• Journal of The Korean Astronomical Society
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• v.36 no.spc1
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• pp.37-44
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• 2003

In this paper, we review recent studies on the magnetic helicity changes of solar active regions by photospheric horizontal motions. Recently, Chae(200l) developed a methodology to determine the magnetic helicity change rate via photospheric horizontal motions. We have applied this methodology to four cases: (1) NOAA AR 8100 which has a series of homologous X-ray flares, (2) three active regions which have four eruptive major X-ray flares, (3) NOAA AR 9236 which has three eruptive X-class flares, and (4) NOAA AR 8668 in which a large filament was under formation. As a result, we have found several interesting results. First, the rate of magnetic helicity injection strongly depends on an active region and its evolution. Its mean rate ranges from 4 to $17 {\times} 10^{40}\;Mx^2\;h^{-1}$. Especially when the homologous flares occurred and when the filament was formed, significant rates of magnetic helicity were continuously deposited in the corona via photospheric shear flows. Second, there is a strong positive correlation between the magnetic helicity accumulated during the flaring time interval of the homologous flares in AR 8100 and the GOES X-ray flux integrated over the flaring time. This indicates that the occurrence of a series of homologous flares is physically related to the accumulation of magnetic helicity in the corona by photospheric shearing motions. Third, impulsive helicity variations took place near the flaring times of some strong flares. These impulsive variations whose time scales are less than one hour are attributed to localized velocity kernels around the polarity inversion line. Fourth, considering the filament eruption associated with an X1.8 flare started about 10 minutes before the impulsive variation of the helicity change rate, we suggest that the impulsive helicity variation is not a cause of the eruptive solar flare but its result. Finally, we discuss the physical implications on these results and our future plans.

• Journal of the Korean earth science society
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• v.36 no.4
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• pp.351-359
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• 2015

This study is to analyze the sensitivity for the parameters (a and b values, $M_{max}$, attenuation formula, and seismo-tectonic model) which are essential for the seismic hazard map. The values of each parameter were suggested by 10 members of the expert group. The results show that PGA increases as a value and $M_{max}$ become larger and as b value smaller. Big impact on the seismic hazard is observed for attenuation formula, a and b values although there is little impact on $M_{max}$ and seismo-tectonic model. These parameters with big impact require careful consideration for obtaining adequate values that well reflects the seismic characteristics of the Korean peninsula.

• The Journal of Bigdata
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• v.1 no.2
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• pp.9-19
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• 2016

Since ICT convergence became a major issue, German government has carried forward a policy 'Industry 4.0' that triggered ICT convergence with manufacturing. Now this trend gets into our stride. From this facts, we can expect great leap up to quality perfection in low cost. Recently Korean government also enforces policy with 'Manufacturing 3.0' for upgrading Korean manufacturing industry with being accelerated by many related technologies. We, in the paper, developed a custom-made operational big data analysis platform for the implementation of operational intelligence to improve industry capability. Our platform is designed based on spring framework and web. In addition, HDFS and spark architectures helps our system analyze massive data on the field with streamed data processed by process mining algorithm. Extracted knowledge from data will support enhancement of manufacturing performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.4
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• pp.987-996
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• 2015

According to the recent research results of the Ministry of Environment, the indoor air quality of large general hospitals and university hospitals(58 hospitals) exceeded the maintenance standard. On top of such indoor air quality, it is also desperately required to have the environment-friendly building design and also low carbon green design in accordance with the increase of hospital size and enlarged hospital buildings. Especially, the increase of carbon dioxide, heat, garbage, waste energy, exhaust heat from power plants and sewage heat in each medical center brings up lots of problems to the health of hospital patients and customers. Thus this study aims to convergently develop the green environment-friendly architecture design technology concerning the organic relations between each medical building, and technical development which should be introduced to the low carbon green environment-friendly architecture design based on the characteristics of each medical center in large-scale medical complex.

• The Mathematical Education
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• v.59 no.4
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• pp.373-387
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• 2020

The purpose of this study is to verify the effects of personalized learning platforms applied with machine learning recommendation modules that upgrade recommended algorithms by themselves through learning big data analysis on students' learning time, self-directed learning ability, mathematics achievement, and attitudes toward mathematics, and the correlation between them. According to the study, customized learning affected learning time, self-directed learning ability and mathematics attitude, while learning time affected self-directed learning ability. Self-directed learning ability has had a significant impact on the attitude of mathematics and mathematical achievements. As a result of the mediated effectiveness test, the indirect impact of customized learning on mathematics attitude and mathematics performance was significant through the medium of learning time and self-directed learning ability.

• Korean Journal of Clinical Pharmacy
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• v.27 no.4
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• pp.221-227
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• 2017

Background: As personalized healthcare industry has attracted much attention, big data analysis of healthcare data is essential. Lots of healthcare data such as product labeling, biomedical literature and social media data are unstructured, extracting meaningful information from the unstructured text data are becoming important. In particular, text mining for adverse drug reactions (ADRs) reports is able to provide signal information to predict and detect adverse drug reactions. There has been no study on text analysis of expert opinion on Korea Adverse Event Reporting System (KAERS) databases in Korea. Methods: Expert opinion text of KAERS database provided by Korea Institute of Drug Safety & Risk Management (KIDS-KD) are analyzed. To understand the whole text, word frequency analysis are performed, and to look for important keywords from the text TF-IDF weight analysis are performed. Also, related keywords with the important keywords are presented by calculating correlation coefficient. Results: Among total 90,522 reports, 120 insulin ADR report and 858 tramadol ADR report were analyzed. The ADRs such as dizziness, headache, vomiting, dyspepsia, and shock were ranked in order in the insulin data, while the ADR symptoms such as vomiting, 어지러움, dizziness, dyspepsia and constipation were ranked in order in the tramadol data as the most frequently used keywords. Conclusion: Using text mining of the expert opinion in KIDS-KD, frequently mentioned ADRs and medications are easily recovered. Text mining in ADRs research is able to play an important role in detecting signal information and prediction of ADRs.

• Journal of the Korea Convergence Society
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• v.6 no.4
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• pp.25-31
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• 2015

General student orchestra activity is known as desirable hobby for students of adolescent period, developing their creativity and sensitivity, give students sense of belonging and stability by resolving their social, emotional anxiety. Accordingly, his research investigated whether orchestra club activity also has similar effect on university students. As a result unlike of adolescent students, orchestra activity turned out to be not that helpful for the social, self-confidence improvement of university students, though achievement of the activity itself was high. Despite of the result, there exist positive factors; obviously the activity has positive factors analyzing through recognition analysis (opinion mining) using big data. Therefore national support is required also for the orchestra activity of the undergraduates.

• Journal of KIISE
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• v.44 no.4
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• pp.383-391
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• 2017

As we enter a new era of Big Data, the amount of semantic data has rapidly increased. In order to derive meaningful information from this large semantic data, studies that utilize the SWRL(Semantic Web Rule Language) are being actively conducted. SWRL rules are based on data extracted from a user's empirical knowledge. However, conventional reasoning systems developed on single machines cannot process large scale data. Similarly, multi-node based reasoning systems have performance degradation problems due to network shuffling. Therefore, this paper overcomes the limitations of existing systems and proposes more efficient distributed inference methods. It also introduces data partitioning strategies to minimize network shuffling. In addition, it describes a method for optimizing the incremental reasoning process through data selection and determining the rule order. In order to evaluate the proposed methods, the experiments were conducted using WiseKB consisting of 200 million triples with 83 user defined rules and the overall reasoning task was completed in 32.7 minutes. Also, the experiment results using LUBM bench datasets showed that our approach could perform reasoning twice as fast as MapReduce based reasoning systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.667-677
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• 2013

As the firewall is a typical network security equipment, it is usually installed at most of internal/external networks and makes many packet data in/out. So analyzing the its logs stored in it can provide important and fundamental data on the network security research. However, along with development of communications technology, the speed of internet network is improved and then the amount of log data is becoming 'Massive Data' or 'BigData'. In this trend, there are limits to analyze log data using the traditional database model RDBMS. In this paper, through our Method of Analyzing Firewall log data using MapReduce based on NoSQL, we have discovered that the introducing NoSQL data base model can more effectively analyze the massive log data than the traditional one. We have demonstrated execellent performance of the NoSQL by comparing the performance of data processing with existing RDBMS. Also the proposed method is evaluated by experiments that detect the three attack patterns and shown that it is highly effective.

• Journal of the Korean Institute of Rural Architecture
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• v.17 no.4
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• pp.75-82
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• 2015

The elderly rate in South Korea in 2015 is over 13.1%. Especially, the elderly rate in rural area is high. Senior community project in rural that is being promoted by the government. This study's purpose is to provide the reserch group-home for the elderly in Japan rural area. And this paper provided planning of group-home for the elderly in Korea rural area. For this study, respective 5senior housing of Korea and Japan were chosen as respresenting two nations, and every manager was interviewed on housing pattern. This study suggests the planning material as following. First, the effectiveness of the group-home are big. Especially, the elderly was far healthier. Design point is public space(living room, small living room, etc). Maybe, healthy group-home concept is that would be design by Korean traditional housing. Also important public space design is that would be inner courtyard-house, wood floor, Deachong, etc. Two group-homes will construct elderly welfare facilities in between. Otherwise that is need layout of a big public space. In the case of vacant house can used by considering of scale, structure, site condition. Closed school can used through so easy remodeling too. More often than not complex type(hospital, community heath center) was appeared in Japan rural area. In the case of Korea, recommend complex type in community health center and public building. In this case, considering communication, access, contact, group-home keeps on ground floor. In this paper, we hope to take a lesson from group-home planning source for the elderly in Korea rural area.