DLG2ISM, a Fortran program to read DLG-3 optional format digital data files into the VAX/VMS version of the interactive surface modeling software package; B, Source code DLG2ISM.FOR

Due to drastic growth of digital data, data deduplication has become a standard component of modern backup systems. It reduces data redundancy, saves storage space, and simplifies the management of data chunks. This process is performed in three steps: chunking, fingerprinting, and indexing of fingerprints. In chunking, data files are divided into the chunks and the chunk boundary is decided by the value of the divisor. For each chunk, a unique identifying value is computed using a hash signature (i.e. MD-5, SHA-1, SHA-256), known as fingerprint. At last, these fingerprints are stored in the index to detect redundant chunks means chunks having the same fingerprint values. In chunking, the chunk size is an important factor that should be optimal for better performance of deduplication system. Genetic algorithm (GA) is gaining much popularity and can be applied to find the best value of the divisor. Secondly, indexing also enhances the performance of the system by reducing the search time. Binary search tree (BST) based indexing has the time complexity of which is minimum among the searching algorithm. A new model is proposed by associating GA to find the value of the divisor. It is the first attempt when GA is applied in the field of data deduplication. The second improvement in the proposed system is that BST index tree is applied to index the fingerprints. The performance of the proposed system is evaluated on VMDK, Linux, and Quanto datasets and a good improvement is achieved in deduplication ratio.

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Source code and ancillary data files for the MODPATH particles tracking package of the ground-water flow model MODFLOW

Open-File Report ◽

10.3133/ofr94463 ◽

1994 ◽

Cited By ~ 1

Author(s):

David W. Pollock

Keyword(s):

Ground Water ◽

Water Flow ◽

Flow Model ◽

Source Code ◽

Ground Water Flow ◽

Ancillary Data ◽

Data Files

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User Innovation and System Management

Information Technology and Military Power ◽

10.7591/cornell/9781501749568.003.0005 ◽

2020 ◽

pp. 109-135

Author(s):

Jon R. Lindsay

Keyword(s):

Air Force ◽

Relevant Information ◽

Digital Data ◽

Software Systems ◽

Weapon System ◽

Defense Contractors ◽

Air Defense ◽

Weapon Systems ◽

Data Files ◽

Operations Center

This chapter investigates the Combined Air Operations Center (CAOC), the analogue to the Fighter Command Ops Room in the modern U.S. Air Force. The air force formally designates the CAOC as a weapon system, even as it is basically just a large office space with hundreds of computer workstations, conference rooms, and display screens. The CAOC is an informational weapon system that coordinates all of the other weapon systems that actually conduct air defense, strategic attack, close air support, air mobility and logistics, and intelligence, surveillance, and reconnaissance (ISR). One might be tempted to describe the CAOC as “a center of calculation,” but modern digital technology tends to decenter information practice. Representations of all the relevant entities and events in a modern air campaign reside in digital data files rather than a central plotting table. The relevant information is fragmented across collection platforms, classified networks, and software systems that are managed by different services and agencies. Thus, in each of the four major U.S. air campaigns from 1991 to 2003, CAOC personnel struggled with information friction. They rarely used the mission planning systems that were produced by defense contractors as planned, and they improvised to address emerging warfighting requirements.

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CAFE 5 models variation in evolutionary rates among gene families

Bioinformatics ◽

10.1093/bioinformatics/btaa1022 ◽

2020 ◽

Author(s):

Fábio K Mendes ◽

Dan Vanderpool ◽

Ben Fulton ◽

Matthew W Hahn

Keyword(s):

Software Package ◽

Computational Analysis ◽

Source Code ◽

Gene Families ◽

Gene Family Evolution ◽

Supplementary Information ◽

Rate Variation ◽

Gene Gain ◽

Command Line ◽

Gains And Losses

Abstract Motivation Genome sequencing projects have revealed frequent gains and losses of genes between species. Previous versions of our software, Computational Analysis of gene Family Evolution (CAFE), have allowed researchers to estimate parameters of gene gain and loss across a phylogenetic tree. However, the underlying model assumed that all gene families had the same rate of evolution, despite evidence suggesting a large amount of variation in rates among families. Results Here, we present CAFE 5, a completely re-written software package with numerous performance and user-interface enhancements over previous versions. These include improved support for multithreading, the explicit modeling of rate variation among families using gamma-distributed rate categories, and command-line arguments that preclude the use of accessory scripts. Availability and implementation CAFE 5 source code, documentation, test data and a detailed manual with examples are freely available at https://github.com/hahnlab/CAFE5/releases. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

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