurate Numerical Method Using Exponential Spline for solving boundary Value Problems

This study introduces a precise numerical technique employing exponential splines for singly perturbed singularity boundary values problems. A numerical scheme is devised to address issues encountered in diverse scientific and engineering domains. The framework consists of a triad of nonlinear equations. The approach is employed in several test cases to demonstrate accuracy and implementation.

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Ahmed R Khlefha mail
link https://doi.org/10.54216/PMTCS.040204

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

Enhancing Convolutional Neural Network for Image Retrieval

With the continuous progress of image retrieval technology, the speed of searching for the required image from a large amount of image data has become an important issue. Convolutional neural networks (CNNs) have been used in image retrieval. However, many image retrieval systems based on CNNs have poor ability to express image features. Content-based Image Retrieval (CBIR) is a method of finding desired images from image databases. However, CBIR suffers from lower accuracy in retrieving images from large-scale image databases. In this paper, the proposed system is an improvement of the convolutional neural network for greater accuracy and a machine learning tool that can be used for automatic image retrieval. It includes two phases; the first phase (offline processing) consist of two stages; stage1 for CNN model classification while stage 2 for extracts high-level features directly from CNN by a flattening layer, which will be stored into a vector. In the second phase (online processing), the retrieval depends on query by image (QBI) from the system, which relies on the online CNN model stage to extract the features of the transmitted image. Afterward, an evaluation is conducted between the extracted features and the features that were previously stored by employing the Hamming distance to return all similar images. Last, it retrieves all the images and sends them to the system. Classification for images was achieved with 97.94% deep learning results, while for retrieved images, the deep learning was 98.94%. For this paper, work done on COREL image dataset. The images in the dataset used for training are more difficult than image classification due to the need for more computational resources. In the experimental part, training images using CNN achieved high accuracy, proving that the model has high accuracy in image retrieval.

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Zena M. Saadi mail -
Ahmed T. Sadiq mail -
Omar Z. Akif mail -
El-Sayed M. El-Kenawy mail
link https://doi.org/10.54216/JISIoT.140212

Volume & Issue

Vol. Volume 14 / Iss. Issue 2

Details open_in_new

Turiyam a Co-ordinate Free Geometry and its exploration

Recent time data representation and visualization is considered as one of the major issues. It become more crucial when the data sets exists beyond the non-euclidean geometry and its hybridization also. There are several examples given by non-euclidean geometry by Lobachevsky, Bolyai, Riemannian which contains failure of Euclid postulates V and II, respectively. The problem arises when none of the Euclid Postulates exists. It might possible that the data sets contains unknown or co-ordinate free geometry. In this case the data can be explored based on a defined vector space rather than available co-ordinate geometry. It require human Turiyam consciousness to explore these types of unknown, undefined, co-ordinate free data. To understand this problem current paper explores the Turiyam geometry and its basic for exploring the unknown or undefined data with an example.

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Prem Kumar Singh mail
link https://doi.org/10.54216/JNFS.090106

Volume & Issue

Vol. Volume 9 / Iss. Issue 1

Details open_in_new

On The Diagonalization Problem of Weak Fuzzy Complex Matrices Based On a Special Isomorphism

In this paper, we study the diagonalization problem of weak fuzzy complex matrices. To solve this problem we build a special algebraic isomorphism between the ring of weak fuzzy complex matrices and the direct product of the classical ring of real-entries matrices with itself, then we use it to solve the diagonalization problem by using the classical diagonalization problem for real matrices with the inverse isomorphism formula. Also, we illustrate many examples to explain the validity of our method.

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Maretta Sarkis mail
link https://doi.org/10.54216/GJMSA.0110203

Volume & Issue

Vol. Volume 11 / Iss. Issue 2

Details open_in_new

On The Algebraic Classification of the 4-Cyclic Refined Neutrosophic Real Roots of Unity Group

This paper is dedicated to finding all 4-cyclic refined neutrosophic real solutions of the equation 𝑋𝑛=1 which are called 4-cyclic refined real roots of unity. Also, we classify the algebraic group of these solutions as a direct product of some familiar finite cyclic groups. On the other hand, we illustrate many examples to clarify the validity of our work.

groups
Agnes Osagie mail
link https://doi.org/10.54216/GJMSA.0110204

Volume & Issue

Vol. Volume 11 / Iss. Issue 2

Details open_in_new