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Benchmarking and Scheduling Strategies for Distributed Stream Processing
(2018-08-20)
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 ...
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 ...
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 ...
Coarse-grained dynamics derived structural ensemble for prediction of metal binding sites of protein and phenotypic effects of variants
Structures of proteins play a key role in determining their functions. Knowledge of structure,
especially the details of specific sites of a protein can help us understand their contribution to
the overall activity. ...
Learning Across Domains: Applications to Text-based Person Search and Multi-Source Domain Adaptation
With rapid development in technology and ubiquitous presence of diverse types of sensors, a large
amount of data from different modalities (e.g., text, audio, images etc.) describing the same person/
object/event has ...
An Accelerator for Machine Learning Based Classifiers
Artificial Neural Networks (ANNs) are algorithmic techniques that simulate biological neural systems. Typical realization of ANNs are software solutions using High Level Languages (HLLs) such as C, C++, etc. Such solutions ...
Numerical Analysis of Some Preconditioners and Associated Error Estimators for Solving Linear Systems
Convergence of iterative algorithms in solving large linear systems is largely affected by the condition number of the matrix. Preconditioners reduce the condition number of the system matrix, thereby letting the linear ...
Vector Extrapolation and Guided Filtering Methods for Improving Photoacoustic and Microscopic Images
Photoacoustic imaging is a noninvasive imaging modality which combines the bene ts
of optical contrast and ultrasonic resolution. It is applied widely for monitoring tissue
health conditions in the elds of cardiology, ...
A Numerical Method for Modeling Light Scattering from Spherical Particles with a Probability Density in the Parametric Space
With modern computational tools, modeling light scattering from a particle with known physical parameters has become relatively trivial.
Evaluation using analytical solutions is highly eficient compared to a full ...
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 ...