Sunhwa Annie Nam¹, Kyungwoon Cho², Hyokyung Bahn^3,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6823-6833, 2023, DOI:10.32604/cmc.2023.035481

Abstract AI (Artificial Intelligence) workloads are proliferating in modern real-time systems. As the tasks of AI workloads fluctuate over time, resource planning policies used for traditional fixed real-time tasks should be re-examined. In particular, it is difficult to immediately handle changes in real-time tasks without violating the deadline constraints. To cope with this situation, this paper analyzes the task situations of AI workloads and finds the following two observations. First, resource planning for AI workloads is a complicated search problem that requires much time for optimization. Second, although the task set of an AI workload may change over time, the possible… More >

Surbhi Bhatia^*, Mohammed Alojail

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1261-1271, 2022, DOI:10.32604/iasc.2022.023501

Abstract The last decade has seen a rapid increase in big data, which has led to a need for more tools that can help organizations in their data management and decision making. Business intelligence tools have removed many of the obstacles to data visibility, and numerous data mining technologies are playing an essential role in this visibility. However, the increase in big data has also led to an increase in ‘dark data’, data that does not have any predefined structure and is not generated intentionally. In this paper, we show how dark data can be mined for practical purposes and utilized… More >