• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.627-639
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• 2014

Accurate correction of surface effect from back scattered solar radiance is one of key issue to retrieve aerosol information from satellite measurements. In this study, two different methods are applied to retrieve surface reflectance by using single visible channel measurement from meteorological imager onboard COMS. The first one is minimum reflectance method, which composes the minimum value among previously measured reflectances at each pixel over a certain search window length. This method assumes that the darkest pixel corresponds to the aerosol-free condition, and deduces surface reflectance by correcting atmospheric scattering from the measured visible reflectance. The second method, named as the "atmospheric correction method" in this study, estimates the result by correcting aerosol and atmospheric scattering with ground-based observation of aerosol optical properties. The purpose of this study is to investigate the retrieval accuracy of the widelyused minimum reflectance method. Also, the retrieval error caused by the loading of background aerosol is mainly estimated. The comparison between surface reflectances retrieved from the two methods shows good agreement with the correlation coefficient of 0.87. However, the results from the minimum reflectance method are slightly overestimated than the values from the atmospheric correction method when surface reflectance is lower than 0.2. The average difference between the two results is 0.012 without the background aerosol correction. By considering the background aerosol effect, however, the difference is reduced to 0.010.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.149-157
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• 2013

The purpose of this study is to listen to vivid story on economic life of marriage immigrant women using phenomenological study out of qualitative study methods, and to analyze the meaning of dynamicity of experiences through in-depth interviews. The research question is "What is the meaning of economic life that marriage immigrant women experience?" From the research, 67 meaningful statements were abstracted and 15 core meanings were organized. The 15 core meanings were categorized as 5 theme categories such as 'Tough Life', 'Unstable Income such as Children Education Expense and Insurance Premium', 'Search for Changes in Life Style for Adaptation', 'Pursuit of Economic Stability through Employment', 'Expectation of Supports and Return to Married Woman's Parents' Home.' The researcher made structural description through first person speaker for the application of hermeneutical writing. In other words, the meaning of economic life of marriage immigrant women in Korea is 'difficult coping process to family-oriented culture pursuing changes in life style to adapt themselves to difficult reality.' Various undertones of practice were proposed through those statements such as policy to expand opportunities to receive an old-age pension by applying 'Joint Scheme for Couples' (Virtual Name) to People's pension for stable economic life of marriage immigrant women in old age.

• Journal of Korean Library and Information Science Society
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• v.52 no.3
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• pp.21-48
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• 2021

Today, with countless health information being accessible through online and offline, the public has been able to explore health-related information in various ways. The current study focuses on the information-seeking behavior of the mothers who actively explore information related to the health of their healthy infants (aged between 0 and 3 years). The researcher had conducted in-depth interviews of 24 American, Korean, and Korean immigrant mothers living in the United States, and then analyzed the sequential order of the information sources that they have used to search for the health-related information about their children. The current research highlights that the mothers' information-seeking pathways and searched topics tended to differ in accordance with their child(ren)'s health conditions (e.g., ill vs. healthy). For instance, regarding the information sources used, more diverse health information sources (e.g., public libraries, government health agencies, daycare teachers) were used when their child(ren) was not ill. In addition, when a child was ill, mothers were likely to focus on information about specific diseases or symptoms first, whereas when the child was healthy, they used to explore information on various health topics such as growth and development, nutrition and diets, parenting, and so on. Based on the results, implications for the information professionals are discussed when designing and providing health-related information services to mothers of healthy infants and toddlers.

• Korean Journal of Heritage: History & Science
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• v.46 no.4
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• pp.144-159
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• 2013

This study covers Namwoneupseong Fortress(南原邑城), Historic Site No. 298, which played a pivotal role in the urban development and military defense history of Namwon during the Joseon Dynasty. From the related historical records, Namwoneupseong Fortress was first constructed during the reign of King Seongjong. Discussion on the extension of Namwoneupseong Fortress, afterwards, was mainly guided by he traces of Yuingweseong Fortress(劉仁軌城). In other words, the original construction of the Fortress was in the original shape of the current Namwoneupseong Fortress, and Yuingweseong Fortress heavily impacted the extension works of Namwoneupseong Fortress. Although some studies covered Namwoneupseong Fortress and its overall construction process, no in-depth study exists on the original Namwoneupseong Fortress and Yuingweseong Fortress. This study covers the overall construction process of Namwoneupseong Fortress. At the same time, we tried to confirm inclusively and objectively the facts related to the relationship between Yuingweseong Fortress and Namwoneupseong Fortress, process and range of the expansion of Namwoneupseong Fortress among others through the location search of the originally built Namwoneupseong Fortress and Yuingweseong Fortress. The study discovered that Yuingweseong Fortress was built in A.D. 660~665 and that Namwoneupseong Fortress, which was built in the early stage of King Seongjong's reign, was extended along the traces of Yuingweseong Fortress towards the southeast. Furthermore, the study confirmed that Namwoneupseong Fortress is consisted of three sections - the section with Namwoneupseong Fortress's original walls preserved, newly constructed section, and the section following Yuingweseong Fortress's traces.

• Journal of Korean Medicine Rehabilitation
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• v.33 no.4
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• pp.31-44
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• 2023

Objectives The purpose of this study is to check the research trends of pharmacopuncture treatment in nerve entrapment syndrome, identify specific techniques, identify which pharmacopuncture are used, and provide directions for future research. Methods This study was conducted based on the five steps suggested by Arksey and O'Malley. We searched five domestic databases (Research Information Sharing Service, Oriental Medicine Advanced Searching Integrated System, Korean studies Information Service System, Science ON, and KMBASE) and identified studies with key search terms like "nerve entrapment" And "pharmacopuncture" until June 23, 2023. Results Twenty-nine studies were finally selected. among them, 25 papers were non-comparative studies (86.2%). The most common disease was carpal tube syndrome (n=10). All the investigated studies were treated by injecting pharmacopuncture into the pathway of the entraped nerve. The depth of pharmacopuncture injection was mentioned only in 13 studies. As for the pharmacopuncture used, sweet bee venom was 8 studies and bee venom was 6 studies, and about half of the pharmacopuncture manufactured with Bee venom as the main component accounted for. Conclusions This study is a scoping review of the pharmacopuncture treatment for nerve entrapment, which was first conducted in Korea. The treatment is mainly performed on the path way of the entraped nerve. After that, it is necessary to study the standardization of the specific technique method of pharmacopuncture and the uniformity of evaluation criteria.

• Archives of design research
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• v.19 no.5 s.67
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• pp.203-212
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• 2006

With interests and participation in the costumeplay that mimics characters appeared on carton or animation in recent days, the costumeplay becomes one of cultural phenomena. Using a qualitative research method, this study identified costumeplayers' costume consumption pattern and explored its meanings from the perspective of consumption culture. Indeed, this study intended to help for understanding costumeplayer group as a consumer, and to provide basic knowledge about new market analysis related to fashion design and marketing. The results from the analyzing participant observation and in-depth interviews data are as follows: first, costumeplayers usually begin costumeplay by friends' invitations or by themselves and then continue on participating. Through the costumeplay, participants have benefits such as fun, departure from the daily life, and social interaction. Second, participants acquire costumes through purchase, rent, producing or combination of daily wear, but both purchase and rent account high. Third, the meanings of consumption culture in costumeplay include consumption behavior repeating possession and disposal. Also, costumeplayers concerns efficiency when purchasing or renting the costumes, and internet is a place where information search, comparison, and actual purchasing are occurred. Based on the results, fashion design and marketing implication, limitation of this study and further research ideas were suggested.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.33-62
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• 2009

Internet computing is a disruptive IT innovation. Semantic Web can be considered as an IT innovation because the Semantic Web technology possesses the potential to reduce information overload and enable semantic integration, using capabilities such as semantics and machine-processability. How should organizations adopt the Semantic Web? What factors affect the adoption and diffusion of Semantic Web innovation? Most studies on adoption and diffusion of innovation use empirical analysis as a quantitative research methodology in the post-implementation stage. There is criticism that the positivist requiring theoretical rigor can sacrifice relevance to practice. Rapid advances in technology require studies relevant to practice. In particular, it is realistically impossible to conduct quantitative approach for factors affecting adoption of the Semantic Web because the Semantic Web is in its infancy. However, in an early stage of introduction of the Semantic Web, it is necessary to give a model and some guidelines and for adoption and diffusion of the technology innovation to practitioners and researchers. Thus, the purpose of this study is to present a model of adoption and diffusion of the Semantic Web and to offer propositions as guidelines for successful adoption through a qualitative research method including multiple case studies and in-depth interviews. The researcher conducted interviews with 15 people based on face-to face and 2 interviews by telephone and e-mail to collect data to saturate the categories. Nine interviews including 2 telephone interviews were from nine user organizations adopting the technology innovation and the others were from three supply organizations. Semi-structured interviews were used to collect data. The interviews were recorded on digital voice recorder memory and subsequently transcribed verbatim. 196 pages of transcripts were obtained from about 12 hours interviews. Triangulation of evidence was achieved by examining each organization website and various documents, such as brochures and white papers. The researcher read the transcripts several times and underlined core words, phrases, or sentences. Then, data analysis used the procedure of open coding, in which the researcher forms initial categories of information about the phenomenon being studied by segmenting information. QSR NVivo version 8.0 was used to categorize sentences including similar concepts. 47 categories derived from interview data were grouped into 21 categories from which six factors were named. Five factors affecting adoption of the Semantic Web were identified. The first factor is demand pull including requirements for improving search and integration services of the existing systems and for creating new services. Second, environmental conduciveness, reference models, uncertainty, technology maturity, potential business value, government sponsorship programs, promising prospects for technology demand, complexity and trialability affect the adoption of the Semantic Web from the perspective of technology push. Third, absorptive capacity is an important role of the adoption. Fourth, suppler's competence includes communication with and training for users, and absorptive capacity of supply organization. Fifth, over-expectance which results in the gap between user's expectation level and perceived benefits has a negative impact on the adoption of the Semantic Web. Finally, the factor including critical mass of ontology, budget. visible effects is identified as a determinant affecting routinization and infusion. The researcher suggested a model of adoption and diffusion of the Semantic Web, representing relationships between six factors and adoption/diffusion as dependent variables. Six propositions are derived from the adoption/diffusion model to offer some guidelines to practitioners and a research model to further studies. Proposition 1 : Demand pull has an influence on the adoption of the Semantic Web. Proposition 1-1 : The stronger the degree of requirements for improving existing services, the more successfully the Semantic Web is adopted. Proposition 1-2 : The stronger the degree of requirements for new services, the more successfully the Semantic Web is adopted. Proposition 2 : Technology push has an influence on the adoption of the Semantic Web. Proposition 2-1 : From the perceptive of user organizations, the technology push forces such as environmental conduciveness, reference models, potential business value, and government sponsorship programs have a positive impact on the adoption of the Semantic Web while uncertainty and lower technology maturity have a negative impact on its adoption. Proposition 2-2 : From the perceptive of suppliers, the technology push forces such as environmental conduciveness, reference models, potential business value, government sponsorship programs, and promising prospects for technology demand have a positive impact on the adoption of the Semantic Web while uncertainty, lower technology maturity, complexity and lower trialability have a negative impact on its adoption. Proposition 3 : The absorptive capacities such as organizational formal support systems, officer's or manager's competency analyzing technology characteristics, their passion or willingness, and top management support are positively associated with successful adoption of the Semantic Web innovation from the perceptive of user organizations. Proposition 4 : Supplier's competence has a positive impact on the absorptive capacities of user organizations and technology push forces. Proposition 5 : The greater the gap of expectation between users and suppliers, the later the Semantic Web is adopted. Proposition 6 : The post-adoption activities such as budget allocation, reaching critical mass, and sharing ontology to offer sustainable services are positively associated with successful routinization and infusion of the Semantic Web innovation from the perceptive of user organizations.

• Journal of the Korean Society of Safety
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• v.7 no.2
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• pp.63-70
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• 1992

The aim of this research is to obtain a basic quantitative understanding of the effect of a noncondensable gas on the absorption of water vapor by a $H_2O$ / LiBr combination with n-octanol as the surfactant. Nonflowing aqueous solutions of LiBr (40,45,50 mass％) were exposed to saturated water vapor following the addition of an n-octanol sufactant (0.01 and 0.6 mass％). A small amount of a noncondensable gas (air) was allowed into the absorber (0.03 volume％) and its effect was analyzed by measuring the amount of water vapor absorbed. This study will aid to predict the performance of heat pump and safety operating condition when the noncondensable gas is not allowed in the absorber The results indicate that, in the presence of small amounts of a noncondensable gas, vapor absorption enhancement ratios are less than half o( those obtained under the same experimental conditions when a noncondensable gas is not present (1). The presence of a noncondensable gas causes the partial vapor pressure of air to increase at the vapor / liquid interface, which results in an instability of vapor absorption rate nd. hence, in an inhibition of interfacial disturbance.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.105-122
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• 2019

Dimensionality reduction is one of the methods to handle big data in text mining. For dimensionality reduction, we should consider the density of data, which has a significant influence on the performance of sentence classification. It requires lots of computations for data of higher dimensions. Eventually, it can cause lots of computational cost and overfitting in the model. Thus, the dimension reduction process is necessary to improve the performance of the model. Diverse methods have been proposed from only lessening the noise of data like misspelling or informal text to including semantic and syntactic information. On top of it, the expression and selection of the text features have impacts on the performance of the classifier for sentence classification, which is one of the fields of Natural Language Processing. The common goal of dimension reduction is to find latent space that is representative of raw data from observation space. Existing methods utilize various algorithms for dimensionality reduction, such as feature extraction and feature selection. In addition to these algorithms, word embeddings, learning low-dimensional vector space representations of words, that can capture semantic and syntactic information from data are also utilized. For improving performance, recent studies have suggested methods that the word dictionary is modified according to the positive and negative score of pre-defined words. The basic idea of this study is that similar words have similar vector representations. Once the feature selection algorithm selects the words that are not important, we thought the words that are similar to the selected words also have no impacts on sentence classification. This study proposes two ways to achieve more accurate classification that conduct selective word elimination under specific regulations and construct word embedding based on Word2Vec embedding. To select words having low importance from the text, we use information gain algorithm to measure the importance and cosine similarity to search for similar words. First, we eliminate words that have comparatively low information gain values from the raw text and form word embedding. Second, we select words additionally that are similar to the words that have a low level of information gain values and make word embedding. In the end, these filtered text and word embedding apply to the deep learning models; Convolutional Neural Network and Attention-Based Bidirectional LSTM. This study uses customer reviews on Kindle in Amazon.com, IMDB, and Yelp as datasets, and classify each data using the deep learning models. The reviews got more than five helpful votes, and the ratio of helpful votes was over 70% classified as helpful reviews. Also, Yelp only shows the number of helpful votes. We extracted 100,000 reviews which got more than five helpful votes using a random sampling method among 750,000 reviews. The minimal preprocessing was executed to each dataset, such as removing numbers and special characters from text data. To evaluate the proposed methods, we compared the performances of Word2Vec and GloVe word embeddings, which used all the words. We showed that one of the proposed methods is better than the embeddings with all the words. By removing unimportant words, we can get better performance. However, if we removed too many words, it showed that the performance was lowered. For future research, it is required to consider diverse ways of preprocessing and the in-depth analysis for the co-occurrence of words to measure similarity values among words. Also, we only applied the proposed method with Word2Vec. Other embedding methods such as GloVe, fastText, ELMo can be applied with the proposed methods, and it is possible to identify the possible combinations between word embedding methods and elimination methods.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.