explainable ai

Adoption of Digitalization in Construction Safety: A TCCM-based Literature Synthesis and Development of the DSRAO Framework

Digitalization has been increasingly portrayed as a game-changing approach to enhancing construction safety through the adoption of technologies like Building Information Modelling (BIM), sensors, Artificial Intelligence (AI), and data analytics-based safety tools. While research interest and adoption of digital safety...

AI-Driven Data Governance: Intelligent Metadata, Lineage, and Compliance Automation in Cloud Data Platforms

This research examines how artificial intelligence and machine learning can automate and improve data governance across cloud data platforms. It focuses on intelligent metadata management, automated data lineage tracking, and continuous regulatory compliance monitoring. The proposed framework integrates machine learnin...

Number Behaviorism and the Number Periodic Table in Mathematics Education

We propose a new approach to mathematics education in which the objective is to understand the structural reasons behind number properties. We call this approach Number Behaviorism (NB) and present it as an additional teaching tool that can help mathematics reach more learners. Its starting point is an invitation: obse...

Neither substitutable for the other: non-commensurable contributions in human-machine collaboration

AI-assisted science increasingly asks who contributed what, and answers with a share: the machine did eighty percent, so the human did twenty. We argue that the shared scale is the problem. Under an observation protocol the state of the world is not a point but an equivalence class, and work on it divides into two oper...

Replication Materials for: "Explainable Machine Learning for SDG 3: Nonlinear Patterns, Domain Specificity, and Information Structures Across OECD Health Outcomes"

Description: This repository contains the complete empirical replication pipeline for the research paper titled “Explainable Machine Learning for SDG 3: Nonlinear Patterns, Domain Specificity, and Information Structures Across OECD Health Outcomes”. The study investigates the predictive performance and explainable driv...

Explainable AI for Multi-Disease Prediction in Poultry

Yes, ChatGPT (and other models) need a psychiatrist: parallels between experimental neuropsychiatry and AI alignment science

AI chatbots (such as ChatGPT or Claude) sometimes state false information with confidence, a behavior popularly termed “hallucination.” In their recent perspective, de Boer et al. [1] compared these errors to confabulation in patients with memory disorders, and asked whether ChatGPT needs a psychiatrist. I argue that i...

Smart Manufacturing and Industry 4.0 Explained: IoT, AI, Automation and Smart Factories

Context & Educational Focus: This open educational resource delivers a comprehensive, mathematically rigorous treatment of Smart Manufacturing and Industry 4.0 within modern production engineering. Formulated in alignment with the Washington Accord, EUR-ACE, and IEA global frameworks, the curriculum examines how physic...

Protocol of the Laboratory of Meanings, Borodin O.A. (Mirny) 10.10.2026

The Journal entry records the protocol of events at the Laboratory of Meanings, which documents the planned work and its results: He revised the role of gravity — not as a fundamental force, but as a derivative of induction. He explained the flat rotation curves of galaxies without dark matter — through coercive vacuum...

Evaluating the performance of long short-term memory to other time series models for univariate and multivariate data

Abstract Time series data analysis is one of the difficult tasks in real-world data problems because the data entities are determined not only by physical causes, but also by the chronological sequence in which they occurred. In this work, we have examined how Long Short-Term Memory (LSTM) model is perform well to trad...

On a Problem of Ferrand and Stoimenow Answered in Print by Rutherford and Ito: A Sharper Signature Bound for the HOMFLY Polynomial of Alternating Links, and a Short Proof that Quasipositive Alternating Links Are Positive

Problem 1.16 of Ohtsuki's list (E. Ferrand, A. Stoimenow) asks whether every alternating link L satisfies σ(L) ≥ min deg_l P_L ≥ min deg_a F_L(a^-1, z), where σ is the signature, P_L(l, m) the HOMFLY polynomial and F_L(a, z) the Kauffman polynomial. Both inequalities are in print: the second is a corollary of Rutherfor...

THE ROLE OF DIGITAL TECHNOLOGIES IN ENSURING RAILWAY TRANSPORT SAFETY

The rapid integration of digital technologies—encompassing Artificial Intelligence (AI), Digital Twins (DT), and the Internet of Things (IoT)-is fundamentally transforming railway transport safety. This paper presents a critical scientific literature review of recent peer-reviewed advancements in digital railway safety...