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Comparison of physical materials using the 3D Clothing Simulation Z-weave program and its feasibility in the sustainable fashion industry (3D 의류 시뮬레이션 Z-weave 프로그램을 이용한 실물 소재 비교와 지속 가능한 패션 산업에서의 실현성)

  • Heeju Chae;Doeun Kim;Yoonji Shin
    • Smart Media Journal
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    • v.13 no.6
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    • pp.80-89
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    • 2024
  • This study aims not only to address environmental issues caused by indiscriminate fashion consumption, specifically in the context of Fast Fashion but also to find an alternative and a sustainable solution that is 'Upcycling' using the 3D clothing simulation program Z-weave. Upcycling products have limitations in that it is difficult to produce samples since finished products must be produced directly with limited materials and resources like waste clothes. To overcome these limitations, a 3D clothing simulation program is introduced to effectively utilize the limited resources of waste clothing. The purpose of this study is to confirm the similarity between a virtual fabric created through Z-weave and a real fabric, through this, to evaluate the possibility of application in the actual fashion industry. As a research method, surveys and interviews were conducted with related majors on virtual clothing created as similar as possible to actual clothing by adjusting the physical properties within the Z-weave program. This study attempted to describe the impact of digital technology on the fashion industry and how 3D clothing simulation programs can be used in sustainable fashion production.

Effect of a Mixture of Centella asiatica and Rosamarinus officinalis Leaf Extracts on Delayed Cortisol-induced Keratinocyte Migration (병풀과 로즈마리 잎 추출 혼합물의 코티솔로 유도된 각질형성세포 이동지연에 미치는 영향)

  • WonTae Jo;Miji Yeom;ShinHwan Cho;Eunae Cho;Deokhoon Park;Eunsun Jung
    • Journal of the Society of Cosmetic Scientists of Korea
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    • v.50 no.2
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    • pp.111-118
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    • 2024
  • A key component of wound healing is epithelialization, which involves the proliferation and migration of epidermal keratinocytes surrounding the wound. Increasing cortisol, a stress hormone, is known to slow the healing process by inhibiting cell proliferation and migration. This study aims to develop an ingredient that can promote delayed wound healing by cortisol through a combination of Centella asiatica (C. asiatica), known for its excellent wound healing effect, and Rosamarinus officinalis (R. officinalis) leaf known for their antipsychotic effect. R. officinalis leaf extract was found to inhibit the activity of 11β-HSD1, an enzyme involved in the production of cortisol. A combination of C. asiatica and R. officinalis leaf extracts (AlfaCalm) was found to enhance cortisol induced delayed keratinocyte migration to a greater extent than C. asiatica extract. AlfaCalm enhanced the expression of CDC42 and the formation of filopodia, which are crucial for the relaxation of the actin skeleton. These results suggest that AlfaCalm can be used as an effective wound healing material in stress condition.

A Study on the Optimization Period of Light Buoy Location Patterns Using the Convex Hull Algorithm (볼록 껍질 알고리즘을 이용한 등부표 위치패턴 최적화 기간 연구)

  • Wonjin Choi;Beom-Sik Moon;Chae-Uk Song;Young-Jin Kim
    • Journal of Navigation and Port Research
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    • v.48 no.3
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    • pp.164-170
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    • 2024
  • The light buoy, a floating structure at sea, is prone to drifting due to external factors such as oceanic weather. This makes it imperative to monitor for any loss or displacement of buoys. In order to address this issue, the Ministry of Oceans and Fisheries aims to issue alerts for buoy displacement by analyzing historical buoy position data to detect patterns. However, periodic lifting inspections, which are conducted every two years, disrupt the buoy's location pattern. As a result, new patterns need to be analyzed after each inspection for location monitoring. In this study, buoy position data from various periods were analyzed using convex hull and distance-based clustering algorithms. In addition, the optimal data collection period was identified in order to accurately recognize buoy location patterns. The findings suggest that a nine-week data collection period established stable location patterns, explaining approximately 89.8% of the variance in location data. These results can improve the management of light buoys based on location patterns and aid in the effective monitoring and early detection of buoy displacement.

A Study on Analysis and Enhancement Strategy of South Korea's Defense Industry Exports Amidst Global Geopolitical Crisis (세계 지정학적 위기 속에서 한국의 방산수출 분석 및 강화 전략 연구)

  • Dongbum Kim;Youngsam Yoon
    • Convergence Security Journal
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    • v.24 no.2
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    • pp.181-188
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    • 2024
  • Amid global geopolitical crises that are heightening tensions worldwide, the importance of national security is being reevaluated. Consequently, South Korea is gaining attention in the global defense market due to its superior technology, competitive pricing, and rapid delivery capabilities. The increasing international demand for defense materials offers opportunities for the development of the domestic defense industry and has the potential to lead to long-term defense strategies and an expansion of exports. In particular, the development of future advanced weapons systems and the expansion of defense exports are likely to be possible through a deep understanding of the international political and economic situation and proactive defense diplomacy. This study analyzes the impact of current global geopolitical crises on Korea's defense industry and presents effective strategies based on these findings, including innovative improvements to defense acquisition systems and the discovery of overseas defense cooperation partners to strengthen defense exports. This strategic approach aims to balance domestic consumption with exports, enhance military strength, and improve the country's standing in the international community. Therefore, efforts are needed to ensure the sustainable growth of the defense industry, enabling South Korea to achieve economies of scale and play a pivotal role in the global defense industry.

Pig Image Learning for Improving Weight Measurement Accuracy

  • Jonghee Lee;Seonwoo Park;Gipou Nam;Jinwook Jang;Sungho Lee
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.7
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    • pp.33-40
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    • 2024
  • The live weight of livestock is important information for managing their health and housing conditions, and it can be used to determine the optimal amount of feed and the timing of shipment. In general, it takes a lot of human resources and time to weigh livestock using a scale, and it is not easy to measure each stage of growth, which prevents effective breeding methods such as feeding amount control from being applied. In this paper, we aims to improve the accuracy of weight measurement of piglets, weaned pigs, nursery pigs, and fattening pigs by collecting, analyzing, learning, and predicting video and image data in animal husbandry and pig farming. For this purpose, we trained using Pytorch, YOLO(you only look once) 5 model, and Scikit Learn library and found that the actual and prediction graphs showed a similar flow with a of RMSE(root mean square error) 0.4%. and MAPE(mean absolute percentage error) 0.2%. It can be utilized in the mammalian pig, weaning pig, nursery pig, and fattening pig sections. The accuracy is expected to be continuously improved based on variously trained image and video data and actual measured weight data. It is expected that efficient breeding management will be possible by predicting the production of pigs by part through video reading in the future.

A study on the estimation of the K-address information industry and its economic effect (주소정보산업 규모 산정 및 경제적 효과 분석)

  • Kim, Daeyong
    • Journal of Cadastre & Land InformatiX
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    • v.54 no.1
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    • pp.33-48
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    • 2024
  • This study aims to establish the scope and statistics of the K-address information industry in Korea, estimating its size and prospects and estimates the economic effects through K-address information industry based on Input-Output analysis. Considering the characteristics and sectoral structure of the K-address information industry, the study delineates the scope and specific sectors, constructing sectoral statistics linked to the KSIC and the Bank of Korea's industrial classification. The study estimates the sectoral industry size, taking into account potential markets. Furthermore, it analyzes the economic impact of each sector within the K-address information industry. To figure out the economic effects, the study conducts Input-Output analysis by setting the K-address information industry as an exogenous sector in the input-output table. The results indicate that the overall size of the K-address information industry is estimated to grow from 406.1 billion KRW in 2021 to 3.65 trillion KRW in 2030. The economic effects of the K-address information industry vary by sector, emphasizing the importance of synergies and integration with related sectors, particularly those with significant inducement effects in high value-added manufacturing and service sectors. Furthermore, the industry's sensitivity to economic fluctuations is evident through the input-output analysis of inter-industry chain effects.

Leveraging LLMs for Corporate Data Analysis: Employee Turnover Prediction with ChatGPT (대형 언어 모델을 활용한 기업데이터 분석: ChatGPT를 활용한 직원 이직 예측)

  • Sungmin Kim;Jee Yong Chung
    • Knowledge Management Research
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    • v.25 no.2
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    • pp.19-47
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    • 2024
  • Organizational ability to analyze and utilize data plays an important role in knowledge management and decision-making. This study aims to investigate the potential application of large language models in corporate data analysis. Focusing on the field of human resources, the research examines the data analysis capabilities of these models. Using the widely studied IBM HR dataset, the study reproduces machine learning-based employee turnover prediction analyses from previous research through ChatGPT and compares its predictive performance. Unlike past research methods that required advanced programming skills, ChatGPT-based machine learning data analysis, conducted through the analyst's natural language requests, offers the advantages of being much easier and faster. Moreover, its prediction accuracy was found to be competitive compared to previous studies. This suggests that large language models could serve as effective and practical alternatives in the field of corporate data analysis, which has traditionally demanded advanced programming capabilities. Furthermore, this approach is expected to contribute to the popularization of data analysis and the spread of data-driven decision-making (DDDM). The prompts used during the data analysis process and the program code generated by ChatGPT are also included in the appendix for verification, providing a foundation for future data analysis research using large language models.

A Study on the Analysis of Park User Experiences in Phase 1 and 2 Korea's New Towns with Blog Text Data (블로그 텍스트 데이터를 활용한 1, 2기 신도시 공원의 이용자 경험 분석 연구)

  • Sim, Jooyoung;Lee, Minsoo;Choi, Hyeyoung
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.3
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    • pp.89-102
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    • 2024
  • This study aims to examine the characteristics of the user experience of New Town neighborhood parks and explore issues that diversify the experience of the parks. In order to quantitatively analyze a large amount of park visitors' experiences, text-based Naver blog reviews were collected and analyzed. Among the Phase 1 and 2 New Towns, the parks with the highest user experience postings were selected for each city as the target of analysis. Blog text data was collected from May 20, 2003, to May 31, 2022, and analysis was conducted targeting Ilsan Lake Park, Bundang Yuldong Park, Gwanggyo Lake Park, and Dongtan Lake Park. The findings revealed that all four parks were used for everyday relaxation and recreation. Second, the analysis underscores park's diverse user groups. Third, the programs for parks nearby were also related to park usage. Fourth, the words within the top 20 rankings represented distinctive park elements or content/programs specific to each park. Lastly, the results of the network analysis delineated four overarching types of park users and the networks of four park user types appeared differently depending on the park. This study provides two implications. First, in addition to the naturalistic characteristics, the differentiation of each park's unique facilities and programs greatly improves public awareness and enriches the individual park experience. Second, if analysis of the context surrounding the park based on spatial information is performed in addition to text analysis, the accuracy of interpretation of text data analysis results could be improved. The results of this study can be used in the planning and designing of parks and greenspaces in the Phase 3 New Towns currently in progress.

Proximal Policy Optimization Reinforcement Learning based Optimal Path Planning Study of Surion Agent against Enemy Air Defense Threats (근접 정책 최적화 기반의 적 대공 방어 위협하 수리온 에이전트의 최적 기동경로 도출 연구)

  • Jae-Hwan Kim;Jong-Hwan Kim
    • Journal of the Korea Society for Simulation
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    • v.33 no.2
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    • pp.37-44
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    • 2024
  • The Korean Helicopter Development Program has successfully introduced the Surion helicopter, a versatile multi-domain operational aircraft that replaces the aging UH-1 and 500MD helicopters. Specifically designed for maneuverability, the Surion plays a crucial role in low-altitude tactical maneuvers for personnel transportation and specific missions, emphasizing the helicopter's survivability. Despite the significance of its low-altitude tactical maneuver capability, there is a notable gap in research focusing on multi-mission tactical maneuvers that consider the risk factors associated with deploying the Surion in the presence of enemy air defenses. This study addresses this gap by exploring a method to enhance the Surion's low-altitude maneuvering paths, incorporating information about enemy air defenses. Leveraging the Proximal Policy Optimization (PPO) algorithm, a reinforcement learning-based approach, the research aims to optimize the helicopter's path planning. Visualized experiments were conducted using a Surion model implemented in the Unity environment and ML-Agents library. The proposed method resulted in a rapid and stable policy convergence for generating optimal maneuvering paths for the Surion. The experiments, based on two key criteria, "operation time" and "minimum damage," revealed distinct optimal paths. This divergence suggests the potential for effective tactical maneuvers in low-altitude situations, considering the risk factors associated with enemy air defenses. Importantly, the Surion's capability for remote control in all directions enhances its adaptability in complex operational environments.

Analysis of The Human Thermal Environment in Jeju's Public Parking Lots in Summer and Suggestion for Its Modification (제주시 공영 주차장 내 여름철 인간 열환경 분석 및 저감 방안 제안)

  • Choi, Yuri;Park, Sookuk
    • Journal of the Korean Institute of Landscape Architecture
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    • v.52 no.3
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    • pp.18-32
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    • 2024
  • This study aims to analyze the summer human thermal environment in Jeju City's outdoor parking lots by measuring microclimate data and comparing pavement and vegetation albedoes and elements through computer simulations. In measured cases, results due to albedo showed no significance, but there was a significant difference between sunny and shaded areas by trees. The sunny area had a PET (physiological equivalent temperature) in the 'very hot' level, while the shaded area exhibited a 2-step lower 'warm' level. UTCI (universal thermal climate index) also showed that the sunny area was in the 'very strong heat stress' level, whereas the shaded area was 1-step lower in the 'strong heat stress' level, confirming the role of trees in reducing incoming solar radiant energy. Simulation results, using the measured albedoes, closely resembled the measured results. Regarding vegetation, scenarios with a wide canopy, high leaf density, and narrow planting spacing were effective in mitigating the human thermal environment, and the differences due to tree height varied across scenarios. The scenario with the lowest PET value was H9W9L3D8 (tree height 9m, canopy width 9m, leaf area index 3.0, planting spacing 8m), indicating a 0.7-step decrease compared to the current landscaping scenario. Thus, it was confirmed that, among landscaping elements, trees have a significant impact on the summer human thermal environment compared to ground pavement.