• The Journal of Korean Association of Computer Education
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• v.17 no.6
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• pp.115-122
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• 2014

One of the problems with current youth generations is increasing rate of violence and suicide in their school lives, and this study aims at the design of a sentiment analysis system to prevent suicide by uising big data process. The main issues of the design are economical implementation, easy and fast processing for the users, so, the open source Hadoop system with MapReduce algorithm is used on the HDFS(Hadoop Distributed File System) for the experimentation. This study uses word count method to do the sentiment analysis with informal data on some sns communications concerning a kinds of violent words, in terms of text mining to avoid some expensive and complex statistical analysis methods.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.49-55
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• 2019

Organizations design and operate business process models to achieve their goals efficiently and systematically. With the advancement of IT technology, the number of items that computer systems can participate in and the process becomes huge and complicated. This phenomenon created a more complex and subdivide flow of business process.The process instances that contain workcase and events are larger and have more data. This is an essential resource for process mining and is used directly in model discovery, analysis, and improvement of processes. This event log is getting bigger and broader, which leads to problems such as capacity management and I / O load in management of existing row level program or management through a relational database. In this paper, as the event log becomes big data, we have found the problem of management limit based on the existing original file or relational database. Design and apply schemes to archive and analyze large event logs through Hadoop, an open source distributed file system, and HBase, a NoSQL database system.

• Steel and Composite Structures
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• v.37 no.6
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• pp.741-759
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• 2020

Steel plate-concrete composite slabs provide attractive features, such as more effective loading transfer, and more cost-effective stay-in-place forms, thereby enabling engineers to design more high-performance light structures. Although significant studies in the literatures have been directed toward designing and implementing the steel plate-concrete composite beams, there are limited data available for understanding of the composite slabs. To fill this gap, nine the composite slabs with different variables in this study were tested to unveil the impacts of the critical factors on the ultimate strength behavior. The key information of the findings included sample failure modes, crack pattern, and ultimate strength behavior of the composite slabs under either four-point or three-point loading. Test results showed that the failure modes varied from delamination to shear failures under different design factors. Particularly, the shear stud spacing and thicknesses of the concrete slabs significantly affected their ultimate load-carrying capacities. Moreover, an analytical model of the composite slabs was derived for determining their ultimate load-carrying capacity and was well verified by the experimental data. Further extensive parametric study using the proposed analytical methods was conducted for a more comprehensive investigation of those critical factors in their performance. These findings are expected to help engineers to better understand the structural behavior of the steel plate-concrete composite slabs and to ensure reliability of design and performance throughout their service life.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.369-372
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• 2006

Optimal engineering design is challenging because nonlinear objective functions need to be evaluated in a high-dimensional space. This paper presents a data-mining aided optimal design method. The method is employed in designing an optimal multi-station fixture layout. Its benefit is demonstrated by a comparison with currently available optimization methods.

• Tunnel and Underground Space
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• v.24 no.5
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• pp.335-343
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• 2014

Room-and-pillar mining method is one of the most popular underground mining method in the world. If the room-and-pillar mining method is able to be adopted in civil works, it would be highly probable to reduce underground construction costs and to expand a underground structure in use. Therefore, this study aims to analyze the design procedure of unsupported rock pillars which are indispensable to ensure the stability of a room-and-pillar underground structure. Parametric studies on their key design parameters are also carried out for 125 different kinds of design conditions. From the study, the width of a rock pillar is found to show a linear relationship with its corresponding safety factor. The safety factor of a unsupported rock pillar decreased drastically like a negative exponential function as the ratio of room width to pillar width increases in the same rock strength condition. Based on the parametric studies, a design chart to simply evaluate the geometric design parameters of a unsupported rock pillar satisfying a design safety factor is also proposed in this study.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.6
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• pp.677-682
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• 2014

In the present study, a decision tree and artificial neural network were used to determine critical design parameters for lithium ion batteries and compare their performances. First, a design method that used a decision tree-artificial neural network model was used to determine the major design factors among early pole plate design factors that showed nonlinearity. Then, the artificial neural network was used to implement a weighted value analysis of the importance of the design factors and their effect on the current density. The second method involved the use of an artificial neural network model to construct artificial networks without separate determinations of the major early design factors to analyze the connections and weighted values related to the current density.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.77-85
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• 1999

The 3-D seismic research vessel, Tamhae II, was built to raise up the probability of the hydrocarbon discovery in the Korean continental shelf and the first test survey was completed in the East Sea. During the survey, the 240 channel 2-D marine seismic data were acquired by the Korean flag vessel for the first time. Tamhae II has been equipped with source, receiver, recording equipment, and navigation equipment as well as an onboard processing system. The source is composed of four subarrays and each subarray has six airguns. Total airgun volume is 4578 $in^3$. The receiver consists of two sets of 3 km long 240 channel streamer. In the first survey, the successful acquisition of 2-D seismic data was accomplished. From the result of the data processing, we confirmed that the high quality seismic data were acquired. For the high quality data acquisition, technology of survey design and planning, operation of vessel and equipments and systematic quality control should be developed.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.173-183
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• 2019

This study aims to utilize big data contents of news and social media for developing a corporate strategy of multinational enterprises and their global decision-making through the data mining technique, especially text mining. In this paper, the data of 2 news media (BBC and CNN) and 2 social media (Facebook and Twitter) were collected for the three global leading Korean companies (Samsung, Hyundai Motor Company, and LG) from April, 2018 to April, 2019. The findings of this paper have shown that traditional news media and also modern social media have become devastating tools to extract global trends or phenomena for businesses. Moreover, this presents that a company can adopt a two-track strategy through two different types of media by deriving the key issues or trends from news media channels and also grasping consumers' sentiments, preference or issues of interest such as battery or design from social media. In addition, analyzing the texts of those media and understanding the association rules greatly contribute to the comparison between two different types of media channels to see the difference. Lastly, this provides meaningful and valuable data empowered insights to find a future direction comprehensively and develop a global strategy for sustainability of business.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.205-210
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• 2006

Nowaday manufacture technology and manufacture environment are changing rapidly. By development of computer and enlargement of technique, most of manufacture field are computerized. It is measured automatically do much quality characteristics thereby and great many data happen in a day. corporations is important if have gotten fast information that are useful from wide data to go first in international competition according to these change. Statistical process control(SPC) techniques are used as a problem solution tool at manufacturing process until present. However, this statistical methods is not applied more extensively because have much restrictions in realistic problem. In this paper, wish to develop more realistic and scientific new statistical design techniques doing to integrate data mining(DM) and statistical methods by the alternative to cope these problem. First step selects significant factor using DM techniques from datas of manufacturing process including much factors and second step wish to find optimum of process after get the estimated response function through response surf ace methodology(RSM) that is statistical techniques.

• Journal of Distribution Science
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• v.15 no.4
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• pp.33-40
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• 2017

Purpose - This study aims to examine the analysis of pattern on Arab countries consumers' preferences of the Korean Contents using social media, Facebook since Korean entertainment contents have been distributed in the global marketplace. Then we focus on developing Predictive model using a Data Mining Technique. Research design, data and methodology - In order to understand preference growth of Korean contents in Arabic countries, we- collected data from two popular Facebook pages: 'Korean movies and drama' and 'K-pop'. Then, we adopted a data-driven approach based on Data Mining techniques. Results - It is obvious that the number of likes for K-pop will increase for all North African and Middle Eastern countries, however concerning Korean Movies and Drama except Tunisia it is decreasing for Algeria, Egypt and Morocco. Also, concerning Saudi Arabia and United Arab Emirates, the number of likes will decrease for Korean Movies and Drama which is not the case for Iraq. Conclusions - It is noted in this study that K-contents such as drama, movie and music are sometimes a gateway to a wider interest in Korean culture, food and brands. Moreover, this study gives significant implications for developing predictive model to forecast Korean contents' consumption and preferences.