• Korean Architects
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• s.659
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• pp.118-121
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• 2024

• Korean Architects
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• s.657
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• pp.128-132
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• 2023

• Korean Architects
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• s.657
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• pp.36-39
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• 2023

• Korean Architects
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• s.657
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• pp.44-45
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• 2023

• Journal of Korean Society for Atmospheric Environment
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• v.18 no.E2
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• pp.69-77
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• 2002

The nationwide NO$_2$monitoring program has been carried out using the passive sampler in Korea since 1993. During the sixteenth periods of measurement, total 26,474 sites of data were collected through eight years. In this paper, the roadside NO$_2$concentration of six major cities were analyzed. As results, the most frequent NO$_2$concentration of Seoul, Incheon, and Daegu ranged from 40 to 60 ppb, and that of Pusan, Kwanju, and Daejeon was from 20 to 40 ppd. Despite that the automobile number of Incheon was less than that of Daegu and Pusan, the exceedence rate of Korean national ambient air quality standard and ninetieth percentile concentration of Incheon were almost the same level as Seoul. In addition, the mean and standard deviation of roadside NO$_2$concentration of Seoul and Incheon was also appeared to be higher than that of other cities. These results indicates that NO$_2$concentration on roadside was affected by the traffic volumes and the traffic flow conditions.

• Journal of the Korean Society for Library and Information Science
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• v.31 no.4
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• pp.239-266
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• 1997

The purpose of this study is to interpret the growth and the present status of in 6 major Korean cities and 9 provinces libraries using statistical data. The data were collected from The Statistics on Libraries in Korea, and were analyzed for a time series by using the Excel program. The result shows that there are great differences in major statistics of libraries in Korea due to the historical backgrounds and various political and social conditions of the country. The differences are also more likely related to the size of the library collections, budget and number of staffs.

• Journal of Ocean Engineering and Technology
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• v.12 no.1
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• pp.3-9
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• 1998

According to the developement of cities, electric wires and commuinication lines which are currently above the ground effect on the bad. Nowadays, it is necessary to build up underground facilities because the construction is increasing. Excavation work has been dominant even though the inconvenient things occurred, for example a civil appeal, a traffic obstacle, safety and spoiling the fine view because of the cost or period of the construction work. But the congestion of cities are more and more serious. Therefore shield-method is the way to escape from congestion. I considered all the construction fields which are in progress or finished.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.317-327
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• 2012

This paper uses the sensibility engineering method to find the model of automobile most appealing to buyers in the $4^{th}$ and $5^{th}$ tier cities of China. Samples of class A & A0 cars were shown to 96 subjects in those cities to investigate their responses in relation to the concepts 'modern' and 'smart'. The result shows that even though men tend to be more sensitive to automobile models in general than women are, both genders showed similar responses to specific models when they were asked to identify a model 'magnificent', 'modern', 'lively', 'smart' or 'cute'. This implies that despite the gender differences in terms of aesthetic sensitivity, both men and women share similar taste in relation to the appearance of cars. Apart from aesthetics, however, men tend to pay a greater attention to the details of design and material used for the cars, while women tend to pay attention to higher priced and better looking cars.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.149-155
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• 2020

Air pollution is a problem of environmental health risk in big cities. Recently, researchers have proposed using various artificial intelligence technologies to predict air pollution. The proposed model is Cooperative of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS), to predict air pollution of Korean cities using Python. Data air pollutant variables were collected and the Air Korean Web site air quality index was downloaded. This paper's aim was to predict on the health risks and the very unhealthy values of air pollution. We have predicted the air pollution of the environment based on the air quality index. According to the results of the experiment, our model was able to predict a very unhealthy value.