International Journal of Neutrosophic Science

Homeless people are marginalized because they lack the resources necessary to participate in mainstream culture. It is not unusual to come across homeless persons in the streets of Quito, Ecuador, particularly in the downtown area. Society often refers to them as the unaccepted, the outcasts, the marginalized, and the homeless. Being a victim of aggressiveness is not an inevitable part of life on the streets. Still, unfortunately, we are seeing more and more instances of it being shown nearly every day. Many groups work to alleviate this problem by providing aid or enhancing the quality of life for these individuals. The goal of this study is to aid in strengthening the work of such institutions by providing a rationale for why so many crimes are decided to commit even against the homeless and how these institutions can better equip themselves to deal with the issue, as well as by providing tasks to assist direct the Homeless toward the Good Having to live Plan. A  cognitive map of neutrosophic causes and effects was constructed.

Social Science deals with the study of phenomena related to the social status of human beings. The importance of such sciences lies in the fact that they make it possible to know, predict, modify and improve the functioning of human societies today. Due to the great complexity of modern societies, it is virtually impossible to have accurate data or knowledge about any contemporary society. That is why neutrosophic theory is suitable for representing and modeling the data from studies on any social sciences. They may contain data that is contradictory, incomplete, inaccurate, vague, and so on. In particular, neutrosophic statistics generalizes classical statistics to interval-valued data. Since classical statistics are of great importance for the study of Social Sciences. We will emphasize the Legal Sciences in our approach

In this paper we introduce and then study the general concept of neutrosophic Borda method. The idea is to combine Borda count (in one of its most typical versions) with neutrosophic sets (which allow us to deal with uncertainty in a very broad sense). We show the whole algorithm which is then illustrated with some numerical examples. Finally, we discuss several possible extensions of the proposed method. For example, we present neutrosophic approach to the problem of weights.

In this paper, we introduce the concepts of neutrosophic nano M-open sets and some stronger and weaker forms of neutrosophic nano open sets in neutrosophic nano topological spaces. Further, we dealt with the concepts of neutrosophic nano M-interior and M-closure operators. Moreover, we define the product related neutrosophic nano topological spaces and proved some theorems related to this.

Information explosion in this era has led to the proliferation of digital data in form of images, text, video, and audio. Uncertainty is a major issue in information access and retrieval models, and incomplete information needs to be treated in information systems because imprecision indicates the existence of a value that cannot be measured. There is no denial of the fact that uncertainty puts a hindrance in obtaining information in real-time systems, and as per knowledge rarely does any study of information retrieval using image segmentation treat imprecise and inconsistent information inherited in information systems. This work proposes to transform images in the neutrosophic domain for the treatment of uncertainty that persists in information recovery. Later, the image is segmented using the neutrosophic segmentation algorithm and its results are compared with the Modified Fuzzy c-Means segmentation algorithm, which is the earlier used segmentation algorithm in information systems. The experiment is conducted on a variety of multimodal images from the Berkeley Segmentation Dataset and Benchmark, showing the effectiveness of the proposed method for information systems. The proposed image segmentation using neutrosophy seems to yield a smaller error of 0.011, but the error obtained using the fuzzy c-means (MFCM) method is 0.13, which is larger than the proposed approach. The work also demonstrates how well neutrosophic segmentation can segment images having different noise levels as well as clean images. The results show that the proposed algorithm yields the most accurate segmented image for feature extraction which can be utilized while designing effective information systems.

In this work, the idea of neutrosophic thick function has been proposed for solving a neutrosophic system of ordinary differential equations of various orders by the Laplace transform. This proposed scheme method is effective and simple to reach an exact solution.

The concept of the "Internet of Things" (IoT) has emerged in recent years to describe our increasingly interconnected physical world. Even if there are now goods on the market that are connected to the Internet of Things, there are still obstacles to be addressed, such as security concerns and a general lack of trust in and familiarity with the technology. The purpose of this research is to examine what goes into making a good Internet of Things (IoT) system for smart education that deals with IoT. In this research, we use neutrosophic theory and the Analytic Hierarchy Process (AHP) to create a decision-support system based on rules for assessing the impactful elements of the Internet of Things in smart education. According to the results of this investigation, security, value, and connectivity are more crucial than intangible qualities (Telepresence and Intelligence). This research suggests that the internet of behavior (IoB) and a sustainable Internet of Things (IoT) ecosystem requires strong IoT security measures to be implemented once smart education has established a reliable IoT connection. Likewise, smart education needs to think about the benefits of IoT security and IoT ethics for the goods they use and the comfort of their staff.

Financial organizations can no longer ignore the problem of managing risk. As a component of the financial system, efficient Financial Risk Management (FRM) may significantly affect business results. These findings show that the triangular neutrosophic numbers simulate capital asset key metrics. Performance metrics for capital assets may be modeled using this kind of value by accounting for all conceivable outcomes for their attainment. The profit on capital instruments, the risk of financial investments, and the covariance of capital instruments are the Key Performance Metrics (KPIs) modeled using triangular neutrosophic values. Specifically, this research employs two techniques. Prioritizing parameters for financial risk management dimensions using the Analytic Hierarchy Process (AHP). Second, the performance evaluation of financial risk management was evaluated from the perspective of several groups of specialists by the COCOSO method to assess the ranking of possible replies further. By using the presented method, we may better identify where to put our efforts and how to allocate our resources for greater effectiveness in managing financial risks.

Early detection and classification of skin lesions using dermoscopic images have attracted significant attention in the healthcare sector. Automated skin lesion segmentation becomes tedious owing to the presence of artifacts like hair, skin line, etc. Earlier works have developed skin lesion detection models using clustering approaches. The advances in neutrosophic set (NS) models can be applied to derive effective clustering models for skin lesion segmentation. At the same time, artificial intelligence (AI) tools can be developed for the identification and categorization of skin cancer using dermoscopic images. This article introduces a Neutrosophic C-Means Clustering with Optimal Machine Learning Enabled Skin Lesion Segmentation and Classification (NCCOML-SKSC) model. The proposed NCCOML-SKSC model derives a NCC-based segmentation approach to segment the dermoscopic images. Besides, the AlexNet model is exploited to generate a feature vector. In the final stage, the optimal multilayer perceptron (MLP) model is utilized for the classification process in which the MLP parameters are chosen by the use of a whale optimization algorithm (WOA). A detailed experimental analysis of the NCCOML-SKSC model using a benchmark dataset is performed and the results highlighted the supremacy of the NCCOML-SKSC model over the recent approaches.

This paper introduces the generalized q-rung neutrosophic soft set (GqRNSSS) theory and its use to solve actual problems. We also define a few operations that make use of the GqRNSSS. The GqRNSSS is constructed by generalizing both the Pythagorean neutrosophic soft set (PyNSSS) and Pythagorean fuzzy soft set (PyFSS). We give a method for agricultural output that is based on the proposed similarity measure of GqRNSSS. If two GqRNSSS are compared, it can be determined whether or not a person produces good agricultural output. We support a strategy for dealing with the decision-making (DM) problem that makes use of the generalized qrung soft set model. In this article, we discuss the application of a similarity measure between two GqRNSSS in agricultural output. Show how they can be successfully applied to challenges with uncertainty.

We introduce the notion of interval valued neutrosophic subbisemirings (IVNSBSs), level sets of IVNSBSs and interval valued neutrosophic normal subbisemirings (IVNNSBSs) of bisemirings. Also, we introduce an approach to (α , β)-IVNSBSs and IVNNSBSs over bisemirings. Let à be an interval valued neutrosophic set (IVN set) in a bisemiring S. We have proved that š = (sTA‚ sIA‚ sFA) is an IVNSBS of S if and only if all non-void level set S(T,S) is a subbisemiring of S for t, s ∈ [[0,1]].  Let à be an IVNSBS  of a bisemiring S and V be the strongest interval valued neutrosophic relation (SIVNR) of S.  Prove that à is an IVNSBS of S if and only if  V is an IVNSBS of S  X S. We illustrate homomorphic image of IVNSBS is an IVNSBS. We find that homomorphic preimage of IVNSBS is an IVNSBS. Examples are provided to illustrate our results.

In this paper, we prove that Neutrosophic Statistics is more general than Interval Statistics, since it may deal with all types of indeterminacies (with respect to the data, inferential procedures, probability distributions, graphical representations, etc.), it allows the reduction of indeterminacy, and it uses the neutrosophic probability that is more general than imprecise and classical probabilities and has more detailed corresponding probability density functions. While Interval Statistics only deals with indeterminacy that can be represented by intervals. And we respond to the arguments by Woodall et al. [1]. We show that not all indeterminacies (uncertainties) may be represented by intervals. Also, in some cases, we should better use hesitant sets (that have less indeterminacy) instead of intervals. We redirect the authors to the Plithogenic Probability and Plithogenic Statistics which are the most general forms of MultiVariate Probability and Multivariate Statistics respectively (including, of course, the Imprecise Probability and Interval Statistics as subclasses).

This study reveals new concepts of neutrosophic crisp closed sets named neutrosophic crisp g-closed sets, neutrosophic crisp αg-closed sets, neutrosophic crisp gα-closed sets, and neutrosophic crisp gαg-closed sets. Furthermore, their ultimate features in neutrosophic crisp topological spaces are examined. Moreover, the consequent new concepts are introduced, such as neutrosophic crisp gαg-closure and neutrosophic crisp gαg-interior and finding some of their characteristics.  

The paper provided a new notion of neutrosophic separation axioms as neutrosophic gαg-Ri-space & neutrosophic gαg-Tj-space (note that the indexes i & j are natural numbers of the spaces R & T are from 0 to 1 & from 0 to 2 alternately).

In the present paper, we use the difference operator ∆m (Iλ )-summability to define some new summability concepts on neutrosophic normed spaces. We also introduce concepts of generalized limit point, and cluster point and obtain some relationships among these notions. Finally, we define generalized Cauchy sequences on these spaces and present a characterization of a new summability method that preserves linear operators on neutrosophic normed spaces.