• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.4
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• pp.396-402
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• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.

• Journal of Environmental Impact Assessment
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• v.30 no.6
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• pp.339-354
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• 2021

The purpose of this study is to provide valuable information and data by analyzing the environmental status and potential forrenewable energy projects (or plans) based on environmental assessment (EA) data, so that more objective and scientific environmental assessments can be conducted. The study also suggests regional directions that could satisfy the goals of nature conservation and renewable energy. Based on the analysis of EA data that was conducted up until June 2019, the study analyzed the size, location and characteristics of both onshore wind power and onshore photovoltaic. The environmentally available potential by region was also derived by considering the main constraints and requirements related to the potential siting ofrenewable energy projects at the EA. Based on EA data, 63 out of 80 (79%) onshore wind power projects are shown to be located in mountainous areas. For onshore photovoltaic projects, a total of 7,363 projects were subjected to environmental assessment over the country. The environmentally potential area for onshore wind power, considering all the environmental regulatory factors, is 2,440 km². For onshore photovoltaic, the environmentally available area estimated as idle farmland is 2,877 km². The distribution and characteristics of the environmentally available potential of the region may be the most important factor that local governments should bear in mind in terms of promoting renewable energy development projects in the region. Based on the results of this study, even if we consider the national energy plan including the expected future increase, as well as environmental goals and socio-economic acceptance through an environmental assessment, the available resources forrenewable energy projects are not insufficient. It is possible to examine the adequacy of the target distribution rate of renewable energy sources by region taking into consideration the quantitative and scientific results such as the environmentally available potential data derived from this study.

• Korean Journal of Ecology and Environment
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• v.33 no.3 s.91
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• pp.187-196
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• 2000

This paper describes a simple method that uses differences among Carlson's (1977) trophic state index (TSI) values based on total phosphorus (TP), chlorophyll a (CHL) and Secchi depth (SD) to draw inferences regarding the factors that are limiting to phytoplankton growth and the composition of lake seston. Examples are provided regarding seasonal and spatial patterns in a large subtropical lake (Lake Okeechobee, Florida, USA) and inter- and intra-lake variations from a multilake data set developed from published studies. Once an investigator has collected routine water quality data and established TSI values based on TP, CHL, and SD, a number of inferences can be made. Additional information can be provided where it also is possible to calculate a TSI based on total nitrogen (TN). Where TSI (CHL)<>TSI (SD), light attenuating particles are large (large filaments or colonies of algae), and the phytoplankton may be limited by zooplankton grazing. Other limiting conditions are inferred by different relationships between the TSI values. Results of this study indicate that the analysis is quite robust, and that it generally gives good agreement with conclusions based on more direct methods (e.g., nutrientaddition bioassays, zooplankton size data, zooplankton removal experiments). The TSI approach, when validated periodically with these more costly and time-intensive methods, provides an effective, low cost method for tracking long-term changes in pelagic structure and function with potential value in monitoring lake ecology and responses to management.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.2
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• pp.109-120
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• 2017

A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.

• Journal of Korean Society of Forest Science
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• v.80 no.2
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• pp.202-209
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• 1991

This study was carried out to examine seed germination, seedling growth, and biomass production of Eucommia ulmoides. The results were summarized as follows ; 1. Cold moist stratification at a refrigerator showed 60.3% of seed germination, which is the most effective among pretreatment methods. 2. In case of 1-0 seedlings, sixty seedlings per $1m^2$ was the most appropriate density, and the growth quality of seedlings differed significantly among densities. 3. Height growth showed continuous growth pattern and the maximum growth was shown during the period 21 June to 20 July, which corresponds 32.7% of total annual growth. 4. As tree age and DBH increased, the production of bark and leaf increased, however, its increment rate remarkably dropped down after ten years. 5. When tree age was ten years, the rate of bark volume showed the maximum value, 12.42%. 6. Dry weight of barks and leaves and bark volume were positively related to the growth of DBH and height. 7. As tree age increased, leaf area decreased, but the number of leaves increased.

• Economic and Environmental Geology
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• v.41 no.3
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• pp.287-297
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• 2008

In order to estimate the preliminary development feasibility according to the commodity, the content of 8 strategic metallic commoditites(Pb, Zn, Cu, Fe, Mo, W, Au, U) in 68 ore specimens obtained from 34 metallic mines within the Taebaegsan-Hwanggangri mineralized zone were analyzed. Analytical results are as follows. The ore specimen of Sangdong mine contained 23% copper(cut-off grade=0.7%) and those of Cheongil and Samhwanghak mines contained average 5% zinc(cut-off grade=2.0%). Especially, the detailed investigation on the above-mentioned mines is required. And, in case of molybdenum(cut-off grade=0.02%) content in Yeonhwa No. 2(0.04%) and Hong-cheon mine(0.02%), and lead(cut-off grade=0.58%) content in Wongasa mine(0.70%), and gold(cut-off grade=10ppm) content in Dongmyoung(279ppm) and Samhwanghak mine(251ppm), it is required to elastically carry out the revaluation on reopening of mines in terms of the international metal price. On the other hand, in case of uranium, iron and tungsten, it is thought that there are no mines with the development potential value in this study.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.

• Knowledge Management Research
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• v.22 no.4
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• pp.103-118
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• 2021

Gross Domestic Product(GDP) is affected by the economic power of each industry. Therefore, using statistical data related to the food and drug industry, we tried to determine the proportion of GDP and analyzed the impact of the food, medical & drug industry on the domestic economy through comparison with other industries. The food, medical & drug industry has a wide range of industries among domestic industries and is closely related to the lives of the people. In addition, human lifespan is increasing, and recently, due to the spread of an infectious disease called COVID-19, the bio sector belonging to the food, medical & drug industry is in the spotlight. Attention is needed to the industry as the competitiveness of the food, medical & drug industry is expected to increase. The Ministry of Food and Drug Safety provides statistics on the food, medical & drug industry, but does not provide a systematic share of GDP. Since it is difficult to determine how influential the industry is compared to other industries, this study attempts to obtain the share of GDP in the food, medical & drug industry and compare it with other industries. In the process of obtaining GDP in the food, medical & drug industry sector, there was a difficulty in that the figures in statistical data were not unified by time point. In order to overcome the limitations, statistical data as a standard are determined. The GDP of the Food, Medical & Drug Industry was estimated using total added value, production, sales, and added value by industry. Compared to other industries, the Food, Medical & Drug Industry's GDP ranked second after the GDP of the manufacturing industry. As a result, it suggests that the food, medical & drug industry has a great influence on the national economic power among domestic industries.

• Journal of agricultural medicine and community health
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• v.29 no.1
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• pp.43-63
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• 2004

Objectives: The purpose of this study was to classify the patterns of health behaviors of some rural residents in Korea by sub-grouping them into populations with similar patterns of diet quality, physical activity, alcohol consumption and cigarette smoking, and then to investigate the relationship between these health behavior patterns and health status or health management of them. Methods: The study subjects were 722 rural residents above 20 years old on a typical rural district in Korea, and the data used in this study was from the survey data for health planning of a health center. Study questionnaire for this survey was developed from modifying the questionnaire for 'National Nutrition and Health Study' conducted in 1998. To classify health behavior patterns, cluster analysis was conducted. And to test the association of health behavior patterns with health status or health management, multiple logistic regression analysis were conducted. Results: The results and their implications of this study were as follows: 1. We identified six health behavior typologies : 67.8% of the sample had a good diet quality but showed sedentary activity level(good diet lifestyle) and 10.9% had heavy smoking behavior(smoking lifestyle). Individuals included in fitness lifestyle cluster(6.2%) had high physical activity level and those in drinking life style(2.6%) had had mainly large amount of alcohol. Zero point six percent of sample were included in hedonic lifestyle cluster, who showed poor health behaviors in all. Those included in passive lifestyle(11.9%) had no active health promoting activities but tended to avoid risk taking health behavior such as cigarette smoking and alcohol drinking. 2. As a result of logistic regression analysis, to compare with the individuals in good diet lifestyle, the prevalence of chronic diseases of those in fitness lifestyle showed higher and that of those in smoking lifestyle, drinking lifestyle, hedonic lifestyle, passive lifestyle showed lower than them, retrospectively. 3. Adjusting with general characteristics and health status, to compare with the individuals in good diet lifestyle, the proportion of those who had good health management practices in fitness lifestyle was higher, and the proportion of those who had health check in past 2 years was lower than them, retrospectively. Conclusions: There were some differences in health behavior patterns between rural population and national population, which influenced significantly on health status and health management practice of them. We suggested that the health promotion program for them be developed with considering these points.