• Journal of Industrial Convergence
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• v.21 no.1
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• pp.175-185
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• 2023

Recently, novel viral infections such as COVID-19 have spread and pose a serious public health problem. In particular, these diseases have a fatal effect on the elderly, threatening life and causing serious social and economic losses. Accordingly, applications such as telemedicine, healthcare, and disease prevention using the Internet of Things (IoT) and artificial intelligence (AI) have been introduced in many industries to improve disease detection, monitoring, and quarantine performance. However, since existing technologies are not applied quickly and comprehensively to the sudden emergence of infectious diseases, they have not been able to prevent large-scale infection and the nationwide spread of infectious diseases in society. Therefore, in this paper, we try to predict the spread of infection by collecting various infection information with regional limitations through a virus disease information collector and performing AI analysis and severity matching through an AI broker. Finally, through the Korea Centers for Disease Control and Prevention, danger alerts are issued to the elderly, messages are sent to block the spread, and information on evacuation from infected areas is quickly provided. A realistic elderly support system compares the location information of the elderly with the information of the infected area and provides an intuitive danger area (infected area) avoidance function with an augmented reality-based smartphone application. When the elderly visit an infected area is confirmed, quarantine management services are provided automatically. In the future, the proposed system can be used as a method of preventing a crushing accident due to sudden crowd concentration in advance by identifying the location-based user density.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.211-221
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• 2022

Recently, the demand for the cultivation of upland soil has been increasing, and the rate of conversion of paddy soil into upland soil is also increasing. Theincrease in uneven precipitation due to climate change has resulted in dramatic effects of waterlogging stress on upland crops. Therefore, the present study was conducted to investigate the changes in growth characteristics and the expression patterns of proteins at the two-leaf stage of adzuki beans. The domestic cultivar, Arari (Miryang No. 8), was used to test waterlogging stress. At the two-leaf stage of adzuki beans, plant height slightly decreased androot fresh weight showed significant changes after 3 days of waterlogging treatment. Chlorophyll content was also significantly different after 3 days of waterlogging treatment compared to its content in control plants. Using two-dimensional gel electrophoresis, more than 400 protein spots were identified. Twenty-one differentially expressed proteins from the two-leaf stage were analyzed using linear trap quadrupole-Fourier transform-ion cyclotron resonance mass spectrometry. Of these 21 proteins, 9 were up-regulated and 12 were down-regulated under waterlogging treatment. Protein information resource (https://pir.georgetown.edu/) categories were assigned to all 49 proteins according to their molecular function, cellular component localization, and biological processes. Most of the proteins were found to be involved in the biological process, carbohydrate metabolism and were localized in chloroplasts.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1231-1237
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• 2022

In the present study, the optimization of the main particulars of a ship using AI-based design search techniques was investigated. For the design search techniques, the SHERPA algorithm by HEEDS was applied, and CFD analysis using STAR-CCM+ was applied for the calculation of resistance performance. Main particulars were automatically transformed by modifying the main particulars of the ship at the stage of preprocessing using JAVA script and Python. Small catamaran was chosen for the present study, and the main dimensions of the length, breadth, draft of demi-hull, and distance between demi-hulls were considered as design variables. Total resistance was considered as an objective function, and the range of displaced volume considering the arrangement of the outfitting system was chosen as the constraint. As a result, the changes in the individual design variables were within ±5%, and the total resistance of the optimized hull form was decreased by 11% compared with that of the existing hull form. Throughout the present study, the resistance performance of small catamaran could be improved by the optimization of the main dimensions without direct modification of the hull shape. In addition, the application of optimization using design search techniques is expected for the improvement in the resistance performance of a ship.

• Journal of Life Science
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• v.33 no.1
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• pp.8-14
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• 2023

Peroxidasin (PXDN), a multidomain heme peroxidase containing extracellular matrix (ECM) motifs, as well as a catalytic domain, catalyzes the sulfilimine crosslink of collagen IV (Col IV) to reinforce Col IV scaffolds. We previously reported that PXDN is required for endothelial cell (EC) survival and growth signaling through sulfilimine crosslink-dependent matrix assembly. In this study, we examined whether peroxidase activity is required for PXDN function in ECs. First, we constructed a mutant PXDN by point mutation of two highly conserved amino acids, Q823 and D826, which are present in the active site of the peroxidase domain. After isolation of HEK293 clones highly expressing the mutant protein, conditioned medium (CM) was obtained after incubating the cells in serum-free medium for 24 hours and then analyzed by Western blot analysis under nonreducing conditions. The results revealed that the mutant PXDN formed a trimer and that it was cleaved by proprotein convertase-like wild-type (WT) PXDN. However, peroxidase activity was not detected in the CM containing the mutant PXDN, in contrast to that of WT PXDN. In addition, the sulfilimine crosslink ability of the mutant PXDN was lost. Moreover, the CM containing the mutant PXDN failed to promote the growth of PXDN-depleted ECs, unlike the CM containing WT PXDN. These results suggest that the peroxidase activity of PXDN affects EC growth by forming a sulfilimine crosslink.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.16-30
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• 2023

As the concept of metaverse has received great attention, interest in metaverse related to landscape architecture is also increasing. The aim of this research is to understand the potential and tasks of applying metaverse in the field of landscape architecture by analyzing the user experience of a metaverse platform. The object of the research is Meta-Everland built in the Roblox platform, which has the most users among landscape architectural metaverses in Korea. NPS of 30 users who have been to Everalnd was investigated after using Meta-Everland with interviews. NPS before the metaverse experience was -16 and NPS after the experience was -24. This result means that the promotion level was lowered after the experience of the metaverse. There were three causes of lowered NPS: lack of users, low-quality graphics and interface, and lack of content. The factor of lack of users was the result of the other two problems. The factor of low technical quality is hard to be improved in a short period of time. Therefore, the main task to improve the metaverse is developing better metaverse content related to landscape architecture. It is more appropriate to develop metaverse-specific content rather than improve reality issues. Applying AR and VR devices, enhancing communication function, and developing potential as a simulation device are needed to be considered.

• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.45-64
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• 2022

Due to the recent and rapid globalization, logistics outsourcing has expanded globally and is seen as a means of creating a robust logistics system. However, many businesses continue to have difficulties with their logistics outsourcing contracts, which compels them to reinstate the logistics function for internal management. This study aims to investigate how organizational capabilities of logistics service providers (LSPs), notably flexibility, integration, innovation, and technological capabilities, impact on the logistics outsourcing success in Ugandan food processing firms. Using a structured questionnaire survey, cross-sectional data collected from 211 food processing firms in Kampala - Uganda were analyzed by partial least squares-structural equation modeling (PLS-SEM) using SmartPLS 3.3.7 software to examine the theorized relationships. The study findings revealed that whereas the technological and innovation capabilities positively and significantly influence logistics outsourcing success, the effects of flexibility and integration capabilities were insignificant. Additionally, the importance-performance map analysis (IPMA) reveals that the technological capability is a priority capability, followed by the innovation capability if logistics outsourcing success is to be achieved. Conversely, flexibility and integration capabilities are of low priority.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.105-126
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• 2023

The domestic used car market continues to grow along with the used car online platform service. The used car online platform service discloses vehicle specifications, accident history, inspection history, and detailed options to service consumers. Most of the preceding studies were predictions of used car prices using vehicle specifications and some options for vehicles. As a result of the study, it was confirmed that there was a nonlinear relationship between used car prices and some specification variables. Accordingly, the researchers tried to solve the nonlinear problem by executing a Machine Learning model. In common, the Regression based Machine Learning model had the advantage of knowing the actual influence and direction of variables, but there was a disadvantage of low Cost Function figures compared to the Decision Tree based Machine Learning model. This study attempted to predict used car prices of six domestic brands by utilizing both vehicle specifications and vehicle options. Through this, we tried to collect the advantages of the two types of Machine Learning models. To this end, we sequentially conducted a regression based Machine Learning model and a decision tree based Machine Learning model. As a result of the analysis, the practical influence and direction of each brand variable, and the best tree based Machine Learning model were selected. The implications of this study are as follows. It will help buyers and sellers who use used car online platform services to predict approximate used car prices. And it is hoped that it will help solve the problem caused by information inequality among users of the used car online platform service.

• Atmosphere
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• v.33 no.4
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• pp.367-385
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• 2023

The variabilities of precipitation and particulate matters (i.e., PM₁₀ and PM_2.5) and the scavenging efficiency of PMs by precipitation were quantified using long-term measurements in Seoul, Korea. The 21 years (2001~2021) measurements of precipitation and PM₁₀ mass concentrations, and the 7 years (2015~2021) of PM_2.5 mass concentrations were used. Statistical analysis was performed for each period (i.e., year, season, and month) to identify the long-term variabilities of PMs and precipitation. PM₁₀ and PM_2.5 decreased annually and the decreasing rate of PM₁₀ was greater than PM_2.5. The precipitation intensity did not show notable variation, whereas the annual precipitation amount showed a decreasing trend. The summer precipitation amount contributed 61.10% to the annual precipitation amount. The scavenging efficiency by precipitation was analyzed based on precipitation events separated by 2-hour time intervals between hourly precipitation data for 7 years. The scavenging efficiencies of PM₁₀ and PM_2.5 were quantified as a function of precipitation characteristics (i.e., precipitation intensity, amount, and duration). The calculated average scavenging efficiency of PM₁₀ (PM_2.5) was 39.59% (35.51%). PM₁₀ and PM_2.5 were not always simultaneously scavenged due to precipitation events. Precipitation events that simultaneously scavenged PM₁₀ and PM_2.5 contributed 42.24% of all events, with average scavenging efficiency of 42.93% and 43.39%. The precipitation characteristics (i.e., precipitation intensity, precipitation amount, and precipitation duration) quantified in these events were 2.42 mm hr^-1, 15.44 mm, and 5.51 hours. This result corresponds to 145% (349%; 224%) of precipitation intensity (amount; duration) for the precipitation events that do not simultaneously scavenge PM₁₀ and PM_2.5.

• Journal of the korean academy of Pediatric Dentistry
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• v.50 no.2
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• pp.229-238
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• 2023

The objective of this study was to investigate trends in ankyloglossia and its surgical treatment among pediatric patients in South Korea from 2011 to 2020. Data from Health Insurance Review and Assessment Service (HIRA)'s Healthcare Bigdata Hub were used for analysis of the ankyloglossia diagnosis rate and frenum surgery rate. Considering annual population change, crude rates per 100,000 were calculated and analyzed. To investigate other factors of frenum surgery incidence besides gender and age, pediatric patient sample data from HIRA were used. The diagnosis rate of ankyloglossia increased from 204.4 in 2011 to 356.6 per 100,000 people in 2020, while the frenum surgery rate increased from 26.8 to 34.3 per 100,000 people. Males were more likely to receive frenum surgery than females. Surgeries were more likely to be done at a hospital instead of a clinic or a general hospital. In the age group of 0 - 4 years, the largest number of frenum surgeries were performed in pediatrics, and in the age group of 5 - 9 years, the largest number of surgeries were conducted in pediatric dentistry. In the older age groups, the largest proportion of frenum surgeries were performed in the departments of conservative dentistry and oral and maxillofacial surgery. The diagnosis of ankyloglossia and the operation of frenum surgery among South Korean children increased during the last decade. Since the function of the tongue can affect maxillofacial development in many aspects, pediatric dentists should pay more attention to the functional management of intraoral soft tissue in growing children.