• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.295-300
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• 2024

This paper discusses the incompleteness of the SNOMED CT and proposes a noble metric which evaluates similarity among sibling nodes as a method to address this incompleteness. SNOMED CT encompasses an extensive range of medical terms, but it faces issues of ontology incompleteness, such as missing concepts in the hierarchy. We propose a noble metric for evaluating similarity among nodes within a node group, composed of multiple sibling nodes, to identify missing concepts, and identify groups with low similarity. Analyzing the similarity of sibling node groups in the March 2023 international release of SNOMED CT, the average similarity of 29,199 sibling node groups, which are sub-concepts of the clinical finding concept and are consist of two or more sibling nodes, was found to be 0.81. The group with the lowest similarity was associated with child concepts of poisoning, with a similarity of 0.0036.

• Korean Journal of Radiology
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• v.23 no.1
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• pp.139-149
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• 2022

Objective: To compare the effects of bone suppression imaging using deep learning (BSp-DL) based on a generative adversarial network (GAN) and bone subtraction imaging using a dual energy technique (BSt-DE) on radiologists' performance for pulmonary nodule detection on chest radiographs (CXRs). Materials and Methods: A total of 111 adults, including 49 patients with 83 pulmonary nodules, who underwent both CXR using the dual energy technique and chest CT, were enrolled. Using CT as a reference, two independent radiologists evaluated CXR images for the presence or absence of pulmonary nodules in three reading sessions (standard CXR, BSt-DE CXR, and BSp-DL CXR). Person-wise and nodule-wise performances were assessed using receiver-operating characteristic (ROC) and alternative free-response ROC (AFROC) curve analyses, respectively. Subgroup analyses based on nodule size, location, and the presence of overlapping bones were performed. Results: BSt-DE with an area under the AFROC curve (AUAFROC) of 0.996 and 0.976 for readers 1 and 2, respectively, and BSp-DL with AUAFROC of 0.981 and 0.958, respectively, showed better nodule-wise performance than standard CXR (AUAFROC of 0.907 and 0.808, respectively; p ≤ 0.005). In the person-wise analysis, BSp-DL with an area under the ROC curve (AUROC) of 0.984 and 0.931 for readers 1 and 2, respectively, showed better performance than standard CXR (AUROC of 0.915 and 0.798, respectively; p ≤ 0.011) and comparable performance to BSt-DE (AUROC of 0.988 and 0.974; p ≥ 0.064). BSt-DE and BSp-DL were superior to standard CXR for detecting nodules overlapping with bones (p < 0.017) or in the upper/middle lung zone (p < 0.017). BSt-DE was superior (p < 0.017) to BSp-DL in detecting peripheral and sub-centimeter nodules. Conclusion: BSp-DL (GAN-based bone suppression) showed comparable performance to BSt-DE and can improve radiologists' performance in detecting pulmonary nodules on CXRs. Nevertheless, for better delineation of small and peripheral nodules, further technical improvements are required.

• Korean Journal of Community Nutrition
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• v.29 no.1
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• pp.34-50
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• 2024

Objectives: Transformation through a sustainable food system to provide healthy diets is essential for enhancing both human and planetary health. This study aimed to explain about sustainable diets and illustrate appropriate measurement of adherence to sustainable diets using a pre-existing index. Methods: For literature review, we used PubMed and Google Scholar databases by combining the search terms "development," "validation," "sustainable diet," "sustainable diet index," "planetary healthy diet," "EAT-Lancet diet," and "EAT-Lancet reference diet." For data presentation, we used data from National Health and Nutrition Examination Survey, 2017-2018, among adults aged 20 years and older (n = 3,920). Sustainable Diet Index-US (SDI-US), comprising four sub-indices corresponding to four dimensions of sustainable diets (nutritional quality, environmental impacts, affordability, and sociocultural practices), was calculated using data from 24-hour dietary recall interview, food expenditures, and food choices. A higher SDI-US score indicated greater adherence to sustainable diets (range: 4-20). This study also presented SDI-US scores according to the sociodemographic status. All analyses accounted for a complex survey design. Results: Of 148 papers, 16 were reviewed. Adherence to sustainable diets fell into 3 categories: EAT-Lancet reference diet-based (n = 8), Food and Agriculture Organization (FAO) definition-based (n = 4), and no specific guidelines but including the sustainability concept (n = 4). Importantly, FAO definition emphasizes on equal importance of four dimensions of diet (nutrition and health, economic, social and cultural, and environmental). The mean SDI-US score was 13 out of 20 points, and was higher in older, female, and highly educated adults than in their counterparts. Conclusions: This study highlighted that sustainable diets should be assessed using a multidimensional approach because of their complex nature. Currently, SDI can be a good option for operationalizing multidimensional sustainable diets. It is necessary to develop a Korean version of SDI through additional data collection, including environmental impact of food, food price, food budget, and use of ready-made products.

• Ocean Systems Engineering
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• v.14 no.1
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• pp.85-99
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• 2024

Ocean surface currents have an essential role in the Earth's climate system and significantly impact the marine ecosystem, weather patterns, and human activities. However, predicting ocean surface currents remains challenging due to the complexity and variability of the oceanic processes involved. This review article provides an overview of the current research status, challenges, and opportunities in the prediction of ocean surface currents. We discuss the various observational and modelling approaches used to study ocean surface currents, including satellite remote sensing, in situ measurements, and numerical models. We also highlight the major challenges facing the prediction of ocean surface currents, such as data assimilation, model-observation integration, and the representation of sub-grid scale processes. In this article, we suggest that future research should focus on developing advanced modeling techniques, such as machine learning, and the integration of multiple observational platforms to improve the accuracy and skill of ocean surface current predictions. We also emphasize the need to address the limitations of observing instruments, such as delays in receiving data, versioning errors, missing data, and undocumented data processing techniques. Improving data availability and quality will be essential for enhancing the accuracy of predictions. The future research should focus on developing methods for effective bias correction, a series of data preprocessing procedures, and utilizing combined models and xAI models to incorporate data from various sources. Advancements in predicting ocean surface currents will benefit various applications such as maritime operations, climate studies, and ecosystem management.

• Journal of Korean Medical classics
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• v.37 no.3
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• pp.37-60
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• 2024

Objectives : First, to investigate the diffusion of the Daoist Yangseng(養生) Method of Bokshik(服食) as an individual strategy to deal with poor a medical environment in Joseon from mid to late 16th century, through microhistorical methodology. Second, to reveal the process of Bokshik(服食) being recognized as a social phenomenon through the deaths of Bokshik(服食) takers. Methods : 1. Trace the entire treating process of a Scholar-Physicians(儒醫) and evaluate sub-par treatments within the process. 2. Analyze in detail the understandings and assessments of the Scholar-Physician and various related agencies on selected strategies made on the individual level. Results & Conclusions : 1. The dissemination of the Daoist Yangseng(養生) Method of Bokshik(服食), occurred since the mid-16th century within Confucian Joseon. 2. Hidden behind the contemporary medical ideology-'a disease should be treated by medicine'-were realities that were difficult to put into practice due to an insufficient medical system and lack of human and material medical resources. 3. The Daoist Yangseng(養生) Method of Bokshik(服食) was disseminated amid the gap between this ideology and reality, due to its claimed ability that ranged from treating a disease to recovery of health, juvenescence and longevity, with the simple intake of a single prescription consisted of one or two or a handful of medicinal ingredients. 4. As Bokshik(服食) spread throughout society, side effects and deaths came about and became known as well. Bokshik(服食) as a personal strategy on an individual level and its problems became recognized as a social phenomenon through hearsay which includes medical experiences.

• Economic and Environmental Geology
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• v.47 no.4
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• pp.421-430
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• 2014

In this study, a series of autoclave experiments were conducted in order to investigate the geochemical and mineralogical effects of carbon dioxide on deep subsurface environments. High pressure and temperature conditions of $50^{\circ}C$ and 100 bar, which are representative environments for geological $CO_2$ sequestration, were created in stainless-steel autoclaves for simulating the interactions in the $scCO_2$-groundwater-mineral reaction system. Zeolite, a widespread mineral in Pohang Basin where many researches have been focused as a candidate for geological $CO_2$ sequestration, and groundwater sampled from an 800 m depth aquifer were applied in the experiments. Geochemical and mineralogical alterations after 30 days of $scCO_2$-groundwater-zeolite sample reactions were quantitatively examined by XRD, XRF, and ICP-OES investigations. The results suggested that dissolution of zeolite sample was enhanced under the acidic condition induced by dissolution of $scCO_2$. As the cation concentrations released from zeolite sample increase, $H^+$ in groundwater was consumed and pH increases up to 10.35 after 10 days of reaction. While cation concentrations showed increasing trends in groundwater due to dissolution of the zeolite sample, Si concentrations decreased due to precipitation of amorphous silicate, and Ca concentrations decreased due to cation exchange and re-precipitation of calcite. Through the reaction experiments, it was observed that introduction of $CO_2$ could make alterations in dissolution characteristics of minerals, chemical compositions and properties of groundwater, and mineral compositions of aquifer materials. Results also showed that geochemical reactions such as cation exchange or dissolution/precipitation of minerals could play an important role to affect physical and chemical characteristics of geologic formations and groundwater.

• Journal of the Korean Society for Marine Environment & Energy
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• v.8 no.2
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• pp.100-110
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• 2005

We carried oui a study on the marine environment and distribution of phytoplankton community, such as chlorophyll a, species composition, dominant species and standing crops in the Northern East China Sea during early summer of 2004. According to the analysis of a T-S diagram, three characteristics of water masses were identified. We classified them into the coastal water mass, the cold water mass and the oceanic water mass. The first was characterized by the low temperature and the low salinity originated from China territory, the secondary was characterized by the low temperature, the low salinity and the high density originated from bottom cold water of Yellow Sea, and the third was done by the high temperature and salinity originated from Tsushima warm current. The internal discontinuous layer among them was farmed at the intermediate depth (about $5{\sim}30m$ layer). And the thermal front by upwelling region between the cold water mass and Tsushima warm current appeared in the central parts of the South Sea of Korea. The Phytoplankton community in the surface and stratified layers was a total of 44 species belonging to 26 genera. Dominant species were Prorocentrum triestinum, Scrippsiella trochoidea, Skeletonema costatum & Leptocylindrus mediterraneus. Standing crops of phytoplankton in the surface layer fluctuated between $0.3{\times}10^3$ cells/L and $10.8{\times}10^3$ cells/L. Diatoms appeared mainly in the Tsushima warm current regions, and flagellates occurred in the frontal zone and the low salinity regions where was the transfer areas of Chinese continental coastal waters. Chlorophyll a concentration by controlled phytoflagellate ratio in the South Sea of Korea was high values in the frontal zone and sub-surface layer. It was high concentration in the upwelling and coastal waters regions, but low concentration in the Tsushima warm current regions. The Chl-a maximum layers appeared in the thermochline depth or sub-surface layer lower than thermocline. The phytoplankton production in the South Sea of Korea was controlled by the expanded coastal waters of Chinese Continent which include a high concentrations of nutrients.

• Journal of Korea Water Resources Association
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• v.40 no.11
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• pp.887-898
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• 2007

A physically based semi-distributed model, SWAT was applied to the Chungju Dam upstream watershed in order to investigate the spatial and temporal characteristics of watershed sediment yields. For this, general features of the SWAT and sediment simulation algorithm within the model were described briefly, and watershed sediment modeling system was constructed after calibration and validation of parameters related to the runoff and sediment. With this modeling system, temporal and spatial variation of soil loss and sediment yields according to watershed scales, land uses, and reaches was analyzed. Sediment yield rates with drainage areas resulted in $0.5{\sim}0.6ton/ha/yr$ excluding some upstream sub-watersheds and showed around 0.51 ton/ha/yr above the areas of $1,000km^2$. Annual average soil loss according to land use represented the higher values in upland areas, but relatively lower in paddy and forest areas which were similar to the previous results from other researchers. Among the upstream reaches, Pyeongchanggang and Jucheongang showed higher sediment yields which was thought to be caused by larger area and higher fraction of upland than other upstream sub-areas. Monthly sediment yields at the main outlet showed same trend with seasonal rainfall distribution, that is, approximately 62% of annual yield was generated during July to August and the amount was about 208 ton/yr. From the results, we could obtain the uniform value of sediment yield rate and could roughly evaluate the effect of soil loss with land uses, and also could analyze the temporal and spatial characteristics of sediment yields from each reach and monthly variation for the Chungju Dam upstream watershed.

• Korean Journal of Environment and Ecology
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• v.34 no.6
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• pp.601-609
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• 2020

This study aims to draw suggestions for establishing the Post-2020 national policy direction and goals related to protected areas in Korea by analyzing the trends of major discussion issues on protected areas in the Convention on Biological Diversity (CBD) and reviewing the achievement progress of the Aichi target-11. Regarding the CBD decisions on protected areas, two decisions (Decisions II/7 and II/8) were adopted in 1995, and then the Program of Work on Protected Areas (PoWPA), which presented an ideal blueprint for protected areas, was adopted at the 7th Conference of the Parties (COP) in 2004. At the 10th COP in 2010, the "Strategic Plan for Biodiversity 2011-2020 and the Aichi Biodiversity Target" (Decision X/2) was adopted along with the Decision X/31, which presented ten key issues related to protected areas. The global outcomes of the Aichi Target-11 include 15% of the earth's land area and 7.4% of the ocean being designated as protected areas. In Korea, 16.63% of the land and 2.12% of the ocean have been designated as protected areas. However, the outcomes of the effective and equitable management, protection of areas important to biodiversity and ecosystem services, and identifying "Other effective area-based conservation measures" (OECMs) and linking them with protected areas have been found to be significantly short of global goals. The first draft of the Post-2020 Global Biodiversity Framework (Post-2020 GBF) prepared in January 2020 presented multi-step objectives. They included protecting at least 60% of particularly important sites for biodiversity through protected areas and other effective area-based conservation measures, at least 30% of the entire land and sea areas, and at least 10% of them under strict protection by 2030. The Updated Zero drafted in August 2020 concisely set out one quantitative goal of at least 30% of the globe by 2030, adding qualitative goals that these areas should be protected and conserved through "well connected and effective system of protected areas and OECMs at least 30 % of the planet with the focus on areas particularly important for biodiversity." Based on the draft Post-2020 GBF's targets related to protected areas and Korea's national targets reflecting the current state of Korea and established national plans, we suggest the national targets "to protect and conserve at least 30% of the land area and 10% of the marine area and to strengthen the means of qualitative achievement by establishing sub-targets through an effective system of protected areas and OECMs by 2030.".

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.