• Journal of the Korean earth science society
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• v.43 no.5
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• pp.604-617
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• 2022

Sea surface temperature (SST) is a key variable that can be used to understand ocean-atmosphere phenomena and predict climate change. Satellite microwave remote sensing enables the measurement of SST despite the presence of clouds and precipitation in the sensor path. Therefore, considering the high utilization of microwave SST, it is necessary to continuously verify its accuracy and analyze its error characteristics. In this study, the validation of the microwave global precision measurement (GPM)/GPM microwave imager (GMI) SST around the Northwest Pacific and Korean Peninsula was conducted using surface drifter temperature data for approximately eight years from March 2014 to December 2021. The GMI SST showed a bias of 0.09K and an average root mean square error of 0.97K compared to the actual SST, which was slightly higher than that observed in previous studies. In addition, the error characteristics of the GMI SST were related to environmental factors, such as latitude, distance from the coast, sea wind, and water vapor volume. Errors tended to increase in areas close to coastal areas within 300 km of land and in high-latitude areas. In addition, relatively high errors were found in the range of weak wind speeds (<6 m s^-1) during the day and strong wind speeds (>10 m s^-1) at night. Atmospheric water vapor contributed to high SST differences in very low ranges of <30 mm and in very high ranges of >60 mm. These errors are consistent with those observed in previous studies, in which GMI data were less accurate at low SST and were estimated to be due to differences in land and ocean radiation, wind-induced changes in sea surface roughness, and absorption of water vapor into the microwave atmosphere. These results suggest that the characteristics of the GMI SST differences should be clarified for more extensive use of microwave satellite SST calculations in the seas around the Korean Peninsula, including a part of the Northwest Pacific.

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.145-154
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• 2022

Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.535-543
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• 2022

A CPFD (Computational particle fluid dynamics) model of solar fluidized bed receiver of silicon carbide (SiC: average d_p=123 ㎛) particles was established, and the model was verified by comparing the simulation and experimental results to analyze the effect of particle behavior on the performance of the receiver. The relationship between the heat-absorbing performance and the particles behavior in the receiver was analyzed by simulating their behavior near bed surface, which is difficult to access experimentally. The CPFD simulation results showed good agreement with the experimental values on the solids holdup and its standard deviation under experimental condition in bed and freeboard regions. The local solid holdups near the bed surface, where particles primarily absorb solar heat energy and transfer it to the inside of the bed, showed a non-uniform distribution with a relatively low value at the center related with the bubble behavior in the bed. The local solid holdup increased the axial and radial non-uniformity in the freeboard region with the gas velocity, which explains well that the increase in the RSD (Relative standard deviation) of pressure drop across the freeboard region is responsible for the loss of solar energy reflected by the entrained particles in the particle receiver. The simulation results of local gas and particle velocities with gas velocity confirmed that the local particle behavior in the fluidized bed are closely related to the bubble behavior characterized by the properties of the Geldart B particles. The temperature difference of the fluidizing gas passing through the receiver per irradiance (∆T/I_DNI) was highly correlated with the RSD of the pressure drop across the bed surface and the freeboard regions. The CPFD simulation results can be used to improve the performance of the particle receiver through local particle behavior analysis.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.594-605
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• 2022

CaO was prepared by calcining for oyster shells using a microwave kiln. It was analyzed to Ca(OH)₂ synthed on hydration reaction from prepared CaO. The synthesized Ca(OH)₂ was formulated as an external water paint. Oyster shells (325 mesh, 43 ㎛) were decarbonized for (a) 950 ℃/1 hr and (b) 1,150 ℃/1 hr to prepare CaO. In the calcination condition of (a), CaO was 56.7 wt%, and in the calcination condition of (b), CaO was 100 wt%. To compare CaO by calcination of oyster shells with that of limestone, limestone (25~30 mm) was decarbonized at 950 ℃/1 hr to prepare CaO, and as a result of the analysis(XRD), it was analyzed as CaO 100 wt%. CaO was prepared under the calcining conditions of oyster shells (b) 1,150 ℃/1 hr, and Ca(OH)₂ was synthesized through hydration. Hydration conditions of the prepared CaO were (a) CaO : H₂O(100 g : 200 g) and (b) CaO : H₂O(100 g : 400 g). As a result of the hydration reaction, it was confirmed as low reactivity. 100 wt% of Ca(OH)₂ was synthesized. In particular, Ca(OH)₂ synthesized under the hydration condition of (a) was analyzed in a plate shape. An external water paint was formulated with Ca(OH)₂ synthesized from oyster shells as the main component. When 15 items of the external water paint standard specification (KS M 6010) were analyzed, it was confirmed that all other criteria were satisfied except for freezing stability.

• Korean Journal of Environment and Ecology
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• v.36 no.4
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• pp.368-380
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• 2022

Biomonitoring of an invasive alien crayfish species, Procambarus clarkii (Girard, 1852), was performed from February to October 2021, along with environmental DNA analysis, at five locations including Wanju-gun, Hampyeong-gun, Naju-si, Gurye-gun, and Cheongju-si. For the investigation, an umbrella-shaped trap for adults and a hand net for young crayfish were used, and 8 to 10L of freshwater was collected for eDNA analysis. The current status and past distributional records of crayfish in Korea were analyzed along with benthic macroinvertebrates at each survey site. As a result of the investigation, a total of 122 individuals were identified, and Hampyeong-gun recorded the largest number of populations with 59 individuals (48.36%) and the highest environmental DNA (eDNA). The frequency of appearance of P. clarkii was highest in May. The ratio of females to males was 21:5, and the body size was 72.2±21.1mm for female, 80.5±15.6mm for male, and 25.3±9.8mm for young crayfish. P. clarkii introduced into Korea is mainly spreading in the southwest region and it has not been observed in Seoul where there had been a record of appearance in the past. No external symbiosis (Branchiobdellida) of P. clarkii has been identified, and P. clarkii that has appeared in Korea was presumed to be imported from Japan. There are more than eight kinds of exotic crayfish distributed in Korea, and among them, the marbled crayfish (P. virginalis) was identified as a harmful species to the ecosystem of Korea by the Ministry of Environment in 2021. The identified species of benthic macroinvertebrates inhabiting the survey area where P. clarkii has appeared were 69 belonging to 39 families, 15 orders, five classes, and three phyla. Among them, Odonata were the most abundant (16 spp.; 24.62%), followed by Coleoptera (11 spp.; 16.92%) and Hemiptera (11 spp.; 16.92%). In the survey area, one Korean endemic species (Rhoenanthus coreanus), one species (Helophorus auriculatus) classified as Near Threatened (NT) on the Korean Red List, and six species of Crustaceans appeared. In the functional feeding group, the predators appeared predominantly while in habitat oriented group, the climbers appeared to be abundant. It was confirmed that P. clarkii in the survey area prefers an area rich in aquatic vegetation with waterside vegetation, and has high resistance to turbid water quality. The omnivore invader P. clarkii is expected to maintain a competitive relationship with carnivorous benthic macroinvertebrates that are predominant in the same species, and is expected to continue to generate ecosystem disturbance along the food chains.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.3
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• pp.145-154
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• 2022

Due to abnormal weather conditions caused by climate change, natural disasters and damages are gradually increasing around the world. Global climate change as accompanied by warming is projected to exert adverse impact on production of potato, which is known as cool season crop. Even though, role of potato as a food security crop is expected to increase in the future, the climate change impacts on potato and adaption strategies are not sufficiently established. Therefore, this study was conducted to analyze the damage pattern of potatoes due to high temperature treatment and to evaluate the response of cultivars. T he high temperature treatment (35~38℃) induced heat stress by sealing the plastic house in midsummer (July), and the quantity and quality characteristics of potatoes were compared with the control group. T otal yield, marketable yield (>80 g) and the number of tubers per plants decreased when heat treatment was performed, and statistical significance was evident. In the heat treatment, 'Jayoung' cultivar suffered a high heat damage with an 84% reduction in yield of >80 g compared to the control group. However, in Jopung cultivar, the decrease was relatively small at 26%. Tuber physiological disturbances (Secondary growth, Tuber cracking, Malformation) tended to increase in the heat stress. Under heat conditions, the tubers were elongated overall, which means that the marketability of potatoes was lowered. T he tuber firmness and dry matter content tended to decrease significantly in the heat-treated group. T herefore, the yield and quality of tubers were damaged when growing potatoes in heat conditions. T he cultivar with high heat adaptability was 'Jopung'. T his result can be used as basic data for potato growers and breeding of heat-resistant cultivars.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.105-117
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• 2022

This study analyzes the effects between stock returns and interest rate spread, difference between long-term and short-term interest rate through the polynomial linear regression analysis. The existing research concentrated on the business forecast through the interest rate spread focusing on the US market. The previous studies verified the interest rate spread based on the leading indicators of business forecast by moderating the period of long-term/short-term interest rates and analyzing the degree of leading. After the 7th reform of composite indices of business indicators in Korea of 2006, the interest rate spread was included in the items of composing the business leading indicators, which is utilized till today. Nevertheless, there are a few research on stock returns of each industry and interest rate spread in domestic stock market. Therefore, this study analyzed the stock returns of each industry and interest rate spread targeting Korean stock market. This study selected the long-term/short-term interest rates with high causality through the regression analysis, and then understood the correlations with each leading period and industry. To overcome the limitation of the simple linear regression analysis, polynomial linear regression analysis is used, which raised explanatory power. As a result, the high causality was verified when using differences between returns of corporate bond(AA-) without guarantee for three years by leading six months and call rate returns as interest rate spread. In addition, analyzing the stock returns of each industry, the relation between the relevant interest rate spread and returns of the automobile industry was the closest. This study is significant in the aspect of verifying the causality of interest rate spread, business forecast, and stock returns in Korea. Even though it could be limited to forecast the stock price by using only the interest rate spread, it would be working as a strong factor when it is properly utilized with other various factors.

• Journal of Mushroom
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• v.20 no.3
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• pp.138-146
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• 2022

To optimize initial cooling conditions, forced-air cooling was applied to freshly harvested oak mushrooms at 2 levels (0℃ for 30 minutes, at 0℃ for 1 hour) followed by room cooling at 3 levels (-3℃ for 1 day, 0℃ for 1 day, 3℃ for 1 day). After initial cooling, the oak mushrooms were packaged with PVC film, then held in a storage room at 1℃ for 6 weeks. Quality characteristics and percentage marketability were then investigated. As a control, Mushrooms were placed in storage with no initial cooling. The quality factors impacting marketability of fresh oak mushrooms were color change and appearance of decay. Off-odor did not occur or developed only slightly, so it did not affect oak mushroom quality within 6 weeks of low temperature storage. In all treatment groups, the shelf life in which 100% marketability was maintained was up to 3 weeks. At week 5, percent marketability of the 3 treatment groups 1 hour room cooling treatment at 0℃, 1 hour forced air cooling, and control was 100%. 80% In the group that underwent 30 min forced air cooling retained 80% marketability, and the group exposed to 1 day in room cooling at -3℃ retained 86.7% marketability. At week 6 of 1℃ storage, the marketability ratio was 80% in the 1 day room cooling at 0℃ group, 66.7% in the 1 day room cooling at 3℃ group, 46.7% in the 1 hour forced air cooling group, and 33% or less in all other treatment groups. Therefore, the most suitable initial cooling parameter to extend shelf-life of oak mushrooms is 1 day of in room cooling at 0℃ immediately after harvest.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.606-612
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• 2022

Relatively high indoor CO₂ concentration (>1,000 ppm) has a negative impact on human health. In this work, indoor CO₂ adsorbent was developed by impregnating KOH or K₂CO₃ on commercial activated carbon, named as KOH/AC and K₂CO₃/AC. Commercial activated carbon (AC) showed relatively high BET surface area (929 m²/g) whereas KOH/AC and K₂CO₃/AC presented lower BET surface area of 13.6 m²/g and 289 m²/g. Two experimental methods of TGA (2,000 ppmCO₂, weight basis) and chamber test (initial concentration: 2,000 ppmCO₂, CO₂ IR analyzer) were used to investigate the adsorption capacity. KOH/AC and K₂CO₃/AC exhibited similar adsorption capacities (145~150 mg_CO2/g), higher than K₂CO₃/Al+Si supports adsorbent (84.1 mg_CO2/g_sample). Similarly, chamber test also showed similar trend. Both KOH/AC and K₂CO₃/AC represented higher adsorption capacities (KOH/AC: 93.5 mg_CO2/g K₂CO₃/AC: 94.5 mg_CO2/g_sample) K₂CO₃/Al+Si supports. This is due to the KOH or K₂CO₃ impregnation increased alkaline active sites (chemical adsorption), which is beneficial for CO₂ adsorption. In addition, the regeneration test results showed both K-based adsorbents pose a good regeneration and reusability. Finally, the current study suggested that both KOH/AC and K₂CO₃/AC have a great potential to be used as CO₂ adsorbent for indoor CO₂ adsorption.