• Journal of Environmental Science International
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• v.16 no.4
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• pp.523-532
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• 2007

This study utilized the 1/25,000 topographic map of the upper area from the Geum-ho watermark located at the middle of Geum-ho river from the National Geographic Information Institute. For the analysis, first, the influence of the size of critical area to the hydro topographic factors was examined changing grid size to $10m{\times}10m,\;30m{\times}30m\;and\;50m{\times}50m$, and the critical area for the formation of a river to $0.01km^2{\sim}0.50km^2$. It is known from the examination result of watershed morphology according to the grid size that the smaller grid size, the better resolution and accuracy. And it is found, from the analysis result of the degree of the river according to the minimum critical area for each grid size, that the grid size does not affect on the degree of the river, and the number of rivers with 2nd and higher degree does not show remarkable difference while there is big difference in the number of 1st degree rivers. From the results above, it is thought that the critical area of $0.15km^2{\sim}0.20km^2$ is appropriate for formation of a river being irrelevant to the grid size in extraction of hydro topographic parameters that are used in the runoff analysis model using topographic maps. Therefore, the GIUH model applied analysis results by use of the river level difference law proposed in this study for the explanation on the outflow response-changing characters according to the decision of a critical value of a minimum level difference river, showed that, since an ogival occurrence time and an ogival flow volume are very significant in a flood occurrence in case of not undertow facilities, the researcher could obtain a good result for the forecast of river outflow when considering a convenient application of the model and an easy acquisition of data, so it's judged that this model is proper as an algorism for the decision of a critical value of a river basin.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1319-1326
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• 2019

The KARI(Korea Aerospace Research Institute) operates the government satellite information application consultation to cope with ever-increasing demand for satellite images in the public sector, and carries out various support projects including the generation and provision of mosaic images on the Korean Peninsula every year to enhance user convenience and promote the use of satellite images. In particular, the government has wanted to increase the utilization of mosaic images on the Korean Peninsula and seek to classify and update mosaic images so that users can use them in their businesses easily. However, it is necessary to test and verify whether the classification results of the mosaic images can be utilized in the field since the original spectral information is distorted during pan-sharpening and color balancing, and there is a limitation that only R, G, and B bands are provided. Therefore, in this study, the reliability of the classification result of the mosaic image was compared to the result of KOMPSAT-3 image. The study found that the accuracy of the classification result of KOMPSAT-3 image was between 81~86% (overall accuracy is about 85%), while the accuracy of the classification result of mosaic image was between 69~72% (overall accuracy is about 72%). This phenomenon is interpreted not only because of the distortion of the original spectral information through pan-sharpening and mosaic processes, but also because NDVI and NDWI information were extracted from KOMPSAT-3 image rather than from the mosaic image, as only three color bands(R, G, B) were provided. Although it is deemed inadequate to distribute classification results extracted from mosaic images at present, it is believed that it will be necessary to explore ways to minimize the distortion of spectral information when making mosaic images and to develop classification techniques suitable for mosaic images as well as the provision of NIR band information. In addition, it is expected that the utilization of images with limited spectral information could be increased in the future if related research continues, such as the comparative analysis of classification results by geomorphological characteristics and the development of machine learning methods for image classification by objects of interest.

• Journal of the Korea Society of Computer and Information
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• v.8 no.2
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• pp.51-56
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• 2003

The structuring of Web information supports a strong user side viewpoint that a user wants his/her own needs on snooping a specific Web site. Not only the depth first algorithm or the breadth-first algorithm, but also the Web information is abstracted to a hierarchical structure. A prototype system is suggested in order to visualize and to represent a semantic significance. As a motivating example, the Web test site is suggested and analyzed with respect to several keywords. As a future research, the Web site model should be extended to the whole WWW and an accurate assessment function needs to be devised by which several suggested models should be evaluated.

• Archives of design research
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• no.16
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• pp.41-51
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• 1996

A matter of primary concern about all design is concentrated on how to create more valuable things to allow people to live an affluent life. However, it is very difficult to achieve the goal because every design work is changed in accordance with given situatio ns. In this sense, it is significant to study on biodesign because it can be both a basic principle and a fudamantal index to show the way of new design direction. Accordingly, the main purpose of the thesis is to catch every meaning of bio-design and to close analyze its factors in order to generate more fresh ideas and put them into practice. The thesis is composed of five Chapters: Introduction, Background of bio-design, Principle of bio-design, Practice of bio-design, and Conclusion. In Introduction, the purpose and background of the study are presented. I n Chapter 2, source of design orgin, vernacular design, and design for life are researched. In Chapter 3, organic order. the survial of the fittest, and subjective & objective are considered. In Chapter 4, hi-tech & hi-touch, criteria of problem -solving, and harmony with nature are searched. In Conclusion, some suggestive words on the study are mentioned.

• Korea Science and Art Forum
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• v.37 no.4
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• pp.297-308
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• 2019

Air pollution due to the fine dust level updating every day, and the problem of indoor air pollution due to ventilation difficulties and indoor discharge pollutants is also serious. In order to improve the indoor air quality, the air purification effect using the plants is prominent. In this study was started to investigated the living environment of modern people, the risk of indoor air pollution and the improvement function of plants, and to activate plant application. The purpose of this study is to analyze the main functions and design status of domestic and overseas plant - related applications, and to understand the actual use of modern plant applications and to help them learn more convenient plant - related knowledge. Therefore, this paper attempted to establish a basis for suggesting a new plant application by conducting a survey on the health effects of indoor air pollution and user awareness of plant - related applications. The results and contents of the study are as follows. First, as a theoretical review, indoor air pollution is more dangerous to modern people who have a high proportion of indoor living time and adversely affects their health. In order to solve such a problem, it has been shown that air conditioning and stress reduction can be effectively achieved by placing plants in the indoor space. Second, the analysis of the previous study shows the risk of indoor air pollution and its adverse effects on health. In addition, I have been able to find some researches related to the improvement of the indoor air by using the air purifying plants, and I can see the improvement of the user's behavior through the development or improvement of the application. Third, as a result of the survey on the status of domestic and overseas plant application, the main function of the application having high installation number was watering notification, provision of basic information of plants, and most of the functions were plant discerment through cameras. Fourth, most of the survey respondents have either raised or raised plants. Those who have little experience with plant applications have also shown positive feedback in the future on the use of plant-related applications. In addition, due to social problems such as air pollution, air purification using plants and functional plants showed high interest. Based on these results, we propose the need for a multi-functional plant application that can improve the indoor air pollution and facilitate the provision of information related to it.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.25-38
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• 2019

Selecting high-quality information that meets the interests and needs of users among the overflowing contents is becoming more important as the generation continues. In the flood of information, efforts to reflect the intention of the user in the search result better are being tried, rather than recognizing the information request as a simple string. Also, large IT companies such as Google and Microsoft focus on developing knowledge-based technologies including search engines which provide users with satisfaction and convenience. Especially, the finance is one of the fields expected to have the usefulness and potential of text data analysis because it's constantly generating new information, and the earlier the information is, the more valuable it is. Automatic knowledge extraction can be effective in areas where information flow is vast, such as financial sector, and new information continues to emerge. However, there are several practical difficulties faced by automatic knowledge extraction. First, there are difficulties in making corpus from different fields with same algorithm, and it is difficult to extract good quality triple. Second, it becomes more difficult to produce labeled text data by people if the extent and scope of knowledge increases and patterns are constantly updated. Third, performance evaluation is difficult due to the characteristics of unsupervised learning. Finally, problem definition for automatic knowledge extraction is not easy because of ambiguous conceptual characteristics of knowledge. So, in order to overcome limits described above and improve the semantic performance of stock-related information searching, this study attempts to extract the knowledge entity by using neural tensor network and evaluate the performance of them. Different from other references, the purpose of this study is to extract knowledge entity which is related to individual stock items. Various but relatively simple data processing methods are applied in the presented model to solve the problems of previous researches and to enhance the effectiveness of the model. From these processes, this study has the following three significances. First, A practical and simple automatic knowledge extraction method that can be applied. Second, the possibility of performance evaluation is presented through simple problem definition. Finally, the expressiveness of the knowledge increased by generating input data on a sentence basis without complex morphological analysis. The results of the empirical analysis and objective performance evaluation method are also presented. The empirical study to confirm the usefulness of the presented model, experts' reports about individual 30 stocks which are top 30 items based on frequency of publication from May 30, 2017 to May 21, 2018 are used. the total number of reports are 5,600, and 3,074 reports, which accounts about 55% of the total, is designated as a training set, and other 45% of reports are designated as a testing set. Before constructing the model, all reports of a training set are classified by stocks, and their entities are extracted using named entity recognition tool which is the KKMA. for each stocks, top 100 entities based on appearance frequency are selected, and become vectorized using one-hot encoding. After that, by using neural tensor network, the same number of score functions as stocks are trained. Thus, if a new entity from a testing set appears, we can try to calculate the score by putting it into every single score function, and the stock of the function with the highest score is predicted as the related item with the entity. To evaluate presented models, we confirm prediction power and determining whether the score functions are well constructed by calculating hit ratio for all reports of testing set. As a result of the empirical study, the presented model shows 69.3% hit accuracy for testing set which consists of 2,526 reports. this hit ratio is meaningfully high despite of some constraints for conducting research. Looking at the prediction performance of the model for each stocks, only 3 stocks, which are LG ELECTRONICS, KiaMtr, and Mando, show extremely low performance than average. this result maybe due to the interference effect with other similar items and generation of new knowledge. In this paper, we propose a methodology to find out key entities or their combinations which are necessary to search related information in accordance with the user's investment intention. Graph data is generated by using only the named entity recognition tool and applied to the neural tensor network without learning corpus or word vectors for the field. From the empirical test, we confirm the effectiveness of the presented model as described above. However, there also exist some limits and things to complement. Representatively, the phenomenon that the model performance is especially bad for only some stocks shows the need for further researches. Finally, through the empirical study, we confirmed that the learning method presented in this study can be used for the purpose of matching the new text information semantically with the related stocks.

• Journal of the Korean Society of Clothing and Textiles
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• v.28 no.12 s.138
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• pp.1571-1582
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• 2004

Consumer's impulse buying behavior is extensive in everyday contexts. Credit cards promote spending by making the transaction simpler and by removing the immediate need for money. College students grown up in a credit card society attain cards at college's time and keep cards for 10 years over. In an effort to extend understanding of consumer behavior across cultures, this paper examines the cultural differences of impulse buying behavior and credit card use between Korean and American college students, and to investigate the relationships between impulse buying behavior and credit card use in each group. Data were obtained from student credit card users attending universities in metropolitan areas in Korea(N=154) and America(N=194). Data were analyzed using by Confirmatory Factor Analysis, MANOVA, MDA, and Regression. The results indicated there are significant differences of fashion-oriented impulse buying and credit card use between American and Korean college students. The impulse buying behavior is likely to increase for both Korean and American students who use credit cards for spending. Findings suggest that credit card use is important in predicting impulse buying behavior across these two cultures. Implications are drawn for the increasing global phenomenon impulse buying behavior and credit card use.

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.629-636
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• 2008

In recent years, a large number of robots have been developed in several countries, and these robots have been built for the purpose to appeal to users by well designed human-robot interaction. In case of the robots developed so far, they show proper reactions only when there is a certain input. On the other hands, they cannot perform in a standby mode which means there is no input. In other words, if a robot does not make any motion in standby mode, users may feel that the robot is being turned-off or even out of work. Especially, the social service robots maintain the standby status after finishing a certain task. In this period of time, if the robots can make human-like behavioral patterns such like a person in help desk, then they are expected to make people feels that they are alive and is more likely to interact with them. It is said that even if there is no interaction with others or the environment, people normally reacts to internal or external stimuli which are created by themselves such as moving their eyes or bodies. In order to create robotic behavioral patterns for standby mode, we analyze the actual facial expression and behavior from people who are in neutral affective emotion based on ethnographic methodology and apply extracted characteristics to our robots. Moreover, by using the robots which can show those series of expression and action, our research needs to find that people can feel like they are alive.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.869-874
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• 2005

In the recent years there has been an increase of service competition in the activity of product selling, especially in the extension of warranty coverage and qualify. The variables in connection with the service competition are not crisp, and required the expertise of the production line. It thus becomes all the more necessary to use subtler tools as decision supports. These problems are typical not only of product companies but also of financial organizations, credit institutions, insurance, which need predictions of credibility for firms or persons in which they have any kind of interest. A suitable approach for minimizing the risk is to use a knowledge-based system. Most often expert systems are not standalone programs, but are embedded into a larger application. The aim of this paper is to discuss an approach for developing an embedded fuzzy expert system with respect to the product selling policy, especially to present the decision system of automobile selling activity around the extension of warranty coverage and quality. We use the MATLAB tools which integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation. Also, we present the API functions embedding into the existing application.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.135-142
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• 2014

As interest in social safety has recently increased at the national level, the various activities which can effectively prevent crimes are being carried out. Because the existing maps related to crimes provide the information about the present condition of crimes by administrative district for users, women and pedestrians who go by night could not actually grasp safe roads in advance. Therefore, this study developed the methodology that can easily extract dangerous areas due to crimes by the digital map 2.0. In the digital map 2.0, location and attribute information of center-lines of roads and building layers were used to find dangerous areas of crimes in these layers. Pavement materials and road width which are already built by the attribute information were used in the center-lines of roads. Crossing angles that roads and roads cross each other were additionally extracted and utilized. The attribute information about building types were input in the building layers of the digital map 2.0. The areas that are more the threshold values set by totaling up all the risk scores when considering pavement materials, road width, crossing angles of road, and building types in the center-lines of roads and road crossings were extracted as the dangerous areas that crimes can occur. Verification of the developed methodology was done by experiment. In the spatial apsect, the dangerous areas of crimes could be found by using the digital 2.0, roads, and building layers only through the experiment. In the administrative aspect to prevent crimes, additional installation of safety facilities such as street lights and security lights in the identified areas which are vulnerable for crimes is thought to be increasing safety of dangerous areas.