• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of Practical Agriculture & Fisheries Research
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• v.20 no.1
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• pp.107-123
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• 2018

The global impact of climate change on agriculture is now increasing. The purpose of this study was to investigate the effect of climate change on livestock productivity. The variables that have the greatest influence on climate change factors were examined through previous studies and expert surveys. We also used the actual productivity data of livestock farmers to investigate the relationship with climate change. In order to evaluate the climate for changes in livestock productivity, national representative data (such as bullocks, dairy, pigs, laying hens, and broilers) were surveyed in Korea. Also, to select and classify evaluation indexes, we selected climate change factor variables as prior studies and studied the weighting factor of climate variable factors. In this study, the researchers of industry, academia, and farmers in the livestock sector conducted questionnaires on the indicators of vulnerability to climate change using experts, and then weighed the selected indicators using the hierarchical analysis process (AHP). In order to verify the validity of the evaluation index, was examined using domestic climate data (temperature, precipitation, humidity, etc.). Correlation and regression analysis were performed. The empirical relationship between climate change and livestock productivity was examined through this study. As a result, we used data with high reliability of statistical analysis and found that there are significant variables.

• Journal of Chest Surgery
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• v.29 no.6
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• pp.606-613
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• 1996

Cardiac transplantation has been the treatment of patients with end-stage heart disease since it was first performed in 1967. In Korea the first case was performed in 1992 and 42 patients underwent heart trans- plantation so far. The purpose of this article is to report short-term result of cardiac transplantation at our center. Between April 1994 and September 1995, 14 patients had undergone orthotopic heart transplantations. There was 12 male and 2 female patients. Mea recipient age was 34 years(range 11 to 54 years) and mean donor age was 28.4 years(16 to 50 years). Mean graft ischemic time was 120.7minutes(80 to 280 minutes). The follow-up period after transplantation was 11 months(3 to 17 months). Recipient diagnosis included dilated cardiomyopathy in 10, ischemic cardiomyopathy in 2, valvular cardiomyopathy in 1, congenital complex heart disease in 1 patient. The preoperative status of the recipients were state I (50%) and ll (50%) by UNOS classification and class 111 (5 patients) and class IV (9) by NYHA functional class. All patients were treated with triple-drug immunosuppression (cyclosporine, azathioprine, steroid) and induction with RATG. The rejection episodes were 5 times in 3 patients during the follow-up. Causes of infection were aspergillosis (2), and hepes zoster (1), CMV pneumonitis (1). Permanent pace- maker was inserted in 1 patient. Currently 9 patients are alive with seven patients in WYHA functional class I and two in class l . The ejection fraction increased from preoperative value of 19.9 $\pm$ 3.4% to postoperative value of 69.0 $\pm$ 5.6%. The causes of death were cellular rejection (1),chronic graft failure due to size-mismatching (1),respirat- oxy insufficiency due to asthma attack (1), subarachnoid hemorrhage (1), and RIO humoral rejection (1).

• Cartoon and Animation Studies
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• s.28
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• pp.235-263
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• 2012

Regarding the theme park business as an area of cultural content business, this study focuses on the trend of pursuing indoor theme parks as a small-scale small capital strategy escaped from the existing approach oriented to large-scale outdoor complex theme parks. It is because although existing large-scale outdoor complex theme parks require the capital with the scale of hundreds of billion won and also high-level technique and the latest operational know-how that they have a great barrier for new entry as well as enormous risk, the rent indoor theme parks succeed in market entry with efficient risk management and flexible market strategies. Thereupon, this study examines the current status of the children's indoor theme park market with Korean characters as their theme as a new market among the indoor theme parks and also investigates the market strategies of this market in the two aspects of expansion: the expansion of Korean characters' property value and the expansion of the local theme park market. For that, this article reviewed the advanced researches on theme parks and divided the types of theme parks existing in Korea with the criteria of classification by space and theme or classification by main users. Also, among the children's indoor theme parks with Korean characters as their theme, this study visited five ones located in the capital area to examine the current status. And about two located in the capital area and also four in the local area, the current data were received from the persons in charge of the companies for analysis. Also, with the subjects of spectators visiting the 'DIBO VILLAGE, Cheonggye-cheon' newly opened on April 25th, 2012, the research on satisfaction was conducted for analysis. Through that, this study analyzed the structure of the existing children's indoor theme park business with Korean characters as their theme and suggested the ground to analyze the effectiveness of market strategies being implemented. It is expected that this study will establish the clues of systematic and profound discussion for the indoor theme park business that can be said to be the niche market of the theme park business and allow the small-scale areal indoor theme parks to be examined as a significant business model for the local theme park industry. In the aspect of character business as well, it is expected that this will give a chance to establish a new model of spatial storytelling expansion in terms of the property value of Korean animation characters.

• Korean Journal of Heritage: History & Science
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• v.43 no.3
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• pp.144-179
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• 2010

Investigation into iron manufacture relics has been active since 1970s, especially accelerated in 1990s across the country. Consideration of the importance of production site relics has lately attracted attention to iron manufacture relics. Methodological studies of the investigation into iron manufacture relics, however, were less made compared with those of the investigation into tomb, dwelling, or swampy place relics. It is because the process of iron manufacture is too complicated to understand and also requires professional knowledge of metal engineering. With the recognition of these problems this research is to form an opinion about how to excavate, to rearrange and classify, and to examine iron manufacture relics, based upon the understanding of the nature of iron, iron production process, and metal engineering features of related relics like slag, iron lumps and so on. This research classifies iron manufacture relics into seven types according to the production process; mining, smelting, refining, tempering, melting, steelmaking, and the others. Then it arranges methods to survey in each stage of field study, trial digging, and excavation. It also explains how to classify and examine excavated relics, what field of natural science to be used to know the features of relics, and what efforts have been made to reconstruct a furnace and what their problems were, making the best use of examples, drawings, and photos. It comes to the conclusion, in spite of the lack of in-depth discussion on application and development of various investigation methods, that iron manufacture relics can be classified according to the production process, that natural sciences should be applied to get comprehensive understanding of relics as well as archeological knowledge, and that efforts to reconstruct a furnace should be continued from the aspect of experimental archeology.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Journal of Korea Port Economic Association
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• v.27 no.1
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• pp.75-94
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• 2011

This paper is concerned about applying the AHP(Analytic Hierarchy Process) for a priority analysis of equipment operation plan to improve productivity of the container terminal in Gwangyang port. In this study, main elements of container terminal are assumed as into yard equipment area, transport equipment area, berth equipment area and C/Center area. A questionnaire is used to collect the opinions of equipment operating department and operational planning department. On the whole, the result of the analyses reveals that the most important area is yard equipment area. Examining each department is responses, equipment operating department preferred the C/Center area to other areas, on the other hand, operational planning department preferred yard equipment area. The result of this study suggests some guidelines for deciding priority of operation plan in the container terminal.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.20-27
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• 2006

Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.9-18
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• 2020

Recently, studies of integrated management platform and performance-based maintenance decision-marking systems have proceeded to the efficient management of port facilities. The purpose of this study was to manage and operate port facilities based on performance and to provide long-term durability and budgetary execution. Thus, it is essential to secure basic data to be analyzed in an integrated platform and decision-marking system. This study derived the data linkage measures to secure port facility design and management information. The target of deriving the data linkage was the POMS (Port Facility Management System) currently in operation by the MOF (Ministry of Oceans and Fisheries). To derive data linkage, analyze the database of POMS and select the data required for the operation-integrated platform and decision-marking system. The final data linkage target was determined by compiling the requirements of the relevant experts and selecting the final target of three groups (port and facility information, management information, and user information). As a result, the API interface design was prepared for detailed linked data and data linkage framework between the linkage data of POMS. The provision of real-time data linkage between POMS and integrated platform is expected to improve the operational efficiency of the integrated platform.