AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The paper discusses some of the challenges associated with automated evaluation of employee performance such as opacity of algorithms, discrimination or bias, inaccuracies in the use of data, failure to take context into consideration, over monitoring, accountability issues, and power asymmetry.
An integrated technology framework that connects infrastructure, services, and stakeholders through intelligent systems is presented that enhances energy efficiency, operational performance, and user satisfaction and provides a roadmap for developing scalable, sustainable, and intelligent campus ecosystems.
This study presents a scalable framework that integrates distributed event brokers, stream processing engines, cloud-native microservices, and scalable storage solutions to support real-time decision-making and dynamic scalability for next-generation real-time analytics and big data applications.
The intersection of XAI and IIoT is explored, highlighting the challenges of applying explainable models in real-time, data-intensive industrial contexts and demonstrating the potential of XAI to enhance transparency, user trust, and operational safety in next-generation industrial systems.
The study concludes that intelligent robotic pick-and-sort systems are a key technology for smart factories, supporting flexible manufacturing, mass customization, and sustainable industrial production, with future opportunities in digital twins, explainable AI, cloud-edge intelligence, and collaborative human-robot sy...
This research proposes an Explainable Machine Learning (XML)–based framework to assess software quality by integrating code metrics, defect datasets, and advanced interpretability methods such as SHAP, LIME, and permutation importance.
Experimental results show that AI-driven knowledge graphs significantly enhance decision accuracy, reduce ambiguity, and improve interpretability, achieving up to 85–92% higher decision efficiency compared to traditional methods.
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