• The Journal of Society for e-Business Studies
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• v.19 no.4
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• pp.231-249
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• 2014

We define $21^{st}$ century as an amalgamation of globalization and localization, or Glocalization. Additionally, due to the increasing supply of smart phones and wide usage of social networking services, the ability to utilize such global and regional information has increased a coperation's competitiveness in its market, and even the business models have evolved from the conventional "production and distribution" to E-commerce, through which either a direct or a non-direct transaction is possible. My hypothesis is that the ability to adapt to this trend is possible through transfer of learning, and consequently, this will have an impact on company's performance. Thus, this thesis analyzes the mid- to the long-term impact of such ability and environmental factors on the performance and technology innovation of Korean companies in China. Ultimately, this study intends to engender a basic foundation for a corporation's management strategy in China. Finally this research focuses on those Korean companies in China only and on the proof of influential factors' impact on technological innovation and technological innovation's impact on those corporations' future performances. Section I is an abstract and section II, the case examines the uniqueness and current status of Korean companies in China identifies the concept and the definition of influential factors such as education-orientation, technological innovation, and performance, and then scrutinizes each factors through a closer look at their past researches. Section III explains the thesis model, the survey's method and target, the thesis, variable factors, the content, and the method of analysis. In section IV, the thesis is proved based on the outcome of the survey. The result in Section V highlights the high comprehension of technological innovation: both education-orientation and technological innovation prove to have a positive (+) correlation with the performance. The vision on education orientation proves to have a positive (+) influence on technological innovation. The vision on education-orientation and technological innovation prove to have a positive (+) influence individually on company's performance.

• 대한공업교육학회지
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• v.44 no.2
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• pp.142-163
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• 2019

The purpose of this study is to analyze the effect of problem solving ability and satisfaction of university students who are pre-technology teachers in woodworking products(birdhouse) making program using design thinking. Survey responses are analyzed by statistical programs(SPSS ver.20) such as satisfaction, confidence in problem solving, difficulties and causes of difficulties according to gender and grade of 33 students who conducted experience programs in extra-curricular programs to improve creativity and problem solving ability. The main conclusions of this study are as follows: First, the average of total satisfaction about experience programs is 4.39, which is somewhat high. The highest average response is 'feelings of accomplishment' and 'advice in the surroundings'(M = 4.46). There is no significant difference between male and female, and grade. The students interest in group-based different birdhouse woodworking together with the help of the surrounding people by the process of design thinking rather than practice to follow. Therefore, I'd like to recommend to other students due to this program shows a high self-confidence, sense of accomplishment, and satisfaction. Second, the total average response of students 'self-confidence for problem solving at the group based making experience program using design thinking is 3.80. In result of group activities, the students have self-confidence of 'problem-solving ability and deal with difficult situations'. Later, in making programs, complementing difficulties of making can enhance the satisfaction of the students. Third, in the survey questionnaire related with problem solving ability confidence, between 'I have the ability to solve many problems' and 'I always have the ability to cope with new and difficult business situations' show the highest correlation. Therefore, in order to improve self-confidence of problem solving ability, it is necessary to prepare teaching learning programs that can strengthen problem solving ability. Fourth, in the new design and making process not a given product design, the most difficult step is 'the process of rework and modifying idea product'. The main reason that students have difficulty in the production process is 'lack of knowledge and ability to produce'. To make various woodworking products using design thinking process, it can be helpful to make works if you have enough training on woodworking and design thinking before product making. The students' satisfaction about team-based learning using design thinking that helps improving creativity and problem solving ability is high. Therefore, the result of the research in other making activity program that design thinking is applied and analyzed can improve students' problem solving ability.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.1-13
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• 2015

As opinion mining in big data applications has been highlighted, a lot of research on unstructured data has made. Lots of social media on the Internet generate unstructured or semi-structured data every second and they are often made by natural or human languages we use in daily life. Many words in human languages have multiple meanings or senses. In this result, it is very difficult for computers to extract useful information from these datasets. Traditional web search engines are usually based on keyword search, resulting in incorrect search results which are far from users' intentions. Even though a lot of progress in enhancing the performance of search engines has made over the last years in order to provide users with appropriate results, there is still so much to improve it. Word sense disambiguation can play a very important role in dealing with natural language processing and is considered as one of the most difficult problems in this area. Major approaches to word sense disambiguation can be classified as knowledge-base, supervised corpus-based, and unsupervised corpus-based approaches. This paper presents a method which automatically generates a corpus for word sense disambiguation by taking advantage of examples in existing dictionaries and avoids expensive sense tagging processes. It experiments the effectiveness of the method based on Naïve Bayes Model, which is one of supervised learning algorithms, by using Korean standard unabridged dictionary and Sejong Corpus. Korean standard unabridged dictionary has approximately 57,000 sentences. Sejong Corpus has about 790,000 sentences tagged with part-of-speech and senses all together. For the experiment of this study, Korean standard unabridged dictionary and Sejong Corpus were experimented as a combination and separate entities using cross validation. Only nouns, target subjects in word sense disambiguation, were selected. 93,522 word senses among 265,655 nouns and 56,914 sentences from related proverbs and examples were additionally combined in the corpus. Sejong Corpus was easily merged with Korean standard unabridged dictionary because Sejong Corpus was tagged based on sense indices defined by Korean standard unabridged dictionary. Sense vectors were formed after the merged corpus was created. Terms used in creating sense vectors were added in the named entity dictionary of Korean morphological analyzer. By using the extended named entity dictionary, term vectors were extracted from the input sentences and then term vectors for the sentences were created. Given the extracted term vector and the sense vector model made during the pre-processing stage, the sense-tagged terms were determined by the vector space model based word sense disambiguation. In addition, this study shows the effectiveness of merged corpus from examples in Korean standard unabridged dictionary and Sejong Corpus. The experiment shows the better results in precision and recall are found with the merged corpus. This study suggests it can practically enhance the performance of internet search engines and help us to understand more accurate meaning of a sentence in natural language processing pertinent to search engines, opinion mining, and text mining. Naïve Bayes classifier used in this study represents a supervised learning algorithm and uses Bayes theorem. Naïve Bayes classifier has an assumption that all senses are independent. Even though the assumption of Naïve Bayes classifier is not realistic and ignores the correlation between attributes, Naïve Bayes classifier is widely used because of its simplicity and in practice it is known to be very effective in many applications such as text classification and medical diagnosis. However, further research need to be carried out to consider all possible combinations and/or partial combinations of all senses in a sentence. Also, the effectiveness of word sense disambiguation may be improved if rhetorical structures or morphological dependencies between words are analyzed through syntactic analysis.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1449-1463
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• 2020

As recent global warming and climate changes become more serious, the importance of CO2 absorption by forests is increasing to cope with the greenhouse gas issues. According to the UN Framework Convention on Climate Change, it is required to calculate national CO2 absorptions at the local level in a more scientific and rigorous manner. This paper presents the gridded expansion of forest flux observations and mapping of daily CO2 absorption by the forests in Korea using numerical weather prediction data and satellite images. To consider the sensitive daily changes of plant photosynthesis, we built a machine learning model to retrieve the daily RACA (reference amount of CO2 absorption) by referring to the climax forest in Gwangneung and adopted the NIFoS (National Institute of Forest Science) lookup table for the CO2 absorption by forest type and age to produce the daily AACA (actual amount of CO2 absorption) raster data with the spatial variation of the forests in Korea. In the experiment for the 1,095 days between Jan 1, 2013 and Dec 31, 2015, our RACA retrieval model showed high accuracy with a correlation coefficient of 0.948. To achieve the tier 3 daily statistics for AACA, long-term and detailed forest surveying should be combined with the model in the future.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.71-89
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• 2016

Sentiment analysis is used for identifying emotions or sentiments embedded in the user generated data such as customer reviews from blogs, social network services, and so on. Various research fields such as computer science and business management can take advantage of this feature to analyze customer-generated opinions. In previous studies, the star rating of a review is regarded as the same as sentiment embedded in the text. However, it does not always correspond to the sentiment polarity. Due to this supposition, previous studies have some limitations in their accuracy. To solve this issue, the present study uses a supervised sentiment classification model to measure a more accurate sentiment polarity. This study aims to propose an advanced sentiment classifier and to discover the correlation between movie reviews and box-office success. The advanced sentiment classifier is based on two supervised machine learning techniques, the Support Vector Machines (SVM) and Feedforward Neural Network (FNN). The sentiment scores of the movie reviews are measured by the sentiment classifier and are analyzed by statistical correlations between movie reviews and box-office success. Movie reviews are collected along with a star-rate. The dataset used in this study consists of 1,258,538 reviews from 175 films gathered from Naver Movie website (movie.naver.com). The results show that the proposed sentiment classifier outperforms Naive Bayes (NB) classifier as its accuracy is about 6% higher than NB. Furthermore, the results indicate that there are positive correlations between the star-rate and the number of audiences, which can be regarded as the box-office success of a movie. The study also shows that there is the mild, positive correlation between the sentiment scores estimated by the classifier and the number of audiences. To verify the applicability of the sentiment scores, an independent sample t-test was conducted. For this, the movies were divided into two groups using the average of sentiment scores. The two groups are significantly different in terms of the star-rated scores.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.481-491
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• 2018

As the global business environment is dynamic, uncertain, and complex, supply chain management determines the performance of the supply chain in terms of the utilization of resources and capabilities of companies involved in the supply chain. Companies pursuing open innovation gain greater access to the external environment and accumulate knowledge flows and learning experiences, and may generate better business performance from dynamic capabilities. This study analyzed the effects of supply chain dynamic capabilities, open innovation, and supply uncertainty on supply chain performance. Through questionnaires on 178 companies listed on KOSDAQ, empirical results are as follows: First, integration and reactivity capabilities among supply chain dynamic capabilities have a positive effect on supply chain performance. Second, the moderating effect of open innovation showed a negative correlation in the case of information exchange, and a positive correlation in the cases of integration, cooperation and reactivity. Third, two of the 3-way interaction terms, "information exchange*open innovation*supply uncertainty" and "integration*open innovation*supply uncertainty" were statistically significant. The implications of this study are as follows: First, as the supply chain needs to achieve optimization of the whole process between supply chain components rather than individual companies, dynamic capabilities play an important role in improving performance. Second, for KOSDAQ companies featuring limited capital resources, open innovation that integrates external knowledge is valuable. In order to increase synergistic effects, it is necessary to develop dynamic capabilities accordingly. Third, since resources are constrained, managers must determine the type or level of capabilities and open innovation in accordance with supply uncertainty. Since this study has limitations in analyzing survey data, it is necessary to collect secondary data or longitudinal data. It is also necessary to further analyze the internal and external factors that have a significant impact on supply chain performance.

• The Korean Journal of Nuclear Medicine
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• v.37 no.2
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• pp.73-82
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• 2003

Objectives: A new software (Cardiac SPECT Analyzer: CSA) was developed for quantification of volumes and election fraction on gated myocardial SPECT. Volumes and ejection fraction by CSA were validated by comparing with those quantified by Quantitative Gated SPECT (QGS) software. Materials and Methods: Gated myocardial SPECT was peformed in 40 patients with ejection fraction from 15% to 85%. In 26 patients, gated myocardial SPECT was acquired again with the patients in situ. A cylinder model was used to eliminate noise semi-automatically and profile data was extracted using Gaussian fitting after smoothing. The boundary points of endo- and epicardium were found using an iterative learning algorithm. Enddiastolic (EDV) and endsystolic volumes (ESV) and election fraction (EF) were calculated. These values were compared with those calculated by QGS and the same gated SPECT data was repeatedly quantified by CSA and variation of the values on sequential measurements of the same patients on the repeated acquisition. Results: From the 40 patient data, EF, EDV and ESV by CSA were correlated with those by QGS with the correlation coefficients of 0.97, 0.92, 0.96. Two standard deviation (SD) of EF on Bland Altman plot was 10.1%. Repeated measurements of EF, EDV, and ESV by CSA were correlated with each other with the coefficients of 0.96, 0.99, and 0.99 for EF, EDV and ESV respectively. On repeated acquisition, reproducibility was also excellent with correlation coefficients of 0.89, 0.97, 0.98, and coefficient of variation of 8.2%, 5.4mL, 8.5mL and 2SD of 10.6%, 21.2mL, and 16.4mL on Bland Altman plot for EF, EDV and ESV. Conclusion: We developed the software of CSA for quantification of volumes and ejection fraction on gated myocardial SPECT. Volumes and ejection fraction quantified using this software was found valid for its correctness and precision.

• Journal of Korean Home Economics Education Association
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• v.23 no.1
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• pp.159-176
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• 2011

The purpose of this study was to investigate 1) how the middle school Home Economics teachers perceive the importance of the practical problem-focused instruction, 2) how often they perform the instruction, and 3) what they require for the implementation the instruction. Data were collected from 150 Home Economics teachers via e-mail survey and from 6 Home Economics teachers' face-to-face interviews. Descriptive statistics including frequency, percentage, average, and standard deviation, and the results of such analyses as ANOVA, T-test, and correlation were reported using SPSS/win 10.1. The results of this research were as follows: First, even though the majority of the respondents recognized the high need for practical problem-focused instruction, only a small portion of the respondents reported that they performed that instruction in the classroom. There was no correlation between the perception of the need for practical problem-focused instruction and the degree of performance of practical problem-focused instruction. Secondly, the of performance of practical problem-focused instruction was significantly different depending on the years of teaching experience and the subject that the teachers majored in. Job satisfaction had positive correlations with the perception of the need for practical problem-focused instruction and the degree of performance of practical problem-focused instruction. Thirdly, the more teachers shared information and materials with colleagues, the better they tended to be at practical problem-focused instruction. On the other hand, insufficient time for their instruction and a deficiency in understanding the rationale of the instruction were pointed out as barriers to classroom practice. The respondents answered that long-term training programs on the philosophical foundation of practical problem-focused instruction, materials related to the instruction as well as additional credits for Home Economics are most critical to reduce the discrepancy between the teacher perception and the classroom practice of practical problem-focused instruction.

• Investigative Magnetic Resonance Imaging
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• v.17 no.4
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• pp.294-307
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• 2013

Purpose : To investigate the correlations between Seoul Neuropsychological Screening Battery (SNSB) scores and the gray matter volumes (GMV) in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and cognitively normal (CN) elderly subjects with correcting the genotypes. Materials and Methods: Total 75 subjects were enrolled with 25 subjects for each group. The apolipoprotein E (APOE) epsilon genotypes, SNSB scores, and the 3D T1-weighted images were obtained from all subjects. Correlations between SNSB scores and GMV were investigated with the multiple regression method for each subject group using both voxel-based and region-of-interest-based analyses with covariates of age, gender, and the genotype. Results: In the AD group, Rey Complex Figure Test (RCFT) delayed recall scores were positively correlated with GMV. In the MCI group, Seoul Verbal Learning Test (SVLT) scores were positively correlated with GMV. In the CN group, GMV negatively correlated with Boston Naming Test (K-BNT) scores and Mini-Mental State Examimation (K-MMSE) scores, but positively correlated with RCFT scores. Conclusion: When we used covariates of age, gender, and the genotype, we found statistically significant correlations between some SNSB scores and GMV at some brain regions. It may be necessary to further investigate a longitudinal study to understand the correlation.

• Journal of Educational Research in Mathematics
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• v.22 no.1
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• pp.1-22
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• 2012

The purpose of this study is to understand Korea students' characteristics as well as to give important information of improving our education using comparative analysis of framework, test booklets, test results between PISA 2009 and NAEA 2009. PISA 2009 was administered on May of 2009 and NAEA was administered on October of same year. The summary of the results of comparing two assessment is as follows First, cut score of NAEA Advance level is bigger than the cut score of level 5, which is considered as high achievement level. The cut score of Basic level of NAEA is also higher than the level 2 of PISA, which is considered as basic achievement level. This phenomenon can show that NAEA achievement level is set little bit higher than the achievement level of PISA in mathematics domain. Second, the percentage of female students on higher level was higher than that of male students. In suburban area, the percentage of high level was small and the percentage of low level was big. Third, students of Advanced level are distributed concentrating in PISA levels 4~6, Proficient achievement level concentrating in PISA levels 3~5, Basic achievement level concentrating in PISA levels 2~4, and below basic achievement levels concentrating in below level 1 and level 3 of PISA. Fourth, the correlation between NAEA 2009 and PISA 2009 achievement scores are significantly positive. However, the correlation of subscales were low. Fifth, analysis of non-equivalent group, 11 items located in 'change and relationship', 'uncertainty', 'connection cluster' domains found to be significantly different. The percent correct showed very big difference. The analysis results presents the implication of mathematics curriculum, teaching and learning methods as well as National Assessment of Educational Achievement.