• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.101-107
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• 2014

With the development of online service, recent forms of databases have been changed from static database structures to dynamic stream database structures. Previous data mining techniques have been used as tools of decision making such as establishment of marketing strategies and DNA analyses. However, the capability to analyze real-time data more quickly is necessary in the recent interesting areas such as sensor network, robotics, and artificial intelligence. Landmark window-based frequent pattern mining, one of the stream mining approaches, performs mining operations with respect to parts of databases or each transaction of them, instead of all the data. In this paper, we analyze and evaluate the techniques of the well-known landmark window-based frequent pattern mining algorithms, called Lossy counting and hMiner. When Lossy counting mines frequent patterns from a set of new transactions, it performs union operations between the previous and current mining results. hMiner, which is a state-of-the-art algorithm based on the landmark window model, conducts mining operations whenever a new transaction occurs. Since hMiner extracts frequent patterns as soon as a new transaction is entered, we can obtain the latest mining results reflecting real-time information. For this reason, such algorithms are also called online mining approaches. We evaluate and compare the performance of the primitive algorithm, Lossy counting and the latest one, hMiner. As the criteria of our performance analysis, we first consider algorithms' total runtime and average processing time per transaction. In addition, to compare the efficiency of storage structures between them, their maximum memory usage is also evaluated. Lastly, we show how stably the two algorithms conduct their mining works with respect to the databases that feature gradually increasing items. With respect to the evaluation results of mining time and transaction processing, hMiner has higher speed than that of Lossy counting. Since hMiner stores candidate frequent patterns in a hash method, it can directly access candidate frequent patterns. Meanwhile, Lossy counting stores them in a lattice manner; thus, it has to search for multiple nodes in order to access the candidate frequent patterns. On the other hand, hMiner shows worse performance than that of Lossy counting in terms of maximum memory usage. hMiner should have all of the information for candidate frequent patterns to store them to hash's buckets, while Lossy counting stores them, reducing their information by using the lattice method. Since the storage of Lossy counting can share items concurrently included in multiple patterns, its memory usage is more efficient than that of hMiner. However, hMiner presents better efficiency than that of Lossy counting with respect to scalability evaluation due to the following reasons. If the number of items is increased, shared items are decreased in contrast; thereby, Lossy counting's memory efficiency is weakened. Furthermore, if the number of transactions becomes higher, its pruning effect becomes worse. From the experimental results, we can determine that the landmark window-based frequent pattern mining algorithms are suitable for real-time systems although they require a significant amount of memory. Hence, we need to improve their data structures more efficiently in order to utilize them additionally in resource-constrained environments such as WSN(Wireless sensor network).

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.63-75
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• 2016

Aquaculture has historically delivered marine products because the country is surrounded by ocean on three sides. Surveys on production have been conducted recently to systematically manage aquaculture facilities. Based on survey results, pricing controls on marine products has been implemented to stabilize local fishery resources and to ensure minimum income for fishermen. Such surveys on aquaculture facilities depend on manual digitization of aerial photographs each year. These surveys that incorporate manual digitization using high-resolution aerial photographs can accurately evaluate aquaculture with the knowledge of experts, who are aware of each aquaculture facility's characteristics and deployment of those facilities. However, using aerial photographs has monetary and time limitations for monitoring aquaculture resources with different life cycles, and also requires a number of experts. Therefore, in this study, we investigated an automatic prototype system for detecting boundary information and monitoring aquaculture facilities based on satellite images. KOMPSAT-3 (13 Scene), a local high-resolution satellite provided the satellite imagery collected between October and April, a time period in which many aquaculture facilities were operating. The ANN classification method was used for automatic detecting such as cage, longline and buoy type. Furthermore, shape files were generated using a digitizing image processing method that incorporates polygon generation techniques. In this study, our newly developed prototype method detected aquaculture facilities at a rate of 93%. The suggested method overcomes the limits of existing monitoring method using aerial photographs, but also assists experts in detecting aquaculture facilities. Aquaculture facility detection systems must be developed in the future through application of image processing techniques and classification of aquaculture facilities. Such systems will assist in related decision-making through aquaculture facility monitoring.

• Journal of Korean Home Economics Education Association
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• v.23 no.3
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• pp.139-160
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• 2011

The purpose of this study is twofold: (i) to develop a teaching and learning plan and practical performance assessment tools for the improvement of teenager-parent communication and relationships as well as explore their effects on the communication in the everyday family life; and (ii) to find the underlying problems of teenager- parent communication through conversation analysis and to provide a improved dialogue model. We provided the experimental group with a performance task of communication training between teenagers and their parents in the real family situation while the control group practiced communication skills in a learning situation. However for both classes, before and after performance tasks were equally provided. The experimental group exhibited a longer conversation time with their parents, better communication skills, and higher degrees of relational satisfaction than the control group. Conversation analysis revealed that the experimental group reduced the use of blocking techniques in the teenager-parent conversations more than the control group, and all so raised the frequency of functional communications more than the control group. In both areas of communication in the experimental group was significantly improved, Most notably, a problem-solving case through no-lose conflict resolution methods was effective, succeeding by 70% in the e experimental group and 43.3% in the control group. Parents use blocking techniques like admonition, lecturing, blaming. sarcastic remarking, ordering and so forth, while teenagers use dispute, avoidance, blaming, and teasing in this order. The communication problems during the conversation process, teenagers' evasive and rebellious way of speaking instigates adverse communication responses from parents, so their conversation tends to unfold as ambiguous evasion opposed to: inquiring or evasion by short answers vs. ordering-preaching, or disputing vs. criticizing-making sarcastic, disputing vs. disputing-teaching, and criticizing vs. criticizing.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.25-41
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• 2011

Recently, support vector machines (SVMs) are being recognized as competitive tools as compared with other data mining techniques for solving pattern recognition or classification decision problems. Furthermore, many researches, in particular, have proved them more powerful than traditional artificial neural networks (ANNs) (Amendolia et al., 2003; Huang et al., 2004, Huang et al., 2005; Tay and Cao, 2001; Min and Lee, 2005; Shin et al., 2005; Kim, 2003).The classification decision, such as a binary or multi-class decision problem, used by any classifier, i.e. data mining techniques is so cost-sensitive particularly in financial classification problems such as the credit ratings that if the credit ratings are misclassified, a terrible economic loss for investors or financial decision makers may happen. Therefore, it is necessary to convert the outputs of the classifier into wellcalibrated posterior probabilities-based multiclass credit ratings according to the bankruptcy probabilities. However, SVMs basically do not provide such probabilities. So it required to use any method to create the probabilities (Platt, 1999; Drish, 2001). This paper applied AdaBoost algorithm-based support vector machines (SVMs) into a bankruptcy prediction as a binary classification problem for the IT companies in Korea and then performed the multi-class credit ratings of the companies by making a normal distribution shape of posterior bankruptcy probabilities from the loss functions extracted from the SVMs. Our proposed approach also showed that their methods can minimize the misclassification problems by adjusting the credit grade interval ranges on condition that each credit grade for credit loan borrowers has its own credit risk, i.e. bankruptcy probability.

• Cartoon and Animation Studies
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• s.26
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• pp.1-30
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• 2012

The purpose of animation is to give interesting stories to an audience through motion. To achieve the purpose, over the past century since its inception, animation has adopted many kinds of technologies, and thus developed diverse narrative methods and visual expression techniques. In addition, with the advancement of expression techniques, all elements making up animation have gradually been systemized, and at the same time, have helped express the worlds beyond the reality. As a result, people have faced the era when an audience can watch everything imaginated by an animation director on a big screen. These days, more efforts have been made in order for the audience to feel much more than enjoy pictures moving in a frame. In other words, the purpose of the animation is changing from the passive viewing of animation to feeling and sensing stuffs through the animation. In the center of the changing process is 3D technology which gives new interesting to an audience. Sometime ago, a 3D animation movie was produced in Korea. But it did not bring out box-office profits, for it failed to give satisfaction to an audience who expected high perfection and beauty being able to be rivalled to those of international 3D animation movies. The failure is attributable to the fact that the domestic 3D animation production industry is merely in the early stage, and has not sufficient human resources, technology, and experiences in producing 3D animation films. Moreover, the problem is that most studies on 3D focus on the technologies related to reenactment, but that few studies on the images, which an audience directly faces, have been conducted. Under the domestic circumstance, the study on stereoscopic image screen of , a 3D stereoscopic animation film which was released in 2010 and has been seen as the best successful 3D stereoscopic animation, is worthwhile. Thus this thesis conducted theoretical consideration and case analysis focusing on the visual direction that creates the pictures to deliver abundant three dimensional effect so that it can be used as a basic data when producing high quality-domestic 3D animation and training professional labor forces. In the result, it was found that the 3D animation was not a new area, but the area which has been expanded and changed by applying the characteristics of 3D image based on the principles of the existing media aesthetics. This study might be helpful to establish the foundation of the theoretical studies necessary for producing 3D animation contents for realizing the sense of reality.

• Korean Journal of Heritage: History & Science
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• v.50 no.1
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• pp.42-57
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• 2017

The Joseon Dynasty (1392~1910) had a long tradition of making official seals to commemorate the granting of official royal titles, including posthumous honorary titles, to its kings, queens, crown princes and queen dowagers. These royal seals were typically gold-plated or made of jade. After the death of its holder, each seal would be stored in the royal seal depository in the Royal Ancestral Shrine. Extensive efforts were made to restore the traditions and culture of the royal family of Joseon during the reign of King Sukjong (r. 1674~1720). In 1705, discussions were held about the royal ceremonial objects, including the royal seals, stored in the Royal Ancestral Shrine, resulting in the reproduction of a set of accessories related with the storage of royal seals and ten golden royal seals which had been lost during wars or had yet to be made. With these reproductions, each shrine chamber of the Royal Ancestral Shrine would have had at least one seal. The details of the reproduction project were meticulously recorded in The Royal Protocol by the Directorate for the Restoration of Golden Royal Seals("金寶改造都監儀軌"). Given that the restoration project was the single event that led to the reproduction of all the golden royal seals, it is reasonable to conclude that the directorate had fulfilled a historically significant function. In this study, the main discussion is focused on the establishment of the directorate and the storage and management of the damaged royal seals. The discussion includes the manufacturing process of the golden seals, for which The Royal Protocol is compared with other similar documents in order to gain more detailed knowledge of the measurements of the turtle knob, the lost-wax casting technique, the gold plating with mercury amalgamation technique, and other ornamentation techniques. The discussion also covers the activities of the artisans who made the royal seals, based on a study of the royal protocols; the styles of the artifacts, based on an examination of the remaining examples; and the techniques used by the Directorate for the Restoration of Golden Royal Seals to produce the royal seals in 1705.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.237-262
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• 2022

There has been a growing interest in IPOs (Initial Public Offerings) due to the profitable returns that IPO stocks can offer to investors. However, IPOs can be speculative investments that may involve substantial risk as well because shares tend to be volatile, and the supply of IPO shares is often highly limited. Therefore, it is crucially important that IPO investors are well informed of the issuing firms and the market before deciding whether to invest or not. Unlike institutional investors, individual investors are at a disadvantage since there are few opportunities for individuals to obtain information on the IPOs. In this regard, the purpose of this study is to provide individual investors with the information they may consider when making an IPO investment decision. This study presents a model that uses machine learning and text analysis to predict whether an IPO stock price would move up or down after the first 5 trading days. Our sample includes 691 Korean IPOs from June 2009 to December 2020. The input variables for the prediction are three tone variables created from IPO prospectuses and quantitative variables that are either firm-specific, issue-specific, or market-specific. The three prospectus tone variables indicate the percentage of positive, neutral, and negative sentences in a prospectus, respectively. We considered only the sentences in the Risk Factors section of a prospectus for the tone analysis in this study. All sentences were classified into 'positive', 'neutral', and 'negative' via text analysis using TF-IDF (Term Frequency - Inverse Document Frequency). Measuring the tone of each sentence was conducted by machine learning instead of a lexicon-based approach due to the lack of sentiment dictionaries suitable for Korean text analysis in the context of finance. For this reason, the training set was created by randomly selecting 10% of the sentences from each prospectus, and the sentence classification task on the training set was performed after reading each sentence in person. Then, based on the training set, a Support Vector Machine model was utilized to predict the tone of sentences in the test set. Finally, the machine learning model calculated the percentages of positive, neutral, and negative sentences in each prospectus. To predict the price movement of an IPO stock, four different machine learning techniques were applied: Logistic Regression, Random Forest, Support Vector Machine, and Artificial Neural Network. According to the results, models that use quantitative variables using technical analysis and prospectus tone variables together show higher accuracy than models that use only quantitative variables. More specifically, the prediction accuracy was improved by 1.45% points in the Random Forest model, 4.34% points in the Artificial Neural Network model, and 5.07% points in the Support Vector Machine model. After testing the performance of these machine learning techniques, the Artificial Neural Network model using both quantitative variables and prospectus tone variables was the model with the highest prediction accuracy rate, which was 61.59%. The results indicate that the tone of a prospectus is a significant factor in predicting the price movement of an IPO stock. In addition, the McNemar test was used to verify the statistically significant difference between the models. The model using only quantitative variables and the model using both the quantitative variables and the prospectus tone variables were compared, and it was confirmed that the predictive performance improved significantly at a 1% significance level.

• Conservation Science in Museum
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• v.27
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• pp.147-164
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• 2022

Over 200,000 Korean cultural heritage items are currently located abroad. They have made their way to 22 countries under different circumstances and with unique backgrounds. While some of them continue to contribute to promoting Korean culture around the world, others cannot be exhibited due to damage or poor condition. In view of these circumstances, the Overseas Korean Cultural Heritage Foundation (OKCHF) has since 2013 provided museums and art galleries abroad with support for the conservation, restoration, and utilization of the Korean cultural heritage items that they house. As a part of these efforts and on the occasion of the 120th anniversary of the diplomatic relationship between the Republic of Korea and the Kingdom of Belgium in 2021, a gilt-bronze case for acupuncture needles dating to the Goryeo period (918-1392) from the collection of the Royal Museums of Art and History (RMAH), Belgium was brought to Korea for conservation treatment. The primary purpose of this conservation treatment was to restore the original form of the relic and slow to the degree possible the progress of corrosion. The conservation treatment of the gilt-bronze case followed the fundamental order of conservation treatment: removal of corrosive substances, stabilization, and reinforcement. Since this was the first case of restoring metallic cultural properties under the abovementioned support program by the OKCHF, special methodologies distinct from those available in overseas institutions were required. Diverse scientific methods (e.g., X-ray inspection, CT scanning, 3D microscopy) were applied to identify the metalcraft techniques used in the Goryeo period. The analysis found that several designs, including lotus and scrollwork, were exquisitely engraved on the surface of the case by making dots using a round-edged chisel. A bronze plate engraved with designs was rolled into a cylindrical form. The ends were overlapped by 2 to 3 centimeters and then attached to each other by silver soldering. The overlapping ends were welded flat with nearly no gaps. As the final process in the production, the case was lavishly gilt with gold powder using amalgam gilding. The conservation treatment of the gilt-bronze case for acupunctural needles in the RMAH collection restored the original form of the relic and arrested further corrosion. Above all, it revived the historic and academic value of the overseas Korean cultural heritage through scientific analysis.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• The Journal of Learner-Centered Curriculum and Instruction (JLCCI)
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• v.19 no.16
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• pp.471-494
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• 2019

The purpose of this study is to analyze the design and effects of the art therapy program by making analysis framework based on the previous studies. This study aims to establish a clinical · theoretical foundation for introducing the programs for multicultural clients. This study did an literature review based on a journal paper. These papers were published from 2006 to 2018 and collected through the domestic database homepage, Riss. Dissertations were excluded from this study. This study was divided into three categories: basic information(publication year, publisher), research subject, study method(research methodology, major variables), programs(convergence of therapy techniques, session analysis, keyword analysis). First, according to the analysis results of the year of publication, research on multicultural families has been active since 2011, and conducted passively until 2016. After that, research has been actively conducted on children of them. These results reflect that the children of them are experiencing psychological difficulties. Second, the difficulties of the client were investigated according to the main variables of the program for the clients and the convergence of treatment techniques on art therapy. Art therapy program based on their psychological difficulties will be more effective for them. Third, group art therapy was the most common among the key words in the thesis. The program was structured so that they could reach the goal by receiving encouragement among the members through the program. Finally, the amount of thesis to which qualitative research methodology is applied is insufficient compared to other methodology. Most researches used questionnaires to statistically measure the psychological difficulties of the subjects. However, there is a limit to developing research when using only quantitative research methodology to demonstrate the effectiveness of the program. In order to analyze the dynamics of the group, we must consider the advantages of the qualitative research methodology.