(IJACSA) International Journal of Advanced Computer Science and Applications, A New Algorithm for Data Compression Optimization People tend to store a lot of files inside theirs storage. When the storage nears it limit, they then try to reduce those files size to minimum by using data compression...
AlgorithmFcompressHuffman CodingNGS sequence compressionNGS technologiesHigh throughput sequencingNext-generation high-throughput sequencing technologies have opened up new and challenging research opportunities. In particular, Next-generation sequencers produce a massive amount of short-reads data in a single ...
Functional Quantization-Based Data Compression in Seismic Acquisition The trend in seismic acquisition is geared toward high geophone densities. Future node densities are expected to be on the order of 1M nodes, leading to a ... HUR Khan,SA Zummo - 《Arabian Journal for Science & Engineering》 ...
we explore data compression by processing information locally. The most common technique for saving energy is the use of sleep mode where significant parts of the sensor's transceiver is switched off. In most cases, the radio transceiver on board sensor nodes is the main cause of energy ...
Summary: Pattern discovery is a potential boon for data compression. By identifying generic patterns without human supervision, pattern discovery algorithms can extract the most relevant information for greatest fidelity in lossy compression. However, current approaches to pattern discovery are inefficient an...
Therefore a compression- transmission-decompression strategy is necessary to facilitate real-time transmission. In the sections that follow, we introduce a new compression-decompression algorithm for transmitting sensor data at low bit rates. The algorithm involves the computation and use of pre-...
(That's whole idea behind data compression in the first place.) For the less frequent long symbols, there will be two lookups. If you had a compression method with really long symbols, you could have as many levels of lookups as is efficient. For inflate, two is enough. So a table ...
The case for Small Data compression Previous charts provide results applicable to typical file and stream scenarios (several MB). Small data comes with different perspectives. The smaller the amount of data to compress, the more difficult it is to compress. This problem is common to all compressi...
Data compression engines and real-time wideband compressor for multi-dimensional data The present invention relates to a real-time wideband compressor for multi-dimensional data. The compressor comprises a plurality of compression engines for simultaneously compressing a plurality of data subsets of a ...
Dimensionality reduction is widely used in the visualization, compression, exploration and classification of data. Yet a generally applicable solution remains unavailable. Here, we report an accurate and broadly applicable data-driven algorithm for dimensionality reduction. The algorithm, which we named ‘...