• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.705-713
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• 2021

Because the cage assembly serves as the launch platform, an accurate aim is essential to ensure shooting accuracy for the target. On the other hand, the abnormal rotation of the cage due to the directional errors of the K-MLRS has continuously caused quality problems. The quality problem of weapon systems may have a negative impact on the military's power loss. In this study, improvement plans were derived by examining the defects and analyzing the directional errors of the K-MLRS launcher. In addition, all possible causes of directional errors were derived from the flow diagram for cage directionality. Based on the results, the defense design through the software program was intended to prevent the loss of direction. Through this study, the signal error of the resolver was improved by preventing unspecific signals in the data. Furthermore, the directional judgment method was improved to minimize the impact of data distortion. Lastly, directional storage and verification methods were improved so that data for the cage rotation direction would not be affected by errors. For the design improvement method, the reliability was verified through the system applicability. This study is expected to be a reference for failure analysis and design for similar weapon systems in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.133-146
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• 2021

Providing weather information on roads today means that the road weather conditions near weather observation points are presented to road managers and road users. These weather observation points are managed by the Korea Meteorological Administration. However, it is difficult to provide accurate weather information due to physical limitations such as the presence of precipitation collection points, distance to weather information provision roads, and the presence of mountains. Therefore, this study intends to perform a comparative analysis by time zone and administrative dong provided by the Meteorological Administration using the wiper information among the information contained in the PVD(Probe Vehicle Data) collected from the highway C-ITS project. As a result of the analysis it was possible to detect rainfall even in the event of local rainfall and rainfall over a long period of time and the higher the cumulative precipitation per hour, the higher the probability of coincidence. This study is meaningful because it used PVD to solve the limitations of the existing road weather information provision method and suggested utilization plan for PVD.

• Journal of Space Technology and Applications
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• v.1 no.1
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• pp.23-32
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• 2021

The high-level Space Situational Awareness (SSA) objective is to provide to the users dependable, accurate and timely information in order to support risk management on orbit and during re-entry and support safe and secure operation of space assets and related services. Therefore the risk assessment for the re-entry of space objects should be managed nationally. In this research, the Software for Re-Entry Prediction of space objects (SREP) was developed for national SSA system. In particular, the rate of change of the drag coefficient is estimated through a newly proposed Drag Scale Factor Estimation (DSFE), and is used for high-precision orbit propagator (HPOP) up to an altitude of 100 km to predict the re-entry time and position of the space object. The effectiveness of this re-entry prediction is shown through the re-entry time window and ground track of space objects falling in real events, Grace-1, Grace-2, Tiangong-1, and Chang Zheng-5B Rocket body. As a result, through analysis 12 hours before the final re-entry time, it is shown that the re-entry time window and crash time can be accurately predicted with an error of less than 20 minutes.

• Journal of the Society of Disaster Information
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• v.18 no.2
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• pp.261-268
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• 2022

Purpose: In the case of cavity discovered by ground penetrating radar exploration, it is necessary to accurately predict the filling amount in the cavity in advance, fill the cavity sufficiently and exert strength to ensure stability and prevent ground subsidence. Method: The cavity waveform analysis method by GPR exploration and the method using the cavity shape imaging equipment were performed to measure the cavity shape with irregular size and shape of the actual cavity, and the amount of cavity filling of the injection material was calculated during rapid restoration. Results: The expected filling amount was presented by analyzing the correlation between the cavity size and the filling amount of injection material according to the cavity scale and soil depth through the method by GPR exploration and the cavity scale calculation using the cavity shaping equipment. Conclusion: The cavity scale measured by the cavity imaging equipment was found to be in the range of 20% to 40% of the cavity scale by GPR exploration. In addition, the filling amount of injection material compared to the cavity scale predicted by GPR exploration was in the range of about 60% to 140%, and the filling amount of the injection material compared to the cavity size by the cavity shaping equipment was confirmed to be about 260% to 320%.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.597-608
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• 2022

Remotely sensed data have been used in various fields, such as disasters, agriculture, urban planning, and the military. Recently, the demand for the multitemporal dataset with the high-spatial-resolution has increased. This manuscript proposed an automatic image matching algorithm using a deep learning technique to utilize a multitemporal remotely sensed dataset. The proposed deep learning model was based on High Resolution Net (HRNet), widely used in image segmentation. In this manuscript, denseblock was added to calculate the correlation map between images effectively and to increase learning efficiency. The training of the proposed model was performed using the multitemporal orthophotos of the National Geographic Information Institute (NGII). In order to evaluate the performance of image matching using a deep learning model, a comparative evaluation was performed. As a result of the experiment, the average horizontal error of the proposed algorithm based on 80% of the image matching rate was 3 pixels. At the same time, that of the Zero Normalized Cross-Correlation (ZNCC) was 25 pixels. In particular, it was confirmed that the proposed method is effective even in mountainous and farmland areas where the image changes according to vegetation growth. Therefore, it is expected that the proposed deep learning algorithm can perform relative image registration and image matching of a multitemporal remote sensed dataset.

• Journal of the Korean Regional Science Association
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• v.38 no.4
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• pp.59-74
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• 2022

We aim to explore how the COVID-19 affects commercial sales of traditional market in Seoul. We obtain data for commercial sales and several spatial variables that are related to commercial sales from the Seoul Open Data Plaza. In order to estimate the effect of COVID-19 occurrence on commercial sales, we employ fixed-effect panel data analysis models. Unlike our expectation, the empirical results show that the effect of the COVID-19 on commercial sales of traditional market is not significant. However, we found that the effects are significant in some types of businesses when we did the same analyses with subsamples. For example, service sectors are mostly negatively affected by COVID-19, and retail sectors are also second mostly affected by COVID-19. However, there is no significant relationship between COVID-19 and restaurant sectors. In addition, these effects vary by size of traditional market. Our results suggest that government should have a plan to help small businesses in traditional market because they do not have sufficient abilities to adjust to the unexpected economic shock, like COVID-19. Findings also suggest that strategies for helping them should be differentiated by business type and market size.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.491-496
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• 2021

In line with the modern era in which the safety of underground facilities and the use of underground information are increasingly emphasized, the state is pushing for more precise and accurate underground spatial information to be secured and utilized. Therefore, we need to pay more attention to subsurface geospatial data. In the future, the Ministry of Land, Infrastructure and Transport will actively utilize the 15 types of Integrated Underground Geospatial Information Map(6 types of underground facilities, 6 types of underground structures, 3 types of ground) that the Ministry of Land, Infrastructure and Transport is building as three-dimensional underground spatial information, and contribute greatly to improving national safety and convenience in underground construction. expected to do However, when a site manager requests an Integrated Underground Geospatial Information Map with a mobile device, if the large-capacity integrated underground space map is not quickly transmitted over the wireless section and is not serviced, it causes inconvenience to the site manager and delays work. In this paper, the goal of this paper is to enable field managers to quickly receive a tiled Integrated Underground Geospatial Information Map with minimal information exchange. Therefore, the tiling system is configured according to the dataset for high-speed Mobile Integrated Underground Geospatial Information Map transmission. In addition, a transmission system for the Mobile Integrated Underground Geospatial Information Map is established, and a TCP/IP (Transmission Control Protocol/Internet Protocol)-based spatial information tiling transmission protocol dedicated to the on-site Integrated Underground Geospatial Information Map is developed.

• Analyses & Alternatives
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• v.7 no.2
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• pp.179-207
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• 2023

Carbon neutrality, the international community's practical challenge in response to climate change, is becoming a key industrial strategy for the future development of nations. Despite concerns that China, as an economic powerhouse in the G2, may face challenges leading global climate change efforts due to its high-carbon-emitting industrial structure, it is leveraging carbon neutrality to enhance its industrial competitiveness. The Chinese government has formulated national policies for achieving carbon neutrality and detailed sector-specific plans to implement them. In particular, it aims to leverage carbon neutrality industrial strategies as a lever for adjusting the domestic industrial structure and fostering new industries, at the same time responding to international climate norms and external pressures. However, the effectiveness of carbon-neutral industrial strategies is expected to vary based on regional conditions such as economic and industrial levels. This article analyzes the regional conditions for implementing carbon neutrality in China, as well as the contents and characteristics of major industrial policies. Due to differing levels of economic development and industrial structures, significant variations in carbon emissions, size, emission sources, and efficiency are inevitable across regions. These disparities introduce diverse initial conditions and endogenous factors in pursuing carbon-neutral goals, limiting the direction and implementation of carbon-neutral industrial strategies favoring certain regions. In particular, the extent of policy autonomy granted to local governments regarding carbon neutrality implementation will influence the regional dynamics of central-local environmental governance. Consequently, it is crucial to emphasize regional monitoring alongside comprehensive national research to accurately navigate the path towards carbon neutrality in China. In summary, the article underscores the importance of understanding regional variations in economic development, industrial structure, and policy autonomy for successful carbon neutrality implementation in China. It highlights the need for regional monitoring and comprehensive national research to determine a more precise direction for achieving carbon neutrality.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.27-40
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• 2022

Every year landslides cause serious casualties and property damages around the world. As the accurate prediction of landslides is important to reduce the fatalities and economic losses, various approaches have been developed to predict them. Prediction methods can be divided into landslide susceptibility analysis, landslide hazard analysis and landslide risk analysis according to the type of the conditioning factors, the predicted level of the landslide dangers, and whether the expected consequence cased by landslides were considered. Landslide susceptibility analyses are mainly based on the available landslide data and consequently, they predict the likelihood of landslide occurrence by considering factors that can induce landslides and analyzing the spatial distribution of these factors. Various qualitative and quantitative analysis techniques have been applied to landslide susceptibility analysis. Recently, quantitative susceptibility analyses have predominantly employed the physically based model due to high predictive capacity. This is because the physically based approaches use physical slope model to analyze slope stability regardless of prior landslide occurrence. This approach can also reproduce the physical processes governing landslide occurrence. This review examines physically based landslide susceptibility analysis approaches.