explainable ai

The Privacy–Support Paradox of AI-Based Employee Stress Management: The Role of Perceived Surveillance, Explainability, Trust, and Employee

Abstract New organizational ATPs are adopting artificial intelligence (AI) across various tools to detect and mitigate employee stress – sentiment analysis, facial-emotion analytics, wearable biosensors, and AI-powered counselling via chatbots. While the technology behind these systems should make effective support for...

Works for 9/19/2026 - Most Reverend Daniel Patrick Reilly

Listen and ask questions on Gemini Notebook: https://notebook.google.com/notebook/24794a74-bf93-42c1-a04e-fdb17d1f50c0?authuser=1 Good Soil Cannot Hold the Seed Yet: Mary Magdalene, Christ the New Adam, and the Father’s House offers a Catholic typological reading of Mary Magdalene’s encounter with the risen Christ in J...

Applications of AI and Computational Biology in Horticultural Science

Horticulture, a critical sector of global agriculture, faces mounting challenges from climate change, resource scarcity, and the increasing demand for sustainable food production. Traditional methods, particularly in phenotyping and breeding, have become a bottleneck for progress. This chapter explores the transformati...

Application of Convolutional Neural Network in Plant Research

Convolutional neural networks (CNNs) are a category of deep learning models engineered to acquire spatial and spectral hierarchies from image input autonomously, rendering them highly effective for visual analysis. They have transformed plant and forest sciences by facilitating automated, accurate, and scalable picture...

Practical Guidance for the Installation and Operation of the CubeTechnology System with Artificial Intelligence Support from ChatGPT

This practical guidance presents a procedure for installing and operating the CubeTechnology system in which artificial intelligence is used as a continuous assistant to the user at all stages of working with the system. The main distinguishing feature of the proposed approach is that the user provides ChatGPT, or anot...

Applying explainable AI to analyze size-sorted ESG portfolios

This research utilizes explainable artificial intelligence (XAI) techniques to explore the relationship between size-sorted environmental, social, and governance (ESG) portfolio indices (large-cap, mid-cap, and small-cap ESG portfolios) and their corresponding base indices (large-cap, mid-cap, and small-cap portfolios)...

Artificial Intelligence and Machine Learning for Crop Disease Detection: A Systematic Review and Research Agenda

Crop diseases constrain global agricultural productivity and food security, particularly for smallholder farmers who lack timely, affordable diagnostic tools. Artificial intelligence and machine learning have transformed automated crop disease detection, but much reported performance rests on controlled laboratory data...

Calibrated Residual Tube Projection During Conditional Diffusion Sampling for Thermal Time Series — Code and Experimental Evidence

Code and experimental evidence supporting Calibrated Residual Tube Projection During Conditional Diffusion Sampling for Thermal Time Series, by Hyojin Park and Jinhong Yang (corresponding author). The release contains the selected B6 checkpoint, original method implementations, exact simulator and score settings, froze...

MalXGraph-ViT: A Hybrid Transformer-graph Neural Network Framework with Explainable AI for Robust Malware Detection and Classification on Emerging Public Benchmarks

The exponential growth of malware variants, propelled by automated obfuscation, polymorphism, and AIassisted code generation, has rendered signature-based and heuristic detection ineffective.This paper proposes MalXGraph-ViT, a multi-stage framework integrating grayscale visual feature extraction, Global Context Vision...

Artificial intelligence and Machine learning in pharmacy and pharmaceutical technology

Artificial intelligence (AI) and Machine learning (ML) are transforming the pharmaceutical lifecycle—from target identification and lead optimization to clinical development, manufacturing, supply chain orchestration, and real-world pharmacovigilance. This review synthesizes recent advances (2018–2025) across core meth...

AI Models for Advancing Plant Tissue Culture and Bioreactors

Artificial intelligence (AI) is altering plant biotechnology by solving significant problems in tissue culture and bioreactor systems, including variability, man-power intensity, and poor reproducibility. Machine learning (ML) algorithms and artificial neural networks (ANNs) have opened the capability of simulating com...

AI ANXIETY TO AI AGENCY: EXPLAINING EMPLOYEE ADAPTATION TO GENERATIVE AI IN PAKISTANI ORGANIZATIONS