Indexing the Future of Cognition & Machine Intelligence

Cyber Defense Digital Twins: A Federated Learning and Zero-Trust AI Architecture for Autonomous Threat Prediction and Response

Sivaramakrishnan Narayanan

Modern enterprise networks operate under persistent threats that exploit cloud-native misconfigurations, identity sprawl, and API vulnerabilities at machine speed. Existing security operations center (SOC) architectures remain largely reactive, signature-dependent, and incapable…

Vision-based human–robot collaboration for wire harness assembly in automotive manufacturing

Hao Wang, Omkar Salunkhe, Annalena Hartmann, Sven Ekered, Patrick Bründl, Jörg Franke, et al.

Mixed reality and Digital Twins for human–robot training: A comparative study of skill transfer in industrial navigation

Alberto Martínez-Gutiérrez, Iván Sánchez-Calleja, Rubén Ferrero-Guillén, George Arampatzis, Madalena Araujo, Javier Díez-González

A survey of the integration between machine learning and artificial intelligence techniques in software-defined networking

Ariel Łukowski, Grzegorz Papier, Robert Wójcik, Jerzy Domżał

Machine learning for carbon dots: Capabilities, limitations, and the path toward rational design

Shudie Shen, Leilei Zhang, Linquan Gan, Tao Li, Wenli Zhao, Yanfei Wang, et al.

Resilient hierarchical control strategy for digital twin cloud-edge collaboration in multi-energy microgrids under non-ideal communication conditions

Yang Gao, Hongjie Zhu, Zezhen Zhang, Yunqi Wang, Qian Ai, Jianguo Zhu

Process monitoring of thermal crimping systems using sensorisation and Machine Learning

Ioan-Alexandru Herdea, Divya Tiwari, Geraint Jewell, Alexis Lambourne, Michael Farnsworth, Ashutosh Tiwari

Financial development, energy consumption, and environmental degradation: A threshold and causal machine learning approach with explainable AI

Thuy Tu Pham, Hai Yen Nguyen Dang, Anh Thuy Pham

Fully automated pavement crack quantification and PCI estimation via a digital twin-ready vision-based deep learning pipeline

Mohammad Amin Talaghat, Amir Golroo, Vahid Shahhosseini, Mehdi Rasti

A deep reinforcement learning and a dynamic graph neural network-based scheduling agent to control a multi-task robot

Hedi Boukamcha, Anas Neumann, Monia Rekik, Adnene Hajji, Gabriel Caron Guillemette, Mohamed Farah

Machine learning in membrane-based desalination and wastewater treatment: An AI-assisted bibliometric analysis

Azzam Abuhabib, Cao Yuan, Mohd Fadhil Bin Md Din, Ahmed Albahnasavi, Siti Nur Fatihah Binti Moideen, Chen Hong, et al.

Rapid rice seed vigor assessment: A machine learning and deep learning framework with multi-time-point image analysis

Veerasit Kaewbundit, Damrongvudhi Onwimol, Papis Wongchaisuwat

Explainable ensemble machine learning for financial transaction fraud detection: Insights from XGBoost and deep neural networks

Nguyen Duy Anh Luong, Shengkun Xie

Physics-informed Machine Learning for Prognostics and Health Management: Foundations, Advances and Prospects

Danning Sun, Jiangfeng Cheng, Yupeng Wei

AutoSurrogate: An LLM-driven multi-agent framework for autonomous construction of deep learning surrogate models in subsurface flow

Jiale Liu, Nanzhe Wang

A comprehensive analysis of artificial intelligence, machine learning, deep learning and computer vision in food science

Premkumar Borugadda, Hemantha Kumar Kalluri

Understanding the adversary: A survey of adversarial machine learning in network intrusion detection

Allan da S. Espindola, Altair O. Santin, António Casimiro, Pedro M. Ferreira, Eduardo K. Viegas

A survey on machine learning for streaming time series forecasting

L. Melgar-García, A.M. Chacón-Maldonado, G. Asencio-Cortés, A. Troncoso

Measuring the level of circular economy in cities in alignment with sustainable development goal 11: Integration of machine learning algorithms and analytical hierarchical-network processes. A case study in Seville

Nadia Falah, Navid Falah, Madelyn Marrero, Jaime Solis-Guzman

Beyond benchmark accuracy: A generalization-centered analysis of deep learning for skeleton-based human activity recognition

Yi Xia, Sira Yongchareon, Raymond Lutui, Quan Z. Sheng

Bridging soil mapping units and digital soil mapping through probability-driven machine learning: an uncertainty-aware framework for soil class prediction in Antarctica

Rafael G. Siqueira, Cássio M. Moquedace, Márcio R. Francelino, Carlos Ernesto G.R. Schaefer, Roberto F.M. Michel, Daniela Schmitz, et al.

Cross-farm generalisation of machine and deep learning models for lameness prediction in multiparous dairy cows

Katharine Eleanor Lewis, Laura Randall, Luke O’Grady, Martin Green, Al Manning, Andrew Bradley, et al.

Multimodal machine learning in the AEC industry: a lifecycle-aligned review of strategies, challenges, and informatics frameworks

Abdulkadir Hassan Ahmed, Osama Mohsen

Metabolic characteristics of poultry eggs from five species: insights from metabolomics, network analysis, and machine learning

Hongqiang Li, Xiangmin Zhao, Junyang Li, Jing Liang, Xiaoming Li, Fuwei Li, et al.

Think it, Run it: Autonomous machine learning pipeline generation via self-healing multi-agent artificial intelligence

Adela Bâra, Gabriela Dobrița, Simona-Vasilica Oprea

Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications

Ziwei Liu, Hanqing Gu, Liwei Yang, Wencheng Wu, Zhong Huang, Haozhi Wang, et al.

Machine learning and AI-driven digital twins in manufacturing of advanced metal alloys and compounds: A review

Mohsen Soori, Behrooz Arezoo

Digital phenotyping using wearable-determined physical behaviours and machine learning to detect depression and anxiety symptoms in a general population

Alireza Sameh, Laura Nauha, Marjo Seppänen, Maisa Niemelä, Mourad Oussalah, Raija Korpelainen, et al.

Machine learning systems as mentors in human learning: The role of AI output in diagnostic knowledge acquisition

Federico Cabitza, Lucia Vicente

Clustering beyond the binary: Stable machine-learning phenotypes of metabolic syndrome

Jennifer Wilkie, Xu-Feng Huang, Lei Wang, Khin Than Win