scholarly journals Querying Similar Water Masses Visualization Tool Design and Implementation Based on Polynomial Regression

2014 ◽  
Vol 25 (5) ◽  
pp. 727
Author(s):  
Jian-Heng Wu ◽  
Bor-Shen Lin ◽  
Jia-Yu Kuo
Leonardo ◽  
2011 ◽  
Vol 44 (3) ◽  
pp. 248-249
Author(s):  
Barbara Mirel

If whole communities of domain analysts are to be able to use interactive network visualization tools productively and efficiently, tool design needs to adequately support the metacognition implicit in complex visual analytic tasks. Metacognition for such exploratory network-mediated tasks applies across disciplines. This essay presents metacognitive demands inherent in complex tasks aimed at uncovering relevant relationships for hypothesizing purposes and proposes network visualization tool designs that can support these metacognitive demands.


2021 ◽  
Author(s):  
Siyuan Liu

<div>Dashboard has been around for a long time, and many have been developed as a governing and monitoring tool in city management, such as crime monitoring. However, the majority of crime dashboards function as a visualization tool and few of them has been specifically developed for crime analysis and prediction.</div><div>This thesis focuses on the development of geospatially-enabled crime dashboards with spatial analysis capabilities for supporting crime analysis and prediction. A prototype has been designed and implemented to support the understanding of crime events for crime reduction efforts. This dashboard will assist policy makers and leaders in crime fighting by visualizing basic statistical information of crimes, revealing their spatial and temporal patterns, identifying crime clusters, and analyzing relationships between crimes and other factors. Based on the criteria developed in this thesis, the prototype confirmed its ability of enhancing the understanding of crime events.<br></div>


2017 ◽  
Vol 34 (11) ◽  
pp. 2443-2455
Author(s):  
Patricia De La Fuente ◽  
Josep L. Pelegrí ◽  
Antonio Canepa ◽  
Marc Gasser ◽  
Francisco Domínguez ◽  
...  

AbstractThe variability of a biogeochemical property in the ocean is the outcome of both nonconservative (such as respiration and photosynthesis) and conservative (mixing of water masses with distinct concentrations at origin) processes. One method to separate both contributions is based on a multiple regression of the biogeochemical property in terms of temperature θ and salinity S as conservative proxies of water masses. This regression delivers the variability related to the conservative fraction and hence allows for identifying the residual as the biogeochemical anomaly. Here, the standard multiple linear regression (MLR) method, which assumes that water masses mix locally and linearly, is compared with a nonlinear polynomial regression (PR) over the entire (θ, S) space. The PR method has two important advantages over MLR: allows for simultaneous nonlinear mixing of all water masses and does not require knowing the end-member water types. Both approaches are applied to data along 7.5°N in the equatorial Atlantic Ocean, and the biogeochemical anomalies are calculated for humic-like fluorescent dissolved organic matter, apparent oxygen utilization, and nitrate—all of them related through in situ remineralization processes. The goodness of both approaches is assessed by analyzing the linear dependence and the coefficient of correlation between the anomalies. The results show that the PR method can be applied over the entire water column and yet retains the local variability associated with nonconservative processes. The potential of the PR approach is also illustrated by calculating the oxygen–nitrate stoichiometric ratio for the entire 7.5°N transatlantic section.


1997 ◽  
Vol 30 (8) ◽  
pp. 587-592
Author(s):  
Maurizio Mazzucchelli ◽  
Valerio Recagno ◽  
Giuseppe Sciutto

2004 ◽  
Vol 29 (2) ◽  
pp. 157-175
Author(s):  
Edward H. Ip ◽  
Phillip Leung ◽  
Joseph Johnson

We describe the design and implementation of a web-based statistical program—the Interactive Profiler (IP). The prototypical program, developed in Java, was motivated by the need for the general public to query against data collected from the National Assessment of Educational Progress (NAEP), a large-scale US survey of the academic state of American students. The emphasis of the program requirements is on bringing the NAEP data to a broader and not necessarily technically prepared audience. We show that the IP is an intuitive tool for visualizing students’ profiles. Because the same principles for visualization apply to other databases, in this article we also demonstrate how IP can be used to visualize a large marketing database. Besides NAEP, our statistical visualization tool should be pertinent to other federally maintained databases and large-scale marketing databases.


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