• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.116-126
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• 2021

Ground Component Command (GCC) has been developing operational planning and execution systems to implement "Decisive Integrated Operations", which is the concept of ground operations execution, and achieved remarkable results. In particular, "Simultaneous Offense-Defense Integrated Operations" is developed mainly to neutralize enemies in deep areas and develop favorable conditions for the allies early by simultaneously attacking and defending from the beginning of the war. On the other hand, it is limited to providing scientific and reasonable support for the commander's decision-making process because analyzing the effects of the deep operation with existing M&S systems is impossible. This study developed a model for analyzing the effects of deep operations that can be used in the KJCCS. Previous research was conducted on the effects of surveillance, physical strike, and non-physical strike, which are components of deep operations to find the characteristics and limitations and suggest a research direction. A methodology for analyzing the effects of deep operations reflecting the interactions of components using data was then developed by the GCC, and input data for each field was calculated through combat experiments and a literature review. Finally, the Deep operations Effect CAlculating Model(DECAM) was developed and distributed to the GCC and Corps battle staff during the ROK-US Combined Exercise. Through this study, the effectiveness of the methodology and the developed model were confirmed and contribute to the development of the GCC and Corps' abilities to perform deep operations.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• Molecules and Cells
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• v.45 no.7
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• pp.465-478
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• 2022

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate the expression of target messenger RNA (mRNA) complementary to the 3' untranslated region (UTR) at the post-transcriptional level. Hsa-miR-422a, which is commonly known as miRNA derived from transposable element (MDTE), was derived from short interspersed nuclear element (SINE). Through expression analysis, hsa-miR-422a was found to be highly expressed in both the small intestine and liver of crab-eating monkey. AT-Rich Interaction Domain 5 B (ARID5B) was selected as the target gene of hsa-miR-422a, which has two binding sites in both the exon and 3'UTR of ARID5B. To identify the interaction between hsa-miR-422a and ARID5B, a dual luciferase assay was conducted in HepG2 cell line. The luciferase activity of cells treated with the hsa-miR-422a mimic was upregulated and inversely downregulated when both the hsa-miR-422a mimic and inhibitor were administered. Nuclear factor erythroid-2 (NF-E2) was selected as the core transcription factor (TF) via feed forward loop analysis. The luciferase expression was downregulated when both the hsa-miR-422a mimic and siRNA of NF-E2 were treated, compared to the treatment of the hsa-miR-422a mimic alone. The present study suggests that hsa-miR-422a derived from SINE could bind to the exon region as well as the 3'UTR of ARID5B. Additionally, hsa-miR-422a was found to share binding sites in ARID5B with several TFs, including NF-E2. The hsa-miR-422a might thus interact with TF to regulate the expression of ARID5B, as demonstrated experimentally. Altogether, hsa-miR-422a acts as a super enhancer miRNA of ARID5B by collaborating with TF and NF-E2.

• Journal of Marine Life Science
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• v.4 no.2
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• pp.53-62
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• 2019

Heterotrophic bacteria are a major member of the microbial loop in the marine ecosystem and play an important role in the biogeochemical cycle decomposing organic matter. Therefore study of bacterial variation is important to understand the material cycle and energy flow of marine ecosystems. We investigated the monthly variations of bacteria and environmental factors in the Youngsan River estuary, and the correlation between bacteria and phytoplankton biomass (chlorophyll-a) including size-structure. As a result, bacteria of the Youngsan River estuary were higher in the surface than in the bottom layer, and higher in the summer than in winter. And the closer to the dike, the abundance increased, and it increased to the peaks in August, September, and June 2019 at the station closest to the dike. The chlorophyll-a also increases at the stations and time when the bacterial abundance was high and they correlates positively displaying no difference between size fractions. The results indicate that organic matter derived from phytoplankton has an effect on bacterial variation but no size-dependent effects. In addition, the seasonal pattern of bacteria increasing in proportion to the water temperature suggests the effect of water temperature on the growth of bacteria. No association of bacterial abundance variation with nutrient supply due to freshwater input was observed. In this study, dissolved oxygen was depleted and hypoxia was observed for a short time when a strong stratification was not developed. This may be resulted from the supply of organic matter from phytoplankton and the consumption of oxygen due to bacterial decomposition.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.222-237
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• 2022

This study was performed to predict change of forestland area in future to 2050 based on System Dynamics Model which is based on feedback loop by causal relationship. As forestland area change in the future depends on potential forestland conversion demands, each demand type of forestland conversion such as agricultural, industrial, public and residential/commercial use was modeled using annual GDP, population, number of household, household construction permission area (1981~2019). In results, all of conversion demands would have continuously decreased to 2050 while residential and commercial land would be reduced from 2034. Due to such shortage, eventually, total of forestland in South Korea would have decreased to 6.18 million ha when compared to current 6.29 million ha. Moreover, the forestland conversion to other use types must be occurred continuously in future because most of forestland is owned privately in South Korea. Such steady decrement of forestland area in future can contribute to the shortage of carbon sink and encumber achievement of national carbon-neutral goal to 2050. If forestland conversion would be occurred inevitably in future according to such change trends of all types, improved laws and polices related to forestland should be prepared for planned use and rational conservation in terms of whole territory management. Therefore, it is needed to offer sufficient incentive, such as tax reduction and payment of ecosystem service on excellent forestland protection and maintenance, to private owners for minimizing forestland conversion. Moreover, active afforestation policy and practice have to be implemented on idle land for reaching national goal 'Carbon Neutral to 2050' in South Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.261-273
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• 2022

This study aims to predict the land use demand of Seongnam-city using system dynamics and to simulate the effect of changes in family structure and land use density adjustment policy on land use demand. This study attempted to construct causal loop diagrams and an analysis model. The changes in land use demand over time were predicted through simulation results. As a result of the analysis, as of 2035, an additional supply of 2.08 km² for residential land and 1.36 km² for commercial land is required. Additionally, the current supply area of industrial land can meet the demand. Three policy experiments were conducted by changing the variable values in the basic model. In the first policy experiment, it was found that when the number of household members decreased sharply compared to the basic model, up to 7.99 km² of additional residential land were required. In the second policy experiment, if the apartment floor area ratio was raised from 200% to 300%, it was possible to meet the demand for residential land with the current supply area of Seongnam-city. In the third policy experiment, it was found that even if the average number of floors in the commercial area was raised from four to five and the building-to-land ratio in the commercial area was raised from 80% to 85%, the demand for commercial land exceeded the supply area of the commercial area in Seongnam-city. This study is meaningful in that it proposes a new analytical model for land use demand prediction using system dynamics, and empirically analyzes the model by applying the actual urban planning status and statistics of Seongnam-city.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.87-94
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• 2022

In this study, 61 patients who underwent coronary angiography from March 2018 to August 2019 were divided into Group I (Radial, n=34 patients) and Group II (Femoral, n=27 patients), and compared and analyzed methods using radial and femoral arteries when coronary angiography was performed. As a result of comparative analysis, Catheter usage was reduced in the examination using radial artery, and in the abnormal shape of blood vessels, Loops arterial abnormalities were more in the radial artery (20.6% vs, 0%, p<0.05), and it was found that the abnormal shape of the radial vessels increased with age. 60s, 70s, 80s, 90s or older (0%, 18.2%, 25.0%, 100%)

• 지역과문화
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• v.8 no.3
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• pp.27-48
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• 2021

In recent years, China's tourism performing art in a series of new completion of the project, increase the box office of tourism performing arts industry, higher economic income, at the same time led to the formation of brand of tourism performing arts and has a good reputation, with the regional culture, has a certain role in promoting economic development, including Large scenario experience drama is one of the key projects. Large scenario experience drama is a new form of drama that simulates the space design of real environment and enables the audience to have active experience in visual, auditory, smell, taste, touch and other senses with strong interactivity.Large scenario experience drama are adapted from traditional Chinese culture, regional culture and long-passed stories, and combine high technology such as lighting, sound effects, special effects and 3D effects to make the audience's experience more real.As the first Large scenario experience drama in China, 'You Jian Ping-yao' reflects the profound culture of Shanxi with new forms of expression and creative means, in the form of scene experience and make the audience more intuitive feel the 'Shanxi emotion', 'Shanxi sentiment' and 'Shanxi Morality', carry forward the traditional culture at the same time, also passed the Shanxi ancient and great values, strengthened the drama of China's movie village, impetus the development of the tourism industry in Shanxi, drive the Shanxi region of jingjing, gradually formed a complete industrial chain. However, there are also limitations such as improper plot connection and improper tourist management, which can improve the performance effect through more audience interaction and guidance. Therefore, it can be seen that large-scale situational experience dramas play a great role in promoting the dissemination of traditional culture and values, the development of tourism industry, the formation of regional brand characteristics and economic development. Through these, it can be seen that large-scale situational experience plays have enlightenments such as innovative thinking content, gradually forming an industrial chain closed-loop, and broadening publicity channels for the development of live-action performances.