Development of GOSAT ground data system at NIES and the data processing strategy

2007 ◽  
Author(s):  
Hiroshi Watanabe ◽  
Hironari Ishihara ◽  
Keiichiro Ninomiya ◽  
Kaduo Hiraki ◽  
Tsuneo Matsunaga ◽  
...  
Keyword(s):  
Data Processing ◽  
Data System ◽  
Processing Strategy

The Maritime Administration Maintenance and Repair Data Processing and Evaluation System

1969 ◽  
Vol 6 (01) ◽  
pp. 48-57
Author(s):  
Edward S. Karlson ◽  
John J. Davis
Keyword(s):  
Data Processing ◽  
Evaluation System ◽  
Data System ◽  
Automatic Data Processing ◽  
Coding System ◽  
Raw Data ◽  
Automatic Data ◽  
Maintenance And Repair ◽  
Operational System

An operational system for providing processed maintenance and repair information for vessels is described. Content includes description of a detailed coding system for reducing raw data to composite code numbers suitable for automatic data processing. Objectives of the system and constraints thereon are discussed. The Marad data system has been operational for four years. Scope of data processed and its utilization are presented. Seven current studies concerning vessels as a whole and specific shipboard equipments are included.

A Reply to the Inverted Data System

1967 ◽  
Vol 32 (3) ◽  
pp. 395-396
Author(s):  
Sylvia W. Gaines
Keyword(s):  
Data Processing ◽  
Electronic Computer ◽  
Data System ◽  
Data Manipulation ◽  
Computer Research ◽  
Processing Techniques

AbstractThe application of data processing techniques in the field of archaeology is relatively recent. Electronic computer research is rapidly developing equipment which has sufficient application for archaeology to render obsolete the currently employed manual systems. The prime advantage of computers is in the flexibility of data manipulation at both classificatory and analytical levels. It is the writer's opinion that such manual techniques as the Bordaz’ Inverted Data System are too limited in application for widespread utility in the field.

scholarly journals MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies

2015 ◽  
Vol 5 ◽  
Author(s):  
Hiroshi Tsugawa ◽  
Erika Ohta ◽  
Yoshihiro Izumi ◽  
Atsushi Ogiwara ◽  
Daichi Yukihira ◽  
...  
Keyword(s):  
Data Processing ◽  
Large Scale ◽  
Processing Strategy ◽  
Differential Analysis

scholarly journals Using Swarm to Detect Total Water Storage Changes in 26 Global Basins (Taking the Amazon Basin, Volga Basin and Zambezi Basin as Examples)

2021 ◽  
Vol 13 (14) ◽  
pp. 2659
Author(s):  
Zhengtao Wang ◽  
Kunjun Tian ◽  
Fupeng Li ◽  
Si Xiong ◽  
Yu Gao ◽  
...  
Keyword(s):  
Gravitational Field ◽  
Data Processing ◽  
Gravity Field ◽  
Water Storage ◽  
Mass Change ◽  
Time Varying ◽  
Processing Strategy ◽  
Terrestrial Water Storage ◽  
Total Water ◽  
Terrestrial Water

The Gravity Recovery and Climate Experiment (GRACE) satellite provides time-varying gravity field models that can detect total water storage change (TWSC) from April 2002 to June 2017, and its second-generation satellite, GRACE Follow-On (GRACE-FO), provides models from June 2018, so there is a one year gap. Swarm satellites are equipped with Global Positioning System (GPS) receivers, which can be used to recover the Earth’s time-varying gravitational field. Swarm’s time-varying gravitational field models (from December 2013 to June 2018) were solved by the International Combination Service for Time-variable Gravity Field Solutions (COST-G) and the Astronomical Institute of the Czech Academy of Sciences (ASI). On a timely scale, Swarm has the potential to fill the gap between the two generations of GRACE satellites. In this paper, using 26 global watersheds as the study area, first, we explored the optimal data processing strategy for Swarm and then obtained the Swarm-TWSC of each watershed based on the optimal results. Second, we evaluated Swarm’s accuracy in detecting regional water storage variations, analyzed the reasons for its superior and inferior performance in different regions, and systematically explored its potential in detecting terrestrial water storage changes in land areas. Finally, we constructed the time series of terrestrial water storage changes from 2002 to 2019 by combining GRACE, Swarm, and GRACE-FO for the Amazon, Volga, and Zambezi Basins. The results show that the optimal data processing strategy of Swarm is different from that of GRACE. The optimal results of Swarm-TWSC were explored in 26 watersheds worldwide; its accuracy is related to the area size, runoff volume, total annual mass change, and instantaneous mass change of the watershed itself, among which the latter is the main factor affecting Swarm-TWSC. Knowledge of the Swarm-TWSC of 26 basins constructed in this paper is important to study long-term water storage changes in basins.

scholarly journals Novel Insights into Quantitative Proteomics from an Innovative Bottom-Up Simple Light Isotope Metabolic (bSLIM) Labeling Data Processing Strategy

2021 ◽  
Vol 20 (3) ◽  
pp. 1476-1487
Author(s):  
Nicolas Sénécaut ◽  
Gelio Alves ◽  
Hendrik Weisser ◽  
Laurent Lignières ◽  
Samuel Terrier ◽  
...  
Keyword(s):  
Data Processing ◽  
Quantitative Proteomics ◽  
Processing Strategy ◽  
Bottom Up ◽  
Light Isotope
Sign in / Sign up

Export Citation Format

Share Document