Browsing Department of Computational and Data Sciences (CDS) by thesis submitted date"2024"
Now showing items 1-11 of 11
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A co-kurtosis tensor based featurization of chemistry for scalable combustion simulations
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 ... -
Data-Driven Approach to Estimate WCET for Real-Time Systems
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 ... -
Efficient and Effective Algorithms for Improving the Robustness of Deep Neural Networks
Deep Neural Networks achieve near-human performance on several benchmark datasets, yet they are not as robust as humans. Their success relies on the proximity of test samples to the distribution of training data, resulting ... -
Fast and Scalable Algorithms for Intelligent Routing of Autonomous Marine Agents
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 ... -
An importance sampling in N Sphere Monte Carlo and its performance analysis for high dimensional integration
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 ... -
Integrating Coarse Semantic Information with Deep Image Representations for Object Localization, Model Generalization and Efficient Training
Coarse semantic features are abstract descriptors capturing broad semantic information in an image, including scene labels, crude contextual relationships between objects in the scene, or even objects described using ... -
Modeling physiological transport at scales: connecting cells to organs
The physiological system is a complex network in which each organ forms a subsystem, and the functional networks in different subsystems communicate to maintain the body’s overall homeostasis. The ability to simultaneously ... -
A scalable asynchronous discontinuous Galerkin method for massively parallel flow simulations
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 ... -
Scalable Video Data Management and Visual Querying System for Autonomous Camera Networks
Video data has been historically known for its unstructured nature, rich semantic content and scalability issues in terms of storage. With advances in computer vision and Deep Neural Net works (DNNs) it is now possible ... -
Sequence Alignment to Cyclic Pangenome Graphs
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 ... -
Structural and functional studies on the hypothetical protein TTHA1873 from Thermus thermophilus
This thesis reports a detailed study on the structural and functional characterization of the hypothetical protein (TTHA1873) from Thermus thermophilus. In this study, both the structure and function of TTHA1873 were ...