Some Features of TOPEX/POSEIDON Data Application in Gravimetry

Author(s):  
O. Yu. Vinogradova ◽  
E. A. Spiridonov
Keyword(s):  
1978 ◽  
Vol 9 (4) ◽  
pp. 220-235
Author(s):  
David L. Ratusnik ◽  
Carol Melnick Ratusnik ◽  
Karen Sattinger

Short-form versions of the Screening Test of Spanish Grammar (Toronto, 1973) and the Northwestern Syntax Screening Test (Lee, 1971) were devised for use with bilingual Latino children while preserving the original normative data. Application of a multiple regression technique to data collected on 60 lower social status Latino children (four years and six months to seven years and one month) from Spanish Harlem and Yonkers, New York, yielded a small but powerful set of predictor items from the Spanish and English tests. Clinicians may make rapid and accurate predictions of STSG or NSST total screening scores from administration of substantially shortened versions of the instruments. Case studies of Latino children from Chicago and Miami serve to cross-validate the procedure outside the New York metropolitan area.


IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 28302-28316
Author(s):  
Maxime Pistono ◽  
Reda Bellafqira ◽  
Gouenou Coatrieux

2020 ◽  
pp. 146144482097970
Author(s):  
Christian Wiencierz ◽  
Marco Lünich

Open data provide great potential for society, for example, in the field of smart cities, from which all citizens might profit. The trust of these citizens is important for the integration of various data, like sensitive user data, into an open data ecosystem. In the following study, we analyzed whether transparency about the application of open data promotes trust. Furthermore, we formulated guidelines on how to create transparency regarding open data in an ethical way. Using an open-data-based fictitious smart city app, we conducted an experiment analyzing to what extent communication of the technical open data application process and the ethical self-commitment for the transparent communication of data application affect trust in the app’s provider. The results indicate that the more information users obtain regarding the use of open data, the more trustworthy they perceive the app provider to be, and the more likely they are to use the app.


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