• Journal of the Korean housing association
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• v.14 no.6
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• pp.205-214
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• 2003

The purpose of this study is to investigate the characteristics of the floor plan of single detached houses in Canada. A quantitative & qualitative analysis method of th 260 house plan was used in this study. The followings were found out from this analysis : 1) There were the differences of the lay-out and the number of public spaces between a small type and a big type. 2) There were the differences of the equipment and the number of bathroom between a small type and a big type. 3) The most work center type of kitchen was 'ㄴ+ㅁ' type(33%). 4) The most type of floor plan was that one with attached garage(87%) and center entry(99%). 5) Almost floor plans having 3 or 4 bed rooms even though medium II and large size plans which is to show that the basic needs of family life rely on the omnifarious public spaces.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.32-39
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• 2016

Machine learning is a field of artificial intelligence (AI), and a technology that collects, forecasts, and analyzes securities data is developed upon machine learning. The difference between using machine learning and not using machine learning is that machine learning-seems similar to big data-studies and collects data by itself which big data cannot do. Machine learning can be utilized, for example, to recognize a certain pattern of an object and find a criminal or a vehicle used in a crime. To achieve similar intelligent tasks, data must be more effectively collected than before. In this paper, we propose a method of effectively collecting data.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.463-469
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• 2016

This paper presents a compression-friendly low power test scheme in EDT environment. The proposed approach exploits scan slices reusing to reduce the switching activity during shifting for test scheme based on linear decompressor. To avoid the impact on encoding efficiency from resulting control data, a counter is utilized to generate control signals. Experimental results obtained for some larger ISCAS'89 and ITC'99 benchmark circuits illustrate that the proposed test application scheme can improve significantly the encoding efficiency of linear decompressor.

• Journal of the Korea Safety Management & Science
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• v.4 no.4
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• pp.27-44
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• 2002

Recently, both management and labor are interested in the increasing ratio of musculoskeletal disorders. And the developed countries make efforts to consider a counterplan such as prevention activity of musculoskeletal disorders and application possibility of ergonomic program, because musculoskeletal disorders take large portion out of occupational disease. Especially, small and medium enterprises have bigger problems due to the inferior work condition and environment in comparison with big businesses. This study is to introduce developed countries' cases such as WISE(Work Improvement in Small Enterprises) and OSHA Handbook for Small Businesses and to suggest the program of ergonomic management for small and medium enterprises having comparative difficulties against big businesses in improving work environment and managing ergonomic operations.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.187-195
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• 2019

In the fourth industrial revolution era, various commercial smart platforms for smart system implementation are being developed and serviced. However, since most of the smart platforms have been developed for general purposes, they are difficult to apply / utilize because they cannot satisfy the requirements of real-time data management, data visualization and data storage of smart factory system. In this paper, we implemented an open source based smart manufacturing big data platform that can manage highly efficient / reliable data integration for the diagnosis diagnostic system of manufacturing robots.

• Korean Journal of Organic Agriculture
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• v.26 no.4
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• pp.619-628
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• 2018

This study analyze the economic effect of chemical fertilizer. We used the input and output data, and the analysis variables include production output nitrogen, phosphoric acid, potassium, seeds, and labor. The main results are as follows. First, for spring potatoes, potassium increases to a certain level of output, but over a certain stage, the output decreases as the input increases. Optimal use of potassium in the calculation of spring potatoes can achieve the effect of reducing input costs and increasing output simultaneously. Second, radish In autumn, nitrogen increases to a certain level, but over a certain stage it represents a reverse U-shaped relationship in which output decreases as input increases. This means that reducing the amount of fertilizer input increases the output. This means that soil-related agricultural big data can contribute to the management of nutrients and greenhouse gas reduction in agricultural land.

• Journal of the Korean Magnetic Resonance Society
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• v.24 no.4
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• pp.129-135
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• 2020

In a relatively short period, monoclonal antibodies have made dramatic success as therapeutics for various diseases such as cancers and autoimmune diseases and become an important development items for many pharmaceutical companies. In order to develop antibody drug, it is important to investigate the structural characteristics of both antibody and antigen. NMR studies on antibody are extremely challenging due to big huddles such as a big size of protein and isotope labeling, nevertheless, several studies have been reported in 10 years. Here, we analyzed 95 papers dealing with antibody-related NMR studies reported in recent 10 years. We categorized papers into 3 types: 1) structural characterization of antibody, 2) structural characterization of antigen using antibody, 3) amyloidosis caused by fragment of antibody. This work would shed new light on antibody-related NMR studies.

• International Journal of Contents
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• v.17 no.4
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• pp.52-61
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• 2021

The 2020 US Presidential Election was a highly-anticipated moment for our global society. During the election period, the most intriguing issue was who would be the winner-Trump or Biden? Among the possible main themes of the 2020 election, from the COVID-19 pandemic to racism, this study focused on feminism ('women') as a main component of Biden's victory. To explore the character of Biden's supporters, this paper focused on internet spaces as a source of public opinion. To guide the data analysis, this study employed four indices from empirical studies on Big Data analytics: issue salience, attention diversity, emotional mentioning, and semantic cohesion. The main finding of this study was that the representative keyword 'women' appeared more prevalently within content related to Biden than Trump, and the keyword pairs indicated that female voters were the main reason for Trump's failure but the root cause of Biden's victory. The results of this study indicated the role of the internet as a forum for public opinion and a fountain of political knowledge, which requires more rigorous investigation by researchers.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.52-57
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• 2022

In this study, keywords from representative online portal sites such as Naver, Google, and Youtube were collected based on text mining analysis technique using Textom to check the changes in metqaverse after COVID-19. before Corona, it was confirmed that social media platforms such as Kakao Talk, Facebook, and Twitter were mentioned, and among the four metaverse, consumer awareness was still concentrated in the field of life logging. However, after Corona, keywords from Roblox, Fortnite, and Geppetto appeared, and keywords such as Universe, Space, Meta, and the world appeared, so Metaverse was recognized as a virtual world. As a result, it was confirmed that consumer perception changed from the life logging of Metaverse to the mirror world. Third, keywords such as cryptocurrency, cryptocurrency, coin, and exchange appeared before Corona, and the word frequency ranking for blockchain, which is an underlying technology, was high, but after Corona, the word frequency ranking fell significantly as mentioned above.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.228-233
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• 2021

In this study, we analyze the credit information (loan, delinquency information, etc.) of individual business owners to generate voluminous training data to establish a bankruptcy prediction model through a partial synthetic training technique. Furthermore, we evaluate the prediction performance of the newly generated data compared to the actual data. When using conditional tabular generative adversarial networks (CTGAN)-based training data generated by the experimental results (a logistic regression task), the recall is improved by 1.75 times compared to that obtained using the actual data. The probability that both the actual and generated data are sampled over an identical distribution is verified to be much higher than 80%. Providing artificial intelligence training data through data synthesis in the fields of credit rating and default risk prediction of individual businesses, which have not been relatively active in research, promotes further in-depth research efforts focused on utilizing such methods.