• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.4
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• pp.139-151
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• 2017

The habitat preference of roe deers(Capreolus pygargus) in Jeju island, South Korea was analyzed by using their occurrence probability in MaxEnt model in this study. Totally 490 surveying data were gathered and 15 environmental variables were chosen for the model in which 6 variables out of 15 ones were filtered and finally removed because of there being higher correlation(over 0.7 in correlation coefficient). According to the modeling, roe deers were known to prefer the area ranging from 200 to 700 meter and over 1,500 meter in sea level, where there were not many dominant tree and/or dominant vegetation with low density so that understory vegetation can grow well with plentiful sunlight and can be used as a food of herbivore like roe deers. Otherwise, the region ranging from 700 to 1,500 meter was mostly covered with high density vegetation which cut off sunlight trying to penetrate through the dominant vegetation. It can cause a lower density of vegetation on surface, which can not attract to roe deers.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.19 no.3
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• pp.300-310
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• 1997

In order to make in vivo model of human oral squamous cell cancer, we brought up BALB/C nude mice in specially designed housystem, and maintained some kind of human oral squamous cancer cell lines ; KB, SCC-4, SCC-9, SCC-15, SCC-25. Various concentration of cancer cells were inoculated subcutaneouly into flank area of nude mice. We observed each nude mouse more than 5 weeks after tumor inoculation. We appraised the results, measured the tumor size, and calculated the growing tumor volumes after tumor inoculation according to cancer cell line and concentration of cancer cells in media. Some cancer cell lines were rapidly growing in nude mice, but some cancer cell line couldn't grow in nude mice and resorbed completely. And in some cancer cell line, some nude mice showed continuously growing tumor, but other didn't show any tumor growing. And as a new try, we implanted specially disigned caps on the back of nude mice, and cancer cell lines were brought into the caps with media. We removed the cap after 1 week, and observed over 4 weeks. The shape and size of growing tumor were observed.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.451-462
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• 2008

Recently, with the advent of applications using locations of moving objects, it becomes crucial to develop efficient index schemes for spatio-temporal databases. The $TPR^*$-tree is most popularly accepted as an index structure for processing future-time queries. In the $TPR^*$-tree, the future locations of moving objects are predicted based on the CBR(Conservative Bounding Rectangle). Since the areas predicted from CBRs tend to grow rapidly over time, CBRs thus enlarged lead to serious performance degradation in query processing. Against the problem, we propose a new method to adjust CBRs to be tight, thereby improving the performance of query processing. Our method examines whether the adjustment of a CBR is necessary when accessing a leaf node for processing a user query. Thus, it does not incur extra disk I/Os in this examination. Also, in order to make a correct decision, we devise a cost model that considers both the I/O overhead for the CBR adjustment and the performance gain in the future-time owing to the CBR adjustment. With the cost model, we can prevent unusual expansions of BRs even when updates on nodes are infrequent and also avoid unnecessary execution of the CBR adjustment. For performance evaluation, we conducted a variety of experiments. The results show that our method improves the performance of the original $TPR^*$-tree significantly.

• Journal of Convergence for Information Technology
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• v.11 no.10
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• pp.302-313
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• 2021

As the domestic consulting industry matured, consultants were required to have insight into customer's business and consulting business. Gaining these insights requires deep understanding of the business domains and high degree of competencies. This study empirically analyzed the data collected through the survey in order to apply the ICMCI competence model to domestic consultants. As a result of the study, it was found that business competency and technical competency had a positive effect on project performance, but values & behavior competency were not statistically significant. On the other hand, it was found that only technical competency, values & behavior competency had a positive effect on social-relational competency. Through this study, it was confirmed that a deep understanding and perception of the consulting business is necessary to grow into a professional consultant, but there is a limit to generalizing the research results because the characteristics of the population cannot be sufficiently reflected with a small sample.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.553-560
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• 2020

This paper presents an algorithm for identifying and eliminating errors by seagrasses in coastal bathymetry surveying using drone and HD camera. Survey errors due to seagrasses were identified, segmentated and eliminated using a L∗a∗b color space model. Bathymetry survey using a drone and HD camera has many advantages over conventional survey methods such as ship-board acoustic sounder or manual level survey which are time consuming and expensive. However, errors caused by sea bed reflectance due to seagrasses habitat hamper the development of new surveying tool. Seagrasses are the flowering plants which start to grow in November and flourish to maximum density until April in Korea. We developed a new algorithm for identifying seagrasses habitat locations and eliminating errors due to seagrasses to get the accurate depth survey data. We tested our algorithm at Wolpo beach. Bathymetry survey data which were obtained using a drone with HD camera and calibrated to eliminate errors due to seagrasses, were compared with depth survey data obtained using ship-board multi-beam acoustic sounder. The abnormal bathymetry data which are defined as the excess of 1.5 times of a standard deviation of random errors, are composed of 8.6% of the test site of area of 200 m by 300 m. By applying the developed algorithm, 92% of abnnormal bathymetry data were successfully eliminated and 33% of RMS errors were reduced.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.129-159
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• 2022

This study generated primary data for supporting the place branding as a part of the library advertising and marketing strategies to increase public library visits. The literature review enabled the use of the place branding concepts to discover the relationships among the constituent parts, factors, expected outcomes, and loyalty, then to develop the research model and the hypothesis, which were verified using the Structural Equation Model. There were 34 research hypotheses, of which 21 were adopted. The place image factors such as library reliability, library reciprocity, and library safety were found to be significant. This study derived social contribution value as new place value and place image factors as the potential brand image of public libraries. It helped select the place image factors that best fit the local library's core values (i.e., place value). This study is meaningful because it is a fundamental study to introduce place branding in public libraries as an advertising and marketing strategy. And it is expected that public libraries will grow into high-quality brands with high awareness, loyalty, and secure leadership in the local community.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.955-967
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• 2022

Existing particle tracking models predict vertical displacement of particles based on the terminal settling velocity in the stagnant water. However, experimental results of the present study confirmed that the settling velocity of particles is influenced by the turbulence effects in turbulent flow, consistent with the previous studies. The settling velocity of particles and turbulent characteristics were measured by using PTV and PIV methods, respectively, in order to establish relationship between the particle settling velocity and the ambient turbulence. It was observed that the settling velocity increase rate starts to grow when the particle diameter is of the same order as Kolmogorov length scale. Compared with the previous studies, the present study shows that the graphs of the settling velocity increase rate according to the Stokes number have concave shapes for each particle density. In conclusion, since the settling velocity in the natural flow is faster than in the stagnant water, the existing particle tracking model may estimate a relatively long time for particles to reach the river bed. Therefore, the results of the present study can help improve the performance of particle tracking models.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.173-178
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• 2023

As Korean literature spreads around the world, its position in the overseas publishing market has become important. As demand in the overseas publishing market continues to grow, it is essential to predict future book sales and analyze the characteristics of books that have been highly favored by overseas readers in the past. In this study, we proposed ensemble learning based prediction model and analyzed characteristics of the cumulative sales of more than 5,000 copies classified as good sellers published overseas over the past 5 years. We applied the five ensemble learning models, i.e., XGBoost, Gradient Boosting, Adaboost, LightGBM, and Random Forest, and compared them with other machine learning algorithms, i.e., Support Vector Machine, Logistic Regression, and Deep Learning. Our experimental results showed that the ensemble algorithm outperforms other approaches in troubleshooting imbalanced data. In particular, the LightGBM model obtained an AUC value of 99.86% which is the best prediction performance. Among the features used for prediction, the most important feature is the author's number of overseas publications, and the second important feature is publication in countries with the largest publication market size. The number of evaluation participants is also an important feature. In addition, text mining was performed on the four book reviews that sold the most among good-selling books. Many reviews were interested in stories, characters, and writers and it seems that support for translation is needed as many of the keywords of "translation" appear in low-rated reviews.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.45-55
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• 2022

Accelerator is a private investment institution that provides startups with comprehensive solutions to solve various difficulties such as startup facilities, funds, commercialization, securing a market etc. In addition to the role of an investor as a new startup support model, accelerators have contributed much to improvement of business ability of startups through intensive mentoring. Considering that previous studies gave weight to the determinants of investment from the perspective of investors, this study made a comparative analysis on the relative importance of determinants of investment in startups among accelerators, investors and entrepreneurs through the method of AHP. Results show that accelerators and investors regard "managerial characteristics" of startups as of the highest importance, whereas entrepreneurs think that "market characteristics" of startups are the most important. The result stems from an empirical judgment from the perspective of investors that success of startups depends on the ability of entrepreneur, and it is considered that investors evaluated marketability of startups as the most important factor in consideration of investment payback period. The result is similar to the result of previous studies on the determinants of investment determinants of angel investors and venture capitals. This paper is expected to make a contribution to the advancement of investment decision-making model for accelerators to discover startups with high possibility to grow and achieve more in incubation and investment.

• Information Systems Review
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• v.21 no.1
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• pp.135-152
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• 2019

Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.