The velocity dimension of Big Data refers to the need to rapidly process data that arrives continuously as streams of messages or events. Distributed Stream Processing Systems (DSPS) refer to distributed programming and ...

The performance of any deep learning model depends heavily on the quantity and quality of the available training data. The generalization of the trained deep models improves with the availability of a large number of ...

Autonomous marine agents play a pivotal role in diverse ocean applications. These agents serve as indispensable instruments for acquiring crucial environmental information. They are used to explore and monitor harsh ...

Estimating Worst-Case Execution Time (WCET) is paramount for developing Real-Time and Em- bedded systems. The operating system’s scheduler uses the estimated WCET to schedule each task of these systems before the assigned ...

Accurate simulations of turbulent flows are crucial for understanding numerous complex phenomena in engineered systems and natural processes. Notably, under realistic conditions with high Reynolds numbers and complex ...

The growing availability of genome sequences of several species, including humans, has created the opportunity to utilize multiple reference genomes for bioinformatics analyses and improve the accuracy of genome resequencing ...

Cloud workload orchestration plays a pivotal role in optimizing the performance, resource utilization, and cost effectiveness of applications in data centers. As modern businesses and IT operations are migrating their ...

Cloud storage service brought the idea of a global scale storage system available on-demand and accessible from anywhere. Despite the benefits, resiliency remains one of the key issues that hinder the wide adaptation of ...

Statistical methods for estimating integrals are indispensable when the number of dimensions (parameters) become greater than ~ 10, where numerical methods are unviable in general. Well-known statistical methods like ...

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale ...