• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6004-6013
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• 2014

The research on resource sharing in the diversification field is concerned mainly with sharing, but there has been little interest in resources. This research examined resource sharing with the main variables and logics of resource-based view. Based on a survey of 263 affiliates of 35 diversified firms, the impacts of resource quantity, resource quality, and resource exploitability on inter-affiliate resource sharing were hypothesized and verified. To confirm the performance implications of resource sharing, the impacts of the combination of resource quantity and resource sharing, the combination of resource quality and resource sharing, and the combination of resource exploitability and resource sharing on the affiliate performance were also hypothesized and verified. According to the empirical results from multiple regression analyses, resource sharing increases in the order of low resource quantity, high resource quality, and high resource exploitability. The performance was advanced in resource sharing under a low resource quantity and resource sharing under high resource exploitability, but it was not advanced in resource sharing under high resource quality. The results highlight the need for a further study on why the resource quality and resource exploitability affect resource sharing in the opposite directions, as expected in the hypotheses, why resource sharing under high resource quality does not lead to high performance, even though resource quality increases resource sharing, and what they would be if resources are subdivided by the types.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.27-38
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• 2018

The purpose of this study is to find out common investment decision factors for CVC's invested technology-based startups and analyze them. We examined 17 CVCs that invested in technology startups for three years and six months from 2015 to June 2018. As a result, the final 9 CVCs that can be used in this study were confirmed and 188 companies were analyzed. This study was conducted as a case study to propose and demonstrate CVC investment objectives and investment decision factors analysis model. The results of this study are as follows. First, CVC focused on strengthening investment. Second, In 2015, Invested in an average of 19 months of technology-based startups. In recent years, we invested in 36 months of proven technology-based startups. Thirdly, ICT service was the main business type of the invested startups. Fourth, the investors were concentrated on the stage of Series A~B. It is observed that CVC investment determinants have a significant impact on product or service and parent company relations. In addition, it was found that factors such as innovation, business planning competency, enterprising, strategic competency, leadership, and opportunity recognition competency were influential factors for the startups of invested companies and it was found that these factors are important for CVC investment decision. Understanding of CVC investment determinants presented in this study is based on the establishment of the investment process of the investee, entrepreneurship and management education program. The results of this study can be applied to the selection of excellent startups, entrepreneurship education programs, mentoring, development of coaching guidelines, and establishment of investment process of other investment institutions when investing in CVC.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.448-465
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• 2020

This study analyzed the effect of self-determination of the intellectually disabled on the quality of life, focusing on the effect of controlling family functions, with the intellectually disabled as the subject of the study. In order to achieve this goal, it was designated as an intellectual disabled person at the early age of 18 to 25 who were diagnosed with intellectual disabilities, and it was selected as a disabled person living in the community, and it selected major welfare institutions that were most frequently used by people with intellectual disabilities in the early age of 20 years, considering the difficulties of conducting the survey. The research results are as follows. First, "self-determination, psychological capacity, and self-realization" of the intellectually disabled were found to affect the quality of life (physical well-being, physical well-being, social well-being, productive activities and development, psychological and emotional well-being). Second, differences in "self-determination (self-reliance, psychological capacity, self-realization)" did not occur in accordance with the "population statistical. Third, differences occurred in the "quality of life (physical well-being, physical well-being, social well-being, productive activities and development, psychological and emotional well-being" of the intellectually disabled. Fourth, the relationship between "self-determination" and "quality of life" of the intellectually disabled resulted in the adjustment effect of family functions. This study is meaningful in that it demonstrated the service practice that should be provided to people with early adult intellectual disabilities in the field of practice by verifying the relationship between self-determination, family function and quality of life viewed from the perspective of the parties.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.133-150
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• 2017

In this study, the performance of the technological innovation of small and medium enterprises is divided into short-term aspects of technological innovation and long-term aspects of ambidextrous innovation, and the effects of dynamic capabilities affecting these achievements are explored. For the purpose of conducting empirical analysis, the survey conducted a survey of 219 small businesses belonging to various industries, and dynamic capabilities performed a parallel multi-parameter analysis to demonstrate the effectiveness of technological innovation performance, including exploratory innovation and exploitative innovation. Through this study, it aims to understand the dynamic capabilities of the small and midsize enterprises and provide suggestions on how to manage of the company, thereby improving the understanding of dynamic capabilities and helping to improve the management of small and medium-sized enterprises.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.114-120
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• 2009

Rupture directivity is the important parameter in estimating damage due to earthquakes. However, the traditional moment tensor inversion technique cannot resolve the real fault plane or the rupture directivity. To overcome these limitations, we have developed a new inversion algorithm to determine the moment tensor solution and the rupture directivity for moderate earthquakes, using the waveform inversion technique in the frequency domain. Numerical experiments for unilateral and bilateral rupture models with various rupture velocities confirm that the method can resolve the ambiguity of the fault planes and the rupture directivity successfully. To verify the feasibility of the technique, we tested the sensitivity to velocity models, which must be the most critical factor in practice. The results of the sensitivity tests show that the method can be applied even though the velocity model is not perfect. If this method is applied in regions where the velocity model is well verified, we can estimate the rupture directivity of a moderate earthquake. This method makes a significant contribution to understanding the characteristics of earthquakes in those regions.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.125-132
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• 2018

The purpose of this study is to analyze the effect of managerial predictive accuracy on managerial performance-compensation. In this study, we compared managerial performance with managerial performance, And to analyze the relationship between manager compensation and manager compensation using managerial profit prediction accuracy. As a result of this study, there is a significant positive relationship between profit prediction accuracy and manager compensation, which can be interpreted as a result of manager's ability to compensate manager's ability to predict the future well. In this paper, we propose a new methodology that can be used to analyze the effects of managerial compensation on managerial compensation. This is because there is a difference in that it is proved to be a factor. Therefore, it is important to note that the prediction of the future of the company also identifies the additional determinants that affect manager compensation contracts with the key managerial capabilities.

• Convergence Security Journal
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• v.22 no.3
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• pp.101-110
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• 2022

As the cases of using artificial intelligence in various fields increase, attempts to solve various issues through artificial intelligence in the intrusion detection field are also increasing. However, the black box basis, which cannot explain or trace the reasons for the predicted results through machine learning, presents difficulties for security professionals who must use it. To solve this problem, research on explainable AI(XAI), which helps interpret and understand decisions in machine learning, is increasing in various fields. Therefore, in this paper, we propose an explanatory AI to enhance the reliability of machine learning-based intrusion detection prediction results. First, the intrusion detection model is implemented through XGBoost, and the description of the model is implemented using SHAP. And it provides reliability for security experts to make decisions by comparing and analyzing the existing feature importance and the results using SHAP. For this experiment, PKDD2007 dataset was used, and the association between existing feature importance and SHAP Value was analyzed, and it was verified that SHAP-based explainable AI was valid to give security experts the reliability of the prediction results of intrusion detection models.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.109-109
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• 2016

유역의 물수지는 기상인자, 지형, 토양, 식생 등 여러 가지 인자들에 의해 결정된다. 물수지 분포를 평가하기 위해 수문모형의 모의 시 필요한 수문요소 조건들을 정보화하게 되며, 동시에 토양수분의 특성, 강우 입력자료, 유역의 지형학적 특성들은 불확실성에 기인하는 요소로 작용한다. 이러한 수문모형 모의 시 불확실성을 제거하기 위해 모형 초기조건에 대한 다각적인 분석이 선행이 필요하다. 특히 토양수분은 대기와 지표 사이의 상호작용에 작용하는 중요한 수문기상학적 인자로 평가되고 있다. 토양수분 데이터 자료를 이용하여 강우-유출모형의 입력자료를 구축하여 실제 토양수분의 변동성을 파악하는 연구가 활발히 진행되고 있으며, 유역기반의 유출현황을 산정하기 위해 매우 유용한 초기조건으로 그 역할이 기대된다. 현장에서 관측하는 토양수분 데이터는 넓은 유역의 토양수분을 대표하는 자료로 사용되기에는 한계점이 있으며, 위성기반 토양수분 데이터는 원격탐사를 통해 획득되기 때문에 토양수분의 시 공간적인 변동성 파악에 용의하며 경제성 또한 높다. 이에 따라, 본 연구에서는 유역의 수문순환 분석을 하고, 위성기반 토양수분의 적용 가능성을 평가하기 위해 Aqua위성에 탑재된 Advanced Mircowave Scanning Radiometer Earth Observing System(AMSR-E)와 Metop-A의 Advanced SCATterometer(ASCAT)의 토양수분 데이터를 이용하여 강우-유출모델의 초기조건을 산정하였다. 또한, 이에 대한 검증을 위해 기존 강우인자 초기조건 및 지점에서 관측된 토양수분 초기조건 등을 비교하여 통계분석을 실시하였다.

• Journal of Software Engineering Society
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• v.26 no.3
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• pp.63-76
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• 2013

We need to measure the quality of each module to assess software quality. Especially, in industry, it is important to measure quality of modules quantitatively in order to improve bad modules and reuse good modules. In this paper, we define moduleness as characteristic that modules should be possessed and propose a method to measure software moduleness quantitatively. A case study conducted in this paper shows the usefulness of the method by measuring and evaluating moduleness of modules based on open source software developed by C, C++ and Java languages.