• Proceedings of the Korean Nuclear Society Conference
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• 2005.05a
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• pp.679-680
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• 2005

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.201-205
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• 2024

Currently, the most important issue on the earth is global warming, which causes climate change and leads to disasters. For this reason, each country is focusing on renewable energy, carbon neutrality, environmentally friendly energy and transportation. Bicycles used as short-distance vehicles do not emit gases harmful to the human body that pollute the Earth's atmosphere. Also, the use of bicycles has the effect of improving the health of people, and each country is designing a short distance transportation network using bicycles. In this study, we propose a model of a bicycle power-train that can use a belt as a power transmission medium. The basic principles and methods for applying the proposed new type of power-train to bicycles are presented.

• Smart Media Journal
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• v.9 no.2
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• pp.92-98
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• 2020

This paper proposes a vehicle license plate recognition system using light weight deep learning models without high-end server. The proposed license plate recognition system consists of 3 steps: [license plate detection]-[character area segmentation]-[character recognition]. SSD-Mobilenet was used for license plate detection, ResNet with localization was used for character area segmentation, ResNet was used for character recognition. Experiemnts using Samsung Galaxy S7 and LG Q9, accuracy showed 85.3% accuracy and around 1.1 second running time.

• Smart Media Journal
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• v.8 no.1
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• pp.82-91
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• 2019

This study provides the analysis and prediction of fruits diseases related to weather conditions (temperature, wind speed, solar power, rainfall and humidity) using Linear Model and Poisson Regression. The main goal of the research is to control the method of fruits diseases and also to prevent diseases using less agricultural pesticides. So, it is needed to predict the fruits diseases with weather data. Initially, fruit data is used to detect the fruit diseases. If diseases are found, we move to the next process and verify the condition of the fruits including their size. We identify the growth of fruit and evidence of diseases with Linear Model. Then, Poisson Regression used in this study to fit the model of fruits diseases with weather conditions as an input provides the predicted diseases as an output. Finally, the residuals plot, Q-Q plot and other plots help to validate the fitness of Linear Model and provide correlation between the actual and the predicted diseases as a result of the conducted experiment in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.135-135
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• 2022

In this study, we evaluated uncertainties in baseflow separation filter methods focusing on changes in recession constant (𝛼) values, which include Lynie & Holick (LH) algorithm, Chapman algorithm, Eckhardt filter, and EWMA filter. Here, we analyzed daily streamflow data at 14 stations in the Urmia Lake basin, Iran, from 2015 to 2019. The 𝛼 values were computed using three different approaches from calculating the slope of a recession curve by averaging the flow over all seasons, a correlation method, and a mean value of the ratio of Q_t+1 to Q_t. In addition to the 𝛼 values, the BFImax (maximum value of the baseflow index (BFI)) was determined for the Eckhardt filter through the backward filter method. As results, it indicates that the estimated baseflow is dependent upon the selection of filter methods, their parameters, and catchment characteristics at different stations. In particular, the EWMA filter showed the least changes in estimating the baseflow value by changing the 𝛼 value, and the Eckhardt filter and LH algorithm showed the highest sensitivity to this parameter at different stations.

• Asia pacific journal of information systems
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• v.26 no.2
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• pp.247-262
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• 2016

Almost all Koreans recognize the Dolhareubang as a representative symbol of Jeju. However, as the development of online technology progressed, the image and perception of the Dolhareubang is also expected to change. Thus, this study explored the perceived images of Dolhareubang by focusing on residents in Seoul, Korea using Q methodology. The goal of this research was to evaluate this iconic representation of Jeju as an important component of the island's online tourism destination image. The Q-set was developed from existing literature and defined conceptually in terms of 'value', 'resource', 'story', and 'image'. Thirty five respondents were recruited as P set. Findings indicated four distinctive clusters that perceived the Dolhareubang differently and differences in perceptions were observed in terms of age. The examination of destination image and the exploration of the perceptions of Dolharuebang as a representative of Jeju could contribute to online destination image management or development, which is a crucial component of smart tourism.

• Journal of the Korean Society of Earth Science Education
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• v.14 no.2
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• pp.159-172
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• 2021

This study is an action study that plans a instructional strategy for improving experimental activities and interactions in online science classes and suggests improvement plans based on the results. To this end, from July 7 to September 9, 2020, the 'Earth and the Moon' unit class was conducted for 20 6th grade elementary school students located in G Metropolitan City. For the class, smart devices and alternative experiments were planned in the experimental activity category, and an online chat room and Q&A strategy were planned in the interaction category. Among the collected data, class activity papers, homework assignments, reflection journals, online conversation contents, and Q&A contents were input into the matrix and analyzed by writing analytical texts. As a result of the implementation, smart devices and alternative experiments provided opportunities for exploration, but there was a risk of misconception formation and hindered experimental activities. The online chat room and Q&A provided opportunities for communication and examination and feedback on scientific concepts. Through this action study, the researcher was able to reflect on the class while writing class reflection notes, and suggested the role of smart devices in terms of the effectiveness and efficiency of science classes.

• Journal of fish pathology
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• v.34 no.2
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• pp.261-269
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• 2021

This study presents the evaluation of sample extraction and purification procedure for the determination of residues of febantel and its metabolites, fenbendazole, oxfendazole and oxfendazole sulfone in rockfish (Sebastes schlegeli) muscle using liquid chromatography-tandem mass spectrometry. Residues of febantel and its metabolites in rockfish muscle were analyzed using each different sample preparation method from Korean Food Standards Codex (KFSC), Food Safety and Inspection Service (FSIS, USA), and the modified FSIS method using QuEChERS kit (FSIS-Q), respectively. Each method was compared for mean recoveries and repeatabilities. Since FSIS-Q showed higher repeatabilities (coefficient of variation, CV of 2.4%~10.9%) than those of FSIS method (CV of 4.6%~17.5%), recoveries from FSIS-Q were compared with those from KFSC method. FSIS-Q showed significantly higher recoveries of 83.1%~110.1% (P < 0.05) than those from KFSC method of 64.7%~107.4%. In addition, FSIS-Q showed a good linearity over the range of 2.5~200 ㎍/kg, and excellent sensitivities with limit of detection of 0.46~0.71 ㎍/kg and limit of quantification of 1.08~2.15 ㎍/kg. Although all the sample preparation methods turned out to be able to meet CODEX guideline for all the compounds, FSIS method and FSIS-Q validated in this study could be applied to screening and quantification for residues of febantel and its metabolites in rockfish muscle with efficient preparation procedures.

• Smart Structures and Systems
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• v.15 no.3
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• pp.807-830
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• 2015

When a building structure requires both health monitoring system and vibration control system, integrating the two systems together will be cost-effective and beneficial for creating a smart building structure with its own sensors (nervous system), processors (brain system), and actuators (muscular system). This paper presents a real-time integrated procedure to demonstrate how health monitoring and vibration control can be integrated in real time to accurately identify time-varying structural parameters and unknown excitations on one hand, and to optimally mitigate excessive vibration of the building structure on the other hand. The basic equations for the identification of time-varying structural parameters and unknown excitations of a semi-active damper-controlled building structure are first presented. The basic equations for semi-active vibration control of the building structure with time-varying structural parameters and unknown excitations are then put forward. The numerical algorithm is finally followed to show how the identification and the control can be performed simultaneously. The results from the numerical investigation of an example building demonstrate that the proposed method is feasible and accurate.

• Smart Structures and Systems
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• v.11 no.1
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• pp.123-134
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• 2013

Identifying structural modal parameters, especially those modes within high frequency range, from ambient data is still a challenging problem due to various kinds of uncertainty involved in vibration measurements. A procedure applying an ensemble empirical mode decomposition (EEMD) method is proposed for accurate and robust structural modal identification. In the proposed method, the EEMD process is first implemented to decompose the original ambient data to a set of intrinsic mode functions (IMFs), which are zero-mean time series with energy in narrow frequency bands. Subsequently, a Sub-PolyMAX method is performed in narrow frequency bands by using IMFs as primary data for structural modal identification. The merit of the proposed method is that it performs structural identification in narrow frequency bands (take IMFs as primary data), unlike the traditional method in the whole frequency space (take original measurements as primary data), thus it produces more accurate identification results. A numerical example and a multiple-span continuous steel bridge have been investigated to verify the effectiveness of the proposed method.