• The Bulletin of The Korean Astronomical Society
• /
• v.36 no.2
• /
• pp.88.2-88.2
• /
• 2011

Fast Imaging Solar Spectrograph (FISS) is an instrument developed by Seoul National University and Korea Astronomy and Space Science Institute and installed at the 1.6 meter New Solar Telescope of Big Bear Solar Observatory. Using this instrument, we observed solar filaments and analyzed the data focusing on determining the temperature and non-thermal velocity. We inferred the Doppler absorption widths of $H{\alpha}$ and Ca II 8542$\bar{A}$ lines from the line profiles using the cloud model. From these values, we separately determined temperature and non-thermal velocity. Our first result came from a solar filament observed on 2010 July 29th. Temperature inside a small selected region of this ranges from 4500K to 12000K and non-thermal velocity, from 3.5km/s to 7km/s. We also found temperature varied a lot with time. For example temperature at a fixed point varied from 8000K to 18000K for 40 minutes, displaying an oscillating pattern with a period of about 8 minutes and amplitude of about 2000K. We will also present new results from filaments observed in 2011 summer.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.2
• /
• pp.529-534
• /
• 2020

The development of civilization is in line with evolution of cities and transportation technology caused by industrialization. Up to now, a city has been developed owing to transportation cost reduction and needs for land utilization as a limited core business district. Continuous increase of urban population density has accompanied by lots of problems socioeconomically such as rise of land value, traffic congestion, gap between the rich and poor, air pollution, etc. Those issues are difficult to be solved in existing city ecosystem. However, a clue for solving the problems could be found in there. The design of Seoul mid-night bus route was from analysis of movement of people in the rural area by using ICT so that a city ecosystem should be firstly analyzed for solving rural issues. If the cause of those is found, big data platform construction is required to raise the life quality of citizen and the problems could be solved. Big data should be located in the middle of the platform connected with every element of city based on ICT for real-time collection, analysis and application. This paper addresses construction of big data platform and its application for sustainable smart city.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.201-208
• /
• 2015

With services such as SNS and facebook, Big Data popularize the use of small size such as micro blogs are increasing. However, the problem of accuracy and computational cost of the search result of big data of a small size is unresolved. In this paper, we propose a subnet selection techniques based probability to improve the browsing speed of the small size of the text information from big data environments, such as micro-blogs. The proposed method is to configure the subnets to give to the attribute information of the data increased the probability data search speed. In addition, the proposed method improves the accessibility of the data by processing a pair of the connection information between the probability of the data constituting the subnet to easily access the distributed data. Experimental results showed the proposed method is 6.8% higher detection rates than CELF algorithm, the average processing time was reduced by 8.2%.

• Korean Journal of Construction Engineering and Management
• /
• v.22 no.6
• /
• pp.24-33
• /
• 2021

Cost management is a major function of CM (construction management) companies for clients and cost estimating is a critical task in that it provides a baseline for cost management and a foundation for decision making in construction projects. For this purpose, CM companies need to obtain and use good quality data, which leads to more accurate and efficient cost estimating. As the use of big data becomes increasingly important in the construction industry, researches related to the theme have become the active areas of studies. However, literature review shows that the current situations in relation to the use of big for cost estimating of CM companies are under-researched. The objective of the study is to identify key characteristics and implications in the use of big data for cost estimating of CM companies, which can contribute to develop strategies for such purposes.

• The Journal of Bigdata
• /
• v.6 no.1
• /
• pp.13-22
• /
• 2021

The purpose of this study is to develop and demonstrate a framework for evaluating the maturity of big data for effective data strategy establishment and efficient investment of companies. By supplementing the shortcomings of the evaluation developed so far, a framework was developed to evaluate the maturity of a company's big data in an integrated process. As a result, four evaluation areas of 'Vision and Strategy', 'Management', 'Analysis' and 'Utilization', assessment items for each area, detailed content, and criteria for each stage were derived. This was verified through a survey of entrepreneurs, and the maturity level of big data of domestic companies was confirmed. As a future research direction, it is proposed to develop detailed assessment factors according to the characteristics of each industry, to develop a data utilization framework according to the assessment results, and to improve validity and reliability through adjustment of verification targets.

• Journal of Korea Society of Industrial Information Systems
• /
• v.25 no.6
• /
• pp.15-23
• /
• 2020

While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.

• Journal of Platform Technology
• /
• v.11 no.6
• /
• pp.89-105
• /
• 2023

With the development of information technology, most of the information has been converted into digital information, leading to the Big Data era. The demand for search platform has increased to enhance accessibility and usability of information in the databases. Big data search software platforms consist of two main components: (1) an indexing component to generate and store data indices for a fast and efficient data search and (2) a searching component to look up the given data fast. As an amount of data has explosively increased, data indexing performance has become a key performance bottleneck of big data search platforms. Though many companies adopted big data search platforms, relatively little research has been made to improve indexing performance. This research study employs Elasticsearch platform, one of the most famous enterprise big data search platforms, and builds physical clusters of 3 nodes to investigate optimal indexing performance configurations. Our comprehensive experiments and studies demonstrate that the proposed optimal Elasticsearch configuration achieves high indexing performance by an average of 3.13 times.

• Publications of The Korean Astronomical Society
• /
• v.26 no.1
• /
• pp.45-54
• /
• 2011

KASI and Seoul National University developed the Fast Imaging Solar Spectrograph (FISS) as one of major scientific instruments for the 1.6 m New Solar Telescope (NST) and installed it in the Coude room of the NST at Big Bear Solar Observatory (BBSO) in May, 2010. The major objective of the FISS is to study the fine-scale structures and dynamics of plasma in the photosphere and chromosphere. To achieve it, the FISS is required to take data with a spectral resolution higher than $10^5$ at the spectrograph mode and a temporal resolution less than 10 seconds at the imaging mode. The FISS is a spectrograph using Echelle grating and has characteristics that can observe dual bands (H${\alpha}$ and CaII 8542) simultaneously and perform fast imaging using fast raster scan and two fast CCD cameras. In this paper, we introduce briefly the whole process of FISS development from the requirement analysis to the first observations.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.1-6
• /
• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Korean Educational Research Journal
• /
• v.43 no.1
• /
• pp.1-27
• /
• 2022

As the COVID-19 virus became prevalent worldwide, non-face-to-face contact was implemented in various ways, and the education system also began to draw much attention due to rapid non-face-to-face contact. The purpose of this study is to analyze the direction of non-face-to-face education in line with the continuously changing educational environment to date. In this study, data were visualized using Textom and Ucinet6 analysis tool programs to collect social network big data with various opinions. As a result of the study, keywords related to "COVID-19" were dominant, and keywords with high frequency such as "article" and "news" existed. As a result of the analysis, various issues related to non-face-to-face education, such as network failures and security issues, were identified. After the analysis, the direction of the non-face-to-face education system was studied according to the growth of the education market and changes in the educational environment. In addition, there is a need to strengthen security and feedback on teaching methods in non-face-to-face education analyzed using big data.