Browsing Department of Computational and Data Sciences (CDS) by Title
Now showing items 41-60 of 116
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Enhancing Blockchain Implementations
Blockchain technology elegantly provides a spectrum of desirable semantic properties, including immutability, authenticity, verifiability, and data integrity. In recent years, implementing blockchains on relational database ... -
Epistasis Detection and Phenotype Prediction in GWAS Using Machine Learning Methods
Genome-wide association studies (GWAS) are used to find the association between genetic variants, Single Nucleotide Polymorphisms (SNPs), and phenotypic traits or diseases in a population. The number of GWAS has increased ... -
An error correction algorithm for long-read sequencing
Long-read sequencing technologies have transformed genomics by generating longer and suffi- ciently accurate DNA sequences, offering advantages in analysing highly repetitive and complex regions of a genome. A long-read ... -
Exploring the Inherent Saliency in Visual Data through Convolutional Neural Networks
Saliency plays a key role in various computer vision tasks. Extracting salient regions from images and videos has been a well-established problem in computer vision. Determining salient regions in an image or video has ... -
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 ... -
Feasible Path Prescription for Engineering Systems in a High-Index Constrained Dynamics Framework
Constrained dynamic performance and control models of complex engineering systems can be represented in the form of a Differential Algebraic Equation (DAE) system. The high-index of this DAE system poses computational ... -
Global control of mechanics on Riemannian manifolds, and applications to under-actuated aerial vehicles
We consider the problem of designing trajectory tracking feedback control laws for La- grangian mechanical systems in a Riemannian geometric framework. Classical nonlinear control techniques that rely on Euclidean ... -
A Hierarchical Control Plane Framework for Integrated SDN-SFC Management in Multi-tenant Cloud Datacenters
Cloud data centers represent one of the most complex and dynamic environments in terms of network management. The multitude of hosted applications in such centers share the same fabric and yet demand easy and fast service ... -
Higher order discrete dipole approximations for solution of light scattering problems
Abstract not available -
Image Representation using Attribute-Graphs
(2017-12-13)In a digital world of Flickr, Picasa and Google Images, developing a semantic image represen-tation has become a vital problem. Image processing and computer vision researchers to date, have used several di erent representations ... -
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 ... -
Improving Data Center Utilisation by Reducing Fragmentation
Virtualization enables better server consolidation and utilisation compared to stand-alone servers running a single workload. This enabled wide-spread cloud adoption among many organizations. Data center utilisation is ... -
Improving hp-Variational Physics-Informed Neural Networks: A Tensor-driven Framework for Complex Geometries, and Singularly Perturbed and Fluid Flow Problems
Scientific machine learning (SciML) combines traditional computational science and physical modeling with data-driven deep learning techniques to solve complex problems. It generally involves incorporating physical ... -
Improving photoacoustic imaging with model compensating and deep learning methods
Photoacoustic imaging is a hybrid biomedical imaging technique combining optical ab- sorption contrast with ultrasonic resolution. It is a non-invasive technique that is scalable to reveal structural, functional, and ... -
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 ... -
Intelligent Methods for Cloud Workload Orchestration in Data Centers
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 ... -
Intelligent Orchestration of Autonomous Systems Across Edge-Cloud Continuum
The benefits of autonomous mobile platforms, such as Unmanned Aerial Vehicles (UAVs) equipped with onboard cameras, are enhanced by compact edge accelerators that are co-located, such as the NVIDIA Jetson with 100s of CUDA ... -
INTERPIN: identifying INtrinsic transcription TERminators, hairPINs in bacteria
The conversion of DNA to RNA through transcription is an important step in the life cycle of every organism. It ensures that the genetic information in DNA is converted through RNA into instructions/blueprints for the ... -
Investigation of the Indian Summer Monsoon Rainfall Using Statistical and Machine Learning Techniques
The Indian Summer Monsoon is an important atmospheric phenomenon, marked by a characteristic seasonal wind reversal pattern, delivering 70 to 90% of the annual rainfall to the Indian subcontinent. Monsoon rain profoundly ...