Search Results (62)

Scalp image detection faces challenges such as limited evaluation dimensions, difficulties in quantifying user perception, and insufficient discriminative power of traditional assessment methods. To address these issues, this paper proposes a multi-attribute decision-making model for deep learning algorithm selection. The model integrates subjective and objective weighting through a hybrid approach, where natural language processing (NLP) techniques extract perceptual preferences from user reviews, and the Interval-valued neutrosophic set analytic hierarchy process (IVNS-AHP) and entropy weight method (EWM) are employed to determine subjective and objective weights, respectively. The combined weights are used within the IVNS-VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje) framework, enhanced by a possibility distribution (PD) to improve discriminative capability. Experiments were conducted using multiple performance metrics, including Precision, Recall, mean Average Precision at IoU = 0.5 (mAP@50), F1 Score, frames per second (FPS), and Parameters, to evaluate mainstream scalp detection algorithms. The results demonstrate that YOLOv8n achieves the highest comprehensive ranking with strong stability across different decision preferences. Comparative analyses with TODIM (an acronym in Portuguese of interactive and multiple attribute decision-making), TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution), and fuzzy VIKOR variants confirm that the proposed PD-VIKOR method provides superior ranking stability and discriminative precision, offering a more reliable and robust evaluation under uncertainty. Full article

In this paper, we introduce and study the concept of rough I–$\alpha \beta$–statistical convergence of order $\gamma$ in neutrosophic normed spaces. This new mode of convergence combines the principles of rough convergence, statistical convergence with respect to an ideal, and the flexible structure of neutrosophic norms to handle indeterminacy and vagueness in sequence behavior. We establish fundamental properties of this convergence type and investigate the structure of its limit set. Specifically, we prove that the set of rough I–$\alpha \beta$–statistical limit points of order $\gamma$ is convex and closed under certain conditions. We further analyze the relationship between cluster points and rough statistical limits in this context. The theoretical results are supported by illustrative examples to demonstrate the validity and applicability of the proposed notions. Our findings generalize several existing convergence concepts and contribute to the growing body of research in neutrosophic functional analysis. Full article

This paper proposes the expressions for the motor airgap torque harmonics induced by a cascaded H-bridge inverter operating with failed cells. These variable frequency drive systems (VFDs), are widely used in oil and gas applications, where a torsional vibration evaluation is a critical challenge for field engineers. This paper proposes mathematical expressions that are crucial for an accurate torsional analysis during the design stage of VFDs, as required by international standards such as API 617, API 672, etc. By accurately reconstructing the electromagnetic torque from the stator voltages and currents in the (αβ0) reference frame, the obtained expressions enable the precise prediction of the exact locations of torque harmonics induced by the inverter under various real-world operating conditions, without the need for installed torque sensors. The neutral-shifted and peak-reduction fault-tolerant control techniques are commonly adopted under faulty operation of these VFDs. However, their effects on the pulsating torques harmonics in machine air-gap remain uncovered. This paper fulfils this gap by conducting a detailed evaluation of spectral characteristics of these fault-tolerant methods. The theoretical analyses are supported by MATLAB/Simulink 2024 based offline simulation and Typhoon based virtual real-time simulation results performed on a (4.16 kV and 7 MW) vector-controlled induction motor fed by a 7-level cascaded H-bridge inverter. According to the theoretical analyses- and simulation results, the Neutral-shifted and Peak-reduction approaches rebalance the motor input line-to-line voltages in the event of an inverter’s failed cells but, in contrast to the normal mode the carrier, all the triplen harmonics are no longer suppressed in the differential voltage and current spectra due to inequal magnitudes in the phase voltages. These additional current harmonics induce extra airgap torque components that can excite the lowly damped eigenmodes of the mechanical shaft found in the oil and gas applications and shut down the power conversion system due torsional vibrations. Full article

Background: The increasing incidence of revision total hip arthroplasties (rTHAs), particularly due to failure of the acetabular components and severe bone loss, necessitates reliable surgical solutions. Iliac stemmed cups (ISCs) have emerged as effective options for managing complex pelvic defects, including Paprosky type 3A and 3B acetabular defects, severe developmental dysplasia, and selected pelvic discontinuities. This review examines the historical evolution, clinical indications, and outcomes associated with ISCs. Methods: This narrative review analyzed the historical and recent literature concerning various ISC designs. We critically assessed clinical outcomes, complication rates, and implant survival from 13 key studies. Results: ISCs have progressed significantly from initial monobloc designs to contemporary modular configurations, substantially enhancing surgical versatility and biomechanical stability. Clinical outcomes varied with reported complications such as infection, dislocation, mechanical failure, and aseptic loosening ranging from 10% to over 30%. Newer modular implants like the Sansone cup have demonstrated improved outcomes, with complication rates below 10% and five-year survival rates exceeding 95%. Conclusions: ISCs are reliable and versatile implants, particularly suited to address significant pelvic bone deficiencies. Optimal surgical techniques and careful implant selection remain essential to minimize complications and achieve favorable long-term functional outcomes, making these implants valuable tools in complex hip arthroplasty. Full article

This study addresses the challenge of effectively modeling uncertainty and hesitation in complex decision-making environments, where traditional fuzzy and vague set models often fall short. To overcome these limitations, we propose the Fermatean neutrosophic vague soft set (FNVSS), an advanced extension that integrates the concepts of neutrosophic sets with Fermatean membership functions into the framework of vague sets. The FNVSS model enhances the representation of truth, indeterminacy, and falsity degrees, providing greater flexibility and resilience in capturing ambiguous and imprecise information. We systematically develop new operations for the FNVSS, including union, intersection, complementation, the Fermatean neutrosophic vague normalized weighted average (FNVNWA) operator, the generalized Fermatean neutrosophic vague normalized weighted average (GFNVNWA) operator, and an adapted Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. To demonstrate the practicality of the proposed methodology, we apply it to a solar panel selection problem, where managing uncertainty is crucial. Comparative results indicate that the FNVSS significantly outperforms traditional fuzzy and vague set approaches, leading to more reliable and accurate decision outcomes. This work contributes to the advancement of predictive decision-making systems, particularly in fields requiring high precision, adaptability, and robust uncertainty modeling. Full article

Humanity faces significant challenges in achieving internationally agreed sustainable development goals, particularly in reducing public health risks and improving the environmental quality. Measuring and comparing performance across regions requires a systematic and transparent framework. This study explores the application of sustainable development indicators, including a mortality rate attributed to exposure to unsafe WASH services (SDG 3.9.2), a mortality rate attributed to household and ambient air pollution (SDG 3.9.1), and a mortality rate attributed to unintentional poisoning to assess regional health outcomes. Using data from 50 countries across five sub-regions of Asia, this research applies a weighted neutrosophic similarity measure based on the Hausdorff metric to evaluate regional alignment with an ideal benchmark. The results reveal significant disparities across regions, highlighting Central Asia as the closest to the benchmark, while South and West Asia exhibit substantial gaps. These findings provide actionable insights for policymakers to improve public health infrastructure and address environmental challenges, promoting equitable and sustainable development. Full article

The exponential growth in global student mobility has resulted in a corresponding increase in demand for international student fairs. Education fairs serve as pivotal platforms for the acquisition of information and the formulation of decisions pertaining to academic pursuits, with a considerable number of students ultimately enrolling in undergraduate, graduate, and language programs abroad. By reaching a large number of students at international education fairs, students from underdeveloped or developing countries benefit from educational opportunities in developed countries, providing significant contributions to social sustainability and socio-economic opportunities. The success of these events is reliant upon the selection of an appropriate location, which necessitates a multifaceted process that considers a range of factors and potential risks. This initial study on the location selection of international education fairs addresses the existing literature gap by employing the interval-valued neutrosophic fuzzy TOPSIS (IVN Fuzzy TOPSIS) method, a novel approach to the location country selection decision problem faced by a fair company operating in Türkiye for international education fairs. IVN Fuzzy TOPSIS is an advanced decision-making method that incorporates interval-valued neutrosophic sets—using high and low values for truthiness (T), indeterminacy (I), and falsity (F)—to more effectively handle uncertainty and indeterminacy in evaluating alternatives. The study demonstrates the efficacy of this method in addressing uncertainty through a real-world case analysis, which provides a balanced assessment of various criteria. The findings, in which Poland was identified as the optimal fair location among five alternatives, demonstrate the efficacy of the method in facilitating expeditious and precise decision-making, particularly through the incorporation of linguistic expressions that simplify the complexities of decision-making processes. This research not only advances the understanding of site selection for education fairs but also offers a practical tool for decision-makers navigating similar challenges in event planning. Full article

To improve the accuracy of choosing restoration materials for repairing ancient Chinese buildings and to mitigate the risk of decision-making, this paper establishes a novel selection model of compositions and proportions of additive lime mortars for the restoration of ancient Chinese buildings. The selection process is influenced by multi-criteria and determined by a group of experts through comprehensive judgment. Thus, it is a multi-criteria group decision-making (MCGDM) problem. Firstly, considering subjective and objective criteria simultaneously, establish a selection index system for compositions and proportions of additive lime mortars in the restoration of ancient Chinese buildings. Secondly, applying a neutrosophic set to characterize experts’ evaluation information and quantify the evaluation information. Thirdly, the best–worst method (BWM) is implemented to obtain criteria weights, and the entropy weight method is utilized to obtain index weights. Finally, obtaining the priority of each alternative solution by using the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) ranking technique. The practicality of the proposed model was demonstrated through a specific case of the selection of repair materials for a decorative window in one ancient Chinese building. The comparative analysis was carried out to verify the reliability and validity of the model. Full article

Recently, Milles and Hammami presented and studied the concept of a neutrosophic topology generated by a neutrosophic relation. As a continuation in the same direction, this paper studies the concepts of neutrosophic ideals and neutrosophic filters on that topology. More precisely, we offer the lattice structure of neutrosophic open sets of a neutrosophic topology generated via a neutrosophic relation and examine its different characteristics. Furthermore, we enlarge to this lattice structure the notions of ideals (respectively, filters) and characterize them with regard to the lattice operations. We end this work by studying the prime neutrosophic ideal and prime neutrosophic filter as interesting types of neutrosophic ideals and neutrosophic filters. Full article

The study of symmetry is a fascinating and unifying subject that connects various areas of mathematics in the twenty-first century. Algebraic structures offer a framework for comprehending the symmetries of geometric objects in pure mathematics. This paper introduces new concepts in algebraic structures, concentrating on semimodules over semirings and analysing the neutrosophic structure in this context. We explore the properties of neutrosophic subsemimodules and neutrosophic ideals after defining them. We discuss, utilizing neutrosophic products, the representations of neutrosophic ideals and subsemimodules, as well as the relationship between neutrosophic products and intersections. Finally, we derive equivalent criteria in terms of neutrosophic structures for a semiring to be fully idempotent. Full article

Governments frequently partner with the private sector to provide infrastructure and public services. These cooperations, known as public–private partnerships (PPPs), have often failed. Sometimes, due to the problem’s complexity, the public sector cannot choose the right partner for these projects, which is one of the main reasons for failures. Complexity in such problems is associated with a large number of indicators, imprecise judgments of decision-makers or problem owners, and the unpredictability of the environment (under conditions of uncertainty). Therefore, presenting a simplified algorithm for this complicated process is the primary goal of the current research so that it can consider the problem’s various dimensions. While many researchers address the critical risk factors (CRFs) and others focus on key performance indicators (KPIs), this research has considered both CRFs and KPIs to choose the best private-sector partner. In addition, we used single-valued neutrosophic sets (SVNSs) to collect decision-makers’ views, which can handle ambiguous, incomplete, or imprecise information. Next, by defining the ideal alternative and using the similarity measure, we specified the ranks of the alternative. Additionally, to face the uncertain environment, we examined the performance of options in four future scenarios. The steps of the proposed algorithm are explained in the form of a numerical example. The results of this research showed that by employing a simple algorithm, even people who do not have significant operations research knowledge could choose the best option by paying attention to the dimensions of the problem complexity. Full article

Site selection for an institute or a university is a challenging task. The selection of sites for setting up a new university depends on multiple criteria. In backward, under privileged area people’s perception towards the co-educational universities and women universities are different. Poor families with their conservative mentality possess inhibitions while sending their girl child to co-educational universities as they have concerns about safety, security and family honor. Hence many attributes which are not so important for co-educational universities are more pertinent for women university. In this research paper, we have considered a model for selecting women’s university sites in different backward locations in the state of West Bengal, India. This model incorporated different types of uncertainty related to site selection. Ten important criteria are chosen for the selection of sites. To capture the uncertainty of the problem, trapezoidal neutrosophic numbers are used along with the Multi-criteria Decision Making tool Analytic Hierarchy Process (AHP) for obtaining criteria weights. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and COmplex PRoportional ASsessment (COPRAS) are applied for ranking of the sites. Comparative and sensitivity analyses are conducted to check the steadiness of the techniques used. Full article

Hausdorff distance is one of the important distance measures to study the degree of dissimilarity between two sets that had been used in various fields under fuzzy environments. Among those, the framework of single-valued neutrosophic sets (SVNSs) is the one that has more potential to explain uncertain, inconsistent and indeterminate information in a comprehensive way. And so, Hausdorff distance for SVNSs is important. Thus, we propose two novel schemes to calculate the Hausdorff distance and its corresponding similarity measures (SMs) for SVNSs. In doing so, we firstly develop the two forms of Hausdorff distance between SVNSs based on the definition of Hausdorff metric between two sets. We then use these new distance measures to construct several SMs for SVNSs. Some mathematical theorems regarding the proposed Hausdorff distances for SVNSs are also proven to strengthen its theoretical properties. In order to show the exact calculation behavior and distance measurement mechanism of our proposed methods in accordance with the decorum of Hausdorff metric, we utilize an intuitive numerical example that demonstrate the novelty and practicality of our proposed measures. Furthermore, we develop a multi-criteria decision making (MCDM) method under single-valued neutrosophic environment using the proposed SMs based on our defined Hausdorff distance measures, called as a single-valued neutrosophic MCDM (SVN-MCDM) method. In this connection, we employ our proposed SMs to compute the degree of similarity of each option with the ideal choice to identify the best alternative as well as to perform an overall ranking of the alternatives under study. We then apply our proposed SVN-MCDM scheme to solve two real world problems of MCDM under single-valued neutrosophic environment to show its effectiveness and application. Full article

The best–worst method (BWM) has recently demonstrated its applicability in addressing various decision-making problems in a practical setting. The traditional BWM method is based on deterministic information gathered from experts as pairwise comparisons of several criteria. The advantage of BWM is that it uses fewer calculations and analyses while maintaining good, acceptable consistency ratio values. A multi-choice best–worst method (MCBWM), which considers several options for pairwise comparison of preferences between the criteria, has recently been developed. The experts are given the option to select values from several comparison scales. The MCBWM technique has been shown to be better. Presenting the options for which an optimal solution has been found simplifies the calculation and establishes the ideal weight values. This study proposes two different mathematical programming models for solving multi-criteria decision-making problems having multiple decision-makers. The two methods are proposed considering the multi-choice uncertainty assumption in pairwise criteria comparisons. Additionally, it considers the best–worst method as the base model. The multi-choice uncertainty is applied to determine the best choice out of multiple choices. It gives a real-life scenario to the decision-making problems. Although there are many other forms of uncertainty, such as fuzzy, intuitionistic fuzzy, neutrosophic, probabilistic, etc., it focuses on choices instead of ambiguity in terms of the probabilistic or fuzzy nature of parameters. The parameter considered as multi-choice is the pairwise comparison. These parameters are handled by applying the Lagrange interpolating polynomial method. The proposed models are novel in terms of their mathematical structure and group decision-making approach. The models are formulated and further validated by solving numerical examples. It provides a framework for solving mcdm problems where the weightage to the decision-makers is also incorporated. The CR values for all the models of example 1 and 2, and the case study has been found acceptable. Full article

Most studies in recent decades focused on transforming linear economics into circular through recovering and remanufacturing the products. Circular Economies (CE) aim to minimize the usage of resources by utilizing the waste in production as new or raw materials. Interconnectivity between parties in the industrial system provides decision-makers with rich information and anticipation of failure. Industry 4.0 technologies (I4.0) allow for handling such issues, protecting the environment by utilizing resources efficiently, and restructuring the industry to be smarter as well. This paper contributes to achieving cleaner production (CP), CE, and social for manufacturers through the linkage between 6R methodology with new technologies of I4.0 such as Blockchain technology (BCT) and big data analytical technology (BDA). In this paper, the authors proposed a Multi-criteria decision-making (MCDM) decision framework based on the best-worst method (BWM), Decision-Making trial and evaluation laboratory (DEMATEL), Technique for order of preference by similarity to ideal solution (TOPSIS), and Complex Proportional Assessment (COPRAS). The authors contributed to addressing the weaknesses and problems of these subjective MCDM methods through the cooperation of the neutrosophic theory with the usage of MCDM methods in this work. In the first stage, all criteria that influence sustainable manufacturer selection are specified using literature research on this topic. BWM-based neutrosophic theory was combined to get the criteria’s weights with the aid of DEMATEL-based neutrosophic to obtain the least and best criteria used in BWM in the second stage. The optimal sustainable manufacturer was selected based on TOPSIS and COPRAS under neutrosophic theory in the third and fourth stages, respectively. Furthermore, a case study performed indicated manufacturer 2 (A₂) is an optimal sustainable manufacturer in two ranking methods otherwise, manufacturer 4 (A₄) is the worst sustainable manufacturer. The contribution of this work is to propose a hybrid MCDM with an uncertainty theory of neutrosophic for sustainable manufacturer selection based BDA-BCT with 6R. Sensitivity analyses were carried out to show the decision’s flexibility in various scenarios. Finally, the consequences for management viewpoints were considered. Full article