相关论文: A Low Cost Distributed Computing Approach to Pulsa…
Workload consolidation, sharing physical resources among multiple workloads, is a promising technique to save cost and energy in cluster computing systems. This paper highlights a few challenges of workload consolidation for Hadoop as one…
A variety of pulsar studies, ranging from high precision astrometry to tests for theories of gravity, require high time resolution data. Few such observations at more than two frequencies below 1 GHz are available. Giant Meterwave Radio…
The problem of unsupervised learning and segmentation of hyperspectral images is a significant challenge in remote sensing. The high dimensionality of hyperspectral data, presence of substantial noise, and overlap of classes all contribute…
Subspace clustering techniques have shown promise in hyperspectral image segmentation. The fundamental assumption in subspace clustering is that the samples belonging to different clusters/segments lie in separable subspaces. What if this…
The Low Frequency Array (LOFAR) radio telescope is an international aperture synthesis radio telescope used to study the Universe at low frequencies. One of the goals of the LOFAR telescope is to conduct deep wide-field surveys. Here we…
Advanced instruments in a variety of scientific domains are collecting massive amounts of data that must be post-processed and organized to support scientific research activities. Astronomers have been pioneers in the use of databases to…
An improved version of the sparse multiway kernel spectral clustering (KSC) is presented in this brief. The original algorithm is derived from weighted kernel principal component (KPCA) analysis formulated within the primal-dual…
Graph clustering is a fundamental computational problem with a number of applications in algorithm design, machine learning, data mining, and analysis of social networks. Over the past decades, researchers have proposed a number of…
Clustering is a fundamental data processing task used for grouping records based on one or more features. In the vertically partitioned setting, data is distributed among entities, with each holding only a subset of those features. A key…
The primary use of technical computing in the oil and gas industries is for seismic imaging of the earth's subsurface, driven by the business need for making well-informed drilling decisions during petroleum exploration and production.…
Recent discoveries of dispersed, non-periodic impulsive radio signals with single-dish radio telescopes have sparked significant interest in exploring the relatively uncharted space of fast transient radio signals. Here we describe V-FASTR,…
The increasing availability of cloud computing services for science has changed the way scientific code can be developed, deployed, and run. Many modern scientific workflows are capable of running on cloud computing resources. Consequently,…
Analyzing large datasets with distributed dataflow systems requires the use of clusters. Public cloud providers offer a large variety and quantity of resources that can be used for such clusters. However, picking the appropriate resources…
In this paper, we propose a novel efficient digital twin (DT) data processing scheme to reduce service latency for multicast short video streaming. Particularly, DT is constructed to emulate and analyze user status for multicast group…
Partitioning a graph into blocks of roughly equal weight while cutting only few edges is a fundamental problem in computer science with numerous practical applications. While shared-memory parallel partitioners have recently matured to…
A new pulsar signal-processing pipeline has been developed for observing pulsars with the Diamond Array Radio Telescope at the Gauribidanur radio observatory. The array consists of 32 off-axis dual-polarised LPDAs, with a nominal gain of 22…
We use a Minimum Spanning Tree algorithm to characterize the spatial distribution of Galactic Far-IR sources and derive their clustering properties. We aim to reveal the spatial imprint of different types of star forming processes, e.g.…
Computer-based scientific experiments are becoming increasingly data-intensive, necessitating the use of High-Performance Computing (HPC) clusters to handle large scientific workflows. These workflows result in complex data and control…
Interactive visualization of embedding projections is a useful technique for understanding data and evaluating machine learning models. Labeling data within these visualizations is critical for interpretation, as labels provide an overview…
We present a deep X-ray selected sample of galaxy clusters which has been created from a serendipitous search in ROSAT-PSPC deep pointed observations at high galactic latitude. This survey, hereafter known as the ROSAT Deep Cluster Survey…