Vol. 1 No. 1 (2026)

Published April 18, 2026
Regular Issue 2026 01 01

Welcome to the inaugural issue of Industrial Robotics and Mechanical Systems Quarterly (IRMSQ).

As the global manufacturing landscape transitions deeper into the Industry 4.0 era, this premiere volume establishes IRMSQ as a rigorous, open-access forum for the most advanced research in mechanical engineering and smart automation.

In this issue, our contributing authors present cutting-edge investigations spanning multi-axis robotic kinematics, human-robot collaboration paradigms, and AI-driven mechanical control systems. These peer-reviewed articles bridge the critical gap between foundational mechanical theories and deployable industrial architectures.

We extend our deepest gratitude to our Editorial Board, rigorous peer reviewers, and pioneering authors for their dedication to launching this European-based initiative. Together, we are forging the future of intelligent mechanical systems.

— The Editorial Team, Call Press Scholarly Group

Articles

Sam Pinkman (Author)
Explainable AI and Agentic Human-AI Teaming for Autonomous Manufacturing Systems: XAI Methods, AR-Enhanced Operator Collaboration, and Multi-Agent Production Orchestration
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Amelia Hughes (Author)
Ensemble Methods and Model Diversity for Robust Stock Prediction: Combining Graph-Based State Space Models Through Bayesian Model Averaging and Stacking
Nicholas Ward (Author)
The Economics of Artificial Intelligence Trust: Calibration as Public Good, Auditing as Market Failure, and the Governance of AI as a Credence Good
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Bao Tang (Author)
Self-Supervised Learning for Industrial Visual Anomaly Detection: A Review of Recent Advances, Applications, and Open Challenges
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Grace Mitchell (Author)
HeMoG: Heterogeneous Multi-Modal Graph Learning with Hierarchical Contrastive Loss for Stock Movement Prediction
Tang Bao (Author)
Artificial Intelligence as Organizational Agent: Legal Standing, Accountability Gaps, and the Governance of Algorithmic Decision-Making Authority
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Klain Aaron (Author)
Intelligent Sensing and Data Analytics in Modern Industrial Systems: A Review of Deep Learning, Causal Inference, and Human-Machine Collaboration
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Hannah Cooper (Author)
CausalKG: Causal Knowledge Graph Construction and Counterfactual Reasoning for Stock Movement Prediction
Olivia Taylor (Author)
Cross-Modal Learning and Alternative Data Integration for Stock Prediction: Fusing Text, News, and Satellite Imagery with Graph-Based Market Models
Loius Nuudle (Author)
Generative Artificial Intelligence for Industrial Design and Manufacturing: Generative Design, Synthetic Data Generation, and Diffusion-Based Optimization
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Lily Anderson (Author)
FinRAG-LM: Retrieval-Augmented Large Language Models with Market Sentiment Grounding for Stock Movement Prediction
Emma Collins (Author)
Continuous Learning and Online Adaptation for Non-Stationary Stock Markets: Addressing Concept Drift in Graph-Based State Space Models
Loius Nuudle (Author)
Federated Learning and Privacy-Preserving AI for Smart Manufacturing and Industrial IoT: Frameworks, Architectures, and Industrial Applications
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Charlotte Evans (Author)
Adversarial Robustness and Stress Testing for Stock Prediction: Defending Graph-Based Models Against Market Manipulations and Extreme Events