ASPG

A Robust MCDM Framework for Cloud Service Selection Using Spherical Fermatean Neutrosophic Bonferroni Mean

P. Roopadevi , M. Karpagadevi , S. Krishnaprakash , Said Broumi , S. Gomathi

This study presents an innovative approach to cloud service provider selection using the spherical Fermatean neutrosophic Bonferroni mean. As organizations increasingly rely on cloud services, selecting the optimal provider becomes critical, necessitating robust multi criteria decision making methods. Traditional approaches often fall short in capturing the diverse perspectives of decision-makers, leading to suboptimal choices. The spherical Fermatean neutrosophic Bonferroni mean addresses this gap by integrating a spherical representation that encompasses membership, non-membership and indeterminacy functions, enhanced by the Bonferroni mean. This structure effectively encapsulates the opinions of all decision makers, offering a comprehensive and balanced perspective. The study evaluates six cloud service providers based on four criteria: cost (nonbeneficiary), performance, security and scalability (beneficiary). Three decision makers with distinct priorities participate in the evaluation, ensuring a thorough assessment. The proposed spherical Fermatean neutrosophic Bonferroni mean method excels in resolving ambiguity and managing risk with greater precision than conventional FNSs, providing a more accurate and effective decision-making framework. A numerical example illustrates the practical application of spherical Fermatean neutrosophic Bonferroni mean, demonstrating its utility in selecting the optimal cloud service provider for an organization.

Vol. 24 Issue. 4 PP. 420-431, (2024)

Numerical Solutions for Fractional Multi-Group Neutron Diffusion System of Equations

Mohammed Shqair , Iqbal M. Batiha , Mohammed H. E. Abu-Sei’leek , Shameseddin Alshorm , Amira Abdelnebi , Iqbal H. Jebril , S. A. Abd El-Azeem

This paper addresses fractional-order versions of multi-group neutron diffusion systems of equations, focusing on two numerical solutions. First, it employs the Laplace transform method to solve the classical version of multi-group neutron diffusion equations. Subsequently, it transforms these equations into their corresponding fractional-order versions using the Caputo differentiator. To handle the resultant fractional-order system, a novel approach is introduced to reduce it from a system of 2α-order to a system of α-order. This converted system is then solved using the so-called Modified Fractional Euler Method (MFEM). As far as we know, this is the first time that such numerical schemes have been used to deal with the systems at hand. The paper covers the multi-group neutron diffusion equations in spherical, cylindrical, and slab reactors, all solved and converted for verification purposes.

Vol. 24 Issue. 4 PP. 08-38, (2024)

Harnessing Dimensionality Reduction with Neutrosophic Net-RBF Neural Networks for Financial Distress Prediction

Tawfiq Hasanin

Neutrosophy is the study of neutralities and extends the discussion of the truth of opinions. Neutrosophic logic may be employed in any domain, for providing the solution for the ambiguity problems. Several real-time data experience problems such as indeterminacy, incompleteness, and inconsistency. A fuzzy set provides an uncertain solution, and intuitionistic fuzzy set handles incomplete data, but both fail to manage uncertain data. Before bankruptcy, financial distress is the early stage. Bankruptcies caused by financial problems can be seen in the financial statement of the company. The capability to predict financial problems became a crucial area of research since it provides earlier warning for the company. Moreover, predicting financial problems is advantageous for creditors and investors. In this article, we develop a new Dimensionality Reduction with Neutrosophic Net-RBF Neural Networks (DR-NSRBFNN) technique for FCP process. The DR-NSRBFNN technique concentrates on the predictive modelling of financial distress. In the DR-NSRBFNN technique, two major stages are involved. In the preliminary phase, the high dimensionality features can be reduced by the use of arithmetic optimization algorithm (AOA). In the second phase, the DR-NSRBFNN technique applies the NSRBFNN model to predict financial distress. The performance evaluation of the DR-NSRBFNN technique can be examined using distinct aspects. The widespread study stated the improved performance of the DR-NSRBFNN technique compared to other systems

Vol. 24 Issue. 4 PP. 39-49, (2024)

Enhancing Inventory Management through Advanced Technologies and Mathematical Methods: Utilizing Neutrosophic Fuzzy Logic

C. Balakrishna Moorthy , D. Rajani , A. P. Pushpalatha , S. Ramya , A. Selvaraj , Mohit Tiwari

Optimal inventory management is one of the most critical components for companies to thrive in the competitive market while meeting their customers’ demands, reducing costs, and developing their operations. In this paper, the utilization of different technologies and instruments ranging from the most modern ones to mathematical ones was analyzed to demonstrate how the system can function successfully. It is expected that Neutrosophic fuzzy logic is one of the most complicated approaches that allow for proper uncertainty management, forecasting, and inventory control improvements. Fundamentally, the process could be that much more insightful due to the availability of mathematical modelling and on-the-go support systems. Through the use of dynamic programming with the help of Python tools to process these models, Full optimization under fuzzy demand is possible to achieve. Therefore, one could conclude that companies have many opportunities to develop their operations, reduce costs, and keep their customers happy even in a highly dynamic and uncertain business environment.

Vol. 24 Issue. 4 PP. 50-58, (2024)

Neutrosophic Delphi for evaluating sustainability models of native and non-native digital media.

Karla Valeria A. Sigcha , Evelyn M. Lema Basantes , Lourdes Y. Cabrera Martinez , Tonguc Cagin

Technological globalization has brought many changes in different fields, one of which is related to the media. In the case of traditional media, they are forced to find new ways to rethink practice, while digital media emerges in a digital context, albeit with limitations. Experience In both cases, sustainability is one of the factors to be rethought. Building on this, the overall objective is to use the Neutrosophic Delphi method to investigate the extent to which native and non-native digital media have durable patterns that allow them to be successful in their communication activities. To achieve this objective, we work with a mixed methodology, that is, qualitative and quantitative approaches: for qualitative, we use interview methods, for quantitative, we use survey methods. The population studied included both native and non-native digital media. Specifically, the survey and interviews were applied to a group of media owners. The article concludes with a series of Neutrosophic reflections on the conditions of media sustainability.

Vol. 24 Issue. 4 PP. 59-70, (2024)

Leveraging Bat Algorithm with Rough Neutrosophic Soft Set for Enhanced Oral Cancer Detection and Classification

Arwa Darwish Alzughaibi , Ebtesam Al-Mansor

Neutrosophic soft sets (NSS) are highly effective in representing neutral uncertain data. NSS model attracts several authors because it has huge range of applications in several areas such as decision-making, data analysis, smoothness of functions, probability theory, measurement theory, predicting, and operations research. Oral squamous cell carcinoma (OSCC) is the most general tumor around the world and its occurrence is on the increase in several populations. Early diagnosis plays vital role in improving diagnosis, treatment outcomes and survival rates. Although the new developments in understanding molecular mechanisms, late analysis and the implementation of precision medicine for OSCC patients continue to present problems. Early diagnosis and detection can support doctors in offering optimum patient care and effectual treatment. In recent years, the execution of several machine-learning (ML) approaches in cancer analysis has provided valuable insights, facilitating more effective and precise treatment decision-making. Oral Cancer screening can progress with the execution of artificial intelligence (AI) approaches. AI offers support to the oncology region by correctly examining a huge database in many imaging modalities. This article develops a Bat Algorithm with Rough Neutrosophic Soft Set for Oral Cancer Diagnosis (BARNSS-OCD) technique. The main intention of the BARNSS-OCD technique is to exploit deep learning (DL) model for enhanced identification of OC. In the BARNSS-OCD technique, median filtering (MF) is used for image pre-processing and the feature extraction takes place using deep convolutional neural network (DCNN) model. In addition, bat algorithm (BA) is used for the hyperparameter selection of the DCNN model. For OC detection process, the BARNSS-OCD technique applies RNSS model. To exhibit the improved performance of the BARNSS-OCD technique, a sequence of experiments is involved. The simulation outcomes indicate that the BARNSS-OCD technique gains better performance compared to other DL models

Vol. 24 Issue. 4 PP. 71-81, (2024)

Neutrosophic analysis of avocado oil extraction conditions by varieties

María M. Morales Padilla , Cristian I. Cuchipe Chacha , Vicente A. Guerrón Troya , Kholmuminov Shayzak Rakhmatovich

Avocado oil is defined by the composition of the fruit and its nutritional value, which according to previous studies suggests that it provides health benefits, reduces cardiovascular disease, and provides anti-inflammatory and antioxidant effects. However, the nutritional value is determined by the amount of acid. Monounsaturated and polyunsaturated fatty acids make this product useful in cooking. The quality of the oil is affected by the method and conditions of extraction, as these processes affect the preservation of nutrients and beneficial properties of avocado oil. This study aimed to conduct a Neutrosophic analysis of avocado oil extraction conditions depending on the cultivar, dehydration and cold pressing conditions. As a result, the physicochemical properties of the reaction variables were determined and the values of acidity, moisture, density, and impurities were obtained for the oil obtained from the Hass variety by dehydration and pressing.

Vol. 24 Issue. 4 PP. 82-92, (2024)

Enhancing Guinea Pig Farming: A Neutrosophic Approach with Interval-Valued and Bipolar Sets in Decision-Making Methods

Patricia M. Andrade-Aulestia , Luis A. Chicaiza-Sánchez , César R. Delgado-Acurio , Rafael A. Garzón-Jarrín , Tonguc Cagin

The study emphasizes the need of implementing several ways to promote guinea pig farming in small family units. It highlights the relevance of enhanced nutrition, effective health management, genetic enhancement, and acceptable habitat conditions as essential factors for enhancing productivity and profitability. Suggestions encompass the adoption of advanced breeding methods, offering training and technical support, and expanding the range of goods and markets to ensure the long-term economic viability of guinea pig farming. The utilization of neutrosophic sets provided a strong framework for assessing these techniques, enabling a thorough study that considers the inherent uncertainties in decision-making processes. To enhance future study, it is recommended to improve and broaden neutrosophic approaches to comprehend the intricacies of guinea pig farming systems more effectively. It will be beneficial to create more advanced models that include a broader set of factors and extensive data, as well as to undertake longitudinal studies to evaluate the long-term effects. It is essential to work together with local communities to customize tactics that are suitable for specific geographical conditions and socioeconomic contexts. This is necessary to ensure that these interventions are practical and successful.

Vol. 24 Issue. 4 PP. 93-104, (2024)

Possibility Fermatean Neutrosophic Soft Set

Shawkat Alkhazaleh , Belal Batiha , Areen Al-khateeb , Hamzeh Zureigat , Abedallah Al-shboul , Khaldoun Batiha

In this paper, we introduce the concept of Possibility Fermatean Neutrosophic Soft Set and define some related concepts such as Possibility Fermatean Neutrosophic Soft subset, Possibility Fermatean Neutrosophic Soft null set, and Possibility Fermatean Neutrosophic Soft universal set. Then, we define set-theoretical operations of Possibility Fermatean Neutrosophic Soft Sets such as union, intersection, and complement, and investigate some properties of these operations. We also introduce AND-product and OR-product operations between two Possibility Fermatean Neutrosophic Soft Sets. We propose a decision-making method called the Possibility Fermatean Neutrosophic Soft decision-making method (PFNS-decision-making method) which can be applied to decision-making problems involving uncertainty based on AND-product operation. We finally give a numerical example to display the application of the method that can be successfully applied to the problems.

Vol. 24 Issue. 4 PP. 105-125, (2024)

Convergence of Filters on Bornological Vector Spaces and Neutrosophic Filters

Fatma Al-Basri , Asawer Khdeidan

In this research, we construct new type of convergence of bornological vector spaces called convergence of filters through using conception bounded sets. As well, we have considered several characteristics of these concepts like Fréchet filter associated with sequence, filter that has a unique limit and ultra-filter which is very useful in the study of neutrosophic topological spaces and neutrosophic filters.

Vol. 24 Issue. 4 PP. 126-132, (2024)

A Study on First and Second Order Bipolar Fuzzy Topological Spaces and Crisp Topological Spaces and Analyzing the Connections Between Them

Muthamizhselvi S. , V. M. Vijayalakshmi

In our previous paper we discussed about the concept of SOBPFS, SOBPFT and its mathematical modelling in medical diagnosis. In this paper, the detailed study about SOBPFT accordance with FOBPFT and crisp topological spaces are analysed and also some natural examples of SOBPFT are provided. In third section, the connections between FOBPFT and SOBPFT under five different cases are discussed. And last section tells that, from a crisp topology τ on X there exists three different SOBPFT denoted by (ω(τ)) ̂, (ω_* (τ)) ̂ and (ω_ε (τ)) ̂ and from a SOBPFT on X there exists three crisp topologies denoted by i(τ ̂_B ), i^* (τ ̂_B ) and i_ε (τ ̂_B ).  

Vol. 24 Issue. 4 PP. 133-150, (2024)

Type-I extension Diophantine neutrosophic interval valued soft set in real life applications for a decision making

Lejo J. Manavalan , Sadeq Damrah , Mutaz M. Abbas Ali , Abdallah Al-Husban , M. Palanikumar

We describe certain operations and present the theory of the Type-I extension Diophantine neutrosophic interval valued soft set. Additionally, we go over an algorithm that uses the Type-I soft set model to address the decision-making problem. We present a similarity measure between two Type-I extension Diophantine neutrosophic interval valued soft sets and talk about how it might be used in practical applications. A few exemplary cases are provided to demonstrate their practical application in solving uncertain problems.

Vol. 24 Issue. 4 PP. 151-164, (2024)

Enhancing Predictive Accuracy of Insurance Stock Market in Jordan using Hyprid GFS.Thrift Model: A Genetic Fuzzy System-based Fintech Approach

Jamil J. Jaber , Anwar Al-Gasaymeh , Maha Shehadeh , Asma S. Alzwi

This study focuses on improving the predicting accuracy of the daily ASE's weighted price index of the insurance sector (ICI) using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions, namely, Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6). Using a nonlinear spectral model called maximum overlapping discrete wavelet transform (MODWT) with five mathematical functions—Haar, Daubechies (d4), least square (la8), best localization (bl14), and Coiflet (c6)—this study aims to increase the daily ASE's weighted price index of the insurance sector's (ICI) prediction accuracy. The model utilizes a genetic fuzzy system based on Thrift's methodology (GFS.Thrift). The Amman Stock Exchange (ASE) supplied a dataset with 4,478 observations for the purpose of the study. The dataset represented daily data from January 2, 2006, to March 24, 2024.  The adaptive GFS.THRIFT model was trained with 90% of the dataset, while the remaining 10% was used to test its prediction performance. Multiple egressions and multicollinearity tests were used to select input variables such as standardized foreign direct investment (FDI), standardized value traded (VT) and consumer price index (CPI). Insights from this study indicate that all input variables are positively related to the output variable. Secondly, the proposed model (MODWT-Haar-GFS. Thrift) significantly outperforms other existing models including the GFS. Thrift model.

Vol. 24 Issue. 4 PP. 165-175, (2024)

A Study on Decision Making and Teaching Competency: Processing Self Perception and Cognitive Schema through Neutrosophic Science

Saziye Yaman

The objective of this research is to examine the decision-making processes of teachers and explore their self-assessments of teaching competency levels based on the competency indicators proposed by the Ministry of National Education (MoNE) in Turkey. The study adopts a constructivist perspective, offering a fresh look at the cognitive levels of teachers and their decision-making mechanisms. Additionally, it integrates neutrosophic science principles to address the uncertainties and indeterminacies present in teachers' self-evaluation and decision-making processes. Data were gathered using the "General Competencies for Teaching Profession (GCTP)" scale, which was developed according to the competencies defined by the MoNE. This new scale, featuring 15 Likert-type items, was validated and tested for reliability before being administered to a sample of 320 volunteering teachers from various disciplines in Turkey. The scale measures data within the "Professional skills" domain and captures teachers' self-perceived competency beliefs related to their professional skills, considering factors such as years of teaching experience, gender, subjects taught, and the type of school (primary or secondary) where they are employed. SPSS 16.0 was used for data analysis and to obtain descriptive statistics for the item results. The analysis revealed that primary school teachers scored higher on the GCTP scale compared to high school teachers. By incorporating neutrosophic science, the study effectively navigates the uncertainties in assessing teaching competencies, offering a more nuanced understanding of the factors that influence teachers' decision-making processes.

Vol. 24 Issue. 4 PP. 176-192, (2024)

On Neutrosophic Truncation

Kawther F. Alhasan

Neutrosophic have found their place in neutrosophic studies due to the prevalence of indeterminacy in the world. We present the novel notion of neutrosophic truncated distribution, which is highly significant in analyzing events that involve the exclusion of certain data from the original dataset, particularly where there is a presence of indeterminacy in data. Unsure or ambiguous information, which is disregarded in classical logic, is incorporated within neutrosophic logic due to its focus on both certain and uncertain data. In this paper, the approach of neutrosophic truncation, and truncated distribution of neutrosophic random variable have been introduced, in addition to deriving some of its properties. And other cases discussed neutrosophic truncation depends on the neutrosophic probability function, a classical probability function, and studies neutrosophic probability and neutrosophic interval together. It studies the neutrosophic left truncated and neutrosophic right truncated. Some illustrative examples and statistical properties such as the cumulative function, the moment generating function, the order statistic, and the rth moment are presented.             

Vol. 24 Issue. 4 PP. 193-204, (2024)

Extended Fuzzy Neutrosophic Classifier for Accurate Intrusion Detection and Classification

Mohamed Elhoseny , Mahmoud Abdel-salam , Ibrahim M. Elhasnony

Intrusion Detection is crucial in contemporary cybersecurity landscapes to proactively thwart and identify possible threats. The risk of data breaches, malicious activities, and unauthorized access escalates as organizations increasingly rely on interconnected systems. Intrusion Detection Systems (IDS) are imperative for the continuous monitoring of system and network activities, quickly identifying patterns or anomalies indicative of cyber threats. IDS acts as a frontline defense mechanism with the ability to identify abnormal behaviors and known attack signatures. Prompt recognition allows for safeguarding sensitive data, timely response, fortifying the overall resilience of IT infrastructures, and reducing the effect of security incidents. The implementation of robust IDS is vital in an era marked by evolving cyber threats to ensure the confidentiality, availability, and integrity of digital assets. This study develops an improved Arithmetic Optimization Algorithm with an Extended Fuzzy Neutrosophic Classifier technique (AOA-EFNSC) for Accurate Intrusion Detection and Classification. The main goal of proposing this model is to recognize the presence of intrusions effectually. A min-max scalar is applied to normalize the input data before using the improved AOA as a feature selection method. For intrusion detection, the proposed model uses the FNSC technique for the recognition and classification of the intrusions. A sequence of experimentations was involved to validate the superior performance of the proposed model. The experimental value pointed out that our proposed approach outperforms the previous models and enhances the intrusion detection results.

Vol. 24 Issue. 4 PP. 205-222, (2024)

Neutrosophic Delphi method to analyze the impact of Internships on the comprehensive development of university students

Nery Elisabeth G. Paredes , Anderson I. Chiliquinga García , Isaac E. Cajas Cayo , Mirian N. Carranza Guerrero , Christian Kümmel

Internships play a crucial role in the comprehensive education of university students as they provide practical experience and promote the development of technical and soft skills. These practices not only promote personal development but also ease the transition into the world of work. The study aims to use a Neutrosophic Delphi method to analyze the extent to which work practices influence the comprehensive education of university students in Ecuador in 2023. A descriptive study was conducted with a sample of 410 students from academies and universities in Ecuador. Country Ecuador. Center of the country This method uses structured surveys to collect qualitative and quantitative data about the experiences, advantages, and skills acquired during internships. The results are presented in the form of data tables and statistical graphics that illustrate the close connection between professional experience and the overall educational level of students. Emphasis was placed on acquiring skills such as teamwork, leadership, and problem-solving. In summary, internships are a valuable learning tool for university students as they provide the opportunity to apply knowledge, develop skills, and improve their employability.

Vol. 24 Issue. 4 PP. 223-232, (2024)

A Neutrosophic Multi-Criteria Methodology to Evaluate Different Competitiveness Indicators of Food and Beverage Companies

Manuel Antonio A. Z. David , David Santiago C. Molina , Rodolfo M. M. Poma , Diana K. Vinueza Morales , Antonella A. García Camacho , Maha Ibrahim

Neutrosophic multicriteria analysis of the competitiveness and sustainability of companies in the agri-food sector, with suggestions for improvement strategies. Competitiveness is measured using a tool developed by the IDB (Inter-American Development Bank) that includes 103 indicators and 9 operational areas (strategic planning, value chain, quality assurance, accounting and finance, environmental management, sales, and human resources). Talents and information systems). Sustainability is assessed using the tool proposed by the " InnovaRSE " methodology (from Navarra), which includes 30 indicators divided into three aspects: social, economic, and environmental. The study population was 100 catering establishments officially established according to the Tourism Registration Body. To obtain the sample size, the finite population formula was applied, and the results were obtained for the 20 companies studied. Sampling was done using the "simple random probability" method. In the Spearman correlation test, the P value is "0.01" (there is a connection between the company's competitiveness and sustainability). 16 improvement strategies were developed using diagnostic tools.

Vol. 24 Issue. 4 PP. 233-244, (2023)

A Neutrosophic multi-criteria approach for implementing technology in education

Darío Díaz Muñoz , Patricia Hernández Medina , Saziye Yaman

The COVID-19 epidemic has greatly expedited the utilization of technology in the realm of education, resulting in the extensive implementation of totally online teaching approaches. These approaches have undergone thorough analysis in various scholarly articles in recent years. This study applies theories of technology acceptance and use in the educational process, employing Neutrosophic analysis to assess criteria for technology utilization in education. The study commenced by formulating an equation to investigate the patterns of technology uptake and use between 2010 and 2024. Additionally, a comprehensive evaluation of the latest literature since 2000 was conducted to identify prevailing trends. The findings suggest that usage plays a vital role in the Technology Acceptance Model (TAM), and structural equations are used as a method to measure it. Neutrosophic analysis provides a thorough and sophisticated viewpoint on the integration of technology in education, emphasizing both the accomplishments made and the obstacles that still exist in this developing area.

Vol. 24 Issue. 4 PP. 245-256, (2024)

LRPS Method for Solving Linear Partial Differential Equations and Neutrosophic Differential Equations of Fractional Order with Numerical Solutions

Mohammed Qassim , Mohammed Abed Daim Zoba , Ahmed Hadi Hussain

In this work, fractional partial equations' and neutrosophic fractional partial equations analytical series solutions are presented, we consider the fractional derivative in the meaning of Caputo in these formulas. We offer a novel objective method the LRPS which is a strong instrument for precise analytically and numerical solutions to these problems by setting an excellent example, we stress precision, effectiveness, and application style, also we can find exact answers when there is a pattern between the series' parts; alternatively, we can only offer approximations. The Mathematica application is used to assess the numerical and graphical findings to make sure the solutions generated are accurate and that the approach can be modified to solve this kind of this problem. The findings obtained demonstrated that our current procedure is appropriate and efficient for resolving PDEs.

Vol. 24 Issue. 4 PP. 257-267, (2024)

Enhanced Brain Tumor Diagnosis through Differential and Canonical Quadri –Partitioned Neutrosophic Set Classification Methods:A Comparative Study

A. Panimalar , P. Sugapriya , D. Aarthi , S. Santhosh Kumar , K. Mohana , F. Nirmala Irudayam

An early cancer diagnosis is carried out for adequate management of diseases. Magnetic resonance imaging (MRI) is most commonly preferred method for cancer diagnosis. Due to the uncontrolled and rapid growth of cells, brain tumor is occurred. If not treated at a preliminary phase, it may lead to death. Thus, a noteworthy prerequisite for a successful treatment outcome is an early and precise diagnosis.Many conventional methods are discussed for performing efficient tumor detection. But, conventional classification methods not distinguish MRI as primary and metastases tumors in an accurate manner. Therefore, the performance comparison of deep learning-based classification (i.e., Differential Quadri-Partitioned Neutrosophic Interval-valued Polynomial Attention-based Deep CNN (DQNI-PADCNN) method and Canonical Quadri-Partitioned Neutrosophic Set based Otsuka–Ochiai Deep Recurrent Neural Network (CQNS-ODRNN) method) is introduced to provide exact image classification results. The brain MRI images are considered as an input. MRI image classification is carried out through CNN and RNN to find the brain tumor disease. Before the classification process, input images are de-noised. The noise-removed images are get segmented to identify the region of interested regions. Later, the images are classified into four classes such as glioma, meningioma, no tumor, and pituitary classes to detect the brain tumor. Both classification methods use Quadri-Partitioned Neutrosophic set for categorizing the images. Depending on CNNs and RNNs achievement in handling intricate tasks, an optimal multi-class brain tumor diagnosis is carried out. Experimental evaluation is implemented using MATLAB 2017 for brain tumor detection with the Brain Tumor MRI dataset. To the total number of MRI images, the various performance metrics are calculated in terms of sensitivity, specificity, accuracy, and time for the detection of brain tumors.

Vol. 24 Issue. 4 PP. 277-292, (2024)

Product of rings based on neutrosophic sets

Aiyared Iampan , S. R. Vidhya , N. Rajesh , B. Brundha

In this paper, we introduce the notion of the intrinsic product of neutrosophic sets, and some related properties are investigated. Characterizations of neutrosophic subrings, neutrosophic ideals, neutrosophic quasi-ideals, and neutrosophic bi-ideals are given.

Vol. 24 Issue. 4 PP. 293-314, (2024)

Two Inclusive Subfamilies of bi-univalent Functions

Tariq Al-Hawary , Ala Amourah , Jamal Salah , Feras Yousef

The aim of this article is to establish two new and qualitative subfamilies F(ε, κ, &alefsym;) and G(ε, κ, &alefsym;) of biunivalent functions. For functions in these subfamilies, we determine the first two Maclaurin coefficient estimations |C2| and |C3|, and address the Fekete–Szeg¨o problem. Additionally, we mention some corollaries related to the main results.  

Vol. 24 Issue. 4 PP. 315-323, (2024)

Neutrosophic analysis of the factors determining the development of humorous discourse in videos using the TOPSIS method

Alejandra A. Vera Vera , Xiomara N. Lindo Quito , Paolo A. Ortiz , Muhammad Eid Balbaa

YouTube is moving towards personalized media. In 2011, Enchufe TV became an Ecuadorian online comedy series known for its witty humor. Taking advantage of the openness of the Internet, the video is currently available to watch on the YouTube platform. The purpose of this study is to conduct an unbiased analysis of the factors that determine the development of humorous discourse in TV Antufe's YouTube videos using the TOPSIS method. To understand the growth of the show and its audience, we compared its premiere year to 2022 across 10 years. At the same time, data such as comedy type, language level, audio-visual narrative, and humorous discourse were collected to quantitatively understand the popularity and influence of the play at the time. There. Variables such as views, audience engagement, and subscriber base growth are analyzed, as well as objective measures of content relevance and influence within the platform environment. Enchufe TV's decline in user activity can also be explained by several factors, such as the emergence of new platforms and content saturation. We also found that blue spoken words were the most widely used, with popularity varying by year of study.  

Vol. 24 Issue. 4 PP. 324-334, (2024)

Selection process based on new type neutrosophic interval-valued set applied to logarithm operator

Lejo J. Manavalan , Sadeq Damrah , Ibraheem Abu Falahah , Abdallah Al-Husban , M. Palanikumar

We introduce the new type neutrosophic interval-valued set (NIVS) problems relevant to multiple attribute decision making (MADM). Pythagorean interval-valued fuzzy set (PIVFS) and neutrosophic set (NS) can be extended into new type neutrosophic interval-valued set. We discusses new type neutrosophic interval-valued weighted averaging (new type NIVWA), new type neutrosophic interval-valued weighted geometric (new type NIVWG), generalized new type neutrosophic interval-valued weighted averaging (new type GNIVWA) and generalized new type neutrosophic interval-valued weighted geometric (new type GNIVWG). A number of algebraic properties of new type NIVSs have been established such as associativity, distributivity and idempotency. Using expert judgments and criteria, we will be able to decide which options are the most appropriate. Several of the proposed and current models are also compared in order to demonstrate the reliability and usefulness of the models under study. Additionally, the findings of the study are fascinating and intriguing.  

Vol. 24 Issue. 4 PP. 335-351, (2024)

Evaluation of the Economic Viability of Circular Models in Agri-culture Based on Neutrosophic Cognitive Maps

Ketty Marilú Moscoso-Paucarchuco , Manuel Michael Beraún-Espíritu , Uriel Rigoberto Quispe-Quezada , Silvia Marina Alvarez-Bernuy , Miguel Angel Quispe Solano , Edson Hilmer Julca-Marcelo , Arturo Gamarra-Moreno , Wilfredo Ramirez-Salas

The main purpose of this evaluation is to analyze the economic viability of the implementation of circular models in agriculture in Tarma, Peru. This involves examining the costs and benefits associated with the adoption of circular practices, as well as identifying possible barriers and opportunities for their implementation at the local level. By better understanding the economic landscape, it will be possible to inform decision-making both at the government level and at the level of individual farmers. For the analysis, we have a committee of 30 experts who will evaluate the relationship between variables that positively or negatively affect the implementation of these models in the town. The tool selected for the analysis is Neutrosophic Cognitive Maps, which includes an indeterminacy component within the calculations. This allows greater accuracy in the results since indeterminacy is an inherent part of prediction.

Vol. 24 Issue. 4 PP. 352-358, (2024)

Design of a Business Sustainability Measurement Method for Based on NeutroAlgebras Generated by the Combining Function in Prospector and Neutrosophic 2-tuple Linguistic Models

Ketty Marilú Moscoso-Paucarchuco , Manuel Michael Beraún-Espíritu , Uriel Rigoberto Quispe-Quezada , Silvia Marina Alvarez-Bernuy , Miguel Angel Quispe Solano , Edson Hilmer Julca-Marcelo , Wilfredo Ramirez-Salas , Arturo Gamarra-Moreno

Business sustainability has become a global imperative in response to the environmental, social, and economic challenges facing our world. In this context, the measurement and evaluation of business sustainability have become crucial to guide the actions of organizations towards more responsible and sustainable practices. However, the lack of specific measurement instruments for specific regional contexts may limit the ability of companies to evaluate and improve their sustainability performance. In this paper, we present the design of a business sustainability measurement method adapted to the context of Tarma, Peru. Tarma, a region located in the heart of the Peruvian Andes, is characterized by its cultural, environmental, and economic diversity, making it a unique context to address business sustainability. This article proposes a method for measuring business sustainability based on the Neutrosophic 2-tuple Linguistic Model, which includes an aggregation operation based on a NeutroAlgebra generated by Combining Functions in Prospector.  

Vol. 24 Issue. 4 PP. 359-366, (2024)

Application of Mentoring and Entrepreneurship Management in Higher Education

Wilmer Ortega Chávez , Janett Karina Vásquez Pérez , Alfredo Paucar Curasma , Yenny Talavera Ore , Daniel Alberto Valenzuela Narváez3 , Carlos Máximo Gonzáles Añorga , Roberth Lozano Tacuri Toribio , Miriam Esther Campos Llana

Mentoring and entrepreneurship management are characteristics that must be promoted in the organization because the success of a business depends on them. Entrepreneurship is an innate quality of personality; however, it can be developed through education. This paper aims to show the initial steps to develop entrepreneurship and mentoring programs within today's Peruvian universities. For this, we count on the support of four specialists who determined the essential factors for designing academic entrepreneurship programs in Peru. They also serve to evaluate the importance of these concepts. From a quantitative point of view, we use the Neutrosophic AHP technique to calculate the weights to measure the importance of each of these factors in the teaching of these concepts on the university campuses of Peru. The Neutrosophic AHP method is the generalization to the neutrosophic framework of the well-known AHP, where indeterminacy is included within decision-making.

Vol. 24 Issue. 4 PP. 367-375, (2024)

Secondary Partial Ordering of Neutrosophic Fuzzy Matrices

Divya Shenoy Purushothama

In this article, we define secondary generalized inverse of a neutrosophic fuzzy matrices whenever exists. . Also, the S-ordering for the set of neutrosophic fuzzy matrices are defined and characterized. A necessary and sufficient condition for the existence of secondary generalized inverse of neutrosophic fuzzy matrices with the help of S-ordering is obtained.

Vol. 24 Issue. 4 PP. 411-419, (2024)

Efforts of Neutrosophic Logic in Medical Image Processing and Analysis

Azmi Shawkat Abdulbaqi , Bourair Al-Attar , Lateef Abd Zaid Qudr , Harshavardhan Reddy Penubadi , Ravi Sekhar , Pritesh Shah , Sushma Parihar , Sushmitha Kallam , Jamal Fadhil Tawfeq , Hassan muwafaq Gheni

Medical image processing is indispensable for correct diagnosis and planning of treatment. However, it is susceptible to many errors due to noise, artifacts, and the variability innate in anatomical structures themselves. Traditional image analysis methods hence suffer from these complexities in the images themselves and lead to probable inaccuracies in image analysis. This paper probes into the role of neutrosophic logic in the domain of medical image processing to seek better handling of these problems. The main objectives of the work were to optimize the noise reduction, image segmentation, feature extraction, and classification using the special capabilities of neutrosophic logic directed toward handling uncertainty and indeterminacy. Contributions The contributions of this study are multifaceted: it contributes by introducing detailed support for applying neutrosophic logic in a number of medical image processing tasks and integrates neutrosophic logic with prior techniques and evaluates their performance with traditional methods. The experimental results in the study are complete and demonstrate significant improvements in key metrics. For example, applying neutrosophic logic in noise reduction increased the peak signal-to-noise ratio of MRI images from 25 dB to 35 dB. In some segmentation tasks, the Dice coefficient for liver CT scans increased from 0.85 to 0.92. It increases the accuracy of feature extraction in breast cancer detection from 88% to 95%, while integrating neutrosophic logic with convolutional neural networks improves the accuracy in retinal image classification from 92% to 97%. All these results underline the strong role that neutrosophic logic can play in enhancing accuracy, robustness, and reliability in the processing of medical images. The result of the study concludes that neutrosophic logic not only improves the current limitations but also holds great promise for handling uncertainty in many medical fields, opening a promising way for future advancements in the field of medical imaging and health applications.

Vol. 24 Issue. 4 PP. 376-388, (2024)

Some results on approximation in neutrosophic normed space

Alaa Adnan Auad , Mohammed A. Hilal

Neutrosophic normed linear spaces are the main significant notion in the study of classical functional analysis under a neutrosophic environment to handle indeterminate and inconsistent information. Where the neutrosophic norm function assigns to each vector in the linear space a neutrosophic number, which is a number with a truth, indeterminacy, and falsity component. The main aim of this work is to study and discuss the important properties of proximinality of specific sets and new results for a large class in neutrosophic normed space. Moreover, we show some results closely related proximainality of classes to the normed construction in the space. Also, we prove achieved for generalized sets in neutrosophic normed space, most marks on convexity and Cheby-shevity classes are considered.

Vol. 24 Issue. 4 PP. 389-396, (2024)

IDLTM-DMT: Intelligent Deep Learning based Trust Management with Decision Making Tool for Healthcare Internet of Things and Big Data Environment with Neutrosophic Set Analysis

C K Marigowda , Thriveni J , Gowrishankar S

Over the last few years development of Internet of Things (IoT) devices and communication technologies have resulted in the massive generation of health-related data. In the context of healthcare, IoT offers several advantages, including being able to observe patients very closely and using data for analytics. A major challenging issue that exists in the usage of IoT and big data in the medical field is security. As healthcare data is highly vulnerable and becomes a target for attacks, there are significant privacy issues related to the usage of big data analytics. Besides, implementing new data analysis tools and strategies for handling big data decision-making is a major issue. The capability to examine this amount of data is a significant aspect of big data in health care.  For resolving these issues, this paper presents a new intelligent deep learning-based trust management with decision making tool (IDLTM-DMT) for IoT healthcare big data environments, incorporating Neutrosophic Set Analysis (NSA). The proposed IDLTM-DMT model enables IoT devices to gather healthcare data. The IDLTM-DMT model involves a DL based bidirectional long short-term memory (BiLSTM) model for vulnerability detection and thereby identifies the malicious traffic in the Network. Hadoop MapReduce is used for handling big data and a decision-making tool using Deep Stacked Auto Encoder (DSAE) is used for the classification of diseases that exist in big data. To optimize the DSAE model's hyperparameters and improve classification performance, the Sandpiper Optimization (SPO) Algorithm is employed. Neutrosophic Set Analysis is integrated to manage the indeterminacy and inconsistency of the data, enhancing the decision-making process. Extensive experimental analysis is conducted on the EEG Eye State Dataset, with results analyzed using various performance measures. The findings indicate that the proposed method achieves improved accuracy compared to existing methods, demonstrating the effectiveness of incorporating Neutrosophic Set Analysis in IoT healthcare big data environments.

Vol. 24 Issue. 4 PP. 397-410, (2024)

New algebraic structures approach towards complex interval valued Q-neutrosophic subbisemiring of bisemiring

Sharifah Sakinah Syed ahmad , Nasreen Kausar , Murugan Palanikumar

The notion of complex interval-valued q-neutrosophic subbisemiring (CIVqNSBS) is developed and examined. Additionally, we examine the homomorphic features and significant attributes of CIVqNSBS. We suggest the CIVqNSBS level sets for bisemirings. Consider a complex neutrosophic subset of bisemiring Δ, denoted as &alefsym; if and only if every non-empty level set Z(∂,♭) is a subbisemiring, where ∂, ♭ ∈ D[0, 1], then Z= )Z,Z, Z) is a CIVqNSBS of Δ. Let &alefsym; be the strongest complex neutrosophic relation of bisemiring Δ, and let Ψ be a CIVqNSBS of bisemiring Δ, if and only if Ψ is a CIVqNSBS of Δ × Δ, then &alefsym; is a CIVqNSBS of bisemiring Δ. We show that homomorphic images of all CIVqNSBSs are CIVqNSBSs, and homomorphic pre-images of all CIVqNSBSs are CIVqNSBSs. There are examples given to illustrate our results.  

Vol. 24 Issue. 4 PP. 451-463, (2024)

Comprehensive Decision-Making with Spherical Fermatean Neutrosophic Sets in Structural Engineering

P. Roopadevi1, M. Karpagadevi , M. Karpagadevi , S. Krishnaprakash , Said Broumi , S. Gomathi

This study introduces the Spherical Fermatean Neutrosophic Sets (SFNSs), representing a significant advancement in the realm of Neutrosophic Sets (NSs) and Fermatean neutrosophic sets (FNSs). In decision making scenarios involving diverse perspectives, a mere average of decision values may fail to capture the entire spectrum of viewpoints. To address this limitation, the SFNS is proposed as a comprehensive solution. It features a spherical representation that encompasses membership, non-membership and indeterminacy functions at its core, complemented by a defined radius. This spherical construct facilitates the encapsulation of all decision makers’ opinions within its bounds, providing a holistic perspective. Leveraging its geometric structure, the SFNS excels in resolving ambiguity and risk with greater accuracy and effectiveness compared to conventional FNSs. This innovative approach aims to better accommodate the complexities of decision making involving diverse perspectives. Selecting the best material for a structural engineering project is given as numerical example at the end.

Vol. 24 Issue. 4 PP. 432-450, (2024)

International Journal of Neutrosophic Science

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