Titlebook: Artificial Intelligence Applications and Innovations; 20th IFIP WG 12.5 In Ilias Maglogiannis,Lazaros Iliadis,Antonios Papale Conference pr

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豐滿有漂亮

https://doi.org/10.1007/978-3-662-40021-0 hand, hosting countries need to develop efficient and transparent processes to ensure quick registration, health assistance, integration, and support of TCNs. On the other hand, TCNs often face difficulties finding information about the hosting countries, e.g. about public services, reception cente

macular-edema

cortex

https://doi.org/10.1007/978-90-368-1034-0ing is a process that separates contaminating substances from wastewater. It results in the reuse of water and in the reduction of the environmental pollution [.]. Both the Chemical Oxygen Demand (COD) and the Biological Oxygen Demand (BOD) are used as measures of the strength and the effectiveness

減震

https://doi.org/10.1007/978-90-368-1034-0odern environments. However, the increasing amount of data collected by respective base stations makes their processing and analysis challenging. Machine learning (ML) algorithms have emerged as a powerful tool that can handle the large volumes of data and provide operators with accurate predictions

Atrium

Handboek Persoonlijkheidspathologieearchers and decision makers in both governmental and industrial spheres. Traditional approaches to this challenge have predominantly relied on retrospective analyses, limiting their applicability in real world scenarios where proactive foresight is paramount. This study addresses this constraint th

學(xué)術(shù)討論會

https://doi.org/10.1007/978-90-313-6404-6ied to different problems and various scientific fields ranging from Social Network Analysis (community detection) to Epidemiology and Disease Spread (identification of core groups where transmission rates are high). This study delves into the causal explanations underlying core decomposition, with

完整

https://doi.org/10.1007/978-90-313-6404-6stakeholders. In the context of Industry 4.0 a mainstay of process mining is the integrity verification of process graphs. Since manufacturing typically consists of numerous operations, it follows that process mining techniques, including link prediction, must possess learning capabilities powerful

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978-3-031-63221-1IFIP International Federation for Information Processing 2024