explainable ai

Beyond DNA: An Explainable AI-Driven Multimodal Framework for Long-Term Missing Person Identification: A Systematic Review and Conceptual Model

Predicting Fines Migration Threshold in Sandstone Reservoir: A Machine Learning Framework for Predicting Critical Salt Concentration

Fines migration is a well-documented phenomenon in sandstones, which impairs permeability and causes productivity and injectivity issues. Critical salt concentration (CSC) defines the lowest brine salinity below which fines detach from sand surface due to increased repulsive forces between fines and sand. While prior...

Modeling artificial intelligence readiness and semiotic override in Indonesian geometry education

Findings show that hardware exposure alone is insufficient for AI-oriented learning transformation, andometry teachers should diagnose symbolic overreliance and strengthen visualization-based scaffolding, while school leaders and policymakers should balance infrastructure procurement with adaptive pedagogy, teacher sup...

ACI 318-25 Concrete Beam Checking Assistant - A Claude AI Skill for Structural Engineering Code Compliance (Version 3.0, Imperial Units)

The ACI 318-25 Concrete Beam Checking Assistant is a reusable Claude AI Skill for checking reinforced concrete beam designs per ACI 318-25 and gravity loads per ASCE 7-22, using US customary (imperial) units exclusively. The skill performs 10 sequential code checks, cites the specific ACI 318-25 section governing every...

The Four Planck Quantities Are Four Instances of One Rule ── 3rd ed.: in the Yamagishi Complete Planck Unit Unpacking Theory, the mass dimension fixes the power of 4π, and l_p/t_p=c holds in every unit system ── [Paper 40]

The Four Planck Quantities Are Four Instances of One Rule: Mass Dimension Fixes the Power of 4pi, and l_p/t_p = c Holds in Every Unit System. Third edition. This paper carried a table showing that under the Yamagishi patch G = 4pi, hbar = 1/(4pi) the four Planck quantities read l_p = c^(-3/2), t_p = c^(-5/2), m_p = sqr...

From Boundary Energy to Volume Energy ── The Einstein–Yamagishi Volume Restoration Equation and the Overclock Pythagoras Equation ── [Paper 12]

What sits at the centre of this paper is not a computation but a re-reading. Substituting the geometric mass parameter m=4π obtained from the n=2 uniqueness theorem into Einstein's relation gives E = mc² = 4π c², and the right-hand side has the same form as the surface area of a sphere of radius c. Read in this form, E...

Toward trustworthy and explainable AI-driven industrial fault diagnosis: A data-to-deployment review

Explainable AI in Automated Financial Reconciliation: A Survey-Based Analysis Across Multi-Location Enterprises

Respondents perceive explainability as a meaningful contributor to reconciliation quality, financial control, and decision support, though cross-location consistency and the clarity of AI-generated explanations remain comparatively weaker areas that warrant targeted investment.

A Study of Explainable AI In Smart Agriculture

Grounding Radiological AI Ethics: Practice-Centered Ethical Guidelines from a Multi-Stakeholder Perspective

This paper presents an empirically grounded study in radiology in Germany, conducted in collaboration with multiple stakeholders, such as ethicists, AI developers, clinicians, and HCI researchers via an ethical, legal, and social implications (ELSI) workshop and in-depth interviews, and proposes ten practice-centered e...

The φ-Selection Conjecture: A Dynamical Selection Principle for Stationary-Action Configurations

VERSION 2 (2026-09-26) — what changed since v1, reported honestly: P1 HAS RUN, AND F1 FIRED. The φ-selection conjecture is FALSIFIED in its tested form. In the two-harmonic standard map (a=0.5), φ⁻¹ ranked 8 of 17 rotation numbers by KAM-breakup threshold (Kc=0.3700); the winner was a near-rational, R1=[0;5,1,1,1,…], a...

AI Governance Assessment Workbook

What is an AI governance assessment workbook? An AI governance assessment workbook is a working document that asks how a system is built, who owns it, what data it touches and how its actions are reviewed. Paloren provides AI governance as part of its broader AI strategy, implementation, automation and training practic...