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Titlebook: Databases in Networked Information Systems; 10th International W Wanming Chu,Shinji Kikuchi,Subhash Bhalla Conference proceedings 2015 Spri

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0302-9743 held in Aizu-Wakamatsu, Japan, March 2015..The 14 revised full papers presented together with 7 invited papers were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on big data analysis, information and knowledge management, business data analy
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https://doi.org/10.1007/978-3-8349-9098-3For bright stars (.′ ≤ 18 mag), with 4500 K ≤ .. ≤ 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of ~0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra.
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A Photometric Machine-Learning Method to Infer Stellar MetallicityFor bright stars (.′ ≤ 18 mag), with 4500 K ≤ .. ≤ 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of ~0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra.
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Synthetic Evidential Study as Primordial Soup of Conversationtational platform that supports the SES workshops, and advanced technologies for increasing the utility of SES. The SES is currently under development. We discuss conceptual issues and technical details to delineate how much we can implement the idea with our technology and how much challenges are left for the future work.
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Efficiency of NoSQL Databases under a Moderate Application Loadider the development and implementation of an application with moderate volume of heterogeneous data using a NoSQL database. We perform comparative performance analysis with a relational database system. The experimental evaluations show that NoSQL databases are also often suitable for handling moderate volume of data.
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A Large Sky Survey Project and the Related Big Data Analysisabout a half billion galaxies to reconstruct the distribution of cosmic dark matter, and we detect a few hundred supernovae that can be used as distance indicators. Combined together, these two data will enable us to derive fundamental parameters, the so-called cosmological paramaters, and to predict the evolution of the universe to the future.
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