generative ai

Conceptual and Methodological Precision in an Early Generative-AI HRM Review: An Academic Evidence Audit of Budhwar et al. (2023)

AI-ENHANCED ENGLISH LANGUAGE LEARNING: EFFECTS ON PROFICIENCY AND COMMUNICATIVE COMPETENCE

This review examines what AI-enhanced English language learning appears to change and where the evidence remains less conclusive. Intelligent tutoring, automated feedback, conversational AI, speech technologies, and generative AI are considered as distinct pedagogical tools rather than as a single intervention. The qua...

Tiered Assessment Framework for Cognitive Errors in Generative AI Systems: A Quality Assurance Methodology for Industrial Control Systems

A quality assurance methodology for cognitive errors in generative AI systems deployed in industrial control environments. Establishes an error-class model / criticality bands, testing methodology, and statistical acceptance criteria. It is the cognitive-error layer of a two-layer hybrid quality assurance architecture,...

UMOSU-UMOKWAI Modular Ruleset – Selective-loading anti-hallucination operational system

Abstract UMOSU-UMOKWAI Modular Ruleset – Selective-loading anti-hallucination operational system This ruleset constitutes the operational implementation of the UMOSU/UMOKWAI model (Unified Model of Social Universe / Unified Model of Knowledge With AI). It translates the ontological and epistemic classification of reali...

Students’ Attitudes towards the Use of Generative Artificial Intelligence in Higher Education Learning

This dataset contains anonymized responses from a questionnaire investigating higher education students' attitudes toward the use of Generative Artificial Intelligence (GenAI) in learning. The survey examines students' perceptions, experiences, and acceptance of GenAI technologies as learning support tools, together wi...

Tiered Assessment Framework for Cognitive Errors in Generative AI Systems: A Quality Assurance Methodology for Industrial Control Systems

A quality assurance methodology for cognitive errors in generative AI systems deployed in industrial control environments. Establishes an error-class model / criticality bands, testing methodology, and statistical acceptance criteria. It is the cognitive-error layer of a two-layer hybrid quality assurance architecture,...

Distinct consecutive products in a density-one set via prime-gap deletions

The preprint constructs a subset of the natural numbers of natural density one whose increasing enumeration has pairwise distinct finite consecutive products, resolving Erdős Problem 421. The proof combines a sparse deletion scheme based on prime-gap interiors and connector intervals with a structural analysis of possi...

Leonardo's Spatial Grammar: A CAD Reverse-Engineering Analysis Corpus: Leonardo's CAD, Leonardo's Rulers, Leonardo's Score

Abstract (it)Il corpus in esame decostruisce il mito dell'applicazione standardizzata della prospettiva albertiana a base quadrata nell'opera di Leonardo da Vinci, proponendo un paradigma metrico-modulare fondato su evidenze geometriche oggettive e falsificabili. Attraverso l'analisi tridimensionale dell'Annunciazione,...

Corrigible Generativity: Alignment as Layer-Relative Recursive Constraint-Audit

Prior work proposed the recursive-coherence kernel R ↦ C(R(R)), where R denotes recursive self-application and C denotes a coherence-preserving constraint selecting which self-transformations persist. A trace-sensitive extension made history explicit: R_{t+1} = C_{τ_t}(R_t(R_t)), τ_{t+1} = U(τ_t, R_{t+1}). This paper e...

Exact Binary Projections for Array-RQMC: Joint Laws and Pathwise-Preserving Execution

Exact Binary Projections for Array-RQMC: Joint Laws and Pathwise-Preserving Execution Aoi Kawasaki. Preprint; not peer reviewed. Contribution For a specified two-dimensional Sobol net with linear matrix scrambling and a digital shift, the complete rank-ordered binary innovation vector is uniform over exactly N outcomes...

Abstraction-Indexed Canonicity: Bidirectional Compression, Generative Authority, and Meta-Axis Governance

Long-lived AI systems may treat records, organizing schemas, and higher-order generative constraints as canonical references in different roles. Abstraction-indexed canonicity makes official standing specific to scope, revision, and functional level; compression or expansion alone grants no new standing. Admission and...

Misguided Corporate AI Promotion: How Shareholder-Oriented Storytelling Can Distort Technology Selection

This paper examines how corporate AI promotion can become detached from rational technology selection. Generative AI is valuable for tasks involving contextual understanding, translation, summarization, text generation, and ideation. However, many deterministic business processes may be better served by conventional pr...