• Food Engineering Progress
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• v.21 no.4
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• pp.326-331
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• 2017

A cultivar (Malus domestica cv. Fuji) of apple was selected to make apple peel (AP) powder by three different powdering methods. Frozen AP was thawed and subsequently was dried or ground without drying. After AP was dried by hot-air drying at $60^{\circ}C$ or freeze-drying, the dried AP was ground using a conventional blender. Separately, the thawed AP was powered by using a cryogenic micro grinding technology (CMGT). The ground AP and three types of AP powder were extracted using deionized water, 20, 40, 60, 80, or 100% methanol, followed by vacuum evaporation. The total phenolics contents (TPC), total flavonoids contents (TFC), DPPH, and ABTS radical scavenging capacities of each extract were compared to determine an efficient powdering method. Lyophilized AP powder extract using 60% methanol showed the highest TPC and DPPH radical scavenging capacity. In contrast, 60% methanol extract of the powder by CMGT, resulting in the smallest particle, exhibited the highest TFC and ABTS radical scavenging capacity. This study suggests that the extraction yield of bioactive compounds from AP may be varied according to different powdering methods and that a new powdering process such as CMGT may be applicable to develop functional foods efficiently.

• Journal of Adhesion and Interface
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• v.22 no.3
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• pp.91-97
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• 2021

By introducing an organic interlayer on the Parylene C dielectric surface, the electrical device performances and the operating stabilities of organic field-effect transistors (OFETs) were improved. To achieve this goal, hexamethyldisilazane (HMDS) and octadecyltrichlorosilane (ODTS), as the organic interlayer materials, were used to control the surface energy of the Parylene C dielectrics. For the bare case used with the pristine Parylene C dielectrics, the field-effect mobility (μ_FET) and threshold voltage (V_th) of dinaphtho[2,3-b:2',3'-f ]thieno[3,2-b]- thiophene (DNTT) FET devices were measured at 0.12 cm²V^-1s^-1 and - 5.23 V, respectively. On the other hand, the OFET devices with HMDS- and ODTS-modified cases showed the improved μ_FET values of 0.32 and 0.34 cm²V^-1s^-1, respectively. More important point is that the μ_FET and V_th of the DNTT FET device with the ODTS-modified Parylene C dielectric presented the smallest changes during a repeated measurement of 1000 times, implying that it has the most stable operating stability. The results could be meaned that the organic interlayer, especially ODTS, effectively covers the Parylene C dielectric surface with alkyl chains and reduces the charge trapping at the interface region between active layer and dielectric, thereby improving the electrical operating stability.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Phonetics and Speech Sciences
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• v.12 no.4
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• pp.1-8
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• 2020

Traditionally it has been understood that the aspirated and lenis stops in Seoul Korean are distinguished primarily by voice onset time (VOT) and secondarily by other cues such as the fundamental frequency (F0) of the following vowel. However, recent studies on stop production have shown that the aspirated and lenis stops are currently merging in VOT and that they are now differentiated primarily by F0. In the present study, we examined whether the currently reported change in the production domain would be also found in the perception domain. To this end, an auditory identification task was conducted using speech materials of varying VOT and F0 values with young and older male and female Seoul listeners. Results revealed that all listener groups used both VOT and F0 to distinguish the lenis vs. aspirated stops but they used the F0 cue more reliably than the VOT cue in discriminating the stop contrast. The effects of gender and age were found only in the VOT cue (i.e., not in the F0 cue), with the greatest VOT cue weight in older males and the smallest in young females, which is in line with recent production studies.

• Journal of Environmental Health Sciences
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• v.46 no.6
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• pp.719-725
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• 2020

Objectives: With the growth of national interest in fine particulate matter, many complaints about pollutants emitted from air pollution emitting facilities have arisen in recent years. In particular, it is thought that a large volume of particulate pollutants are discharged from workplaces that use Solid Refuse Fuel (SRF). Therefore, particulate contaminants generated from SRF were measured and analyzed in this study in terms of respective particle sizes. Methods: In this study, particulate matter in exhaust gas was measured by applying US EPA method 201a using a cyclone. This method measures Filterable Particulate Matter (FPM), and does not consider the Condensable Particulate Matter (CPM) that forms particles in the atmosphere after being discharged as a gas in the exhaust gas. Results: The mass concentration of Total Suspended Particles (TSP) in the four SRF-using facilities was 1.16 to 11.21 mg/Sm3, indicating a very large concentration deviation of about 10 times. When the fuel input method was the continuous injection type, particulate matter larger than 10 ㎛ diameter showed the highest particle size fraction, followed by particulate matter smaller than 10 ㎛ and larger than 2.5 ㎛, and particulate matter of 2.5 ㎛ or less. Contrary to the continuous injection type, the batch injection type had the smallest particle size fraction of particulate matter larger than 10 ㎛. The overall particulate matter decreased as the operating load factor decreased from 100% to 60% at the batch input type D plant. In addition, as incomplete combustion significantly decreased, the particle size fraction also changed significantly. Both TSP and heavy metals (six items) satisfied the emissions standards. The measured value of the emission factor was 38-99% smaller than the existing emissions factor. Conclusions: In the batch injection facility, the particulate matter decreased as the operating load factor decreased, as did the particle size fraction of the particulate matter. These results will help the selection of effective methods such as reducing the operating load factor instead of adjusting the operating time during emergency reduction measures.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.6_2
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• pp.1067-1074
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• 2020

Green houses provide a more conditioned and warmer environment than the outside environment due to insulation. Currently used insulation materials include soft film (PVC, PE, EVA), foamed PE sheet, non-woven fabric, reflective film, and multi-layer insulation curtain, but there are many disadvantages and to compensate for this, silica aerogel insulation material with excellent warmth, light weight, and small volume Research using is in progress. In this study, the temperature change of the quadruple-structure green house and the temperature change in the dual-structure green house of soft film and silica airgel were investigated. The daytime temperature change was highest in A and A2 (soft film) at 10 to 16:00 after sunrise, but showed the lowest temperature at 17 to 18:00, which is the sunset time, showing the greatest change. The airgels of D and D2 showed the smallest change in temperature after sunrise and right after sunset. That is, it can be said that the airgel is hardly affected by external temperature. The temperature change at night was highest in D and D2 (aerogel) for both quadruple and dual structures. The temperature at night was measured higher in the quadruple structure than in the double structure. As for the ratio of the internal temperature to the external temperature for the quadruple structure and the double structure, D (aerogel) was not affected by the external temperature during the day in the quadruple structure and the double structure. D (Aerogel) seems to be able to reduce the damage caused by high temperatures in summer due to the high thermal insulation effect of the airgel, as the temperature rises above 4℃ at night. And in winter, it helps to save heating costs due to less heat emitted to the outside.

• Applied Chemistry for Engineering
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• v.22 no.2
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• pp.161-166
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• 2011

The $CO_2$ dry reforming reaction, which converts carbon dioxide to hydrogen and carbon monoxide, is typical endothermic reaction, and also known as adverse reaction owing to thermodynamics. In order to overcome the problem, the development studies of suitable catalyst based on precious metals for high durability of thermal and optimization of life time have been examined but it had economical problem by high cost. In this study, we confirmed optimum contents of Pt and La with such different contents of Pt (0.02~0.2 wt%) or La (2~20 wt%) over $Co/SiO_2$ which prepared for excellent activity and cost-effective catalysts. As a result, the promoted catalysts with 0.04 wt% Pt or 9 wt% La over $Co/SiO_2$ showed the highest activity which is 57% and 55% $CO_2$ conversion respectively. Also, the particle size of cobalt on the promoted catalysts with 0.04 wt% Pt or 9 wt% La by characterization of catalyst could confirm the smallest particle size in this study. Therefore, it could know that particle size of cobalt had effected the stability and reactivity of catalysts due to the contents of Pt and La.

• Journal of the Korean GEO-environmental Society
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• v.22 no.3
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• pp.37-43
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• 2021

This study aimed to calculate the amount of change in soil carbon due to changes in land cover. Among the various soil carbon models, the InVEST Carbon Storage and Sequestration module was used. LULC is one of the leading factors affecting soil carbon. Therefore, this study compared the total amount of soil carbon due to changes in LULC in 2000 and 2010 across the Republic of Korea, and calculated the changes in each administrative district (city). Changes in LULC in Korea were mainly due to the increase in developed and dry areas and the decrease in grassland, indicating changes in soil carbon. The total amount of soil carbon changes in South Korea has been reduced by 11.48 (millions) in 10 years. The amount of soil carbon by administrative region decreased in most cities and provinces, but Jeju Island, in exception, showed an increase in soil carbon. Among the cities and provinces except Jeju Island, Seoul showed the smallest decrease, with a decrease of 0.033 (million t). On the contrary, the largest number of attempts to decrease was to Gyeongsangbuk-do, which saw a total decrease of 2.893 (million t). Jeju Island is the only soil carbon-increasing area with an increase of 0.547 (millions) and the agricultural area has increased 2.1 times in 10 years. In the case of soil carbon, the construction of ground observation data at the national unit is insufficient, and verification will need to be carried out through linked analysis using multiple models in the future.

• The Journal of the Korea Contents Association
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• v.21 no.3
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• pp.184-193
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• 2021

This paper investigates the performance of technology innovation activities performed by firms in 16 major regions in Korea using 2002-2010 survey data by STEPI. The theoretical and empirical analysis is carried out via the 2 models which are the simple R&D - total revenue model and Cobb-Douglas model based on the simple model adding labor variable. The main results shows that for simple model, the R&D elasticity for total revenue is 0.42 for all areas and Ul-San shows the highest elasticity level, 0.66 and Bu-San the lowest level, 0.2. In case of Cobb Douglas model the R&D elasticities are not statistically significant for many regions. To overcome the low statistical significance, we grouped the 15 regions for 3 wider regions using ANOVA based on the R&D intensity for the homogeneity of R&D activities. By grouping, each region has more observations to analyze and the results from the empirical analysis shows higher statistical significance level and data explanation capability. In this case, Group 3 which shows larger firm size and slightly higher export share shows the highest level of R&D elasticity, 0.088 and Group 1 which has the smallest firm size and the lowest revenue growth rate shows the lowest level, 0.31. For the labor elasticity, Group 1 shows the higest level, 1.16 and Group2 the lowest level, 1.096. These results show that the regions which have many middle and small firms reveal low R&D-revenue elasticity and high labor-revenue elasticity.

• Microbiology and Biotechnology Letters
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• v.48 no.4
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• pp.547-555
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• 2020

Microalgae are a promising resource in energy and food production as they are cost-effective for biomass production and accumulate valuable biological resources. In this study, CO2 assimilation, biomass, and lipid production of 4 microalgal species (Chlorella vulgaris, Mychonastes homosphaera, Coelastrella sp., and Coelastrella vacuolata) were characterized at different CO2 concentrations ranging from 1% to 9%. Microscopic observation indicated that C. vulgaris was the smallest, followed by M. homosphaera, C. vacuolata, and Coelastrella sp. in order of size. C. vulgaris grew and consumed CO2 more rapidly than any other species. C. vulgaris exhibited a linear increase in CO2 assimilation (up to 9.62 mmol·day-1·l-1) as initial biomass increased, while the others did not (up to about 3 mmol·day-1·l-1). C. vulgaris, Coelastrella sp., and C. vacuolata showed a linear increase in the specific CO2 assimilation rate with CO2 concentration, whereas M. homosphaera did not. Moreover, C. vulgaris had a greater CO2 assimilation rate compared to those of the other species (14.6 vs. ≤ 11.9 mmol·day-1·l-1). Nile-red lipid analysis showed that lipid production per volume increased linearly with CO2 concentration in all species. However, C. vulgaris increased lipid production to 18 mg·l-1, compared to the 12 mg·l-1 produced by the other species. Thus, C. vulgaris exhibited higher biomass and lipid production rates with greater CO2 assimilation capacity than any other species.