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explainable ai

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#explainable ai Open access Oct 2026

When Money Ages: Monetary-System Relevance Decay and Regenerative Value in the Age of Artificial Intelligence

Abstract Money is conventionally understood to depreciate when its purchasing power declines, its exchange value falls, or inflation reduces the quantity of goods and services obtainable from a given monetary unit. This paper proposes an additional and distinct concept: monetary-system relevance decay. Under this hypot...

Theodor-Nicolae Carp · 0 citations
#explainable ai Open access Oct 2026

Double treatise: The Field Theory of Life and The photone universe

This treatise is composed of the author's previously unpublished position papers and material on the vibrational physics:This work formulates a fundamental alternative to classical evolutionary biology and astrophysics by consistently subordinating biological, geological, and cosmological phenomena to the laws of vibra...

Thiele · 0 citations
#explainable ai Open access Oct 2026

The fixed space of the ribbon-to-homogeneous transition matrix of noncommutative symmetric functions: a proof of a conjecture recorded by J. M. Campbell

We prove a conjecture recorded by J. M. Campbell in 2018 in the OEIS entry A001405 (the central binomial coefficients binomial(n, floor(n/2))). Let NSym be the algebra of noncommutative symmetric functions of Gelfand, Krob, Lascoux, Leclerc, Retakh and Thibon, and let C_n(R, H) be the transition matrix from the ribbon...

Roberto Blanco Gómez · 0 citations
#explainable ai Open access Oct 2026

A proof of a conjecture of H. Gruber: finite unary languages by the alphabetic width of their regular expressions

We prove a statement recorded by H. Gruber in 2012 in the OEIS entry A000079 (the powers of 2), verified by him up to n = 17: for n >= 1, the number of distinct finite languages over a one-letter alphabet whose minimum regular expression has alphabetic width n is 2^n. The alphabetic width of a regular expression is the...

Roberto Blanco Gómez · 0 citations
#explainable ai Open access Oct 2026

Efficient deep learning models for early Alzheimer’s disease diagnosis

Alzheimer’s Disease (AD) is a progressive neurological disorder that impairs cognitive functions, severely affecting patients’ quality of life. Thus, early and accurate diagnosis is essential to provide a chance for treatment. This paper proposes two deep learning (DL) models to enable automated diagnosis of medical im...

Sarah Oraby, Ahmed A. Emran, Basel El-Saghir et al. · 0 citations
#explainable ai Open access Oct 2026

Three-Stage Deep Learning Approach for Alzheimer’s and Parkinson’s Disease Detection

The proposed three-stage architecture offers clinicians and radiologists an integrated tool capable of supporting early diagnosis, multimodal cross-verification, and long-term monitoring of neurodegenerative disease progression, potentially reducing diagnostic delay and supporting more personalised treatment planning.

S. K. Mohod, R. Thakare · 0 citations
#explainable ai Open access Oct 2026

Double treatise: The Field Theory of Life and The photone universe

This treatise is composed of the author's previously unpublished position papers and material on the vibrational physics:This work formulates a fundamental alternative to classical evolutionary biology and astrophysics by consistently subordinating biological, geological, and cosmological phenomena to the laws of vibra...

Thiele · 0 citations
#explainable ai Open access Oct 2026

A proof of a conjecture of H. Gruber: finite unary languages by the alphabetic width of their regular expressions

We prove a statement recorded by H. Gruber in 2012 in the OEIS entry A000079 (the powers of 2), verified by him up to n = 17: for n >= 1, the number of distinct finite languages over a one-letter alphabet whose minimum regular expression has alphabetic width n is 2^n. The alphabetic width of a regular expression is the...

Roberto Blanco Gómez · 0 citations
#explainable ai Open access Oct 2026

The fixed space of the ribbon-to-homogeneous transition matrix of noncommutative symmetric functions: a proof of a conjecture recorded by J. M. Campbell

We prove a conjecture recorded by J. M. Campbell in 2018 in the OEIS entry A001405 (the central binomial coefficients binomial(n, floor(n/2))). Let NSym be the algebra of noncommutative symmetric functions of Gelfand, Krob, Lascoux, Leclerc, Retakh and Thibon, and let C_n(R, H) be the transition matrix from the ribbon...

Roberto Blanco Gómez · 0 citations
#federated learning Book Oct 2026

Foundations of Human-Centric AI and Machine Learning for Construction 6.0

The foundations of Human-Centric Artificial Intelligence and Machine Learning as enablers of Construction 6.0, emphasizing the integration of automation, cognitive systems, and human expertise are examined. The chapter outlines how Artificial Intelligence is transforming architecture, engineering, and construction thro...

Ibrahim Yitmen, Amjad Almusaed, Asaad Almssad · 0 citations
#reinforcement learning Open access Oct 2026

A context-aware multimodal multi-agent deep reinforcement learning framework for autonomous personalized education

This paper introduces the Context-Aware Multi-Agent Deep Reinforcement Learning (CA-MA-DRL) framework for personalised digital education, shifting from passive analytics to autonomous decision-making agents. The framework integrates Multimodal Learning Analytics with advanced coordination mechanisms, fusing heterogeneo...

Muddsair Sharif, Huseyin Seker · 0 citations
#reinforcement learning Book Oct 2026

Human-Centric AI-Driven Sustainable and Resilient Design AI for Energy-efficient and Carbon-neutral Buildings

This chapter examines how Human-Centric Artificial Intelligence is transforming sustainable and resilient design in the built environment. With buildings responsible for nearly 40% of global energy use and 30% of greenhouse gas emissions, the chapter underscores the need for energy-efficient and carbon-neutral architec...

Ibrahim Yitmen, Amjad Almusaed, Asaad Almssad · 0 citations

From tech blogs

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MIT News · Artificial Intelligence Oct 23, 2026

Q&A: How AI came to model the “messy” human mind

Assistant Professor Benjamin Lindquist studies how engineers deliberately injected randomness into early AI, giving rise to deep-learning models that sometimes hallucinate.

Microsoft Research Blog Oct 22, 2026

Flint-interactive: A language for creating interactive data visualizations

Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.

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