Fuzzy-Soft Modeling to Determine the Best Fertilizer for Lactuca sativa L. Crop Considering Three Agronomic Variables

Himera; Vicente; Kandy Ferrer; Osmin Ferrer; Jos´e

doi:https://doi.org/10.54216/IJNS.260430

International Journal of Neutrosophic Science | 2025

Modeling Legal Integrity Using Plithogenic n-SuperHyperGraphs: A Multidimensional Representation of Moral Coherence in Dworkin's Theory

This project aims to concretize Ronald Dworkin's theory of legal integrity via Plithogenic n-SuperHyperGraphs. Therefore it investigates how such mathematical entities metaphorically and multidimensionally formulate moral coherence in legal interpretation. Using a mixed-method approach, this work will assess documents through a documentary assessment of Dworkin's written works (Law’s Empire and Taking Rights Seriously) to formulate a Plithogenic n-SuperHyperGraph of a case study featuring n-dimensional nodes as moral principles, moral assertions, and past decisions with hyperedges symbolizing the relationship between them generated by degrees of truth, falsity, or indeterminacy. Tools of graph visualization and neutrosophic computing will provide the legal assessment of characterization for coherence. The results will discuss whether the model intentionally visualizes the connections among the principles and how it assessed which characterizations would make the law most morally coherent under Dworkin's theory while acknowledging the indeterminacy in certain complicated cases. Thus, this study seeks to find correlations between which nodes function as the primary principles consistent with Dworkin's metaphor of the law's "chain." Ultimately, this research intends to present Plithogenic n-SuperHyperGraphs as a viable application to formally express Dworkin's theory for the sake of more moral legal determinations applicable to legal education or judicial assistive software, although generalizability will require cross-jurisdicDworkin; Legal Integrity; N- Superhypergraphs; Moral Coherence; Judicial Interpretation; Neutrosophic; Plithogenictional applications of the model.

groups

Carmen Marina Méndez Cabrita mail -

Josía Jeseff Isea Argüelles mail -

Luis Andrés Crespo Berti mail -

María Elena Infante Miranda mail

link https://doi.org/10.54216/IJNS.260330

Volume & Issue

Vol. Volume 26 / Iss. Issue 3

Details open_in_new

Fusion: Practice and Applications | 2025

The Fusion of AI and Group Dynamics: A Case Study of IMC Krems University, Tashkent

This study investigates the fusion of artificial intelligence (AI) and group dynamics by examining undergraduate student perceptions (n=112) of AI tools (e.g., ChatGPT, Grok, Gemini, Grammarly, etc.) in collaborative group work at IMC Krems of Applied Sciences University, Tashkent campus. By using surveys, thematic analysis, it explores AI impact on communication, equity, and task management in culturally diverse, multilingual settings. Results show majority students regularly use AI tools for idea generation, feedback, language support. Qualitative analysis reveals four themes: enhanced efficiency, improved communication support and concerns about over-reliance and reduced interpersonal interaction. While AI serves as cognitive and emotional scaffolding but requires mindful, ethical integration to maximize benefits. The research offers novel insights for non-Western multilingual contexts and practical guidance for educators implementing human-AI hybrid collaboration.

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Khodjaeva Dildora mail -

Ergashboyeva Farangiz mail -

Khodjaeva Elnoz mail

link https://doi.org/10.54216/FPA.200211

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2025

Zero Watermarking Approach Based on Machine Learning and Cryptographic Protocol

With the rapid increase of digital content distribution, video watermarking ownership has become an essential tool for detecting certification and tampering. This paper proposes a novel 3D video Zero-Watermarking Framework that integrates machine learning, cryptographic protocol, and entropy-based keyframe selection to ensure strength, inconvenience, and safety. The method operates at two levels: client-side watermark generation and server-side certification. On the client side, the keyframe is extracted using entropy analysis, features are obtained with different 3D Convolutional Neural Network (S3D-CNN), and adaptive noise is generated through the generative adversarial network (GANS). These components are paired with XOR to create a binary watermark key, which undergoes NIST random tests before being safely sent with the original video. On the server, Feige-Fiat-Shamir (FFS) certifies the watermark without highlighting the sensitive information of the zero-knowledge protocol. The system is evaluated against general attacks such as Gaussian noise, JPEG compression, staining, salt-and-pepper, rotation, and scaling. Performance metrics (PSNR, SSIM, NCC, and BER) with FFS protocols, showing 98.7% accuracy in verifying watermark integrity, display strong strength and inevitability. Experimental results, supporting safe and decentralized certification, confirm the effectiveness of the framework proposed to maintain watermarks under various attacks. Future work will focus on integrating blockchain technology and increasing the GAN model for real-world deployment.

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Dalal Thair Mahjoub mail -

Hala Bahjat Abdulwahab mail

link https://doi.org/10.54216/JISIoT.170229

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

Modeling Bitcoin Price Dynamics Using a Fractional Maxwell-Weibull Copula Distribution

This paper presents the Fractional Maxwell-Weibull Copula (FMWC) distribution to deal with the heavy tails, extended memory, and nonlinear dependence of price returns of Bitcoins, as the existing financial models face limitations in this aspect. The FMWC provides a flexible model that allows incorporating fractional Weibull distributions to capture persistent autocorrelation, Maxwell components to model significant price changes, and a Student-t copula to capture multivariate dependencies to discuss the volatile returns of Bitcoin. The FMWC was applied to historical Bitcoin data between January 2020 and May 2025 and showed better results than other models, such as Weibull, GARCH-t, and Maxwell-Log Logistic, with an MAE of 0.034374, RMSE of 0.0335, and log-likelihood of 4200.0. Its risk measures (VaR 95% = -0.07983, CVaR 95% = -0.10882) improve tail risk estimation, which is important in risk measurement and portfolio management. Robustness tests also validate its performance over periods and proper handling of outliers. Nevertheless, the FMWC is an excellent tool, despite its computational complexity issues, and can be used by investors, traders, and regulators. Further studies on the computational efficiencies and applications to other cryptocurrencies are required to increase their application in dynamic financial markets.

groups

Alshaikh A. Shokeralla mail

link https://doi.org/10.54216/IJNS.260427

Volume & Issue

Vol. Volume 26 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

On Neutrosophic Soft Generalized Semi-Mappings and Their Topological Properties

This paper introduces and systematically studies new classes of mappings and set-theoretic structures in the context of neutrosophic soft topological structures. In particular, this study introduces and examines neutrosophic soft semi closed and semi open sets, generalized semi-mappings, and semi-continuous generalized mappings, highlighting their interrelationships and key topological properties The neutrosophic soft generalized semi-closure and semi-interior operators are also formulated, and their principal algebraic and topological characteristics are derived. These developments generalize and unify several existing notions in classical, fuzzy, and neutrosophic soft topologies. Unlike previous studies, this work provides a comprehensive mapping-based approach that clarifies how generalized semi-properties behave under neutrosophic soft transformations. The findings not only extend the theoretical foundations of NST but also open potential directions for modeling and analyzing uncertainty in advanced topological systems.

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Alkan Özkan mail -

Florentin Smarandache mail -

ٍSeyda Yazgan mail -

Salem Saleh mail -

Ebru Yesil mail

link https://doi.org/10.54216/IJNS.260428

Volume & Issue

Vol. Volume 26 / Iss. Issue 4

Details open_in_new

Fusion: Practice and Applications | 2025

Critical Success Factors for E-Government Implementation: A Comprehensive Framework and Literature Analysis

The implementation of e-government initiatives remains a complex socio-technical challenge, particularly for administrations lacking structured knowledge of the Critical Success Factors (CSF) of E-government. The CSFs refer to the essential elements that must be effectively addressed to ensure the achievement of organizational objectives. In the context of E-government, CSFs encompass key determinants such as leadership commitment, technological infrastructure, user trust, policy support, and citizen engagement that collectively drive successful digital governance implementation. Governments often struggle to operationalize strategies and allocate resources effectively due to the absence of empirically grounded frameworks. To fill these gaps, this study combines systematic evidence synthesis, qualitative factor clustering, and quantitative multi-criteria validation to model and prioritize the interdependent CSFs governing sustainable e-government implementation across technological, organizational, human, environmental, and governance dimensions. The research employs a three-phase methodological pipeline: (1) Systematic Literature Review (SLR) guided by Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) standards to identify CSFs across more than 58 peer-reviewed studies; (2) Thematic Coding and Factor Clustering using NVivo-based qualitative content analysis to categorize determinants into organizational, technological, environmental, human, and governance domains; and (3) Analytic Hierarchy Process (AHP) Validation to assign relative weightings and interdependencies among identified factors. A total of 62 CSFs were extracted and classified under eight major domains: Strategic Planning and Governance, Planning and Execution Efficiency, Technical and Operational Aspects, User-Centric Focus and Quality Assurance, Technological Factors, Organizational Factors, Socio-Political Factors, and Economic Factors. Among these, User-Centric Focus and Quality Assurance (C₄) emerged as the most influential cluster with the highest global weight of 0.286, reflecting the growing emphasis on citizen trust, service quality, and satisfaction in digital governance systems. The top three CSFs identified through AHP were “Building Trust with Users” (LW = 0.266, GW = 0.033), “Visionary Leadership” (LW = 0.265, GW = 0.040), and “Comprehensive Planning” (LW = 0.275, GW = 0.038), representing the intersection of governance, user engagement, and execution excellence. This study contributes a decision-support framework that integrates both quantitative prioritization and qualitative contextualization, serving as a practical tool for policymakers, digital transformation officers, and public sector reform strategists.

groups

Saleh Alharbi mail

link https://doi.org/10.54216/FPA.200212

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things | 2025

Comparative Evaluation of Information Technology Governance Frameworks for Ensuring Cybersecurity Compliance in the Internet of Things Era

The proliferation of Internet of Things (IoT) technologies has transformed digital ecosystems, creating highly interconnected environments that demand robust and adaptive cybersecurity governance. Despite their widespread adoption, existing Information Technology Governance (ITG) frameworks—such as the NIST Cybersecurity Framework (CSF), ISO/IEC 27001, Center for Internet Security (CIS) Controls, and ISA/IEC 62443 vary considerably in scope, applicability, and alignment with the unique characteristics of IoT infrastructures. The absence of a unified approach to address IoT-specific challenges such as device heterogeneity, data provenance, and real-time monitoring underscores the need for a comprehensive comparative analysis. This study conducts a qualitative synthesis and thematic comparison of leading cybersecurity governance frameworks to evaluate their effectiveness in ensuring compliance and resilience within IoT-enabled environments. Each framework was examined across recurring governance domains, including risk management orientation, scalability, control comprehensiveness, interoperability, and contextual adaptability. The analysis integrated findings from scholarly literature, international standards documentation, and expert reports, allowing the identification of emergent patterns, convergences, and gaps in the frameworks’ conceptual foundations and implementation practices. The findings indicate that NIST CSF provides a highly flexible, sector-neutral architecture fostering adaptive governance, whereas ISO/IEC 27001 offers formalized, audit-oriented structures suitable for organizations emphasizing certification and policy compliance. The CIS Controls framework emerges as practical and accessible, favoring rapid implementation and community-driven updates, while ISA/IEC 62443 demonstrates unparalleled domain specificity and defense-in-depth design for industrial and cyber-physical systems. Nevertheless, all frameworks exhibit limitations when addressing IoT-centric issues such as dynamic risk contexts, interoperability among heterogeneous devices, and integration of operational and information technology governance layers. The study concludes that a composite, layered governance approach—anchored in the structural rigor of ISO/IEC 27001, the adaptability of NIST CSF, the practicality of CIS Controls, and the industrial depth of ISA/IEC 62443—can offer a more holistic foundation for IoT cybersecurity compliance.

groups

Saleh Alharbi mail

link https://doi.org/10.54216/JISIoT.170230

Volume & Issue

Vol. Volume 17 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

Possibility of Quadripartitioned Neutrosophic Cubic Sets and Their Application of Multi-Criteria Decision Making

This study introduces the innovative idea of associating a possibility measure with the membership of an element in a set, and further proposes the structure of quadripartitioned neutrosophic cubic sets (PQNCS). Within this framework, the authors define four distinct components—truth, contradiction, ignorance, and falsity—each in two modes: internal and external. They explore the corresponding sets (truth-internal, contradiction-internal, ignorance-internal, falsity-internal and truth-external, contradiction-external, ignorance-external, falsity-external) and uncover their interrelated properties. Moreover, the work emphasizes the role of a score function as a central instrument for multi-attribute decision-making, and examines how measures of PQNCS—through score, accuracy and certainty functions grounded in the possibility concept—can be employed to support and guide decision-making in the quadripartitioned neutrosophic cubic setting.

groups

J. Sharmila mail -

F. Nirmala Irudayam mail

link https://doi.org/10.54216/IJNS.260429

Volume & Issue

Vol. Volume 26 / Iss. Issue 4

Details open_in_new

Fusion: Practice and Applications | 2025

Demystifying Disease Prediction with Explainable Supervised Learning

The ever-worsening mortality rates due to various diseases such as heart disease, breast cancer, and kidney disease are of great concern. Early diagnosis of the disease can be of great help. This process can be automated with the help of Artificial intelligence (AI). But, the main worry of using AI in healthcare is its black-box behaviour. The majority of the models characterized by high accuracy are often black-box in nature. This can be overcome by the use of eXplainable Artificial Intelligence (XAI), which is capable of explaining the predictions made by these black box models. We have exploited 3 different XAI frameworks: SHAP, LIME, and DALEX, to understand the working and the facilities provided by the three frameworks and compare them. We have used 5 disease datasets (3 heart disease, 1 cancer and 1 kidney disease) to carry out our work. Each dataset was trained with 3 machine learning models, namely Support Vector Machine (SVM), Logistic regression (LR), and K-Nearest neighbours (KNN), and the best model was used to feed to the XAI framework. LR performed best for one of the heart disease datasets with 72.31%accuracy, while SVM outperformed in all the other datasets, thus proving the efficacy of such approaches for early disease prediction.

groups

Neel Modi mail -

Astha Soni mail -

Gokul Yenduri mail -

Rutvij H. Jhaveri mail -

Stella Bvuma mail

link https://doi.org/10.54216/FPA.200213

Volume & Issue

Vol. Volume 20 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2025

Fuzzy-Soft Modeling to Determine the Best Fertilizer for Lactuca sativa L. Crop Considering Three Agronomic Variables

Set-based theories have become key tools to address uncertainty and imprecision in complex systems. Fuzzy sets model gradual membership, soft sets add flexibility through parameterization, and neutrosophic sets generalize both by incorporating truth, indeterminacy, and falsity degrees. In this manuscript, a fuzzy-soft expert system is described to determine the efficiency of different fertilizations in lettuce (Lactuca sativa L.) crops considering agronomic variables such as fresh weight (FW), number of leaves (NL), and crown diameter (CD). The model, based on fuzzy membership functions and soft set operations, effectively manages the un- certainty inherent in agricultural data and provides a novel decision-support tool. Although this work focuses on fuzzy and soft sets, its extension to the neutrosophic framework could further enrich the analysis by ex- plicitly modeling indeterminacy and inconsistency, offering a more comprehensive approach to agricultural decision-making.

groups

Himera Hamburguer mail -

Vicente Vergara-Fl´orez mail -

Kandy Ferrer Sotelo mail -

Osmin Ferrer Villar mail -

Jos´e Sanabria mail

link https://doi.org/10.54216/IJNS.260430

Volume & Issue

Vol. Volume 26 / Iss. Issue 4

Details open_in_new