explainable ai

Attribution, zonation, and simulation of spatiotemporal distribution of negative oxygen ions in mountainous megacity: A case study of Chongqing, China

Negative oxygen ions (NOI) are key indicators of urban ecological quality. However, NOI dynamics in mountainous megacities remain poorly understood. A key challenge lies in translating complex environmental observations into interpretable knowledge for environmental planning rather than prediction alone. Therefore, we...

Phase-Aware Interpretable Representations for Cyclical Time Series

Existing local explanation methods for time series models typically construct interpretable representations from contiguous temporal segments. While appropriate for many applications, this assumption maybe unsuitable for cyclical physiological signals, where physiologically equivalent states recur over time. We propose...

Integrated monitoring models for dam health and safety: A review of methods and considerations

Dam safety and health monitoring are critical to ensuring the long-term reliability of water infrastructure, given the complex behavior of dams and the potentially severe consequences of failure. To evaluate current monitoring approaches, this study employs a structured literature review methodology that includes syste...

A Cognitive Task Framework for Evaluating AI-Assisted S&T Planning: Evidence from Tibet’s 2021–2026 Project Classification System

Modeling and measuring graduate students’ generative AI literacy: a study based on Marzano’s taxonomy

Background Generative AI is rapidly reshaping graduate students’ academic research practices. Existing research lacks both literacy models specific to graduate students and a unifying theoretical framework to explain each dimension’s functional role and interrelationships, constraining its cultivation and evaluation. M...

Generative AI for NSF Grant Prewriting: Zero-Shot Protocol Prompting for Tactical Competitive Intelligence

Libraries are increasingly positioned to support faculty grant development, yet proposal-prewriting assistance remains uneven across institutions, particularly where research-development infrastructure is limited. This article presents a practical generative AI workflow for transforming publicly available National Scie...

AI-Assisted Risk and Incident Analysis: Advances and Future Opportunities

Operational risk and security incidents now unfold across distributed, cloud-native estates that generate volumes of telemetry no human team can manually triage at speed. Over the past decade, artificial intelligence (AI) and machine learning (ML) have moved from experimental log-mining prototypes to production compone...

A Depth Psychology Stance on Consciousness and the Unconscious

This chapter demonstrates how the foundational depth psychology theorists—C.G. Jung, Marie-Lousie von Franz, James Hillman, and Marion Woodman—have shared work concerning the modern West&s;s struggle from pressures on consciousness. The four theorists’ s work in this chapter introduces key concepts for evolving conscio...

A drift-aware explainable artificial intelligence framework for dynamic construction risk governance using multi-domain fuzzy inference and Bayesian updating

An integrated DXAI framework that combines fuzzy inference, Bayesian updating, temporal risk drift analysis and explainable governance support for dynamic construction risk management is introduced.

The Application of AI-Based Technology and Psychological Contract in Improving Employee Performance in the Hotel Industry

The findings extend hospitality research by integrating technological and psychological perspectives within a single model and indicate that AI utilization and PC fulfillment are associated with employee performance both directly and through innovative work behavior.

Deterministic and stochastic interventions in reducing drug–drug interactions in inappropriate prescribing: A systematic review

Current evidence does not demonstrate a proportional improvement in clinically reliable decision support in stochastic and generative models for DDI detection, and future interventions must prioritize hybrid architectures that integrate explainable rule-based guardrails with rigorously validated stochastic models.

Collaborating With Artificial Intelligence in Higher Education

This chapter presents a teaching and assessment approach that incorporates generative artificial intelligence (GenAI) into learning while maintaining a focus on students' developing understanding. Drawing on a portfolio-and-interview model implemented in Mathematical Statistics, the approach combines longitudinal portf...