• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.23-48
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• 2021

The Korean economy has achieved continuous economic growth for the past several decades thanks to the government's export strategy policy. This increase in exports is playing a leading role in driving Korea's economic growth by improving economic efficiency, creating jobs, and promoting technology development. Traditionally, the main factors affecting Korea's exports can be found from two perspectives: economic factors and industrial structural factors. First, economic factors are related to exchange rates and global economic fluctuations. The impact of the exchange rate on Korea's exports depends on the exchange rate level and exchange rate volatility. Global economic fluctuations affect global import demand, which is an absolute factor influencing Korea's exports. Second, industrial structural factors are unique characteristics that occur depending on industries or products, such as slow international division of labor, increased domestic substitution of certain imported goods by China, and changes in overseas production patterns of major export industries. Looking at the most recent studies related to global exchanges, several literatures show the importance of cultural aspects as well as economic and industrial structural factors. Therefore, this study attempted to develop a forecasting model by considering cultural factors along with economic and industrial structural factors in calculating the import volume of each country from Korea. In particular, this study approaches the influence of cultural factors on imports of Korean products from the perspective of PUSH-PULL framework. The PUSH dimension is a perspective that Korea develops and actively promotes its own brand and can be defined as the degree of interest in each country for Korean brands represented by K-POP, K-FOOD, and K-CULTURE. In addition, the PULL dimension is a perspective centered on the cultural and psychological characteristics of the people of each country. This can be defined as how much they are inclined to accept Korean Flow as each country's cultural code represented by the country's governance system, masculinity, risk avoidance, and short-term/long-term orientation. The unique feature of this study is that the proposed final prediction model can be selected based on Design Principles. The design principles we presented are as follows. 1) A model was developed to reflect interest in Korea and cultural characteristics through newly added data sources. 2) It was designed in a practical and convenient way so that the forecast value can be immediately recalled by inputting changes in economic factors, item code and country code. 3) In order to derive theoretically meaningful results, an algorithm was selected that can interpret the relationship between the input and the target variable. This study can suggest meaningful implications from the technical, economic and policy aspects, and is expected to make a meaningful contribution to the export support strategies of small and medium-sized enterprises by using the import forecasting model.

• International Journal of Highway Engineering
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• v.8 no.4 s.30
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• pp.49-62
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• 2006

The republic of korea has put a great emphasis on the role of the road as widening a social infra-structural facility. Thus, vast amount of money has been invested on the road establishment. As a result, there has been fruitful outcomes in establishing the road system of the nation especially for the flat road with ease. However, in order to have more systematic and sustainable road system, we should turn our attention to more painful and high-cost regions such as mountainous districts and those are to be developed effectively. The configuration of the road is an important factor to be considered in making a decision for the road planning. Nevertheless, current road planning criterion has no such clarified and objective judging standard for figuring the configuration of the road out and, as a result, speed planning can be decided incorrectly. our research has acknowledged the necessity of estimating the configuration of the road and aimed to make it organized and sorted according to the height, slope, and the vehicle's speed. The results are as follows. First, our research made use of GIS data and classified the road into 9 different areas according to the height and the slope. Also, road classification being matched to the data of vehicle's speed, it has been shown that those characteristics of different areas have made an influence on vehicle's speed. Secondly, based on the results of the similarity between geographical classification and, vehicle's speed of sorted groups according to the height and the slope, conclusively we have classified as flat, rolling region and mountain. Since our research has made use of vehicle's speed for National Highway, it is not applicable to different functional highways. However, for the highway to be established hereafter, it can be a standard for reflection geographical characteristics.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1605-1613
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• 2023

The physical properties of the ocean interior are determined by temperature and salinity. To observe them, we rely on satellite observations for broad regions of oceans. However, the satellite for salinity measurement, Soil Moisture Active Passive (SMAP), has low temporal and spatial resolutions; thus, more is needed to resolve the fast-changing coastal environment. To overcome these limitations, the algorithm to use the Geostationary Ocean Color Imager-II (GOCI-II) of the Geo-Kompsat-2B (GK-2B) was developed as the inputs for a Multi-layer Perceptron Neural Network (MPNN). The result shows that coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (RRMSE) between GOCI-II based sea surface salinity (SSS) (GOCI-II SSS) and SMAP was 0.94, 0.58 psu, and 1.87%, respectively. Furthermore, the spatial variation of GOCI-II SSS was also very uniform, with over 0.8 of R² and less than 1 psu of RMSE. In addition, GOCI-II SSS was also compared with SSS of Ieodo Ocean Research Station (I-ORS), suggesting that the result was slightly low, which was further analyzed for the following reasons. We further illustrated the valuable information of high spatial and temporal variation of GOCI-II SSS to analyze SSS variation by the 11th typhoon, Hinnamnor, in 2022. We used the mean and standard deviation (STD) of one day of GOCI-II SSS, revealing the high spatial and temporal changes. Thus, this study will shed light on the research for monitoring the highly changing marine environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.679-690
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• 2015

The need to remove the cause of traffic accidents by improving the engineering system for a vehicle and the road in order to minimize the accident hazard. This is likely to cause traffic accident continue to take a large and significant social cost and time to improve the reliability and efficiency of this generally poor road, thereby generating a lot of damage to the national traffic accident caused by improper environmental factors. In order to minimize damage from traffic accidents, the cause of accidents must be eliminated through technological improvements of vehicles and road systems. Generally, it is highly probable that traffic accident occurs more often on roads that lack safety measures, and can only be improved with tremendous time and costs. In particular, traffic accidents at intersections are on the rise due to inappropriate environmental factors, and are causing great losses for the nation as a whole. This study aims to present safety countermeasures against the cause of accidents by developing an intersection Traffic safety evaluation model. It will also diagnose vulnerable traffic points through BPA (Back -propagation algorithm) among artificial neural networks recently investigated in the area of artificial intelligence. Furthermore, it aims to pursue a more efficient traffic safety improvement project in terms of operating signalized intersections and establishing traffic safety policies. As a result of conducting this study, the mean square error approximate between the predicted values and actual measured values of traffic accidents derived from the BPA is estimated to be 3.89. It appeared that the BPA appeared to have excellent traffic safety evaluating abilities compared to the multiple regression model. In other words, The BPA can be effectively utilized in diagnosing and practical establishing transportation policy in the safety of actual signalized intersections.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.3
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• pp.124-131
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• 2012

This study was carried out to evaluate a possible change in freeze risk for 'Changhowon Hwangdo' peach buds in three major peach growing areas under the future climate projected by RCP8.5 emission scenario. Mean values of the monthly temperature data for the present decade (2000s) and the future decades (2020s, 2050s, 2080s) were extracted for farm lands in Icheon, Chungju, and Yeongcheon-Gyeongsan region at 1km resolution and 30 sets of daily temperature data were generated randomly by a stochastic process for each decade. The daily data were used to calculate a thermal time-based dormancy depth index which is closely related to the cold tolerance of peach buds. Combined with daily minimum temperature, dormancy depth can be used to estimate the potential risk of freezing damage on peach buds. When the freeze risk was calculated daily for the winter period (from 1 November to 15 March) in the present decade, Icheon and Chungju regions had high values across the whole period, but Yeongcheon-Gyeongsan regions had low values from mid-December to the end of January. In the future decades, the frequency of freezing damage would be reduced in all 3 regions and the reduction rate could be as high as 75 to 90% by 2080's. However, the severe class risk (over 80% damage) will not disappear in the future and most occurrences will be limited to December to early January according to the calculation. This phenomenon might be explained by shortened cold hardiness period caused by winter warming as well as sudden cold waves resulting from the higher inter-annual climate variability projected by the RCP8.5 scenario.

• The korean journal of orthodontics
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• v.24 no.2
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• pp.303-317
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• 1994

This study was designed to measure the changes in the titer of tooth root antibodies accompanying root resorption associated with orthodontic tooth movement in dogs to explore a role of the specific immune response in root resorption during orthodontic tooth movement. Five adult mongrel dogs, 2 years of age, were used in the study. Six lower incisors were extracted as sources of homologous antigen in the dogs. Tooth root antigen preparations were made from a 6M Guanidine-HCl-10% EDTA(pH5.0) extract of these root dentins. Root resorption was elicited by intrusion of six maxillary incisors with 200-250gm intrusive force. In 9th week, resorbing six maxillary anterior teeth were extracted. Serum samples were taken from each dog prior to intrusion and weekly for 11 consecutive weeks. Serum autoantibody titers were determined with an enzyme-linked immunosorbent assay. As controls for antibody specificity, sera which were previously incubated with tooth root antigen as well as sera to an unrelated bacterial antigen (Porphyromonas gingivalis 33277) for 3 hours at 25 were measured in all runs. Root resorption was monitored monthly using occlusal radiographs. And then root resorption patterns were observed with a zoom stereo microscope (Model SZH-121, Olympus optical Co. Ltd.). Incisors did not show clear radiographic evidence of significant and progressive root resorption, but periodontal ligament space had widened. But root resorption was observed on the apical regions of the maxillary incisors with a zoom stereo microscope. Teeth showed the shallow depression generally accompanying deep resorption. These demonstrate a slight tendency for an immediate decrease followed by rebound to levels above the pre-treatment baseline. A peak titer of autoantibody to dentin antigen occurred on day 28, then steadily decreased during the 9th week period as the roots resorbed and then rapidly spiked in animals when the resorbing teeth were extracted. When sera is incubated with tooth root antigen, serum activity in the ELISA was almost absent. This is because serum activity in the ELISA could be removed by absorption of the serum with dog dentin antigen. Serum ELISA activity to the unrelated bacterial antigen remained essentially unchanged in all animals throughout the experimental period. When the time course of changes in autoantibody to homologous tooth root antigen prepatration and unrelated bacterial antigen was compared, no significant differences were found(${\alpha}=0.05$). In general, the overall pattern of changes in autoantibody was similar to the two antigens. These findings suggest the possibility that these immunologic changes precede a significant development of root resorption lesions rather than merely reflecting their presence. Therefore, this suggests that the changes of antibody levels may have some predictive value for root resorption.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.171-182
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• 2018

We performed the seismic field data processing using an open-source software (Madagascar) to verify if it is applicable to processing of field data, which has low signal-to-noise ratio and high uncertainties in velocities. The Madagascar, based on Python, is usually supposed to be better in the development of processing technologies due to its capabilities of multidimensional data analysis and reproducibility. However, this open-source software has not been widely used so far for field data processing because of complicated interfaces and data structure system. To verify the effectiveness of the Madagascar software on field data, we applied it to a typical seismic data processing flow including data loading, geometry build-up, F-K filter, predictive deconvolution, velocity analysis, normal moveout correction, stack, and migration. The field data for the test were acquired in Gunsan Basin, Yellow Sea using a streamer consisting of 480 channels and 4 arrays of air-guns. The results at all processing step are compared with those processed with Landmark's ProMAX (SeisSpace R5000) which is a commercial processing software. Madagascar shows relatively high efficiencies in data IO and management as well as reproducibility. Additionally, it shows quick and exact calculations in some automated procedures such as stacking velocity analysis. There were no remarkable differences in the results after applying the signal enhancement flows of both software. For the deeper part of the substructure image, however, the commercial software shows better results than the open-source software. This is simply because the commercial software has various flows for de-multiple and provides interactive processing environments for delicate processing works compared to Madagascar. Considering that many researchers around the world are developing various data processing algorithms for Madagascar, we can expect that the open-source software such as Madagascar can be widely used for commercial-level processing with the strength of expandability, cost effectiveness and reproducibility.