• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.8
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• pp.1164-1171
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• 2011

The purpose of this study was to compare service quality between local and global coffee brand shops and to investigate improvement. Of 350 questionnaires distributed to customers of six brand coffee shops (three local brands, three global brands) located in Daejeon, 330 complete questionnaires (94.3%) were analyzed. The questionnaire included a seven-point multiple-item scale for measuring service quality. The 21 items measuring service quality were grouped into four factors, and the mean scores for the levels of "representativeness", "coffee sensory and beverage features", "employee attitude" and "physical environment" were 5.42, 4.77, 4.74, and 4.13, respectively. The levels of "coffee sensory and beverage features" and "employee attitude" of the high income customers were significantly lower than those of the low income customers. The results showed that the levels of "employee attitude" of local coffee brand shops was significantly higher (p=0.050) than that of global coffee brand shops. Whereas, the levels of "representativeness" of global coffee brand shops was significantly higher (p=0.003) than that of local coffee brand shops. Based on the results, the global coffee brand shops should pay attention to internal marketing and the local coffee brand shops must strive to improve service quality through strategies such as improving brand awareness and developing representative beverages and foods.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.4
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• pp.392-400
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• 2003

We used an oxygen microelectrode to measure the vertical profiles of oxygen concentration in sediments located near point sources of organic matter. The measurements were carried out between 13th and 17th May, 2003, in semi-closed bay and coastal sediments in the central part of the South Sea. The measured oxygen penetration depths were extremely shallow and ranged from 1.30 to 3.80 mm. This suggested that the oxidation and reduction reactions in the early diagenesis should be studied at the mm depth scale. In order to estimate the oxygen consumption rate, we applied the one-dimension diffusion-reaction model to vertical profiles of oxygen near the sediment/water interface. Oxygen consumption rates were estimated to be between 10.8 and 27.6 mmol O$_2$ m$\^$-2/ day$\^$-1/(average: 19.1 mmol O$_2$ m$\^$-2/ day$\^$-1/). These rates showed a positive correlation with the organic carbon of the sediments. The corresponding benthic organic carbon oxidation rates calculated using an modified Redfield ratio (170/110) at the sediment/water interface were in the range of 89.5-228.1 mg C m$\^$-2/ day$\^$-1/(average: 158.0 mg C m$\^$-2/ day$\^$-1/). We suggest that these results are maximum values at the presents situation in the bay because the sampling sites were located near point sources of organic materials. This study will need to be carried out at many coastal sites and throughout the seasons to allow an understanding of the mechanisms of eutrophication e.g. the spatial distribution of oxygen consumption within the oxic zone and hypoxic conditions in the coastal sea.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• Korean Journal of Environment and Ecology
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• v.35 no.5
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• pp.558-568
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• 2021

Poor supervision and tourism activities have resulted in forest degradation in islands in Korea. Since the southern coastal region of the Korean peninsula was originally dominated by warm-temperate evergreen broad-leaved forests, it is desirable to restore forests in this region to their original vegetation. In this study, we identified suitable areas to be restored as evergreen broad-leaved forests by analyzing the environmental factors of existing evergreen broad-leaved forests in the islands of Jeollanam-do. We classified forest lands in the study area into six vegetation types from Sentinel-2 satellite images using a deep learning algorithm and analyzed the tolerance ranges of existing evergreen broad-leaved forests by measuring the locational, topographic, and climatic attributes of the classified vegetation types. Results showed that evergreen broad-leaved forests were distributed more in areas with a high altitudes and steep slope, where human intervention was relatively low. The human intervention has led to a higher distribution of evergreen broad-leaved forests in areas with lower annual average temperature, which was an unexpected but understandable result because an area with higher altitude has a lower temperature. Of the environmental factors, latitude and average temperature in the coldest month (January) were relatively less contaminated by the effects of human intervention, thus enabling the identification of suitable restoration areas of the evergreen broad-leaved forests. The tolerance range analysis of evergreen broad-leaved forests showed that they mainly grew in areas south of the latitude of 34.7° and a monthly average temperature of 1.7℃ or higher in the coldest month. Therefore, we predicted the areas meeting these criteria to be suitable for restoring evergreen broad-leaved forests. The suitable areas cover 614.5 km², which occupies 59.0% of the total forest lands on the islands of Jeollanamdo, and 73% of actual forests that exclude agricultural and other non-restorable forest lands. The findings of this study can help forest managers prepare a restoration plan and budget for island forests.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.193-204
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• 2022

This study analyzed the degree of influence of measurement and improvement of customer satisfaction level targeting kiosk users. In modern times, due to the development of technology and the improvement of the online environment, the probability that simple labor tasks will disappear after 10 years is close to 90%. Even in domestic research, it is predicted that 'simple labor jobs' will disappear due to the influence of advanced technology with a probability of about 36%. there is. In particular, as the demand for non-face-to-face services increases due to the Corona 19 virus, which is recently spreading globally, the trend of introducing kiosks has accelerated, and the global market will grow to 83.5 billion won in 2021, showing an average annual growth rate of 8.9%. there is. However, due to the unmanned nature of these kiosks, some consumers still have difficulties in using them, and consumers who are not familiar with the use of these technologies have a negative attitude towards service co-producers due to rejection of non-face-to-face services and anxiety about service errors. Lack of understanding leads to role conflicts between sales clerks and consumers, or inequality is being created in terms of service provision and generations accustomed to using technology. In addition, since kiosk is a representative technology-based self-service industry, if the user feels uncomfortable or requires additional labor, the overall service value decreases and the growth of the kiosk industry itself can be suppressed. It is important. Therefore, interviews were conducted on the main points of direct use with actual users centered on display color scheme, text size, device design, device size, internal UI (interface), amount of information, recognition sensor (barcode, NFC, etc.), Display brightness, self-event, and reaction speed items were extracted. Afterwards, using the questionnaire, the Kano model quality attribute classification of each expected evaluation item was carried out, and Timko's customer satisfaction coefficient, which can be calculated with accurate numerical values The PCSI Index analysis was additionally performed to determine the improvement priorities by finally classifying the improvement impact of the kiosk expected evaluation items through research. As a result, the impact of improvement appears in the order of internal UI (interface), text size, recognition sensor (barcode, NFC, etc.), reaction speed, self-event, display brightness, amount of information, device size, device design, and display color scheme. Through this, we intend to contribute to a comprehensive comparison of kiosk-based research in each field and to set the direction for improvement in the venture industry.

• Information Systems Review
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• v.21 no.4
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• pp.1-29
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• 2019

The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.

• Journal of Chest Surgery
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• v.39 no.5 s.262
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• pp.359-365
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• 2006

Background: Arterial grafts have been used to achieve better long-term results for coronary revascularization. Bilateral internal thoracic artery (ITA) grafts have a better results, but it may be not used in some situations such as diabetes and chronic obstructive pulmonary disease (COPD). We evaluated the clinical and angiographic results of composite left internal thoracic artery-radial artery (LITA-RA) Y graft. Material and Method: Between April 2002 and September 2004, 119 patients were enrolled in composite Y graft for coronary bypass surgery. The mean age was $62.6{\pm}8.8$ years old and female was 34.5%. Preoperative cardiac risk factors were as follows: hypertension 43.7%, diabetes 33.6%, smoker 41.2%, and hyperlipidemia 22.7%, There were emergency operation (14), cardiogenic shock (6), left ventricle ejection fraction (LVEF) less than 40% (17), and 17 cases of left main disease. Coronary angiography was done in 35 patients before the hospital discharge. Result: The number of distal anastomoses was $3.1{\pm}0.91$ and three patients (2.52%) died during hospital stay. The off-pump coronary artery bypass (OPCAB) was applied to 79 patients (66.4%). The LITA was anastomosed to left anterior descending system except three cases which was to lateral wall. The radial Y grafts were anastomosed to diagonal branches (4), ramus intermedius (21), obtuse marginal branches (109), posterolateral branches (12), and posterior descending coronary artery (8). Postoperative coronary angiography in 35 patients showed excellent patency rates (LITA 100%, and RA 88.5%; 3 RA grafts which anastomosed to coronary arteries <70% stenosed showed string sign with competitive flow). Conclusion: The LITA-RA Y composite graft provided good early clinical and angiographic results in multivessel coronary revascularization. But it should be cautiously used in selected patients.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.97-117
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• 2020

Product evaluation criteria is an indicator describing attributes or values of products, which enable users or manufacturers measure and understand the products. When companies analyze their products or compare them with competitors, appropriate criteria must be selected for objective evaluation. The criteria should show the features of products that consumers considered when they purchased, used and evaluated the products. However, current evaluation criteria do not reflect different consumers' opinion from product to product. Previous studies tried to used online reviews from e-commerce sites that reflect consumer opinions to extract the features and topics of products and use them as evaluation criteria. However, there is still a limit that they produce irrelevant criteria to products due to extracted or improper words are not refined. To overcome this limitation, this research suggests LDA-k-NN model which extracts possible criteria words from online reviews by using LDA and refines them with k-nearest neighbor. Proposed approach starts with preparation phase, which is constructed with 6 steps. At first, it collects review data from e-commerce websites. Most e-commerce websites classify their selling items by high-level, middle-level, and low-level categories. Review data for preparation phase are gathered from each middle-level category and collapsed later, which is to present single high-level category. Next, nouns, adjectives, adverbs, and verbs are extracted from reviews by getting part of speech information using morpheme analysis module. After preprocessing, words per each topic from review are shown with LDA and only nouns in topic words are chosen as potential words for criteria. Then, words are tagged based on possibility of criteria for each middle-level category. Next, every tagged word is vectorized by pre-trained word embedding model. Finally, k-nearest neighbor case-based approach is used to classify each word with tags. After setting up preparation phase, criteria extraction phase is conducted with low-level categories. This phase starts with crawling reviews in the corresponding low-level category. Same preprocessing as preparation phase is conducted using morpheme analysis module and LDA. Possible criteria words are extracted by getting nouns from the data and vectorized by pre-trained word embedding model. Finally, evaluation criteria are extracted by refining possible criteria words using k-nearest neighbor approach and reference proportion of each word in the words set. To evaluate the performance of the proposed model, an experiment was conducted with review on '11st', one of the biggest e-commerce companies in Korea. Review data were from 'Electronics/Digital' section, one of high-level categories in 11st. For performance evaluation of suggested model, three other models were used for comparing with the suggested model; actual criteria of 11st, a model that extracts nouns by morpheme analysis module and refines them according to word frequency, and a model that extracts nouns from LDA topics and refines them by word frequency. The performance evaluation was set to predict evaluation criteria of 10 low-level categories with the suggested model and 3 models above. Criteria words extracted from each model were combined into a single words set and it was used for survey questionnaires. In the survey, respondents chose every item they consider as appropriate criteria for each category. Each model got its score when chosen words were extracted from that model. The suggested model had higher scores than other models in 8 out of 10 low-level categories. By conducting paired t-tests on scores of each model, we confirmed that the suggested model shows better performance in 26 tests out of 30. In addition, the suggested model was the best model in terms of accuracy. This research proposes evaluation criteria extracting method that combines topic extraction using LDA and refinement with k-nearest neighbor approach. This method overcomes the limits of previous dictionary-based models and frequency-based refinement models. This study can contribute to improve review analysis for deriving business insights in e-commerce market.