• Journal of the Korean Society for Railway
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• v.18 no.5
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• pp.439-446
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• 2015

The turnout system, which determines the direction of the train, is not only a key system but also a vulnerable system. Failure of this system may lead to a delay of the train or even casualties. In this light, it is necessary to precisely the conditions of the turnout system. Currently, ROADMASTER of Germany is used as a diagnostic system in Korea. However, a new diagnostic system should be developed for optimized operation of the turnout system with maintenance that is suitable for the Korean railway environment. In this paper, a Fault Tree Analysis for the representative faults of the turnout system is conducted and physical quantities, which can be the cause of the fault, are classified according to the component and function. Also, the measuring factors for the monitoring are derived and a decision making theory is suggested. On the basis of the results, we propose a new turnout diagnostic system that can provide more driverse and precise information than the conventional system.

• Journal of Ginseng Research
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• v.43 no.4
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• pp.508-516
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• 2019

Background: Ginsenosides are not only the principal bioactive components but also the important indexes to the quality assessment of Panax ginseng Meyer. Their contents in cultivated ginseng vary with the growth environment and age. The present study aimed at evaluating the significant difference between 36 cultivated ginseng of different cultivation areas and ages based on the simultaneously determined contents of 14 ginsenosides. Methods: A high-performance liquid chromatography (HPLC) coupled with triple quadrupole mass spectrometer (MS) method was developed and used in the multiple reaction-monitoring (MRM) mode (HPLC-MRM/MS) for the quantitative analysis of ginsenosides. Multivariate statistical analysis, such as principal component analysis and partial least squares-discriminant analysis, was applied to discriminate ginseng samples of various cultivation areas and ages and to discover the differentially accumulated ginsenoside markers. Results: The developed HPLC-MRM/MS method was validated to be precise, accurate, stable, sensitive, and repeatable for the simultaneous determination of 14 ginsenosides. It was found that the 3- and 5-yr-old ginseng samples were differentiated distinctly by all means of multivariate statistical analysis, whereas the 4-yr-old samples exhibited similarity to either 3- or 5-yr-old samples in the contents of ginsenosides. Among the 14 detected ginsenosides, Rg1, Rb1, Rb2, Rc, 20(S)-Rf, 20(S)-Rh1, and Rb3 were identified as potential markers for the differentiation of cultivation ages. In addition, the 5-yr-old samples were able to be classified in cultivation area based on the contents of ginsenosides, whereas the 3- and 4-yr-old samples showed little differences in cultivation area. Conclusion: This study demonstrated that the HPLC-MRM/MS method combined with multivariate statistical analysis provides deep insight into the accumulation characteristics of ginsenosides and could be used to differentiate ginseng that are cultivated in different areas and ages.

• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.98-105
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• 2022

It is essential for vertical smart farms that artificially grow crops in an enclosed space to properly utilize air environment facilities to create an appropriate growth environment. However, domestic vertical smart farm companies are creating a growing environment by relying on empirical data rather than systematic methods. Using IoT to create a growing environment based on systematic and precise monitoring can increase crop production yield and maximize profitability. This study aims to construct a monitoring system using IoT and to analyze the cause by demonstrating the imbalance of temperature environment, which is a significant factor in crop cultivation. 1) The horizontal temperature distribution of the multi-layer shelf was measured with different operating methods of LED and air conditioner. As a result, there was a temperature difference of "up to 1.7℃" between the sensors. 2) As a result of measuring the vertical temperature distribution, the temperature difference was "up to 6.3℃". In order to reduce this temperature gap, a strategy for proper arrangement and operation of air conditioning equipment is required.

• Journal of the Korean Geotechnical Society
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• v.38 no.11
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• pp.43-54
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• 2022

The settlement at the railroad foundation is often the leading cause of track irregularity and potential derailment. The control of such deformation is considered necessary in track maintenance practice. Nevertheless, the monitoring process performed by in situ surveying requires an excessive amount of manpower and cost. The InSAR, a remote sensing technique by RADAR satellite, is used to overcome such a burden. The PS-InSAR technique is preferred for a long-term precise monitoring method. However, this study aims to obtain relatively brief analysis results from only two satellite images using the D-InSAR technique, while a minimum of 25 images are required for PS-InSAR. This study verifies the precision of D-InSAR within a few millimeters by inspecting railroad facilities and land settlements in Korea Railroad Research Institute's test track with images from TerraSAR-X Satellite. Multiple corner reflectors were adopted and installed on an embankment and the building roof to raise the surface reflectivity. Those reflectors were slightly adjusted periodically to verify the detecting performance. The results revealed the optimum distance between corner reflectors. Further, the deformation of railway tracks, slopes, and concrete structures was analyzed successively. In conclusion, this study indicates that the D-InSAR technique effectively monitors the short-term deformation of a broad area such as railway structures.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.497-510
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• 2022

Agricultural reservoirs are essential structures for water supplies during dry period in the Korean peninsula, where water resources are temporally unequally distributed. For efficient water management, systematic and effective monitoring of medium-small reservoirs is required. Synthetic Aperture Radar (SAR) provides a way for continuous monitoring of those, with its capability of all-weather observation. This study aims to evaluate the applicability of SAR in monitoring medium-small reservoirs using Sentinel-1 (10 m resolution) and Capella X-SAR (1 m resolution), at Chari (CR), Galjeon (GJ), Dwitgol (DG) reservoirs located in Ulsan, Korea. Water detected results applying Z fuzzy function-based threshold (Z-thresh) and Chan-vese (CV), an object detection-based segmentation algorithm, are quantitatively evaluated using UAV-detected water boundary (UWB). Accuracy metrics from Z-thresh were 0.87, 0.89, 0.77 (at CR, GJ, DG, respectively) using Sentinel-1 and 0.78, 0.72, 0.81 using Capella, and improvements were observed when CV was applied (Sentinel-1: 0.94, 0.89, 0.84, Capella: 0.92, 0.89, 0.93). Boundaries of the waterbody detected from Capella agreed relatively well with UWB; however, false- and un-detections occurred from speckle noises, due to its high resolution. When masked with optical sensor-based supplementary images, improvements up to 13% were observed. More effective water resource management is expected to be possible with continuous monitoring of available water quantity, when more accurate and precise SAR-based water detection technique is developed.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.1
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• pp.118-129
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• 2011

This Study has developed the information system of the rivers based on 3D image GIS by converging the latest information technology of GIS(Geographic Information System), RS(Remote Sensing), GNSS(Global Navigation Satellite System), aerial laser survey(LiDAR) with real time network technology in order to understand the current situation of all the four major rivers and support the administrative management system. The said information system acquires the high resolution aerial photographs of 25cm, aerial laser survey and water depth surveying data to express precise space information on the whole Youngsan River which is the leading project site out of the four river sites. Monitoring the site is made available on the transporting means such as a helicopter, boat or a bus in connection with locational coordinate tracking skill for the moving objects in real time using GNSS. It makes monitoring all the information on the four river job sites available at a glance, which can obtain the reliability of the people to such vast areas along with enhancing the recognition of the people by publicity of four Rivers Revitalizing Project and reports thereof.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.421-427
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• 2013

In general, it can be assumed that the tropospheric effect are removed through double-differencing technique in short-baseline GPS data processing. This means that the high-accuracy positioning can be obtained because various error sources can be eliminated and the number of unknown can be decreased in the adjustment computation procedure. As a consequence, short-baseline data processing is widely used in the fields such as deformation monitoring which require precise positioning. However, short-baseline data processing is limited to achieve high positioning accuracy when the height difference between the reference and the rover station is significant. In this study, the effects of tropospheric delays on the determination of short-baseline is analyzed, which depends on the orientation of baseline. The GPS measurements which include tropospheric effect and measurement noises are generated by simulation, and then rover coordinates are computed by short-baseline data processing technique. The residuals of rover coordinates are analyzed to interpret the tropospheric effect on the positioning. The results show that the magnitudes of the biases in the coordinate residuals increase as the baseline length gets longer. The increasing rate is computed as 0.07cm per meter in baseline length. Therefore, the tropospheric effects should be carefully considered in short-baseline data processing when the significant height difference between the reference and rover is observed.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.8-15
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• 2018

This article investigates intelligent security integrated platform for real-time crime response and preventive crime prevention. This study analyzed intelligent crime prevention platform elements by analyzing crime prevention system/platform research, intelligent crime prevention research, and case study of municipality integrated operation center crime prevention system. Through this, we developed a practical intelligent security platform, and suggested a linkage with existing municipalities and smart city integrated platform system considering scalability. This enables CCTV monitoring, which is used only for existing post processing, to cope with real-time crime. It is expected that it will be able to solve the incidents in golden-time by grasping the precise position of the complainant not only in the outdoor but also indoors. It is also possible to provide citizen-centered crime-prevention social safety net information sharing service by enhancing citizen participation as well as improving control efficiency. The intelligent security platform has advantages that it is easy to spread the municipality because it is developed considering existing municipal system, smart city integration platform, and linkage and expansion with other security services.