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Evaluation Software and IT Integration for IoT-based Healthcare Radio Frequency Identification Network Planning

For Internet of Things (IoT)-based on healthcare systems to autonomously monitor patients, radio frequency identification, or RFID, its essential. It is difficult to guarantee complete coverage throughout sizable healthcare facilities with a small number of RFID readers, though Software for RFID network planning must be optimized. The purpose of this paper is about optimizing related software and suggest a topological RFID network planning strategy that will minimize reader interference while deploying the fewest possible readers. The best location for RFID tags on patients as well as readers depends on the layout of the institution and how the patients move. To dependably scan tags across a variety of locations, RFID network design software precisely calculates the number and positions of readers using algorithms. Software features and network planning goals are developed to efficiently track patient status by automating the gathering of medical data. in this paper to find the optimal number of RFID readers required and their location in the system. After the algorithm was tested, it was found that the algorithm can determine the true effectiveness of the coverage and reduce the area of interference between the areas of coverage of RFID readers. PSO is a superior algorithm for solving difficult problems (NP). The PSO algorithm has shown a high efficiency in finding the optimal solution, with some of weakness in the performance of the algorithm, represented in finding functional boundaries that serve the research problem. By providing constant access to health information, this plan raises the standard of care.

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Huda Abdulaali Abdulbaqi mail -
Farah Q. Abdullah AL-Khalidi mail
link https://doi.org/10.54216/FPA.150224

Volume & Issue

Vol. Volume 15 / Iss. Issue 2

Details open_in_new

A Novel Fusion Method for Enhanced Multi-Criteria Decision-Making in Energy Management: Integrating Analytic Hierarchy Process

This paper suggests a novel fusion approach of combining Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance multi-criteria decision-making for energy management. In this way, by integrating the two powerful methodologies, the fusion approach is enabled that allows for dealing with the complex and highly dynamic character of energy management decisions for which there is required the careful consideration of many conflicting criteria. The method uses A to derive weightings for each decision criterion via AHP based on expert judgments, ensuring all relevant factors are systematically considered proportionately. Subsequently, TOPSIS is applied to evaluate and rank the alternatives such that the most effective energy solutions close to the ideal solution are identified. This integration of AHP with TOPSIS leads to comprehensive analysis that draws both the strengths of these techniques and provides a powerful tool to make informed and balanced decisions in the energy sector. The effectiveness of this fusion method, when applied, could then lead to the attainment of subtler findings and dependable suggestions, making it a beneficial contribution to this field of energy management.

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Murodjon Sultanov mail -
Iroda Abdullayeva mail -
Botirjon Karimov mail
link https://doi.org/10.54216/FPA.150225

Volume & Issue

Vol. Volume 15 / Iss. Issue 2

Details open_in_new

Exploring Challenges and Strategies in Managing Remote and Distributed Teams amidst the Rise of Digital Nomadism

This research investigates the evolving landscape of remote work and distributed teams in the context of the growing phenomenon of digital nomadism. As remote work becomes increasingly prevalent, organizations face unique challenges in managing geographically dispersed teams while accommodating the preferences and lifestyles of digital nomads. This study combines qualitative interviews with HR professionals and digital nomads, along with a quantitative survey of remote workers, to identify key challenges and strategies in managing remote and distributed teams amidst the rise of digital nomadism.

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Nilufar Ismaılova mail
link https://doi.org/10.54216/JSDGT.040106

Volume & Issue

Vol. Volume 4 / Iss. Issue 1

Details open_in_new

Impact of FDI on Sustainable Growth in Belt and Road Economies

This paper investigates the relationship between foreign direct investment and economic growth in Belt and Road countries during 1990-2020. Our findings suggest that a 10% increase in FDI relative to GDP is associated with only 0.9 percentage points increase in GDP growth. The results are held after including control variables. The results can be explained based on the facts that forces investors and companies to invest their money in foreign projects including relatively lower cost of deployment, the access to resources, favorable financial environment and developed financial markets. These elements collectively shape the impact of FDI on economic growth in the Belt and Road countries. Future research on the FDI-growth nexus in Belt and Road countries should concentrate on causal links and potential indirect pathways by which FDI can influence economic growth.

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Zebo KULDASHEVA mail
link https://doi.org/10.54216/JSDGT.040207

Volume & Issue

Vol. Volume 4 / Iss. Issue 2

Details open_in_new

On Refined Netrusophic Fractional Calculus

Depending on the geometric isometry (AH-Isometry), it has been proven that every Neutrosophic real function is equivalent to three real functions. Then, the foundation of the Refined Netrusophic calculus was established, where new definitions of Refined Netrusophic integration and Refined Netrusophic differentiation were introduced, along with some illustrative examples. Following that, definitions for the Refined Netrusophic gamma function and Refined Netrusophic beta function were presented to pave the way towards achieving the desired goal, which is Refined Netrusophic Fractional calculus.

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Mohamed Nedal Khatib mail -
Ahmed Hatip mail
link https://doi.org/10.54216/IJNS.240201

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Reliability Function Estimated for Generalized Exponential Rayleigh Distribution Under Type-I Censored Data and Fuzzy Data

In this paper, maximum likelihood estimation method (MLEM), one of the most well-liked and frequently applied classic methods, is used to estimate the two scale and one shape parameters of the Generalized Exponential-Rayleigh distribution for type-I censored data, which is one of the most Rights censored data. Based on an iterative process to get approximated values for these two scale parameters and one shape parameter using the Newton-Raphson method to locate estimate value for these parameters by using the simulation procedure utilizing monte-Carlo technique to find Reliability function underneath various sample sizes and the initial values are different for the parameters for all estimated parameters of Generalized Exponential-Rayleigh by implement the initial value in the MATLAP program, Subsequently, conducting a comparative analysis between the estimated reliability function and its non-estimated counterpart employing the mean squares error methodology. In the last finding the pdf function f (t), reliability function R (t) and hazard function h (t) for simulation data. Also, we provide some examples to clarify how can we apply our results on fuzzy data tables

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Zainab A. Aldraji mail -
Rehab Noori shalan mail
link https://doi.org/10.54216/IJNS.240202

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

RETRACTED ARTICLE: Plithogenic Sociogram based Plithogenic Cognitive Maps Approach in Sustainable Industries

The theory of Plithogeny is primarily attribute based. Plithogenic Sociogram (PS) and Plithogenic cognitive maps (PCM) are distinct decision-making approaches developed to deal with attributes. This paper proposes an integrated decision-making model combining the approaches of PS with PCM and this sets the beginning of new genre of PCM. The development of this model is applied in investigating the association between the factors pertinent to the promotion of sustainable industries.  This work also compares the working of the proposed integrated model of PCM with PS and the independent working of PCM model. The results are more promising to the proposed integrated approach and this paper strongly emphasises the efficacy of this hybrid approach. The blended model of PCM with PS is efficient in handling complex decision circumstances and this approach shall be extended to other kinds of Plithogenic representations.

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N. Angel mail -
Sulbha Raorane mail -
N. Ramila Gandhi mail -
R. Priya mail -
P. Pandiammal mail -
Nivetha Martin mail
link https://doi.org/10.54216/IJNS.240203

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Enhancing Project Selection with Neutrosophic TOPSIS: Navigating Uncertainty in Post-Pandemic Decision-Making

This article explores the implementation of Neutrosophic TOPSIS, an advanced decision-making framework that extends classical and fuzzy set theories to handle the complexities of project selection amid uncertainty and indeterminacy. Neutrosophic sets are characterized by three parameters: truth, indeterminacy, and falsehood, which allow for a nuanced assessment of alternatives against defined criteria. Utilizing neutrosophic scales and expert evaluations, this method prioritizes projects by efficiently balancing multiple truth levels and addressing specific challenges such as judicial process optimization and labor education enhancement. The case study within the article demonstrates the application of Neutrosophic TOPSIS to select the most suitable project for improving labor relations and judicial efficiency in a post-pandemic world. The methodology proved effective in identifying the Digital Platform for Labor Education project as the optimal solution, given its alignment with strategic objectives and potential to handle identified challenges robustly. Future work could integrate Neutrosophic TOPSIS with other decision-making models and expand its application to more complex scenarios, potentially incorporating automated tools for a broader and more dynamic evaluation process.

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Frantz Dimitri V. Barragan mail -
Felipe Garcés Cordova mail -
María J. Calderon Velásquez mail -
Layal Kallach mail
link https://doi.org/10.54216/IJNS.240204

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Fusion of Centrality Measures with D-OWA in Neutrosophic Cognitive Maps to Develop a Composite Centrality Indicator

This study utilized Neutrosophic Cognitive Maps (NCMs) integrated with the D-OWA operator to analyze the nutritional rights of pregnant women in Ecuador, with a focus on the crucial role of nutrition education. The innovative application of the D-OWA operator enabled the computation of a composite centrality measure by merging key centrality indicators—degree, closeness, and betweenness—each appropriately weighted according to its relevance to the analysis. This methodology provided a sophisticated evaluation of the factors impacting maternal nutrition, demonstrating how combining various centrality measures offers a deeper and more comprehensive insight into the dynamics of complex systems. The calculated composite centrality measures revealed the system’s intricate structure, pinpointing critical nodes and pathways that could be targeted most effectively through interventions. The findings underscore the significant benefits of using composite centrality measures to enhance decision-making in public health and other sectors characterized by complexity and uncertainty. The potential for refining and expanding this approach in future research suggests that it could be further supported by technological advancements, enabling more efficient analysis and scalability across diverse complex systems.

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Byron J. Chulco Lema mail -
Carlos Javier L. Chapeta mail -
Rosa E. Chuga Quemac mail -
Layal Kallach mail
link https://doi.org/10.54216/IJNS.240205

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new

Enhancing Decision-Making in Complex Environments: Integrating AHP, Delphi, and Neutrosophic Logic

The integration of the Analytic Hierarchy Process (AHP), the Delphi method, and neutrosophic logic provides a powerful framework for complex decision-making, allowing for an enhanced handling of uncertainties and multiple criteria that characterizes many strategic planning and policy formulation scenarios. AHP’s structured approach helps decompose decision-making into manageable sub-problems, while the Delphi method facilitates expert consensus through iterative rounds, enriching the decision-making process with diverse expert insights. The inclusion of neutrosophic logic allows for better representation and processing of uncertainty, offering a flexible way to handle indeterminate and contradictory information. This robust methodology not only improves the precision of decisions but also adapts to the nuanced requirements of multifaceted decision environments. Future research could benefit from integrating these methods with technological advancements like artificial intelligence to automate and optimize the decision-making process further. Applying this integrated approach in various sectors such as healthcare, environmental management, and urban planning could also provide valuable insights into its effectiveness and scalability.

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Marcia Esther E. Heredia mail -
Jorge Washigton S. Andachi mail -
Nemis García Arias mail -
Saziye Yaman mail
link https://doi.org/10.54216/IJNS.240206

Volume & Issue

Vol. Volume 24 / Iss. Issue 2

Details open_in_new