explainable ai

Performance analysis of vertical patterned glass BIPV in zero energy buildings using explainable AI

The Architecture of AI Governance in Banking: Bridging Compliance and Explainability Gaps

A coordinated governance strategy integrating technical validation, regulatory alignment, traditional risk management, documentation, and necessary human oversight can enhance accountability while addressing the real-world constraints of complex AI systems in regulated banking settings.

Pre-service teachers’ interactions with generative AI for creating culturally grounded visual teaching resources

The findings suggest that meaningful GenAI-supported instructional design involves more than favourable technology appraisal; it also requires usable systems, culturally informed teacher judgement and careful evaluation of generated visual resources.

Development and validation of an explainable artificial intelligence model for training load monitoring and performance risk prediction in university-level football under resource constraints

Findings indicate that explainable machine learning models based on low-resource metrics can provide an accurate, interpretable, and scalable decision-support framework for training load monitoring in educational sport environments.

Integrating ChatGPT into 5E inquiry-based learning to scaffold EFL academic research writing

Large language models such as ChatGPT are increasingly used in education, yet evidence on how to integrate them systematically into EFL academic writing pedagogy remains limited. This study examined a 16-week undergraduate EFL composition course at a national university in Taiwan that embedded ChatGPT within the 5E inq...

Fusion-Based Explainable Deep Learning Framework for Species Classification of Jelly Fungi from Field Images

A novel deep learning framework combining convolutional neural networks, model fusion, and explainable AI to automate and interpret the classification of jelly fungi offers broad potential in biological applications such as spore and pollen identification, contributing to biodiversity monitoring and advancing AI-driven...

Multimodal AI in hematology: a systematic review of fusion approaches for automated diagnosis of blood disorders

Hematological disorders, including anemia and leukemia, pose major health risks globally, especially in developing areas. Around 1.92 billion people are affected by anemia, with about 475,000 new leukemia cases diagnosed yearly, resulting in approximately 310,000 deaths. The reliance on subjective conventional diagnost...

Towards LLM-Driven Transformation of Goal Models for AI-Enabled Socio-Technical Systems

Organizations are increasingly transforming traditional software systems into AI-enabled socio-technical systems. While goal models are widely used to capture stakeholder intentions, organizational objectives, and system requirements, existing approaches provide limited support for systematically evolving these models...

Automated Modelica Model Repair Using Generative AI

This PhD contributes an agentic LLM-based framework for diagnosing and repairing Modelica models, together with the empirical foundations that make it feasible and reproducible.

CircuitIA — herramienta IA para la academia (UMH)

Genera problemas de análisis de circuitos (Ohm, Kirchhoff, nudos y mallas, Thévenin y Norton, operacionales, transitorios RC, RL y RLC, régimen sinusoidal) con su esquema y su solución calculada por un solver propio, contrastado con ngspice. Cada estudiante recibe sus valores a partir de una semilla reproducible; la co...

JAZB Framework v1.3: Judiciary AI Zero-Trust Broker

JAZB (Judiciary AI Zero-Trust Broker) is an Authority-centric, human-sovereign enterprise governance framework and architecture for artificial intelligence designed to govern the establishment, delegation, interpretation, exercise, assurance, and revocation of organizational Authority. JAZB applies Zero Trust, least pr...

AI-Driven Customer Analytics and Personalized Marketing: Examining Customer Experience, Loyalty and Purchase Intention In Digital Markets

The present study investigates how AI-driven customer analytics and personalised marketing influence customer experience, customer loyalty and purchase intention in digital markets, applying a Stimulus-Organism-Response framework extended with privacy concerns as a boundary condition. Data were drawn from a quantitativ...