• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.39-45
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• 2010

Quantification of carbon absorption and understanding the human induced land use changes (LUC) forms one of the major study with respect to global climatic changes. An attempt study has been made to quantify the carbon absorption by LUC through remote sensing technology. The Landsat imagery four time periods was classified with the hybrid classification method in order to quantify carbon absorption by LUC. Thereafter, for estimating the amount of carbon absorption, the stand biomass of forest was estimated with the total weight, which was the sum of individual tree weight. Individual tree volumes could be estimated with the crown width extracted from digital forest cover type map. In particular, the carbon conversion index and the ratio of the $CO_2$ molecular weight to the C atomic weight, reported in the IPCC guideline, was used to convert the stand biomass into the amount of carbon absorption. Total carbon absorption has been modeled by taking areal estimates of LUC of four time periods and carbon factors for land use type and standing biomass. Results of this study, through LUC suggests that over a period of construction, 7.10 % of forest and 9.43 % of barren were converted into urban. In the conversion process, there has been a loss of 6.66 t/ha/y (7.94 %) of carbon absorption from the study area.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.1
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• pp.9-18
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• 2010

Our country has so large mountain area that the tunnel construction is inevitable and the need of incident detection that provides safe management of tunnels is increasing. In this paper, we suggest a tunnel incident detection system using computer vision techniques, which can detect the incidents in a tunnel and provides the information to the tunnel administrative office in order to help safe tunnel operation. The suggested system enhances the processing speed by using simple processing algorithm such as image subtraction, and ensures the accuracy of the system by focused on the incident detection itself rather than its classification. The system is also cost effective because the video data from 4 cameras can be simultaneously analyzed in a single PC-based system. Our system can be easily extended because the PC-based analyzer can be increased according to the number of cameras in a tunnel. Also our web-based structure is useful to connect the other remotely located tunnel incident systems to obtain interoperability between tunnels. Through the experiments the system has successfully detected the incidents in real time including dropped luggage, stoped car, traffic congestion, man walker or bicycle, smoke or fire, reverse driving, etc.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.619-628
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• 2002

Reusable software component is an ultimate goal for the software development. Component based development is focused on advanced concepts rather than passive manipulation or class library with source codes. However, the primary component construction in component based development lead to an additional development cost and effort for reconstructing the new software component within a component model. Java application provides several features based on component model. But, we only have an opportunity to develop the smallest reuse units or the restricted set of GUI components. It cannot contributed as a component and only used in the specific domain component with high cost and efforts. In this paper, we apply java component model to the existing java application and extract javabeans through extending the component scalability. We also discuss the algorithm for transformation mechanism from legacy class to javabeans with a partial of business logic.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.266-272
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• 2021

Water friendly space refers to a place designated to plan and manage spaces for residents Water friendly activities. Efficient management of river Water friendly parks requires automated GIS data and DB construction of the water friendly facilities. Object-based classification using drone images or aerial images is attracting attention as an efficient means to acquire 3D spatial information in the country. To remove the miscellaneous image included in the extracted outline, a linear simplification of the outline is required, and it is difficult to apply manually, so various automation methods have been developed to overcome this, and among them, the most widely studied and utilized is the linear simplification method. In this study, the suitability of linear simplification algorithms such as Douglas-Peucker, Visvalingam-Whyatt, and Bend-simplify algorithms for the geometric shape of hydrophilic facilities was determined.

• Journal of Information Technology Services
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• v.21 no.1
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• pp.127-144
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• 2022

Recently, Korea is promoting cooperation with various countries, centering on ASEAN countries, with the aim of exporting Korean smart cities for the globalization of smart cities. The purpose of this study is to select excellent smart city technologies through analysis of smart city technologies owned by domestic companies and company status, and to prepare a plan for revitalization of companies with smart city technologies. Through prior research, the implications were derived through research on the existing smart city. Next, established a smart city policy analysis and smart city technology classification criteria through Korea and Overseas smart city policy and Korea smart city technology status DB. And the big data of smart city technology possessed by Korea companies and a plan for selecting a smart city export technology was prepared through analysis by region and company. As a result, to activate the technology possessed by Korea companies and to export overseas, it seems to need financial support and tax incentives that secure a pathway to export specialized smart technologies of SMEs, along with citizen participation and institutional supplementation. The smart city technology fields with the highest utilization in Korea were traffic, green energy, e-government, crime prevention, and construction, and the service types were platform, IoT, AI, big data, and GIS/GPS. These technologies are expected to contribute to building a platform for overseas smart city technology exports.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• Korean Journal of Construction Engineering and Management
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• v.21 no.6
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• pp.46-55
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• 2020

The maintenance cost for highway pavement is gradually increasing due to the continuous increase in road extension as well as increase in the number of old routes that have passed the public period. As a result, there is a need for a method of minimizing costs through preventative grievance Preventive maintenance requires the establishment of a strategic plan through accurate prediction old Highway pavement. herefore, in this study, the XGBoost among machine learning classification-based models was used to develop a highway pavement damage prediction model. First, we solved the imbalanced data issue through data sampling, then developed a predictive model using the XGBoost. This predictive model was evaluated through performance indicators such as accuracy and F1 score. As a result, the over-sampling method showed the best performance result. On the other hand, the main variables affecting road damage were calculated in the order of the number of years of service, ESAL, and the number of days below the minimum temperature -2 degrees Celsius. If the performance of the prediction model is improved through more data accumulation and detailed data pre-processing in the future, it is expected that more accurate prediction of maintenance-required sections will be possible. In addition, it is expected to be used as important basic information for estimating the highway pavement maintenance budget in the future.

• Journal of the Korean Geotechnical Society
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• v.28 no.4
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• pp.23-33
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• 2012

Recently, landslide disasters caused by severe rain storms and typhoons have been frequently reported. Due to the geomorphologic characteristics of Korea, considerable portion of urban area and infrastructures such as road and railway have been constructed near mountains. These infrastructures may encounter the risk of landslide and debris flow. It is important to evaluate the highly risky locations of landslide and to prepare measures for the protection of landslide in the process of construction planning. In this study, a landslide-risk prediction equation is proposed based on the statistical analysis of 423 landslide data set obtained from field surveys, disaster reports on national road, and digital maps of landslide area. Each dataset includes geomorphologic characteristics, soil properties, rainfall information, forest properties and hazard history. The comparison between the result of proposed equation and actual occurrence of landslide shows 92 percent in the accuracy of classification. Since the input for the equation can be provided within short period and low cost, and the results of equation can be easily incorporated with hazard map, the proposed equation can be effectively utilized in the analysis of landslide-risk for large mountainous area.

• Science of Emotion and Sensibility
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• v.12 no.4
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• pp.433-442
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• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.74-84
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• 2017

Soil erosion is often extreme in Korea due to high rainfall intensities and steep slopes, and climate change has also increased the risk of erosion. Despite its significane, erosion-induced soil organic carbon (SOC) emission and water resource loss are not well understood, along with the lack of an integrated surface soil erosion protection policy. Therefore, to design adequate protection policies, land users, scientists, engineers and decision makers need proper information about surface soil and watershed properties related to greenhouse gas emission potential and water conservation capability, respectively. Assuming the total soil erosion of $346Tg\;yr^{-1}$, soil organic matter (SOM) content of 2% (58% of SOM is SOC), and mineralization rate of 20% of the displaced carbon, erosion-induced carbon emission could reach $800Gg\;C\;yr^{-1}$. Also the available water capacity of the soil was estimated to be 15.8 billion tons, which was 14 times higher than the yearly water supply demand in Seoul, Korea. Therefore, in order to prevent of soil erosion, this study proposes a three-stage plan for surface soil erosion prevention: 1) classification of soil erosion risk and scoring of surface soil quality, 2) selection of priority areas for conservation and best management practices (BMP), and 3) application of BMP and post management.