• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.201-210
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• 2019

Recently, due to the efforts to mitigate traffic congestion and expansion of space efficiency, the construction of underground roads has been increased in big-scale cities. Since tunnels in the city have a higher chance for a fire leading to a great tragedy during a severe traffic jam than mountain tunnels, it is highly likely that it will be constructed as a tunnel, having a small cross section, for small vehicles. However, if they are constructed as such small-vehicle tunnels, it would be possible to reduce the design fire intensity while the concentration of harmful gases would increase due to a reduction in the small cross sectional area, led by a decrease in the tunnel height. In this study, behaviors of fire smoke by the installation interval and format of large-scale exhaust-gas ports were examined and compared in the analysis of temperatures and CO concentrations of a tunnel and its results were as the following. Although there were no significant differences in the smoke spreading distance between installation intervals, but in this study, 100 m was found to be the most effective installation interval. The smoke exhaustion performance was found to be excellent in the order of $4m{\times}3m$, $6m{\times}2m$, and $3m{\times}2m$ (2 lane) of the smoke spreading distance. Although there was no significant difference in the smoke spreading distance between formats of large-scale exhaust-gas ports, it was found that the smoke spreading distance was larger than other cases when it was $3m{\times}2m$ in the fire growing process. The analysis of smoke spreading distances by the aspect ratio showed that a smoke spreading distance was shorted when its the smoke spreading distance was found to be shorter when its traverse distance was relatively longer than its longitudinal distance.

• Economic and Environmental Geology
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• v.53 no.6
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• pp.687-694
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• 2020

Two oxidizing agents (KMnO4, H2O2), and one neutralizing agent (NaOH) were applied to evaluate Mn removal in mine drainage. A Mn2+ solution and artificial mine drainage were prepared to identify the Fe2+ influence on Mn2+ removal. The initial concentrations of Mn2+ and Fe2+ were 0.1 mM and 1.0 mM, respectively. The injection amount of oxidizing and neutralizing agents were set to ratios of 0.1, 0.67, 1.0, and 2.0 with respect to the Mn2+ mole concentration. KMnO4 exhibited a higher removal efficiency of Mn2+ than did H2O2 and NaOH, where approximately 90% of Mn2+ was removed by KMnO4. A black MnO2 was precipitated that indicated the oxidation of Mn2+ to Mn4+ after an oxidizing agent was added. In addition, MnO2 (pyrolusite) is a stable precipitate under pH-Eh conditions in the solution. However, relatively low removal ratios (6%) of Mn2+ were observed in the artificial mine drainage that included 1.0 mM of Fe2+. The rapid oxidation tendency of Fe2+ as compared to that of Mn2+ was determined to be the main reason for the low removal ratios of Mn2+. The oxidation of Fe2+ showed a decrease of Fe concentration in solution after injection of the oxidizing and neutralizing agents. In addition, Mn7+ of KMnO4 was reduced to Mn2+ by Fe2+ oxidation. Thus, the concentrations of Mn increased in artificial mine drainage. These results revealed that the oxidation method is more effective than the neutralization method for Mn removal in solution. It should also be mentioned that to achieve the Mn removal in mine drainage, Fe2+ removal must be conducted prior to Mn2+ oxidation.

• Journal of Mushroom
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• v.18 no.4
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• pp.398-402
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• 2020

This study was conducted to set up a proper replacement cycle of High Efficiency Particulate Air (HEPA) filters by observing the microbial populations in the air of the cultivation house of Pleurotus eryngii, before and after HEPA filter replacement at different periods. The density of bacteria and fungi in the air during each cultivation stage was measured using a sampler before the replacement of the HEPA filter. The results showed that airborne microorganisms had the highest density in the mushroom medium preparation room, with 169.7 CFU/㎥ of bacteria and 570 CFU/㎥ of fungi, and the removed old spaun had 126.3 CFU/㎥ of bacteria and 560 CFU/㎥ of fungi. The density of bacteria and fungi in the air at each cultivation stage before the replacement of the HEPA filter was 169.7 CFU/㎥ and 570 CFU/㎥, and 126.3 CFU/㎥ and 560 CFU/㎥, during the medium production and harvesting processes, respectively. After the replacement of the HEPA filter, the bacterial density was the lowest in the incubation room and the fungal density was the lowest in the cooling room. The microbial populations isolated at each period consisted of seven genera and seven species before the replacement, including Cladosporium sp., six genera and six species after 1 month of replacement, including Penicillium sp., 5 genera and 7 species after 3 months of replacement, including Mucor plumbeus, and 5 genera and 12 species, 5 genera and 10 species, and 5 genera and 10 species, 4, 5, and 6 months after the replacement, respectively, including Penicillium brevicompactum. During the period after replacement, the species were diversified and their number increased. The density of airborne microorganisms decreased drastically after the replacement of the HEPA filter. Its lowest value was recorded after 2 months of replacement, and it increased gradually afterwards, reaching a level similar to or higher than that of the pre-replacement period. Therefore, it was concluded that replacing the HEPA filter every 6 months is effective for reducing contamination.

• Journal of Science Education
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• v.45 no.3
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• pp.292-303
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• 2021

This study identifies the terms frequently used together with energy in online science news articles and topics of the news reports to find out how the term energy is used in everyday life and to draw implications for science curriculum and instruction about energy. A total of 2,171 online news articles in science category published by 11 major newspaper companies in Korea for one year from March 1, 2018 were selected by using energy as a search term. As a result of natural language processing, a total of 51,224 sentences consisting of 507,901 words were compiled for analysis. Using the R program, term frequency analysis, semantic network analysis, and structural topic modeling were performed. The results show that the terms with exceptionally high frequencies were technology, research, and development, which reflected the characteristics of news articles that report new findings. On the other hand, terms used more than once per two articles were industry-related terms (industry, product, system, production, market) and terms that were sufficiently expected as energy-related terms such as 'electricity' and 'environment.' Meanwhile, 'sun', 'heat', 'temperature', and 'power generation', which are frequently used in energy-related science classes, also appeared as terms belonging to the highest frequency. From a network analysis, two clusters were found including terms related to industry and technology and terms related to basic science and research. From the analysis of terms paired with energy, it was also found that terms related to the use of energy such as 'energy efficiency,' 'energy saving,' and 'energy consumption' were the most frequently used. Out of 16 topics found, four contexts of energy were drawn including 'high-tech industry,' 'industry,' 'basic science,' and 'environment and health.' The results suggest that the introduction of the concept of energy degradation as a starting point for energy classes can be effective. It also shows the need to introduce high-tech industries or the context of environment and health into energy learning.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.249-267
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• 2021

The use of big data accumulated along with the progress of digitalization is bringing disruptive innovation to the global agricultural industry. Recently, the government is establishing an agricultural big data platform and a support organization. However, in the domestic agricultural industry, the use of big data is insufficient except for some companies in the field of cultivation and growth. In this context, this study identifies factors affecting the intention to use big data in terms of technology, organization and environment, and also confirm the moderating effect of technical field, focusing on agricultural ventures which should be the main entities in creating innovation by using big data. Research data was obtained from 309 agricultural ventures supported by the A+ Center of FACT(Foundation of AgTech Commercialization and Transfer), and was analyzed using IBM SPSS 22.0. As a result, Among technical factors, relative advantage and compatibility were found to have a significant positive (+) effect. Among organizational factors, it was found that management support had a positive (+) effect and cost had a negative (-) effect. Among environmental factors, policy support were found to have a positive (+) effect. As a result of the verification of the moderating effect of technology field, it was found that firms other than cultivation had a moderating effect that alleviated the relationship between all variables other than relative advantage, compatibility, and competitor pressure and the intention to use big data. These results suggest the following implications. First, it is necessary to select a core business that will provide opportunities to generate new profits and improve operational efficiency to agricultural ventures through the use of big data, and to increase collaboration opportunities through policy. Second, it is necessary to provide a big data analysis solution that can overcome the difficulties of analysis due to the characteristics of the agricultural industry. Third, in small organizations such as agricultural ventures, the will of the top management to reorganize the organizational culture should be preceded by a high level of understanding on the use of big data. Fourth, it is important to discover and promote successful cases that can be benchmarked at the level of SMEs and venture companies. Fifth, it will be more effective to divide the priorities of core business and support business by agricultural venture technology sector. Finally, the limitations of this study and follow-up research tasks are presented.

• 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 Bio-Environment Control
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• v.31 no.4
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• pp.468-475
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• 2022

This study was conducted to find out the efficiency of heating initiative temperature and carbon dioxide fertilization in summer squash (Cucurbita moschata D.). The heating start temperature experiment was performed at 9℃, 12℃, and 15℃ using an electric heater and operated when the temperature was lower than the target temperature. The CO₂ fertilization concentration experiment was performed from 7 to 12 with the control, 500 µmol·mol^-1, and 800 µmol·mol^-1 using liquefied carbon dioxide. Investigation items were plant height, stem diameter, number of leaves, leaf area, fresh weight, dry weight, also economic analysis was conducted by surveying only fruits exceeding 100 g. Photosynthesis was measured for the upper leaf position to calculate the saturation point according to the control. The photo saturation point was 587 µmol·m^-2·s^-1, and the CO₂ saturation point was 702 µmol·mol^-1. A_max values by carbon dioxide were 13.4, 17.8, 17.2, 19.6, and 17.5 µmolCO₂·m^-2·s^-1 in the order of 9℃, 12℃, 15℃, 500 µmol·mol^-1, and 800 µmol·mol^-1. In the temperature experiment, 9℃ in growth did not grow normally and no fruiting was performed. 12℃ and 15℃ were higher than 9℃, but there was no significant difference in growth and production. The CO₂ fertilization experiment showed no significant difference between the treatment in growth, but the productivity of 800 µmol·mol^-1 was the best. Comprehensively, the heating initiative temperature of 15℃ was good for crop growth and production, but there is no significant difference from 12℃, so it is good to set the heating start temperature to 12℃ economically, and maintaining of 800 µmol·mol^-1 is effective in increasing production.

• Journal of the Korean GEO-environmental Society
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• v.23 no.9
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• pp.33-40
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• 2022

Sedimentation and pH neutralization has been investigated as preteatment of acid contaminate water. The settling and neutralizing process derive more effective degradation efficiency as the pre-treatment process before the removal process of adsorption, volatile, biodegradation, or oxidation. Settling velocity, uniformity coefficient, coefficient of curvature, and grain size index can define in the sedimentation process for characteristics of the soil. The stainless steel sieve has been used to separate each particle size of the dry soil by assembling in order of 4, 10, 20, 40, 80, 100, and 200 mesh sizes. The soil from Gamcheon Port in Busan drops upper side of the sieve and shakes back and forth to separate each different size of the particle. The 1L of Imhoff cone and 200 mL of the mass cylinder were used as settling tanks to calculate settling velocity. Stokes' equation was used to figure out the average density of dry soil with a value from settling velocity. In the results, the average particle density and lowest settling velocity were 1.93 g/cm³ and 0.11 cm/s, respectively. These values can detect the range of settling points of sediment to prevent chemical accidents. In pH neutralization, the initial pH of 2, 3, 4, and 5 of nitric acid and sulfuric acid are used as an acid solution; 0.1, 0.01, and 0.001 M of sodium hydroxide and calcium hydroxide are used as a base solution. The main goal of this experiment is to figure out the volume percentage of the acid solution becomes pH 7. The concentration of 0.001 M of base solution exceeds all the conditions, 0.01 M exceeds partially, and 0.1 M does not exceed 5 v/v% except pH 2. Calcium hydroxide present less volume than sodium hydroxide at pH neutralization both sulfuric and nitric acid.

• 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.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.199-210
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• 2022

This study aimed to develop a cropping system to use limited crop-land with optimum efficiency, while considering management from farmers. To establish the cropping system involving a two-year rotation of three crops, three types of cropping system were evaluated in Suwon (Seogcheon series) and Anseong (Geumcheon series) in the middle plain area using six crops from 2018 to 2019: maize-perilla-onion, potato-sesame-garlic, and maize-sesame-onion. The crop productivity and income of the cropping systems involving food-, oilseed-, and horticultural crops were analyzed, and the optimal cropping system was reviewed. The total yield of each crop was as follows: maize 1,281 kg, potato 4,837 kg, perilla 125 kg, sesame 120 kg, onion 6,503 kg, and garlic 1,027 kg per 10a. However, in terms of gross profit, the potato was more than 3.8 times more profitable than corn, sesame was 1.8 times more profitable than perilla, and garlic was more than 2.8 times more profitable than onions. As a result, in terms of net income, the potato-sesame-garlic cropping system produced the highest income per unit area. Sesame seedlings were planted after the potato harvest, thereby solving the problem of competition between the first and last crops. Overall, this study confirmed that the potato-sesame-garlic cropping system, a two-year rotation of three crops, contributed to the improvement of upland crop productivity and farmers' income and was an overall effective cropping system.