Ontology-Driven Data Cleaning Towards Lossless Data Compression
, 2022 With the available data in healthcare, healthcare organizations and practitioners require interoperable, efficient, and non-time-consuming data exchange. Currently, several cases aim to the exchanged data security, without considering the complexity of the data to be exchanged.
Kiourtis, Athanasios +3 more
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On Predictive-Based Lossless Compression of Images with Higher Bit Depths [PDF]
Telfor Journal, 2012 Due to the rapidly increasing requirements for data transmission and storage, applications for fast and efficient compression of data have a very important role. Lossless compression must be applied when data acquisition is expensive.
A. Avramović, G. Banjac
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A Review of Classical Lossless Data Compression Algorithmsand Their Contemporary Relevance [PDF]
Biuletyn Wojskowej Akademii TechnicznejCompression is data processing aimed at reducing the amount of information (e.g., for archiving and transfer). There is lossyand lossless compression. Compression algorithms can be either general-purpose or designed for specific types of data (e.g., for ...
Dominik Maciej Matusiak
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Stream-Based Visually Lossless Data Compression Applying Variable Bit-Length ADPCM Encoding
Sensors, 2021 Video applications have become one of the major services in the engineering field, which are implemented by server–client systems connected via the Internet, broadcasting services for mobile devices such as smartphones and surveillance cameras for ...
Shinichi Yamagiwa, Yuma Ichinomiya
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Lossless Compression Using the Ramanujan Sums: Application to Hologram Compression
IEEE Access, 2020 The Ramanujan sum, introduced by S. Ramanujan, has been utilized-among other applications-for signal processing. It has recently been suggested that transforms using the Ramanujan sums may also provide the benefit of data compression. This study presents
Harutaka Shiomi +3 more
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The compression–error trade-off for large gridded data sets [PDF]
Geoscientific Model Development, 2017 The netCDF-4 format is widely used for large gridded scientific data sets and includes several compression methods: lossy linear scaling and the non-lossy deflate and shuffle algorithms.
J. D. Silver, C. S. Zender
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A New Perspective on Improving the Lossless Compression Efficiency for Initially Acquired Images
IEEE Access, 2019 A new lossless compression scheme of compressing the initially-acquired continuous-intensity images with a lossy compression algorithm to obtain higher compression efficiency is proposed. Even if a lossy algorithm is employed, for decoded original images,
Jianyu Lin
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Dynamic Visual Communication Image Framing of Graphic Design in a Virtual Reality Environment
IEEE Access, 2020 This paper explores dynamic visual communication image framing for graphic design based on virtual reality algorithms; it defines corresponding feature representations by delineating layers of pixels, elements, relationships, planes, and applications ...
Zhiyong Tian
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Planar model system and heterogeneous catalysis [PDF]
, 2012 Vehicles with sensors produce large amounts of data. Transmission of data is connectedwith costs. By using data compression, less data has to be transmitted, reducing priceof operation.
Berkó, András +2 more
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Stream-Based Lossless Data Compression [PDF]
, 2021 AbstractIn this chapter, we introduce aspects of applying data-compression techniques. First, we study the background of recent communication data paths. The focus of this chapter is a fast lossless data-compression mechanism that handles data streams completely.
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