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Nowadays, massive amounts of point cloud data can be collected thanks to advances in data acquisition and processing technologies like dense image matching and airborne LiDAR (Light Detection and Ranging) scanning. With the increase in volume and precision ...
Industry and academia are continuously becoming more data-driven and data-intensive, relying on the analysis of a wide variety of datasets to gain insights. At the same time, data variety increases continuously across multiple axes. First, data comes in mu ...
We are currently witnessing a shift towards the use of high-level programming languages for systems development. These approaches collide with the traditional wisdom which calls for using low-level languages for building efficient software systems. This sh ...
As data continues to be generated at exponentially growing rates in heterogeneous formats, fast analytics to extract meaningful information is becoming increasingly important. Systems widely use in-memory caching as one of their primary techniques to speed ...
The collection of medical data for research purposes is a challenging and long-lasting process. In an effort to accelerate and facilitate this process we propose a new framework for dynamic aggregation of medical data from distributed sources. We use agent ...
The typical enterprise data architecture consists of several actively updated data sources (e.g., NoSQL systems, data warehouses), and a central data lake such as HDFS, in which all the data is periodically loaded through ETL processes. To simplify query p ...
Cryo electron tomography allows macromolecular complexes within vitrified, intact, thin cells or sections thereof to be visualized, and structural analysis to be performed in situ by averaging over multiple copies of the same molecules. Image processing fo ...
Event-series pattern matching is a major component of large-scale data analytics pipelines enabling a wide range of system diagnostics tasks. A precursor to pattern matching is an expensive ``shuffle the world'' stage wherein data are ordered by time and s ...
Modern industrial, government, and academic organizations are collecting massive amounts of data at an unprecedented scale and pace. The ability to perform timely, predictable and cost-effective analytical processing of such large data sets in order to ext ...
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The constant flux of data and queries alike has been pushing the boundaries of data analysis systems. The increasing size of raw data files has made data loading an expensive operation that delays the data-to-insight time. Hence, recent in-situ query proce ...
