• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.2
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• pp.84-91
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• 2019

Recently, there has been a tendency to improve seismic performance of building structure by installing a steel hysteretic damping device which is economically efficient and easy to install and maintain. However, for a reinforced concrete building, a set of complicated connecting hardware and braces to fix the steel hysteretic damping device yields deteriorated reliability in damping performance. Therefore, this study presents a method of directly embedding a Kagome damper, which was investigated in previous researches, into a concrete structure without additional connecting hardware. Moreover, in this study, a series of experiments conducted to provide a basis of the Kagome damper by confirming the seismic behavior for various embedded lengths. As a result, in a group of the embedded length of $1.0l_d$, the dampers were pulled out, while concrete breakout occurs. In a group of $2.0l_d$, neither pull-out nor concrete breakout occurred, while the dampers show stable behavior. Moreover, the buried length of $2.0l_d$ has 1.3 times better energy dissipation capacity. The system presented in this study can reduce the cost and period for installing, omitting making additional hardware.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.329-338
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• 2019

Suction of unsaturated bentonite buffers is a very important input parameter for hydro-mechanical performance assessment and design of an engineered barrier system. This study analyzed suction measurement techniques and constitutive models of unsaturated porous media reported in the literature, and suggested suction measurement techniques and constitutive models suitable for bentonite buffer in an HLW repository. The literature review showed the suction of bentonite buffer to be much higher than that of soil, as measured by total suction including matric suction and osmotic suction. The measurement methods (RH-Cell, RH-Cell/Sensor) using a relative humidity sensor were suitable for suction measurement of the bentonite buffer; the RH-Cell /Sensor method was more preferred in consideration of the temperature change due to radioactive decay heat and measurement time. Various water retention models of bentonite buffers have been proposed through experiments, but the van Genuchten model is mainly used as a constitutive model of hydro-mechanical performance assessment of unsaturated buffers. The water characteristic curve of bentonite buffers showed different tendencies according to bentonite type, dry density, temperature, salinity, sample state and hysteresis. Selection of water retention models and determination of model input parameters should consider the effects of these controlling factors so as to improve overall reliability.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.944-953
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• 2020

Object detection plays a crucial role in a self-driving system. With the advances of image recognition based on deep convolutional neural networks, researches on object detection have been actively explored. In this paper, we proposed a lightweight model of the mask R-CNN, which has been most widely used for object detection, to efficiently predict location and shape of various objects on the road environment. Furthermore, feature maps are adaptively re-calibrated to improve the detection performance by applying an attention module to the neural network layer that plays different roles within the mask R-CNN. Various experimental results for real driving scenes demonstrate that the proposed method is able to maintain the high detection performance with significantly reduced network parameters.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.176-187
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• 2022

Due to recent mid-scale earthquakes in the Korean Peninsula, the Korean central and local governments are preparing new measures for earthquake hazard mitigation. Geological and geotechnical information is essential for earthquake hazard assessment. Thus, related data have been collected and assimilated as DBs by various national organizations. However, several problems arise when local governments intend to use this information to establish earthquake hazard mitigation measures. In the case of the geological information, small-scale geological maps make it difficult to acquire detailed information, whereas lithofacies and faults do not often match at the boundaries of large-scale geological maps. Significant geotechnical information is lost due to lack of digitalization. Present study proposes four policy plans for geological and geological information management. First, it is necessary to link industry-academictechnology fields to use the information that has already been or to be produced more efficiently and professionally. Second, local government regulations are required to be enacted and revised to accumulate a lot of geological and geotechnical information. Third an expert system should be prepared to improve the quality of the information. Fourth, it is necessary to establish a dedicated department and expand budget support for efficient information management.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1257-1271
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• 2022

Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

• Journal of Bio-Environment Control
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• v.31 no.1
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• pp.1-7
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• 2022

Strawberry is a stand-out cultivating fruit in Korea. The optimum production of strawberry is highly dependent on growing environment. Smart farm technology, and automatic monitoring and control system maintain a favorable environment for strawberry growth in greenhouses, as well as play an important role to improve production. Moreover, physiological parameters of strawberry plant and it is surrounding environment may allow to give an idea on production of strawberry. Therefore, this study intends to build a machine learning model to predict strawberry's yield, cultivated in greenhouse. The environmental parameter like as temperature, humidity and CO₂ and physiological parameters such as length of leaves, number of flowers and fruits and chlorophyll content of 'Seolhyang' (widely growing strawberry cultivar in Korea) were collected from three strawberry greenhouses located in Sacheon of Gyeongsangnam-do during the period of 2019-2020. A predictive model, Lasso regression was designed and validated through 5-fold cross-validation. The current study found that performance of the Lasso regression model is good to predict the number of flowers and fruits, when the MAPE value are 0.511 and 0.488, respectively during the model validation. Overall, the present study demonstrates that using AI based regression model may be convenient for farms and agricultural companies to predict yield of crops with fewer input attributes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.325-333
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• 2021

With the rapidly changing era of the fourth industrial revolution, the utilization of IT technology is increasing. In addition, the demand for security authentication is increasing as shared services or IoT technologies are being developed as new business models. Security authentication is becoming increasingly important for all intelligent devices such as self-driving cars. However, most location-based security authentication technologies are being developed mainly with technologies that utilize server proximity or satellite location tracking, which limits the scope of their physical use. Location-based security authentication technology has recently been developed as a complementary replacement technology. In this study, we introduce location-based security authentication technology using cell broadcasting technology, which has a wider range of applications and is more convenient and business-friendly than existing location-based security authentication technologies. We also introduced application cases and business models related to this. In addition to the current status of technology development, we analyzed current changes in business models being employed. Based on our analysis results, this study draws the implication that technology diversification is necessary to improve the performance of innovative technologies. It is meaningful that it has found and studied advanced technologies other than existing location authentication methods and systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.427-438
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• 2022

With the recent growing importance over safety management the need for advanced and technical approaches for on-site safety inspection methods has increased. Railway construction is subject to its own particular set of temporal and spatial challenges due to its unique facilities and equipment. This study aimed to investigate the field characteristics of railway infrastructure and improve the conventional field safety management methods by identifying the most appropriate features of AR technology. Group interviews and surveys were conducted with field safety experts to derive the major problems and inspection needs. Subsequently, various features of AR, such as BIM model projection, and remote conferencing, were investigated to determine their applicability to address safety issues. As a result, four problems in the current safety management process, such as 'lack of time due to the conventional inspection method and inspection of areas that are difficult to access', and three major inspection types, such as 'observance of work procedures, status of installation, adequate dimensional spacing', were identified to be improved when adopting AR based techniques. Furthermore, AR technology utilizing plans to solve safety inspection problems and effectively manage major inspection types were proposed, and a follow up survey was conducted with the same field safety experts to derive the priority of technology development.

• The Korea Journal of Herbology
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• v.27 no.6
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• pp.29-35
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• 2012

Objectives : To observe the effect of 4 kinds of Korean medicine and complex extracts on the anti-stress of chronic mild stress Rat model, so as to find out the machanism of its pharmacological effects. Methods : 64 healthy SD Rats were randomly divided into 8 groups. Model Design by chronic stress(CSM), and carried out the forced swimming test. We investigated the body weight, feed and water intake, feed conversion ratio and measured parameters to changes in swimming time, immobility time, 2 and 24 hours of feces, corticosterone hormone and blood glucose level. Results : In this experiments, body weight gain and feed intake were higher in all korean medicinal herb group. Swimming time were increased by Zizyphus jujuba and Gagamsanzointang(SZT) groups and immobility time was significantly lower by Zizyphus jujuba and Fluoxetine(FLX) groups. The result of corticosterone hormone level were significantly lower in Fluoxetine(FLX) and Gagamsanzointang(SZT) but blood glucose was not significantly difference. In 2 hours after fecal frequency result were significantly lower in Zizyphus jujuba group. but SZT group were increased. This result caused by acute stress but 24 hours of feces were restored to normal. Conclusions : 5 kind of Korean Medicinal Herbs extracts has good anti-stress effects, and also to clear the circulatory system and regulate blood glucose and improve bowel function. We suggest that use a single Korean medicine rather than the combination to relieve stress.