• The Korean Journal of Nuclear Medicine Technology
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• 제25권2호
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• pp.25-28
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• 2021

Purpose CA 72-4 is a tumor marker that uses two monoclonal antibodies, CC49 and B72.3, to measure tumor-related glycoprotein(TAG72) in the serum. CA 72-4 is used to diagnose stomach, ovarian, and pancreatic cancers, and is known to perform high specificity for stomach cancer. The purpose of this study is to re-evaluate the reference value provided by the manufacturer through revalidation of the reference value in CA 72-4. Furthermore this study was conducted to provide useful help when making a clinical diagnosis at gastric cancer center. Materials and Methods We selected 271 patients who had been to health care center in national cancer center for the month of November 2020. The gender of the subjects was 140 males and 131 females, and the age group was from 30s to 60s. The reagent used in the study was a CA 72-4 IRMA KIT (ISOTOPES, Hungary) and the results were measured using a Dream Gamma-10 gamma counter (Shinjin medics, Korea). Results Statistical analysis of the results of this study used Hoffmann's method and Bayesian's method, which are primarily used in setting reference value. As a result of measuring CA 72-4 of 271 patients, the mean value was 4.54 U/mL and the median value was 3.30 U/mL. 24 people who deviated from 3SD were excluded from the measured value, the mean calculated after that was 3.53 U/mL, median was 3.00 U/mL and SD was 1.89. The reference value calculated based on this results was set to 7.31 U/mL. Conclusion The reference value provided by the manufacturer is less than 4 U/mL. It is slightly different from the value calculated in this study, 7.31 U/mL, so it seems necessary to reset the reference value according to the laboratory environment. Currently, we are receiving inquiries about the reference value from the center for gastric cancer at National Cancer Center. If additional research is carried out along with this study, it will be possible to set more accurate reference value.

• Clean Technology
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• 제28권1호
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• pp.24-31
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• 2022

Petroleum-based plastics are used for various purposes and pose a significant threat to the earth's environment and ecosystem. Many efforts have been taken globally in different areas to find alternatives. As part of these efforts, this study manufactured alginate-based polyvinyl alcohol (PVA) blended films by casting from an aqueous solution prepared by mixing 10 wt% petroleum-based PVA with biodegradable, marine biomass-derived alginate. Glutaraldehyde was used as a cross-linking agent, and cardanol, an alkyl phenol-based bio-oil extracted from cashew nut shell, was added in the range of 0.1 to 2.0 wt% to grant antibacterial activity to the films. FTIR and TGA were performed to characterize the manufactured blended films, and the tensile strength, degree of swelling, and antibacterial activity were measured. Results obtained from the FTIR, TGA, and tensile strength test showed that alginate, the main component, was well distributed in the PVA by forming a matrix phase. The brittleness of alginate, a known weakness as a single component, and the low thermal durability of PVA were improved by cross-linking and hydrogen bonding of the functional groups between alginate and PVA. Addition of cardanol to the alginate-based PVA blend significantly improved the antibacterial activity against S. aureus and E. coli. The antibacterial performance was excellent with a death rate of 98% or higher for S. aureus and about 70% for E. coli at a contact time of 60 minutes. The optimal antibacterial activity of the alginate-PVA blended films was found with a cardanol content range between 0.1 to 0.5 wt%. These results show that cardanol-containing alginate-PVA blended films are suitable for use as various antibacterial materials, including as food packaging.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• 제16권6호
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• pp.17-29
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• 2021

Recently, as social distancing have been raised due to the re-spread of COVID-19, the number of serial entrepreneurs who are closing their business is rapidly increasing. Learning from failure is a source of success, but business failure can result in psychological and economic losses and negative emotions of the serial entrepreneur. At this point, it is very important to find a way to recover the negative emotions caused by business failures of serial entrepreneurs. Recently, a strategic model has emerged to deal with the negative emotions of grief caused by business failures of serial entrepreneurs. This study identified the recovery factors from the grief of business failures of serial entrepreneurs and analyzed Shepherd's(2003) three areas: loss orientation, restoration orientation, and dual process. To this end, individual in-depth interviews were conducted with 12 small business serial entrepreneurs who challenged re-startup to identify the attributes of recovery factors that were not identified with quantitative data. As a result of the study, first, recovery factors were investigated in three areas: individual orientation, family orientation, and network orientation. It was found to help improve recovery in nine categories: self-esteem, persistence, personal competence, hobbies, self-confidence, family support, networks, religion, and social support. Second, recovery obstacle factors were investigated in three areas: psychological, economic, and environmental factors. Nine categories including family, health, social network, business partner, competitor, partner, fund, external environment, and government policy were found to persist negative emotions. Third, the emotional processing process for grief was investigated in three areas: loss orientation, restoration orientation, and dual process. Ten categories such as family, partner support, social member support, government support, hobbies, networks, change of business field, moving, third-party perspective, and meditation were confirmed to enhance rapid recovery in the emotional processing process for grief. The implications of this study are as follows. The process of recovering from the grief caused by business failures of serial entrepreneurs was attempted by a qualitative study. By extending the theory of Shepherd(2003), This study can be applied to help with recovery research. In addition, conceptual models and propositions for future empirical research were presented, which can be discussed in carious academic ways.

• Journal of the Korean Association of Geographic Information Studies
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• 제25권3호
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• pp.100-117
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• 2022

This study examines the spatio-temporal characteristics of the macrobenthic community in the coastal areas of South Korea for the past six years(2015-2020). The relationship between the number of individuals of macrobenthic species and the benthic environments were investigated using data collected at a total of 154 stations located in the West (70), the South (61), and the East Seas (23), except for the Jeju Sea. We examined the benthic environmental characteristics such as water depth, sediment, grain size, ignition loss, and total organic carbon. A total of 1,614 macrobenthic species were found in the coastal area, with a mean density of 0.62 ind./m² by station. The mean density was relatively high in the spring and summer seasons (May to August) with more than 450 species. The most dominant species belong to Polychaetes and the top five of them accounted for more than 20% of the total number of populations. The top five species were Heteromastus filiformis, Scoletoma longifolia, Sigambra tentaculata, Sternaspis scutata, and Notomastus latericeus. Cluster analysis was performed on the top five dominant species. The stations were clustered into three groups with similar locations on the West, South, and East Sea. Cluster 1 and 3 represent Heteromastus filiformis (44% each), but cluster 2 represents Scoletoma longifolia (66%). Each cluster has different benthic environmental characteristics, especially in the sediment's sand (31.0%, 51.9%) and clay (15.9%, 9.7%) contents.

• Korean Journal of Mineralogy and Petrology
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• 제35권3호
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• pp.367-376
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• 2022

This study is a preliminary step to understand the reaction between various liquids and zeolite in the subduction zone environment. Stilbite, NaCa₄(Al₉Si₂₇)O₇₂·28(H₂O), was selected and high pressure study was conducted on compressional behavior by the pressure-transmitting medium (PTM). Water and NaHCO₃ solution that can exist in the subduction zone was used as PTM, and samples were pressurized from ambient to a maximum of 2.5 GPa. Below 1.0 GPa, both experiments show a low linear compressibility in the range of 0.001 to 0.004 GPa^-1 and a high bulk modulus of 220(1) GPa. This is presumably because the structure of the stilbite becomes very dense due to insertion of water molecules or cations into the channel. On the other hand, at 1.0 GPa or higher, the trends of the two experiments are different. In the water run, the linear compressibility of the c-axis is increased to 0.006(1) GPa^-1. In the NaHCO₃ run, the linear compressibility of the b- and c-axis is increased to 0.006(1) GPa^-1. The bulk modulus after 1.0 GPa shows values of 40(1) and 52(7) GPa in water and NaHCO₃ run, respectively, confirming that stilbite becomes more compressible than that before 1.0 GPa. It is caused by the migration of cations and water molecules inside the channel, as the water molecules in the PTM start to freeze and stop to insert toward the channel at 1.0 GPa or more. In the NaHCO₃ run, it is assumed that the distribution of extra-framework species inside the structure is changed by substitution of the Na⁺ cation. It can be expected from tendency of the relative intensity ratio of the (001) and (020) peaks which show a different from that of the water run.

• Journal of the Korean Society of Environmental Restoration Technology
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• 제25권4호
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• pp.33-47
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• 2022

Wild boars(Sus scrofa) are expanding their range of behavior as their habitats change. Appearing in urban centers and private houses, it caused various social problems, including damage to crops. In order to prevent damage and effectively manage wild boars, there is a need for ecological research considering the characteristics and movement characteristics of wild boars. The purpose of this study is to analyze home range and identify land cover types in key areas through tracking wild boars, and to predict the movement connectivity of wild boars in consideration of previous studies and their preferred land use characteristics. In this study, from January to June 2021, four wild boars were captured and tracked in Jinju city, Gyeongsangnam-do, and the preferred land cover type of wild boars was identified based on the MCP 100%, KDE 95%, and KDE 50% results. As a result of the analysis of the home range for each individual, it was found that 100% of MCP was about 0.68km², 2.77km², 2.42km², and 0.16km², and the three individuals overlapped the home range, refraining from habitat movement and staying in the preferred area. The core areas were analyzed as about 0.55km², 2.05km², 0.82km², and 0.14km² with KDE 95%., and about 0.011km², 0.033km², 0.004km², and 0.003km² with KDE 50%. When the preferred land cover type of wild boar was confirmed based on the results of analysis of the total home range area and core area that combined all individuals, forests were 55.49% (MCP 100%), 54.00% (KDE 95%), 77.69% (KDE 50%), respectively, with the highest ratio, and the urbanization area, grassland, and agricultural area were relatively high. A connectivity scenario was constructed in which the ratio of the land cover type preferred by the analyzed wild boar was reflected as a weight for the resistance value of the connectivity analysis, and this was compared with the connectivity evaluation results analyzed based on previous studies and wild boar characteristics. When the current density values for the wild boar movement data were compared, the average value of the existing scenario was 2.76, the minimum 1.12, and the maximum 4.36, and the weighted scenario had an average value of 2.84, the minimum 0.96, and the maximum 4.65. It was confirmed that, on average, the probability of movement predictability was about 2.90% better even though the weighted scenario had movement restrictions due to large resistance values. It is expected that the identification of the movement route through the movement connectivity analysis of wild boars can be suggested as an alternative to prevent damage by predicting the point of appearance. In the future, when analyzing the connectivity of species including wild boar, it is judged that it will be effective to use movement data on actual species.

• Korean Journal of Food Science and Technology
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• 제54권1호
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• pp.43-51
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• 2022

Regulation of the hair follicle cycle in association with dermal papilla cells is one of the most interesting targets for promoting hair regrowth. In this study, we examined whether steam-dried Betula platyphylla extracts (BPE) promote hair growth by upregulating in vitro and in vivo responses of dermal papilla cells. The data showed that BPE3 contained high amounts of phenolic compounds with higher antioxidant effects and increased hair growth-related genes, including fibroblast growth factor7 and Wnt7b, in dermal papilla cells. Notably, BPE3 effectively enhanced the formation of hair follicles by increasing FGF7, Wnt7b, and vascular endothelial growth factor in C57BL/6N dorsal skins. Additionally, BPE3 significantly decreased the expression of inflammatory repertoires, inducible nitric oxide synthase, interleukin-6, and cyclooxygenase 2. Several small molecules, such as betulin and unsaturated fatty acids, support the pharmacological activity of BPE3. In conclusion, BPE3 effectively promoted hair growth by activating dermal papilla cells and enhancing hair follicle cycles by attenuating the inflammatory environment in the scalp.

• Journal of Navigation and Port Research
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• 제46권1호
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• pp.1-10
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• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Journal of Intelligence and Information Systems
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• 제28권1호
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Economic and Environmental Geology
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• 제56권3호
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• pp.311-330
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• 2023

Development of Carbon Capture and Storage (CCS) technique is becoming increasingly important as a method to mitigate the strengthening effects of global warming, generated from the unprecedented increase in released anthropogenic CO₂. In the recent years, the characteristics of basaltic rocks (i.e., large volume, high reactivity and surplus of cation components) have been recognized to be potentially favorable in facilitation of CCS; based on this, research on utilization of basaltic formations for underground CO₂ storage is currently ongoing in various fields. This study investigated the feasibility of underground storage of CO₂ in basalt, based on the examination of the CO₂ storage mechanisms in subsurface, assessment of basalt characteristics, and review of the global research on basaltic CO₂ storage. The global research examined were classified into experimental/modeling/field demonstration, based on the methods utilized. Experimental conditions used in research demonstrated temperatures ranging from 20 to 250 ℃, pressure ranging from 0.1 to 30 MPa, and the rock-fluid reaction time ranging from several hours to four years. Modeling research on basalt involved construction of models similar to the potential storage sites, with examination of changes in fluid dynamics and geochemical factors before and after CO₂-fluid injection. The investigation demonstrated that basalt has large potential for CO₂ storage, along with capacity for rapid mineralization reactions; these factors lessens the environmental constraints (i.e., temperature, pressure, and geological structures) generally required for CO₂ storage. The success of major field demonstration projects, the CarbFix project and the Wallula project, indicate that basalt is promising geological formation to facilitate CCS. However, usage of basalt as storage formation requires additional conditions which must be carefully considered - mineralization mechanism can vary significantly depending on factors such as the basalt composition and injection zone properties: for instance, precipitation of carbonate and silicate minerals can reduce the injectivity into the formation. In addition, there is a risk of polluting the subsurface environment due to the combination of pressure increase and induced rock-CO₂-fluid reactions upon injection. As dissolution of CO₂ into fluids is required prior to injection, monitoring techniques different from conventional methods are needed. Hence, in order to facilitate efficient and stable underground storage of CO₂ in basalt, it is necessary to select a suitable storage formation, accumulate various database of the field, and conduct systematic research utilizing experiments/modeling/field studies to develop comprehensive understanding of the potential storage site.