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Jik-Soo Kim

Researcher at Korea Institute of Science and Technology Information

Publications -  57
Citations -  622

Jik-Soo Kim is an academic researcher from Korea Institute of Science and Technology Information. The author has contributed to research in topics: Grid & Load balancing (computing). The author has an hindex of 13, co-authored 51 publications receiving 516 citations. Previous affiliations of Jik-Soo Kim include University of Maryland, College Park.

Papers
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Journal ArticleDOI

Overview of KSTAR initial operation

M. Kwon, +146 more
- 01 Sep 2011 - 
TL;DR: The first phase (2008-2012) of operation of KSTAR was dedicated to the development of operational capabilities for a superconducting device with relatively short pulse as mentioned in this paper, which achieved steady-state operations with high performance plasmas relevant to ITER and future reactors.
Journal ArticleDOI

Quantitative Evaluation of EEG-Biomarkers for Prediction of Sleep Stages

TL;DR: The EEG-based sleep stage prediction approach is expected to be utilized in a wearable sleep monitoring system and the neurological EEG-biomarkers may be considered biomarkers for their characteristics of attenuation in NREM sleep and subsequent increase in REM sleep.
Proceedings ArticleDOI

Using content-addressable networks for load balancing in desktop grids

TL;DR: In this article, a new decentralized algorithm for maintaining approximate global load information, and a job pushing mechanism that uses the global information to push jobs towards underutilized portions of the system is proposed.
Journal ArticleDOI

An overview of KSTAR results

Jong-Gu Kwak, +158 more
- 01 Oct 2013 - 
TL;DR: In this paper, a second neutral beam (NB) source and improved tuning of equilibrium configuration with real-time plasma control has been achieved with a corresponding energy confinement time of?E???163?ms.
Proceedings ArticleDOI

Resource Discovery Techniques in Distributed Desktop Grid Environments

TL;DR: A comparative analysis on the experimental results obtained via simulation of three different types of matchmaking algorithms under different workload scenarios shows the trade-offs between effcient matchmaking and good load balancing in a fully decentralized, heterogeneous computational environment.