• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.61-75
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• 2021

Recently, as the occurrence frequency of sudden floods due to climate change increased and the aging of the existing spillway, it is necessary to establish a plan to utilize an auxiliary spillway to minimize the flood damage of downstream rivers. Most studies have been conducted on the review of flow characteristics according to the operation of auxiliary spillway through the hydraulic experiments and numerical modeling. However, the studies on examination of flood damage in the downstream rivers and the stability of the revetment according to the operation of the auxiliary spillway were relatively insufficient in the literature. In this study, the stability of the revetment on the downstream river according to the outflow conditions of the existing and auxiliary spillway was examined by using 3D numerical model, FLOW-3D. The velocity, water surface elevation and shear stress results of FLOW-3D were compared with the permissible velocity and shear stress of design criteria. It was assumed the sluice gate was fully opened. As a result of numerical simulations of various auxiliary spillway operations during flood season, the single operation of the auxiliary spillway showed the reduction effect of maximum velocity and the water surface elevation compared with the single operation of the existing spillway. The stability of the revetment on downstream was satisfied under the condition of outflow less than 45% of the design flood discharge. However, the potential overtopping damage was confirmed in the case of exceeding the 45% of the design flood discharge. Therefore, the simultaneous operation with the existing spillway was important to ensure the stability on design flood discharge condition. As a result of examining the allocation ratio and the total allowable outflow, the reduction effect of maximum velocity was confirmed on the condition, where the amount of outflow on auxiliary spillway was more than that on existing spillway. It is because the flow of downstream rivers was concentrated in the center due to the outflow of existing spillway. The permissible velocity and shear stress were satisfied under the condition of less than 77% of the design flood discharge with simultaneous operation. It was found that the flood damage of downstream rivers can be minimized by setting the amount allocated to the auxiliary spillway to be larger than the amount allocated to the existing spillway for the total outflow with simultaneous operation condition. However, this study only reviewed the flow characteristics around the revetment according to the outflow of spillway under the full opening of the sluice gate condition. Therefore, the various sluice opening conditions and outflow scenarios will be asked to derive more efficient utilization of the auxiliary spillway in th future.

• Korean Journal of Poultry Science
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• v.47 no.4
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• pp.267-274
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• 2020

This study was conducted to estimate genetic parameters for growth and egg production traits in Black Korean native chicken (L strain) and Korean White Leghorn (F, K strains) using a multi-traits animal model BLUP. Traits used for this study were body weight at 150 days (BW150) and 270 days (BW270), age at first egg (DAY1st), egg weight at first egg (EW1st) and 270 days (EW270), and number of eggs laid by 270 days (EP270), and included 68,688 pedigree and 123,905 performance records collected from 2001 to 2013. In L, F, K strains, heritability estimates of BW150 were high (0.48, 0.52 and 0.50, respectively); of BW270 were high (0.56, 0.57 and 0.56); of DAY1st were medium to high (0.45, 0.39 and 0.31); of EW1st were low (0.15, 0.16 and 0.15); of EW270 were high (0.58, 0.55 and 0.59) and of EP270 were moderate (0.22, 0.21 and 0.20). The genetic and phenotypic correlation of DAY1st with EP270 were highly negative (-0.73 to -0.63 and -0.48 to -0.42). The genetic and phenotypic correlation of EP270 with BW150 and BW270, respectively were low negative (-0.16 to 0.01 and -0.14 to -0.03) and low to moderate positive (-0.08 to 0.07 and -0.13 to 0.04). The genetic and phenotypic correlation of EW270 with BW150 and BW270, respectively were moderate to high positive (0.39 to 0.49 and 0.36 to 0.46) and (0.29 to 0.33 and 0.34 to 0.37). The study showed that there is a potential for genetic improvement of Korean Indigenous chicken through selection program.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Life Science
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• v.32 no.1
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• pp.11-22
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• 2022

N-methyl-D-aspartate (NMDA) receptors have received considerable attention regarding their involvement in glutamate-induced neuronal excitotoxicity. Resveratrol has been shown to exhibit neuroprotective effects against this kind of overactivation, but the underlying cellular mechanisms are not yet clearly understood. In this study, HT-22 neuronal cells were treated with NMDA in Mg²⁺-free buffer and subsequently used as an experimental model of glutamate excitotoxicity to elucidate the mechanisms of resveratrol-induced neuroprotection. We found that NMDA treatment causes a drop in MTT reduction ability, disrupts inside-negative transmembrane potential of mitochondria, depletes cellular ATP levels, and stimulates intracellular ROS production. Double fluorescence imaging studies demonstrated an increased formation of mitochondrial permeability transition (MPT) pores accompanied by apoptotic cell death, while cobalt protoporphyrin and bilirubin showed protective effects against NMDA-induced mitochondrial injury. On the other hand, zinc protoporphyrin IX significantly attenuated the protective effects of resveratrol which was itself shown to enhance heme oxygenase-1 (HO-1) mRNA and protein expression levels. In cells transfected with HO-1 small interfering RNA, resveratrol failed to suppress the NMDA-induced effects on MTT reduction ability and MPT pore formation. The present study suggests that resveratrol may prevent mitochondrial injury in NMDA- treated HT-22 cells and that enhanced expression of HO-1 is involved in the underlying cellular mechanism.

• Resources Recycling
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• v.31 no.4
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• pp.56-65
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• 2022

Copper is one of the non-ferrous metals used in the electrical/electronic manufacturing industries due to its superior properties particularly the high conductivity and less resistivity. The effluent generated from the surface finishing process of these industries contains higher copper content which gets discharged in to water bodies directly or indirectly. This causes severe environmental pollution and also results in loss of an important valuable metal. To overcome this issue, continuous R & D activities are going on across the globe in adsorption area with the purpose of finding an efficient, low cost and ecofriendly adsorbent. In view of the above, present investigation was made to compare the performance of a plant root (Datura root powder) as a bio-adsorbent to that of the synthetic one (Tulsion T-42) for copper adsorption from such effluent. Experiments were carried out in batch studies to optimize parameters such as adsorbent dose, contact time, pH, feed concentration, etc. Results of the batch experiments indicate that 0.2 g of Datura root powder and 0.1 g of Tulsion T-42 showed 95% copper adsorption from an initial feed/solution of 100 ppm Cu at pH 4 in contact time of 15 and 30 min, respectively. Adsorption data for both the adsorbents were fitted well to the Freundlich isotherm. Experimental results were also validated with the kinetic model, which showed that the adsorption of copper followed pseudo-second order rate expression for the both adsorbents. Overall result demonstrates that the bio-adsorbent tested has a potential applicability for metal recovery from the waste solutions/effluents of metal finishing units. In view of the requirements of commercial viability and minimal environmental damage there from, Datura root powder being an effective material for metal uptake, may prove to be a feasible adsorbent for copper recovery after the necessary scale-up studies.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Land and Housing Review
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• v.14 no.1
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• pp.47-66
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• 2023

This study reviews prior studies on the residential environment characteristics, residential satisfaction, residential ownership consciousness and housing movement of MZ generation and analyze the structural equation models using the 2020 Korea Housing Survey data. Using 14 residential characteristics based on three classifications, we explore the effects on residential satisfaction, residential ownership consciousness, and housing movement. The empirical results are summarized as follows. First, based on factor analysis with Varimax of principal component analysis, parking facility items were excluded from the analysis by hindering validity, and as a result, KMO was 0.925 and Bartlett's test result showed a significant probability of less than 0.01. This indicates that the factor analysis model was suitable. Second, the results of the structural equation analysis for the MZ generation show that the surrounding environment, which is a potential variable of the residential environment characteristics, was statistically significant, but the accessibility and convenience were not statistically significant. Third, we find that the higher the satisfaction with the accessibility of commercial facilities, the more significant the sense of housing ownership appears. This suggests that the younger generation such as the MZ generation has a stronger desire for consumption. Fourth, the overall housing satisfaction of the MZ generation was significant for housing movement, but not for housing ownership. Compared to the industrialized generation, the baby boom generation, and the X generation, MZ generation shows distinct factors for housing satisfaction, housing ownership, and housing movement. Therefore, the residential environment characteristics of the residential survey should be improved and supplemented following the trend of the times. In addition, the government and local governments should prioritize actively participating in the housing market that suits the environment and characteristics of the target generation. Finally, our study provides implications regarding the need for housing-related research on how differ in special temporal situations such as COVID-19 in the future.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Resources Recycling
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• v.31 no.5
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• pp.67-76
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• 2022

The furniture industry has a high possibility to create value-added and a high potential to create new occupations due to the characteristics of the industry, which mainly consists of small and medium-sized enterprises (SMEs). However, the used furniture, which has sufficient reuse value, is also crushed and used as solid refuse fuel (SRF) recently. Besides, the number of waste treatment companies continues to decrease, and it occurs congestion of wood waste. As a way to solve the issue, a business model development of remanufacturing used furniture can be suggested as an alternative due to its high circular economic efficiency. Remanufacturing business including furniture industry creates positive effects in various aspects such as economic, environmental and job creation. In other words, remanufacturing is an effective recycling way to reduce input resources and energy in the production process. The results of economic analysis show that the expected annual revenue from the single worker furniture remanufacturing site was 104 million won which is 3.11 times more than the average income of a single-worker household in Korea and its B/C ratio was estimated about 30 which means high business feasibility. Revenue through furniture remanufacturing also showed 320 times higher than that of SRF production from the perspective of weight. In addition, it is shown that the GHGs reduction from the furniture remanufacturing is 2.2 ton CO₂-eq. per year, which is similar to the amount of GHGs absorption effect of 937 pine trees or 622 Korean oak trees annually. Thus the results of this study demonstrate that it is important to adopt an appropriate recycling method considering the economic and environmental effects at the end-of-life stage.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.47-72
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• 2022

This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.