explainable ai

Zone-Wise Wildlife Detection and Population Analysis Using Computer Vision

Wildlife monitoring is essential for biodiversity conservation, ecological research, habitat management, and protection of endangered species. Traditional wildlife population monitoring methods often require extensive fieldwork, manual observation, and expert analysis, making them time-consuming and difficult to scale...

Identifying and explaining effective indicators in choosing financial software packages: English research companion to the 2023 Persian article

English research companion to the Persian article by Ghodratpanah, Malekian, and Kamyabi (2023), Financial Economics, 17(2), 25–48. It presents the study framework, Delphi method, and reported selection criteria for international readers. The original study assessed 48 criteria in two Delphi rounds with ten experts in...

Gaps Below n in Multiset Resolving Spectra

A set S of vertices of a connected graph is multiset resolving if every vertex has a distinct multiset of distances to S. We study graphs whose identification spectrum (the set of sizes of multiset resolving sets) contains the order n but skips the sizes just below it, and define the top gap g(G) as n minus the largest...

Replication code for "When software evaluates: Performance evaluation and the AI wage premium in the UK, with comparative evidence from the EU"

Python code and frozen result files reproducing all tables, figures and supplementary tables of the article "When software evaluates: Performance evaluation and the AI wage premium in the UK, with comparative evidence from the EU" (submitted to PLOS ONE). The analysis uses the UK Skills and Employment Survey 2024 (UK D...

Infrastructure for Effective Human Oversight of Distributed AI Agents

This paper proposes how institutions could preserve effective human oversight as AI agents increasingly help build, test and operate more capable AI systems. The architecture aims to connect independent observation, bounded delegation, challengeable safety conditions and intervention enforced at the resources where con...

Explainable Machine Learning-Based Diabetes Prediction Using Clinical Features: A Comparative Evaluation of Ensemble and Boosting Algorithms A Comparative Study with Explainable Artificial Intelligence Analysis

Works for 10/10/2026 - Thomas James Davis

Listen and ask questions with Gemini Notebook: https://notebook.google.com/notebook/c0a1c2f5-a68b-48f5-9cd6-81734c9ed863?authuser=1 Rabboni! How to Learn Like a God — The Father, the Holy Spirit, and Jesus Christ — Agape, Relational Learning, the Garden, and the Joy of Seeing the Work of Others What does it mean to lea...

Humarticosynergy: A New Word for Cognitive Human–AI Synergy

This essay introduces humarticosynergy as a concise term for the previously developed concept of Cognitive Human–AI Synergy. The proposed word combines elements referring to the human, artificial intelligence, cognition, and synergy. The essay explains its formation, defines the concept it denotes, and outlines possibl...

GROWING OYSTER MUSHROOMS: A STARTER GUIDE FOR FIRST-TIME GROWERS

A short, free introductory guide to growing oyster mushrooms (Pleurotus spp.) for first-time and small-scale growers.The guide teaches the shape of the craft rather than a recipe: what the oyster mushroom is and why it is a forgiving first crop; the two phases of cultivation — colonisation and fruiting — that organise...

Who Verifies the Verifiers? AI, Local Knowledge Production, and Credibility in Tanzania’s 2025 Election

This study examines how Factchecking AI tools and community-based credibility practices interacted during Tanzania’s 2025 presidential election. Using data from five regions, we analyzed 342 media materials, 87 interviews, field observations, and 22 distinct contested election events. The findings identify three forms...

An Efficient and Privacy-Preserving Framework for Edge AI Using Federated Learning and Homomorphic Encryption

Edge Artificial Intelligence (Edge AI) supports intelligent processing close to where data is generated. However, training machine-learning models across edge devices is difficult when devices have limited memory, processing power, battery capacity, and network bandwidth. Federated learning (FL) addresses one important...

Artificial Intelligence in Education: Impact on Human Skills, Critical Thinking, Independent Learning, and Academic Performance Subtitle: Balancing Technological Innovation with Independent Thinking and Genuine Learning

Alternative Titles The Impact of Generative Artificial Intelligence on Human Cognitive Skills and Educational Outcomes Artificial Intelligence and the Future of Human Learning: Does Technological Assistance Undermine Independent Thinking? Generative AI in Education: Examining the Relationship Between AI Dependence, Cri...