• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.228-237
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• 2021

In those day, the Busan local government had instituted a rule to support and enhance competition as well as improve respect for the ship management industry. This study aims to extract the cause factors to enhance such competition using intuitionistic decision making trial and evaluation laboratory (DEMATEL) and interpretive structural modeling (ISM) methods. First, eight factors were extracted from the specifications in the Ship Management Industry Development Act. Second, the intuitionistic fuzzy number was converted to a crisp number using the standard fuzzy number. Third, the influence relationship was analyzed using DEMATEL, and the priority ranks for the factors are determined using ISM. From the results of the impact relationship analysis, the three main cause factors were determined as improvement of technical ship management capability, improvement of expertise of manpower for onshore management, and improvement of the quality of the Korean seafarer. The priorities under the ISM method, in descending order, were as follows: improvement of the quality of Korean seafarers, improvement of professionalism among the manpower for shore management, improvement of technical ship management capability, improvement of commercial ship management capability, establishment of a comprehensive information system, improvement of the working conditions and employment environment for seafarers, financial support such as overseas orders, and strengthening the availability of foreign seafarers. Therefore, it is necessary to prioritize policy promotion based on these factors, especially the top three, as these have the highest impact.

• Korean Association of Arts Management
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• no.53
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• pp.207-247
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• 2020

is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

• Nutrition Research and Practice
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• v.16 no.6
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• pp.685-699
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• 2022

BACKGROUND/OBJECTIVES: Platycodon grandiflorum (PG) has long been known as a medicinal herb effective in various diseases, including bronchitis and asthma, but is still more widely used for food. Fermentation methods are being applied to increase the pharmacological composition of PG extracts and commercialize them with high added value. This study examines the hydrolyzed and fermented PG extract (HFPGE) fermented with Lactobacillus casei in RAW 264.7 cells, and investigates the effect of amplifying the immune and the probable molecular mechanism. MATERIALS/METHODS: HFPGE's total phenolic, flavonoid, saponin, and platycodin D contents were analyzed by colorimetric analysis or high-performance liquid chromatography. Cell viability was measured by the MTT assay. Phagocytic activity was analyzed by a phagocytosis assay kit, nitric oxide (NO) production by a Griess reagent system, and cytokines by enzyme-linked immunosorbent assay kits. The mRNA expressions of inducible nitric oxide synthase (iNOS) and cytokines were analyzed by reverse transcription-polymerase chain reaction, whereas MAPK and nuclear factor (NF)-κB activation were analyzed by Western blots. RESULTS: Compared to PGE, HFPGE was determined to contain 13.76 times and 6.69 times higher contents of crude saponin and platycodin D, respectively. HFPGE promoted cell proliferation and phagocytosis in RAW 264.7 cells and regulated the NO production and iNOS expression. Treatment with HFPGE also resulted in increased production of interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α, C-X-C motif chemokine ligand10, granulocyte-colony-stimulating factor, granulocyte-macrophage colony-stimulating factor, and monocyte chemoattractant protein-1, and the mRNA expressions of these cytokines. HFPGE also resulted in significantly increasing the phosphorylation of NF-κB p65, extracellular signal-regulated kinase, and c-Jun N-terminal kinase. CONCLUSIONS: Taken together, our results imply that fermentation and hydrolysis result in the extraction of more active ingredients of PG. Furthermore, we determined that HFPGE exerts immunostimulatory activity via the MAPK and NF-κB signaling pathways.

• Journal of the Korean Institute of Gas
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• v.26 no.4
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• pp.41-57
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• 2022

The global demand for carbon neutrality in response to climate change is in a situation where it is necessary to prepare countermeasures for carbon trade barriers for some countries, including Korea, which is classified as an export-led economic structure and greenhouse gas exporter. Therefore, digital transformation, which is one of the predictable ways for the carbon-neutral transition model to be applied, should be introduced early. By applying digital technology to industrial gas manufacturing facilities used in one of the major industries, high-tech manufacturing industry, and hydrogen gas facilities, which are emerging as eco-friendly energy, abnormal detection, and diagnosis services are provided with cloud-based predictive diagnosis monitoring technology including operating knowledge. Here are the trends. Small and medium-sized companies that are in the blind spot of carbon-neutral implementation by confirming the direction of abnormal diagnosis predictive monitoring through optimization, augmented reality technology, IoT and AI knowledge inference, etc., rather than simply monitoring real-time facility status It can be seen that it is possible to disseminate technologies such as consensus knowledge in the engineering domain and predictive diagnostic monitoring that match the economic feasibility and efficiency of the technology. It is hoped that it will be used as a way to seek countermeasures against carbon emission trade barriers based on the highest level of ICT technology.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.563-569
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• 2021

With the launch of Compact Advanced Satellite 500 series of various characteristics and the operation of KOMPSAT-3/3A, uses of high-resolution satellite images have been continuously increased. Especially, in order to provide satellite images in the form of ARD (Analysis Ready Data), various pre-processing such as geometric correction and radiometric correction have been developed. For pre-processing of high spatial satellite imagery, auxiliary information, such as solar zenith, solar azimuth and offnadir angle, should be required. However, most of the high-resolution satellite images provide the solar zenith and nadir angle for the entire image as a single variable. In this paper, the solar zenith and offnadir angle corresponding to each pixel of the image were calculated using RFM (Rational Function Model) and auxiliary information of the image, and the quality of extracted information were evaluated. In particular, for the utilization of pixel-based solar zenith and offnadir angle, pixel-based auxiliary data were applied in calculating the top of atmospheric reflectance, and comparative evaluation with a single constant-based top of atmospheric reflectance was performed. In the experiments using various satellite imagery, the pixel-based solar zenith and offnadir angle information showed a similar tendency to the auxiliary information of satellite sensor, and it was confirmed that the distortion was reduced in the calculated reflectance in the top of atmospheric reflectance.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.267-286
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• 2023

The conversational agents such as AI speakers utilize voice conversation for human-computer interaction. Voice recognition errors often occur in conversational situations. Recognition errors in user utterance records can be categorized into two types. The first type is misrecognition errors, where the agent fails to recognize the user's speech entirely. The second type is misinterpretation errors, where the user's speech is recognized and services are provided, but the interpretation differs from the user's intention. Among these, misinterpretation errors require separate error detection as they are recorded as successful service interactions. In this study, various text separation methods were applied to detect misinterpretation. For each of these text separation methods, the similarity of consecutive speech pairs using word embedding and document embedding techniques, which convert words and documents into vectors. This approach goes beyond simple word-based similarity calculation to explore a new method for detecting misinterpretation errors. The research method involved utilizing real user utterance records to train and develop a detection model by applying patterns of misinterpretation error causes. The results revealed that the most significant analysis result was obtained through initial consonant extraction for detecting misinterpretation errors caused by the use of unregistered neologisms. Through comparison with other separation methods, different error types could be observed. This study has two main implications. First, for misinterpretation errors that are difficult to detect due to lack of recognition, the study proposed diverse text separation methods and found a novel method that improved performance remarkably. Second, if this is applied to conversational agents or voice recognition services requiring neologism detection, patterns of errors occurring from the voice recognition stage can be specified. The study proposed and verified that even if not categorized as errors, services can be provided according to user-desired results.

• Design Convergence Study
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• v.15 no.2
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• pp.347-368
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• 2016

Recently, researches for the word of mouth(WOM) imply that consumers use WOM informations of products in their purchase process. This study suggests methods using opinion mining and visualization to understand consumers' opinion of each goods and each markets. For this study we conduct research that includes developing domain ontology based on reviews confined to "movie" category because people who want to have watching movie refer other's movie reviews recently, and it is analyzed by opinion mining and visualization. It has differences comparing other researches as conducting attribution classification of evaluation factors and comprising verbal dictionary about evaluation factors when we conduct ontology process for analyzing. We want to prove through the result if research method will be valid. Results derived from this study can be largely divided into three. First, This research explains methods of developing domain ontology using keyword extraction and topic modeling. Second, We visualize reviews of each movie to understand overall audiences' opinion about specific movies. Third, We find clusters that consist of products which evaluated similar assessments in accordance with the evaluation results for the product. Case study of this research largely shows three clusters containing 130 movies that are used according to audiences'opinion.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.43-45
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• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Analytical Science and Technology
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• v.22 no.6
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• pp.514-518
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• 2009

Coenzyme $Q_{10}$($CoQ_{10}$), a vitamin E-like substance, represents a components of the complex antioxidant system of the human organism. $CoQ_{10}$ levels in human plasma were determined by high performance liquid chromatography (HPLC) with UV detection. It was dissociated from lipoproteins by methanol and extracted into n-hexane with liquid-liquid extraction procedure, after centrifugation, the supernatant was dried under nitrogen gas stream. The residue was dissolved in the absolute ethanol. Determination of $CoQ_{10}$ was performed on a $C_{18}$ reversed-phase analytical column with ultraviolet detection at 275 nm and the mobile phase containing 15% (v/v) ethanol in methanol at a flow rate of 1.7 mL/min. The low limit of quantitation was 0.02 mg/L (S/N=10), the linearity between the concentration and peak height is from 0.1 to 2.0 mg/L. Twenty-four randomly selected plasma samples from apparently healthy, 27 to 44 year old individuals (males and females) were analyzed for total $CoQ_{10}$. The average level in these subjects was $0.62{\pm}0.13mg/L$ with the range of 0.41-0.98 mg/L. This method has a specific and a sufficient limit of quantitation (LOQ) for analysis of $CoQ_{10}$ in human plasma in both a clinical study and research at laboratories.