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Relevant bibliographies by topics / File processing (Computer scie

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Journal articles

Academic literature on the topic 'File processing (Computer scie'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 February 2022

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Journal articles on the topic "File processing (Computer scie"

1

Malmrose, Kirk L., and Robert P. Burton. "File processing and the undergraduate computer science curriculum." ACM SIGCSE Bulletin 19, no. 1 (1987): 330–35. http://dx.doi.org/10.1145/31726.31781.

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2

Vetova, Stella. "Big Data Integration and Processing Model." WSEAS TRANSACTIONS ON COMPUTERS 20 (May 12, 2021): 82–87. http://dx.doi.org/10.37394/23205.2021.20.10.

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The presented paper deals with data integration and sorting of Covid-19 data. The data file contains fifteen data fiels and for the design of integration and sorting model each of them is configured in data type, format and field length. For the data integration and sorting model design Talend Open Studio is used. The model concerns the performance of four main tasks: data integration, data sorting, result display, and output in .xls file format. For the sorting process two rules are assigned in accordance with the medical and biomedical requirements, namely to sort report date descending order and the Country Name field in alphabetical one

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3

Ferguson, David E. "Bit-Tree: a data structure for fast file processing." Communications of the ACM 35, no. 6 (1992): 114–20. http://dx.doi.org/10.1145/129888.129896.

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4

Zhou, Min. "Research on Recovery of Computer Data Based on Windows System." Applied Mechanics and Materials 608-609 (October 2014): 603–6. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.603.

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This paper researches the computer data recovery in FAT Windows file system, analyzed the storage format and file data operations (such as formatting, partition and delete), specific to the data processing and the data recovery, summarizes the method of data recovery and commonly used software tools, and gives the specific data recovery examples.

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5

Gao, Lei, Cong Wu, and Lin Liu. "AUSPP: A universal short-read pre-processing package." Journal of Bioinformatics and Computational Biology 17, no. 06 (2019): 1950037. http://dx.doi.org/10.1142/s0219720019500379.

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There are many short-read aligners that can map short reads to a reference genome/sequence, and most of them can directly accept a FASTQ file as the input query file. However, the raw data usually need to be pre-processed. Few software programs specialize in pre-processing raw data generated by a variety of next-generation sequencing (NGS) technologies. Here, we present AUSPP, a Perl script-based pipeline for pre-processing and automatic mapping of NGS short reads. This pipeline encompasses quality control, adaptor trimming, collapsing of reads, structural RNA removal, length selection, read mapping, and normalized wiggle file creation. It facilitates the processing from raw data to genome mapping and is therefore a powerful tool for the steps before meta-analysis. Most importantly, since AUSPP has default processing pipeline settings for many types of NGS data, most of the time, users will simply need to provide the raw data and genome. AUSPP is portable and easy to install, and the source codes are freely available at https://github.com/highlei/AUSPP .

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6

Nakazaki, Keiko, and Nagamasa Sakabe. "Data processing system for audiometric file conversion between an office computer and a personal computer." Medical Informatics 12, no. 1 (1987): 73. http://dx.doi.org/10.3109/14639238709010060.

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7

Kralev, Velin, Radoslava Kraleva, and Petia Koprinkova-Hristova. "Data modelling and data processing generated by human eye movements." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 5 (2021): 4345. http://dx.doi.org/10.11591/ijece.v11i5.pp4345-4352.

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Data modeling and data processing are important activities in any scientific research. This research focuses on the modeling of data and processing of data generated by a saccadometer. The approach used is based on the relational data model, but the processing and storage of the data is done with client datasets. The experiments were performed with 26 randomly selected files from a total of 264 experimental sessions. The data from each experimental session was stored in three different formats, respectively text, binary and extensible markup language (XML) based. The results showed that the text format and the binary format were the most compact. Several actions related to data processing were analyzed. Based on the results obtained, it was found that the two fastest actions are respectively loading data from a binary file and storing data into a binary file. In contrast, the two slowest actions were storing the data in XML format and loading the data from a text file, respectively. Also, one of the time-consuming operations turned out to be the conversion of data from text format to binary format. Moreover, the time required to perform this action does not depend in proportion on the number of records processed.

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8

Itai, Alon, and Yoav Raz. "The number of buffers required for sequential processing of a disk file." Communications of the ACM 31, no. 11 (1988): 1338–42. http://dx.doi.org/10.1145/50087.50095.

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9

Solomon, Martin K., and Riva Wenig Bickel. "Self-assessment procedure XV: a self-assessment procedure dealing with file processing." Communications of the ACM 29, no. 8 (1986): 745–51. http://dx.doi.org/10.1145/6424.6440.

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10

Ahn, Woo Hyun, Kyungjae Lee, Jaewon Oh, Kyungsub Min, and Joon Sung Hong. "A multiple-file write scheme for improving write performance of small files in Fast File System." Information Processing Letters 109, no. 18 (2009): 1021–26. http://dx.doi.org/10.1016/j.ipl.2009.05.010.

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