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An Analytical Study on Rational use of Undersea Space (해저공간의 합리적 활용을 위한 분석적 연구)

  • Won-Jo Jung;Nam-Ki Park
    • Journal of Navigation and Port Research
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    • v.47 no.3
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    • pp.147-154
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    • 2023
  • This study aims to determine the necessity, role, utilization, and operation and management plan in relation to the underwater space platform where humans can newly reside. It provides a comprehensive opinion on the need for creating undersea space and operation plans based on opinions of industry-university-affiliated organizations involved in the R&D project of the Ministry of Maritime Affairs and Fisheries for the utilization of undersea space and external experts participating in marine technology development. In this study, a survey was conducted on researchers participating in the construction of a Korean submarine space platform. FGI was conducted on marine technology development experts. Results were then derived. As a result of the analysis, the need for subsea space construction was found to be high. As for the role of subsea space, the most common opinion was to develop technology for utilizing subsea space and to secure marine science research functions. It was found that the creation of subsea space would have a positive impact on the domestic industry, especially the deep-sea development industry and the shipbuilding/offshore structure industry. In terms of utilization, after the end of the seabed space test bed, the response to utilization as a marine observation base and marine ecosystem research had the highest proportion. As for expected inconvenience, discomfort in the psychological environment was the highest. Experts suggest that securing a continuous budget is most important for stable operation in the future and that securing a manpower budget is essential for itemized budgets. In addition, it was judged that it would be appropriate to establish a prior agreement from the time of the prior agreement and prepare a countermeasure before proceeding with the project in order to ensure ownership issues, consignment management issues, and cost issues when using the project after the end of the project.

Satisfaction Analysis for Green Infrastructure Activation around Dam in Terms of Sustainability (지속가능성 측면에서의 댐 주변 그린인프라 활성화를 위한 만족도 분석)

  • Lee, Dong-Kyu;Son, Byung-Hoon;An, Byung-Chul
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.3
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    • pp.83-94
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    • 2023
  • This study analyzed the satisfaction of green infrastructure around 39 dams, including multi-purpose dams, water dams, and flood control reservoir dams, to induce space improvement in terms of sustainability, and the results of the study are as follows. First, the satisfaction level based on the Likert scale of 5 points for the currently created dam green infrastructure was 3.76, and there were differences depending on the respondents' gender, age, residence, number of dam visits, and the need to pursue sustainability, and it was analyzed to be statistically significant. In the case of gender, p<.05, age, residence, number of dam visits, and the need to pursue sustainability were found to be p<.01. Regression analysis was conducted to confirm the effect of these respondents' characteristics on satisfaction, and it was analyzed that only the number of dam visits and the need to pursue sustainability had a statistically significant effect, and other characteristic variables had no significant effect. Second, in terms of satisfaction with the conceptual image of public bridge, view place and play space, which are the main spaces of dam green infrastructure considering sustainability, view place was the highest at 4.43, the play space was 4.35 and public bridge was analyzed as 4.21. The t-test result for the satisfaction of each space was found to be p<.01, and the difference in values was analyzed to be significant. The difference from the current satisfaction with green infrastructure was also analyzed as p<.00, showing a statistically significant difference. Third, as a way to revitalize green infrastructure around the dam through the results of satisfaction analysis, it is necessary to identify needs for major visitors in their 40s and 50s and create a space considering them. It was proposed to derive facilities and programs that can be introduced to other regions through the analysis of green infrastructure status around dams in Chungbuk, Jeonju, and Ulsan, where there are relatively many dams. Furthermore, satisfaction analysis by space showed that green infrastructure around the dam could be activated in terms of sustainability when selecting packaging materials considering the structure and shape of the dam, arranging observation facilities considering lake prospects, and introducing amusement facilities using local environmental resources. This study differs from previous studies in that it presented space improvement measures in consideration of sustainability for green infrastructure around dams for non-urban areas, and space improvement can contribute to improving it connectivity in urban and non-urban areas, which can also contribute to improving the sustainability of green infrastructure in Korea.

An Experimental Study on Fine Dust Emissions near Special Modified Asphalt Pavement and Conventional Asphalt Pavement (특수개질 및 일반 아스팔트 포장체 도로변의 미세먼지 발생에 대한 실험적 연구)

  • Tae-Woo Kang;Hyeok-Jung Kim
    • Journal of the Korean Recycled Construction Resources Institute
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    • v.11 no.3
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    • pp.282-288
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    • 2023
  • In this study, we analyzed the amount of roadside fine dust generated from newly constructed specially modified asphalt pavement and general asphalt pavement from existing roads. We collected the 1,000 g (100 g/day) of dust samples from the roadside of the express bus terminal and commercial facility area in Chungcheongnam-do's C site at three-day intervals during the summer of 2022 and 2023. The collected samples were separated from fine dust according to size in the 75-150 ㎛ range and, were separated only from Tire and Road Wear Particles through density separation. No.1-3 are general asphalt pavement section as an existing road. Fine dust and Tire and Road Wear Particles in No.1-3 were 24.27 g, 24.36 g, 0.53 g, and 0.53 g, respectively, and the quantitative results for 2022 and 2023 were similar. On the other hand, No.4-6 are newly constructed specially modified asphalt pavement section. Fine dust decreased by 14.8 % and tire and road wear particles decreased by 29.6 % in 2023 compared to 2022 in No.4-6. In addition, according to the results of thermogravimetric analysis, Tire and road wear particles in No.1-3 are tire and road components at 30 % and 70 %, respectively. And Tire and road wear particles in No.4-6 are tire and road components at 35 % and 65 % in 2023, respectively. From these results, it was confirmed that the newly constructed specially modified asphalt pavement can be effective in reducing roadside fine dust and Tire and Road Wear Particles. However, there may be some shortcomings in conclusive research results due to limited space and sample collection period. In the future, we plan to conduct various case studies.

Identifying sources of heavy metal contamination in stream sediments using machine learning classifiers (기계학습 분류모델을 이용한 하천퇴적물의 중금속 오염원 식별)

  • Min Jeong Ban;Sangwook Shin;Dong Hoon Lee;Jeong-Gyu Kim;Hosik Lee;Young Kim;Jeong-Hun Park;ShunHwa Lee;Seon-Young Kim;Joo-Hyon Kang
    • Journal of Wetlands Research
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    • v.25 no.4
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    • pp.306-314
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    • 2023
  • Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.

Community Structure of Natural Monument Forest (Forest of Japanese Torreyas in Pyeongdae-ri, Jeju and Subtropical Forest of Nabeup-ri, Jeju) in Jeju-do (제주도 천연기념물 수림지(제주 평대리 비자나무 숲과 제주 납읍리 난대림)의 군집구조)

  • Jeong Eun Lee;Yo Seob Hwang;Ho Jin Kim;Ju Heung Lee;Chung Weon Yun
    • Journal of Korean Society of Forest Science
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    • v.112 no.4
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    • pp.393-404
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    • 2023
  • The Natural Monument Forest (NMF) is a form of natural and cultural heritage that has symbolized the harmony between nature and culture in Korea for a long time. Recently, the NMF has deteriorated due to industrialization and reckless city expansion. Given this situation, it is necessary to preserve and manage the ecosystem of the NMF through preferential research regarding the forest community structure. Accordingly, this study sought to identify the community structure by analyzing the vegetation classification, stratum structure,and species diversity using vegetation data collected from the Forest of Japanese Torreyas in Pyeongdae-ri, Jeju and the Subtropical Forest of Nabeup-ri, Jeju. The results classified the forest vegetation as a Litsea japonica community group divided into two communities: a Torreya nuciferacommunity and a Quercus glauca community. The T. nuciferacommunity was subdivided into the Idesia polycarpa group and Dryopteris erythrosora group, while the Q. glauca community was subdivided into the Mercurialis leiocarpa group and Arachniodes aristata group. The T. nucifera species showed the highest level of importance in vegetation units 1 (Litsea japonicacommunity group-Torreya nucifera community-Idesia polycarpa group) and 2 (Litsea japonica community group-Torreya nucifera community-Dryopteris erythrosora group), whereas Q. glauca showed the highest level of importance in vegetation units 3 (Litsea japonica community group-Quercus glauca community-Mercurialis leiocarpa group) and 4 (Litsea japonica community group-Quercus glauca community-Arachniodes aristata group). In terms of the species diversity, vegetation units 1, 2, 3, and 4 had 2.866, 2.716, 2.222, and 2.326 species, respectively. These findings suggest that it is necessary to prepare a differentiated management plan for each vegetation unit.

The study of heavy rain warning in Gangwon State using threshold rainfall (침수유발 강우량을 이용한 강원특별자치도 호우특보 기준에 관한 연구)

  • Lee, Hyeonjia;Kang, Donghob;Lee, Iksangc;Kim, Byungsikd
    • Journal of Korea Water Resources Association
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    • v.56 no.11
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    • pp.751-764
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    • 2023
  • Gangwon State is centered on the Taebaek Mountains with very different climate characteristics depending on the region, and localized heavy rainfall is a frequent occurrence. Heavy rain disasters have a short duration and high spatial and temporal variability, causing many casualties and property damage. In the last 10 years (2012~2021), the number of heavy rain disasters in Gangwon State was 28, with an average cost of 45.6 billion won. To reduce heavy rain disasters, it is necessary to establish a disaster management plan at the local level. In particular, the current criteria for heavy rain warnings are uniform and do not consider local characteristics. Therefore, this study aims to propose a heavy rainfall warning criteria that considers the threshold rainfall for the advisory areas located in Gangwon State. As a result of analyzing the representative value of threshold rainfall by advisory area, the Mean value was similar to the criteria for issuing a heavy rain warning, and it was selected as the criteria for a heavy rain warning in this study. The rainfall events of Typhoon Mitag in 2019, Typhoons Maysak and Haishen in 2020, and Typhoon Khanun in 2023 were applied as rainfall events to review the criteria for heavy rainfall warnings, as a result of Hit Rate accuracy verification, this study reflects the actual warning well with 72% in Gangneung Plain and 98% in Wonju. The criteria for heavy rain warnings in this study are the same as the crisis warning stages (Attention, Caution, Alert, and Danger), which are considered to be possible for preemptive rain disaster response. The results of this study are expected to complement the uniform decision-making system for responding to heavy rain disasters in the future and can be used as a basis for heavy rain warnings that consider disaster risk by region.

A Study on The Effect of Psychological State occurred by the Organizational Change and Public Service Motivation on the JobAttitude: A comparison before and after the Implementation of Relocation of Electric Power Public Corporation to Local Areas (조직변화에 따른 심리상태와 공공봉사동기가 직무태도에 미치는 영향 조사연구: 전력공기업의 지방 이전 실시 전후의 비교)

  • Lee, Joon Tae
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.3
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    • pp.147-163
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    • 2022
  • The relocation policy of public Institutions throughout provincial areas that implemented for the purpose of "balanced national development" finished in 2019 with the last relocation of the Korea Institute of Science & Technology Evaluation and Planning, which moved to Chungbuk Innovation City. Electric power public corporations also completed relocation program over eight regions across the nation. This study was conducted empirically to identify the structural relationship between the public service motivation and job attitude. In this, the relationship of organizational change, particularly occurred by the regional relocation, with the psychological state of these organization members (experienced direct changes and got substantial impacts in various aspects such as psychological, economic and living environment, etc.,) was studied. This study aims to seek early organizational stabilization ideas for electric power public corporations after relocation, and to present some implications that can contribute to the secondary relocation of public institutions to local areas. This study shows the statistically significant relationship between the psychological state occurred by relocation and organizational commitment. The result shows that the higher the expectation levels, the higher the degree of organizational commitment, while anxious psychological state has no relation with that. Additionally, expectation level has no significant functional relation with turnover intention. Followings are the major conclusions revealed in this study; The stronger the anxious psychological state, the higher the turnover inducement goes up. The higher the expectation levels, the higher the public service motivation grows, and the higher the anxiety psychological state, the public service motivation lowers. The organizational commitment grows according to the public service motivation proportionally, but the turnover inducement intention is weak. The moderating effect of public service motivation between the expectation of organizational change and turnover intention was not significant, but it was analyzed that the moderating effect of public service motivation formed a significant relationship with other anxiety psychology. The expectation levels of employees of electric power public corporations has grown up after moving to provincial areas. Relationship between the expectation mind and the turnover inducement has decreased after local relocation.

A Comparative Study on Factors Affecting Satisfaction by Travel Purpose for Urban Demand Response Transport Service: Focusing on Sejong Shucle (도심형 수요응답 교통서비스의 통행목적별 만족도 영향요인 비교연구: 세종특별자치시 셔클(Shucle)을 중심으로)

  • Wonchul Kim;Woo Jin Han;Juntae Park
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.132-141
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    • 2024
  • In this study, the differences in user satisfaction and the variables influencing the satisfaction with demand response transport (DRT) by travel purpose were compared. The purpose of DRT travel was divided into commuting/school and shopping/leisure travel. A survey conducted on 'Shucle' users in Sejong City was used for the analysis and the least absolute shrinkage and selection operator (LASSO) regression analysis was applied to minimize the overfitting problems of the multilinear model. The results of the analysis confirmed the possibility that the introduction of the DRT service could eliminate the blind spot in the existing public transportation, reduce the use of private cars, encourage low-carbon and public transportation revitalization policies, and provide optimal transportation services to people who exhibit intermittent travel behaviors (e.g., elderly people, housewives, etc.). In addition, factors such as the waiting time after calling a DRT, travel time after boarding the DRT, convenience of using the DRT app, punctuality of expected departure/arrival time, and location of pickup and drop-off points were the common factors that positively influenced the satisfaction of users of the DRT services during their commuting/school and shopping/leisure travel. Meanwhile, the method of transfer to other transport modes was found to affect satisfaction only in the case of commuting/school travel, but not in the case of shopping/leisure travel. To activate the DRT service, it is necessary to consider the five influencing factors analyzed above. In addition, the differentiating factors between commuting/school and shopping/leisure travel were also identified. In the case of commuting/school travel, people value time and consider it to be important, so it is necessary to promote the convenience of transfer to other transport modes to reduce the total travel time. Regarding shopping/leisure travel, it is necessary to consider ways to create a facility that allows users to easily and conveniently designate the location of the pickup and drop-off point.

Hydrochemistry, Isotopic Characteristics, and Formation Model Geothermal Waters in Dongrae, Busan, South Korea (부산 동래 온천수의 수리화학 및 동위원소 특성, 생성모델 연구)

  • Yujin Lee;Chanho Jeong;Yongcheon Lee
    • The Journal of Engineering Geology
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    • v.34 no.2
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    • pp.229-248
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    • 2024
  • This investigated the hydrogeochemical and isotopic characteristics of geothermal waters, groundwaters, and surface waters in Dongrae-gu, Busan, South Korea, in order to determine the origins of the salinity components in the geothermal waters, and their formation mechanisms and heat sources The geothermal waters are Na-Cl-type, distinct from surrounding groundwaters (Na-HCO3- and, Ca-HCO3- (SO4, Cl)-type) and surface waters (Ca-HCO3(SO4, Cl)-type). This indicates the geothermal waters formed at depth as compared with the groundwaters. δ18O and δD values of the geothermal waters are relatively depleted as compared with the groundwaters, due to altitude effects and deep circulation of the geothermal waters. Helium and neon isotope ratios (3 He/4He and, 4He/20Ne) of the geothermal waters plot on a single mixing line between mantle (3He = 3.76~4.01%) and crust (4He = 95.99~96.24 %), indirectly suggesting that the heat source is due to the decay of radioactive elements in rocks. The geothermal reservoir temperatures were calculated using the silica-enthalpy and Giggenbach models, yielding values of 82~130℃, and the depth of the geothermal reservoir is estimated to be 1.7~2.9 km below the surface. The correlation between Cl/Na and Cl/HCO3 for the Dongrae geothermal waters requires the input of salty water. The supply of saline composition is interpreted due to the dissolution of residual paleo-seawater.

A study on improving self-inference performance through iterative retraining of false positives of deep-learning object detection in tunnels (터널 내 딥러닝 객체인식 오탐지 데이터의 반복 재학습을 통한 자가 추론 성능 향상 방법에 관한 연구)

  • Kyu Beom Lee;Hyu-Soung Shin
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.26 no.2
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    • pp.129-152
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    • 2024
  • In the application of deep learning object detection via CCTV in tunnels, a large number of false positive detections occur due to the poor environmental conditions of tunnels, such as low illumination and severe perspective effect. This problem directly impacts the reliability of the tunnel CCTV-based accident detection system reliant on object detection performance. Hence, it is necessary to reduce the number of false positive detections while also enhancing the number of true positive detections. Based on a deep learning object detection model, this paper proposes a false positive data training method that not only reduces false positives but also improves true positive detection performance through retraining of false positive data. This paper's false positive data training method is based on the following steps: initial training of a training dataset - inference of a validation dataset - correction of false positive data and dataset composition - addition to the training dataset and retraining. In this paper, experiments were conducted to verify the performance of this method. First, the optimal hyperparameters of the deep learning object detection model to be applied in this experiment were determined through previous experiments. Then, in this experiment, training image format was determined, and experiments were conducted sequentially to check the long-term performance improvement through retraining of repeated false detection datasets. As a result, in the first experiment, it was found that the inclusion of the background in the inferred image was more advantageous for object detection performance than the removal of the background excluding the object. In the second experiment, it was found that retraining by accumulating false positives from each level of retraining was more advantageous than retraining independently for each level of retraining in terms of continuous improvement of object detection performance. After retraining the false positive data with the method determined in the two experiments, the car object class showed excellent inference performance with an AP value of 0.95 or higher after the first retraining, and by the fifth retraining, the inference performance was improved by about 1.06 times compared to the initial inference. And the person object class continued to improve its inference performance as retraining progressed, and by the 18th retraining, it showed that it could self-improve its inference performance by more than 2.3 times compared to the initial inference.