Advances in Industrial Design
https://doi.org/10.1007/978-3-030-51194-4
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https://doi.org/10.1007/978-3-030-51194-4
Dear Authors and Readers,The closing issue of “Zeszyty Teoretyczne Rachunkowości” (ZTR, “The Theoretical Journal of Accounting”) for 2025, vol. 49, number 4, once again provides an engaging and multidimensional review of contemporary resear...
10.5604/01.3001.0055.5421
Abstract Deciphering the directionality of information flow in cortical circuits is essential for understanding brain dynamics, learning, and neuroplasticity after injury. However, current noninvasive methods cannot distinguish bottom-up fr...
10.1038/s41467-026-71506-9
Abstract The supply chain is a dynamic and uncertain system consisting of material, information, and fund flows between different organizations, from the acquisition of the raw materials to the delivery of the finished products to the end c...
10.1007/s40747-022-00780-z
Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are often considered black boxes as they do not provide any explanation about how outputs are derived from inputs or why a decision is taken. There...
https://doi.org/10.1016/j.iswa.2022.200109
Abstract Background It is estimated that 50–70% of patients with rheumatoid arthritis (RA) are non-adherent to their recommended treatment. Non-adherent patients have a higher risk of not reaching an optimal clinical outcome. We explored fa...
10.1186/s13075-018-1732-7
"This book explores relevant and advanced methodological, technological and scientific approaches related to the application of sophisticated exploitation of artificial intelligence in intelligent systems for healthcare management and deliv...
https://doi.org/10.4018/978-1-5225-7071-4
Part 1 Decentralized robotic system. Part 2 Cellular robotics: concept of cellular robotics optimal structure determination analysis of communication amount knowledge allocation network organization automatic docking mechanism future work. ...
https://doi.org/10.1142/2080
https://doi.org/10.1007/978-3-319-70833-1
https://doi.org/10.1007/978-3-319-27146-0
Rapidly-exploring Random Tree (RRT)-based algorithms have become increasingly popular due to their lower computational complexity as compared with other path planning algorithms. The recently presented RRT * motion planning algorithm improv...
10.5772/59763
abstract The United States Army's Future Combat Systems Project, which aims to manufacture a ‘robot army’ to be ready for deployment by 2012, is only the latest and most dramatic example of military interest in the use of artificially intel...
https://doi.org/10.1111/j.1468-5930.2007.00346.x
Peristaltic conveyance can be used for the sorting and transport of delicate and nonrigid objects such as meat or soft fruit. The non‐linearity and stochastic behavior of peristaltic systems make them difficult to control. Optimizing contro...
10.1002/aisy.201900070
Task‐driven design of soft robots requires models that are physically accurate and computationally efficient, while remaining transferable across actuator designs and task scenarios. However, existing modeling approaches typically face a fu...
10.1002/aisy.70406
Tendon transfer surgery is often used to restore hand grasp function following high median-ulnar nerve palsy. This surgery typically reroutes and sutures the tendon of the extensor carpi radialis longus (ECRL) muscle to all four flexor digi...
10.3390/app13095804
https://doi.org/10.1007/978-3-642-31513-8_43
In this work, we present and analyze reported failures of artificially intelligent systems and extrapolate our analysis to future AIs. We suggest that both the frequency and the seriousness of future AI failures will steadily increase. AI S...
https://doi.org/10.48550/arxiv.1610.07997
Machine learning (ML) techniques are increasingly important in cybersecurity, as they can quickly analyse and identify different types of threats from millions of events. In spite of the increasing number of possible applications of ML, suc...
https://doi.org/10.1002/int.23088
Reliable uncertainty quantification is a first step towards building explainable, transparent, and accountable artificial intelligent systems. Recent progress in Bayesian deep learning has made such quantification realizable. In this paper,...
https://doi.org/10.1609/aaai.v33i01.33017322
https://doi.org/10.1007/978-3-642-21004-4_12