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ScholarAI Scholarly Article Search Strategies with the Ayni Method Multi-Neutrosophic for Ethical Information Management in AI
No full textIn a digital world where scientific articles are published at an unprecedented rate, an additional step in the research process to facilitate discovery is an effective search and filtering for worthwhile articles. Thus, this study aims to solve the following research problem: how to search for scientific articles using artificial intelligence (AI) while applying ethical considerations and ancestral knowledge? The topical relevance is that as AI is a great vessel to seek potentially accessible knowledge, searches can be guaranteed through accuracy, inclusivity, and ethics. While many studies exist on the topic of AI related to searching, few, if any, extend a solution to addressing cultural and ethical ambiguity. Thus, a gap exists within the literature review. This research applies the Ayni Method. Multi-Neutrosophic, which is based on the Andean ancient logic of reciprocity, is fused with neutrosophic to assess truth, falsity, and indeterminacy. Findings indicate that increasing ethical awareness does, in fact, promote success because such factors are considered when creating prompts and Boolean searches. Ultimately, this research contributes to the literature by suggesting a methodologically innovative approach that increases the likelihood for ethically sound information use and successful scientific research with practical applications for any researcher across disciplines
A Neutrosophic Random Forest Framework for Uncertainty-Aware Classification of Nursery School Applications
No full textThis paper presents a novel framework that integrates Random Forest classification with neutrosophic logic to address the challenge of uncertainty-aware decision-making in nursery school application processes. Using the publicly available Nursery dataset—which includes socio-familial attributes such as parental occupation, financial standing, and health conditions—the proposed model not only achieves high predictive accuracy (approximately 95%) but also quantifies uncertainty explicitly through neutrosophic sets defined by truth (T), indeterminacy (I), and falsity (F) membership degrees. This approach allows for a nuanced interpretation of classification confidence, distinguishing between clear-cut cases that can be automated and borderline instances requiring human expert review. By enabling a transparent, tiered decision-making strategy, the framework enhances the fairness, explainability, and operational efficiency of admission systems, offering a practical tool for administrative use in high-stakes educational settings
Prioritization of Risks Detected in Comprehensive Audits Using Neutrosophic TOPSIS and Hausdorff Distance
No full textThis study addresses the phenomenon of prioritization of risks during large-scale audits as risks evident in the complicated environment and uncertain information are challenging to mitigate. The importance of the topic is that for complicated entities with high uncertainty, high impact, and low/high probability of audit detection, proper allocation in this resource sensitive 21st century is needed for effective audit. The literature demonstrates means to assess and rank risk for subsequent corrective actions that traditional statistical methods cannot capture. The developed hybrid model combines Random Forest, fuzzy logic, and neutrosophic logic are used to process homicide data, demographic variables, and socioeconomic factors in Ecuador. The results demonstrate % accuracy in predicting security levels by canton, significantly outperforming traditional deterministic approaches. The developed platform generates interactive, georeferenced visualizations that facilitate understanding of risk patterns and support informed decision-making in citizen security policies. This research contributes to the development of more robust and adaptive predictive systems, establishing a methodological precedent for the application of neutrosophics to public security and social risk management issues
A Neutrosophic Topological Algebraic Structure for Clinical Efficacy Evaluation in Traditional Chinese Medicine Using Artificial Intelligence
No full textInvestment Benefit of Grid Infrastructure Projects: A Neutrosophic SuperHyperFunction-Based Model
No full textA Neutrosophic Framework Design and Performance Evaluation for Ethical Governance Construction in Big Data–Driven Physical Education
No full textNeutrosophic Credibility-based Uncertainty for Evaluating Teaching Quality in College Physical Education: Standards, Criteria, and Practices
No full textNeutrosophic Cultural Resonance for Teaching Effectiveness: A Plithogenic Probabilities-Inspired Framework Model for University Fine Arts Programs Using Red Culture Resources
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