• Journal of Environmental Policy
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• v.11 no.2
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• pp.3-16
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• 2012

Objectives of the Korean Environmental Conservation Value Assessment Map (ECVAM) is to evaluate environmental value used in comprehensive environmental information in order to encourage eco-friendly land use and management. The first research was conducted in 2001 to establish the evaluation items and the criteria of the ECVAM, and the first nationwide map was established in the period of 2003 to 2005. The maps are updated annually to reflect environmental changes of land. The evaluation items and the criteria have been modified based on feasibility studies to improve the accuracy of the maps. This study re-evaluated the ECVAMs from 2005 to 2010 with criteria used in current environment and analyzed the changes in the area of the maps in 6 years. This is also an investigation on the maps whether they are appropriate as an index for sustainable environmental monitoring. The result shows that the 1st grade level of the ECVAM area with the highest conservation value had been expanding since 2005. These changes were analyzed in terms of updating the 4th Forest Map (2008) produced once every 10 years, reflecting the new legal protected areas such as Baekdudaegan Protected Area(2010), and the environmental/ecological assessment items such as the National Ecological Network (2009). This mean the ECVAM are a monitoring index that integrates individual environmental indexes including the increase of forest age and diameter due to sustainable management of forest areas, and the change of conservation areas. Therefore, ECVAM can be used as a new index integrating national environmental indicators for monitoring changes of national environment and policy. In order to utilize the ECVAM, improving accuracy and reducing renewal cycle time of thematic maps are required.

• Journal of Service Research and Studies
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• v.13 no.4
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• pp.97-112
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• 2023

Background: In modern society, the importance of Public Design has become increasingly significant in contributing to the enhancement of urban functionality and the quality of life of citizens. Smart Public Facilities have played a pivotal role in enriching user experience by improving accessibility, convenience, and safety, and in elevating the value of the city. This research recognizes the importance of Public Facilities and explores the potential of Smart Public Facilities in solving urban challenges and progressing towards sustainable and Inclusive cities. Method: The literature review comprehensively examines existing theories and research results on Smart Public Facilities. The case study analyzes actual examples of Smart Public Facilities implemented in cities both domestically and internationally, drawing out effects, user satisfaction, and areas for improvement. Through analysis and discussion, the results of the case studies are evaluated, discussing the potential development of Smart Public Facilities. Results: Smart Public Facilities have been found to bring positive changes in various aspects such as urban management, energy efficiency, safety, and information accessibility. In terms of urban management, they play a crucial role in optimization, social Inclusiveness, environmental protection, fostering citizen participation, and promoting technological innovation. These changes create a new form of urban space, combining physical space and digital technology, enhancing the quality of life in the city. Conclusion: This research explores the implications, current status, and functions of Smart Public Facilities in service and design aspects, and their impact on the urban environment and the lives of citizens. In conclusion, Smart Public Facilities have brought about positive changes in the optimization of urban management, enhancement of energy efficiency, increased information accessibility, User-Centric design, increased interaction, and social Inclusiveness. Technological innovation and the integration of Public Facilities have made cities more efficient and proactive, enabling data-based decision-making and optimized service delivery. Such developments enable the creation of new urban environments through the combination of physical space and digital technology. The advancement of Smart Public Facilities indicates the direction of urban development, where future cities can become more intelligent, proactive, and User-Centric. Therefore, they will play a central role in Public Design and greatly contribute to improving the urban environment and the quality of life of citizens.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.63-83
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• 2019

Investors prefer to look for trading points based on the graph shown in the chart rather than complex analysis, such as corporate intrinsic value analysis and technical auxiliary index analysis. However, the pattern analysis technique is difficult and computerized less than the needs of users. In recent years, there have been many cases of studying stock price patterns using various machine learning techniques including neural networks in the field of artificial intelligence(AI). In particular, the development of IT technology has made it easier to analyze a huge number of chart data to find patterns that can predict stock prices. Although short-term forecasting power of prices has increased in terms of performance so far, long-term forecasting power is limited and is used in short-term trading rather than long-term investment. Other studies have focused on mechanically and accurately identifying patterns that were not recognized by past technology, but it can be vulnerable in practical areas because it is a separate matter whether the patterns found are suitable for trading. When they find a meaningful pattern, they find a point that matches the pattern. They then measure their performance after n days, assuming that they have bought at that point in time. Since this approach is to calculate virtual revenues, there can be many disparities with reality. The existing research method tries to find a pattern with stock price prediction power, but this study proposes to define the patterns first and to trade when the pattern with high success probability appears. The M & W wave pattern published by Merrill(1980) is simple because we can distinguish it by five turning points. Despite the report that some patterns have price predictability, there were no performance reports used in the actual market. The simplicity of a pattern consisting of five turning points has the advantage of reducing the cost of increasing pattern recognition accuracy. In this study, 16 patterns of up conversion and 16 patterns of down conversion are reclassified into ten groups so that they can be easily implemented by the system. Only one pattern with high success rate per group is selected for trading. Patterns that had a high probability of success in the past are likely to succeed in the future. So we trade when such a pattern occurs. It is a real situation because it is measured assuming that both the buy and sell have been executed. We tested three ways to calculate the turning point. The first method, the minimum change rate zig-zag method, removes price movements below a certain percentage and calculates the vertex. In the second method, high-low line zig-zag, the high price that meets the n-day high price line is calculated at the peak price, and the low price that meets the n-day low price line is calculated at the valley price. In the third method, the swing wave method, the high price in the center higher than n high prices on the left and right is calculated as the peak price. If the central low price is lower than the n low price on the left and right, it is calculated as valley price. The swing wave method was superior to the other methods in the test results. It is interpreted that the transaction after checking the completion of the pattern is more effective than the transaction in the unfinished state of the pattern. Genetic algorithms(GA) were the most suitable solution, although it was virtually impossible to find patterns with high success rates because the number of cases was too large in this simulation. We also performed the simulation using the Walk-forward Analysis(WFA) method, which tests the test section and the application section separately. So we were able to respond appropriately to market changes. In this study, we optimize the stock portfolio because there is a risk of over-optimized if we implement the variable optimality for each individual stock. Therefore, we selected the number of constituent stocks as 20 to increase the effect of diversified investment while avoiding optimization. We tested the KOSPI market by dividing it into six categories. In the results, the portfolio of small cap stock was the most successful and the high vol stock portfolio was the second best. This shows that patterns need to have some price volatility in order for patterns to be shaped, but volatility is not the best.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.583-597
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• 2020

This study analyzed how elderly people's perception of social welfare affects social welfare service and social welfare policy satisfaction by paying attention to the use of social welfare services and satisfaction with social welfare policies. In order to achieve this research goal, 465 people aged 60 or older who completed responses to the additional survey were collected and analyzed as research targets based on data from the Korea Welfare Panel, which is accumulated by the Korea Institute for Health and Social Affairs and Seoul National University's Social Welfare Research Institute. The results of this study are as follows. First, "Awareness of welfare for the elderly (recognition of welfare expenditure, recognition of welfare targets, recognition of welfare tax increases)" was found to have a negative impact on "use of social services." Second, "Awareness of welfare for the elderly (recognition of welfare expenditure, recognition of welfare targets, recognition of welfare tax increases)" was found to have a negative impact on "satisfaction with social welfare policies." Third, the impact of the recognition of welfare for the elderly on the use of social services was found to be different according to the demographic characteristics (education level, income level, educational background, gender). Fourth, according to the "population statistical characteristics (education level, income level, educational background, gender)" the impact of the recognition of welfare for the elderly on the satisfaction of social welfare policy was shown to be different. The implications of this study are that we looked at multi-dimensional welfare awareness and social service use experience together as factors affecting social welfare policy satisfaction. In other words, it is meaningful that the government focused on welfare awareness based on individual values and subjective perceptions as an influence on social welfare policy satisfaction, and sought practical alternatives to welfare policies and welfare sites by examining whether the experience of using social services in relation to welfare awareness and social welfare policy satisfaction among the elderly.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Korean Journal of Soil Science and Fertilizer
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• v.36 no.3
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• pp.163-179
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• 2003

Multifunctionality of agriculture which is not traded on the market now has been an important international issue in that it environmental and public benefits. We carried out to modify and to update the function of upland farming on flood prevention and fostering water resources. Economic values of environmental benefits were evaluated by replacement cost methods. Models to evaluate the function of preventing flood were selected as: (1)precipitation(flood-inducing) - runoff(A), (2) soil depth ${\times}$ soil air phase, (3) precipitation (flood-inducing) - runoff(B), (4) soil depth ${\times}$ effective porosity of soil. Models to estimate the function of fostering water resources were (1) saturated hydraulic conductivity (Ks) ${\times}$ duration of saturation(days) ${\times}$ (1-ratio of water flow directly into river), (2) precipitation ${\times}$ ratio of water fostered by rain resources ${\times}$ (area of upland/total land area), and (3) soil water retention quantity(under standing crop or tree) - SWRQ(in bare soil). Function of preventing flood was $883Mg\;ha^{-1}$ of water per year and 645 million Mg for the whole upland area. Function of fostering water resources was $94.1Mg\;ha^{-1}$ of water per year and 69 million Mg for the whole upland area. The value of flood-preventing function evaluated by replacement cost methods was estimated 1,428 billion won per year as compared to the cost for dam construction. The value of water resource fostering were estimated 8.6 billion won in the price of living water.

• (The)Study of the Eastern Classic
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• no.69
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• pp.45-82
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• 2017

This paper aims at concrete examination of the 'Official Road(官路)' of the late Joseon Dynasty through government administration of the 17th - 18th century 'Junsangseo(典牲署)'. Until now, the study of the central political system in the Joseon Dynasty was mainly studied by the politically important bureaucrat 'Dangsanggwan(堂上官)', and even if he studied the 'Official Road(官路)', he was a student from the a graduate of Mungwa(文科) and the 'Clean and imfortant Official(淸要職)' connected with it It was examined mainly. As a result, this research attempts to elucidate the routes of 'non - Clean and imfortant Official(非淸要職)' who have not been studied so far. However, it is difficult to deal with all the 'lower officials(參下官)' reaching 263 in total, so it was targeted at the 'Junsangseo(典牲署)' where the 'List of official(先生案)' exists in the 17th - 18th century. In chapter 2, we examined the historical value of 'List of official(先生案)' and were able to secure the confidence of the materials. In Chapter 3, we specifically examined the origins of officials from the 'Junsangseo(典牲署)', the official route, and the occupation. As a result, the 'Junsangseo(典牲署)' 'lower officials(參下官)' was predominantly from the 'Munum(門蔭)'. In addition, I confirmed that I was stepping on a public road that roughly promoted one rank. The number of days in office has also been promoted satisfying the court occupation days. Although this is an analysis limited to 'Junsangseo(典牲署)', it seems that 'lower officials(參下官)' of 'Junsangseo(典牲署)' had gone through routes and routes that were roughly similar to the 'lower officials' of the main office. If we can assume this, we can understand the character of the late Joseon Dynasty 'lower officials(參下官)' by understanding the character of 'lower officials(參下官)' of 'Junsangseo(典牲署)'. To declare this, more case analysis is necessary, and it is necessary to convert a lot of 'List of official(先生案)' data scattered nationwide into DB.

• 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.

• Cartoon and Animation Studies
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• s.41
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• pp.455-486
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• 2015

The 3D printing technology, which started from the patent registration in 1986, was a technology that did not attract attention other than from some companies, due to the lack of awareness at the time. However, today, as expiring patents are appearing after the passage of 20 years, the price of 3D printers have decreased to the level of allowing purchase by individuals and the technology is attracting attention from industries, in addition to the general public, such as by naturally accepting 3D and to share 3D data, based on the generalization of online information exchange and improvement of computer performance. The production capability of 3D printers, which is based on digital data enabling digital transmission and revision and supplementation or production manufacturing not requiring molding, may provide a groundbreaking change to the process of manufacturing, and may attain the same effect in the character merchandise sector. Using a 3D printer is becoming a necessity in various figure merchandise productions which are in the forefront of the kidult culture that is recently gaining attention, and when predicting the demand by the industrial sites related to such character merchandise and when considering the more inexpensive price due to the expiration of patents and sharing of technology, expanding opportunities and sectors of employment and cultivating manpower that are able to engage in further creative work seems as a must, by introducing education courses cultivating manpower that can utilize 3D printers at the education field. However, there are limits in the information that can be obtained when seeking to introduce 3D printers in school education. Because the press or information media only mentions general information, such as the growth of the industrial size or prosperous future value of 3D printers, the research level of the academic world also remains at the level of organizing contents in an introductory level, such as by analyzing data on industrial size, analyzing the applicable scope in the industry, or introducing the printing technology. Such lack of information gives rise to problems at the education site. There would be no choice but to incur temporal and opportunity expenses, since the technology would only be able to be used after going through trials and errors, by first introducing the technology without examining the actual information, such as through comparing the strengths and weaknesses. In particular, if an expensive equipment introduced does not suit the features of school education, the loss costs would be significant. This research targeted general users without a technology-related basis, instead of specialists. By comparing the strengths and weaknesses and analyzing the problems and matters requiring notice upon use, pursuant to the representative technologies, instead of merely introducing the 3D printer technology as had been done previously, this research sought to explain the types of features that a 3D printer should have, in particular, when required in education relating to the development of figure merchandise as an optional cultural contents at cartoon-related departments, and sought to provide information that can be of practical help when seeking to provide education using 3D printers in the future. In the main body, the technologies were explained by making a classification based on a new perspective, such as the buttress method, types of materials, two-dimensional printing method, and three-dimensional printing method. The reason for selecting such different classification method was to easily allow mutual comparison of the practical problems upon use. In conclusion, the most suitable 3D printer was selected as the printer in the FDM method, which is comparatively cheap and requires low repair and maintenance cost and low materials expenses, although rather insufficient in the quality of outputs, and a recommendation was made, in addition, to select an entity that is supportive in providing technical support.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.171-191
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• 2020

This study focused on digital music, which is the most valuable cultural asset in the modern society and occupies a particularly important position in the flow of the Korean Wave. Digital music was collected based on the "Gaon Chart," a well-established music chart in Korea. Through this, the changes in the ranking of the music that entered the chart for 73 weeks were collected. Afterwards, patterns with similar characteristics were derived through time series cluster analysis. Then, a descriptive analysis was performed on the notable features of each pattern. The research process suggested by this study is as follows. First, in the data collection process, time series data was collected to check the ranking change of digital music. Subsequently, in the data processing stage, the collected data was matched with the rankings over time, and the music title and artist name were processed. Each analysis is then sequentially performed in two stages consisting of exploratory analysis and explanatory analysis. First, the data collection period was limited to the period before 'the music bulk buying phenomenon', a reliability issue related to music ranking in Korea. Specifically, it is 73 weeks starting from December 31, 2017 to January 06, 2018 as the first week, and from May 19, 2019 to May 25, 2019. And the analysis targets were limited to digital music released in Korea. In particular, digital music was collected based on the "Gaon Chart", a well-known music chart in Korea. Unlike private music charts that are being serviced in Korea, Gaon Charts are charts approved by government agencies and have basic reliability. Therefore, it can be considered that it has more public confidence than the ranking information provided by other services. The contents of the collected data are as follows. Data on the period and ranking, the name of the music, the name of the artist, the name of the album, the Gaon index, the production company, and the distribution company were collected for the music that entered the top 100 on the music chart within the collection period. Through data collection, 7,300 music, which were included in the top 100 on the music chart, were identified for a total of 73 weeks. On the other hand, in the case of digital music, since the cases included in the music chart for more than two weeks are frequent, the duplication of music is removed through the pre-processing process. For duplicate music, the number and location of the duplicated music were checked through the duplicate check function, and then deleted to form data for analysis. Through this, a list of 742 unique music for analysis among the 7,300-music data in advance was secured. A total of 742 songs were secured through previous data collection and pre-processing. In addition, a total of 16 patterns were derived through time series cluster analysis on the ranking change. Based on the patterns derived after that, two representative patterns were identified: 'Steady Seller' and 'One-Hit Wonder'. Furthermore, the two patterns were subdivided into five patterns in consideration of the survival period of the music and the music ranking. The important characteristics of each pattern are as follows. First, the artist's superstar effect and bandwagon effect were strong in the one-hit wonder-type pattern. Therefore, when consumers choose a digital music, they are strongly influenced by the superstar effect and the bandwagon effect. Second, through the Steady Seller pattern, we confirmed the music that have been chosen by consumers for a very long time. In addition, we checked the patterns of the most selected music through consumer needs. Contrary to popular belief, the steady seller: mid-term pattern, not the one-hit wonder pattern, received the most choices from consumers. Particularly noteworthy is that the 'Climbing the Chart' phenomenon, which is contrary to the existing pattern, was confirmed through the steady-seller pattern. This study focuses on the change in the ranking of music over time, a field that has been relatively alienated centering on digital music. In addition, a new approach to music research was attempted by subdividing the pattern of ranking change rather than predicting the success and ranking of music.