explainable ai

EXPLORING THE USE OF GENERATIVE AI TOOLS IN INDUSTRIAL ENGINEERING AND MANAGEMENT PROFESSIONALS: AN APPLIED UTAUT2-INFORMED STUDY

This study analyses the factors that explain the acceptance and use of generative Artificial Intelligence (GenAI) tools by Industrial Engineering and Management professionals, based on the UTAUT2 model. An online questionnaire was administered, yielding 140 valid responses, analyzed through descriptive statistics and P...

EQUAINE: Asking machines to understand equine data and keep learning from it

The use of horses in our society comes with a responsibility regarding their health and welfare. Amongst performance-impeding issues, lameness and respiratory pathology are particularly concerning health and welfare. Their early detection relies on regular monitoring of locomotion and physiological statuses. The combin...

ACPNet: adaptive concept-prototype network for interpretable fine-grained image classification

AI maturity as a double-edged capability: planning fallacy and firm performance in technology startups

The study contributes to digital entrepreneurship by showing that AI maturity does not automatically neutralize planning bias; rather, its performance implications depend on alignment among AI capabilities, managerial attention, and venture planning routines.

Explainable AI for predicting and interpreting mathematics achievement: a cross-national analysis of PISA 2018

PV-robust SHAP summaries showed that books at home, highest parental occupational status, grade placement, mathematics learning time, socioeconomic status, test effort, directed instruction, and disciplinary climate were among the most stable predictors.

Pinching Antennas for Next-Generation Wireless Communications: A Network Perspective

This tutorial presents radiation locations as configurable network resources and provides a framework for understanding how pinching antennas may reshape future wireless network.

The Pain Axis: LLMs Represent Self-Directed Harm and Act to Relieve It

Large language models sometimes behave in ways resembling human emotional responses, and recent work has identified internal representations that may explain this. We ask whether LLMs represent pain distinctly from fear, sadness, and generic negative valence, and whether this representation functions as pain would be e...

Characterizing Red Blood Cell Rheological Parameters Using Automated Syllectometry: Conventional and Exploratory Multivariate Analyses.

These findings provide the first preliminary reference dataset for MIZAR-derived RBC parameters and identify patterns of covariance and interrelationships within a healthy cohort.

The impact of obesity and obstructive sleep apnea on vascular hemodynamics in men under 40: a 15-year retrospective cohort study.

Objectively measured arterial insufficiency affects a clinically meaningful minority of men under 40 with ED, is associated with OSA independently of BMI, and is not identified by routine laboratory testing or explained by psychological factors.

When AI Says"I Am Unable to Answer": Understanding User Responses to AI Refusals

A tension between hallucination avoidance and user satisfaction is revealed and the importance of designing balanced refusal strategies is highlighted, to highlight the importance of designing balanced refusal strategies.

Designing for disagreement: epistemic friction, sycophancy, and the ethics of human–AI advice—a critical integrative review

This critical integrative review synthesizes research on automation bias, algorithm appreciation and aversion, large-language-model sycophancy, persuasive dialogue, anthropomorphic interaction, explainable AI, and human autonomy to reposition productive disagreement as a positive safety and autonomy property of human–A...

Privacy-aware adversarial defense with explainable AI for adversarial robustness in AI model

The Attention Concentration Score (ACS) is introduced, which measures how DP training shifts Transformer attention away from task-critical features toward non-functional ones, providing a mechanistic explanation of the trade-off.