… In the public sector, data-driven HRM is a strategic process that aims to improve HR
decisions and policies throughout the government by collecting, measuring, and using HR data, …

… Lately, advanced data driven ML modeling techniques like … to handle multi-modal, multi-application
data, the latest AI … -based simulation models as the environment and a RL agent. …

… procedures, and eventually advancing data-driven, individualized healthcare practices for
… the ways that predictive models make decisions. In our work, it use model-agnostic methods, …

… Thirdly, for ML-based multi-application materials design with … physical laws, whereas the
data-driven twin is trained using … provide much needed solutions for pressing climate concerns. …

… Moreover, an additional problem arising in data-driven contexts is the difficult provision of
the right … use case of Prognostic and Health Management inside an Industry 4.0 environment, …

… as edge IoT-assisted AR, multi-application context sharing, and multi-time context sharing. …
context data model? Environment understanding is fundamentally a datadriven process, and …

… To meet the challenges associated with data-driven application-specific requirements, the …
This work addresses the problem of data collection in an indoor monitoring environment while …

… -core system design using data-driven ML techniques, while … 1) Environment (Architecture):
The environment of the NoC … We also simulate complex multi-application domain systems …

… The study offers an organized and comprehensive overview of multi-application domain …
model-based or data-driven. Model-based fault diagnosis methods utilize a mathematical …

… are also able to support multi-application networks. In such way… control of SDN in harsh ocean
environments, we propose a semi… intelligence (AI) and data-driven tools, such as machine …