• Korean Journal of Environment and Ecology
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• v.26 no.4
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• pp.528-536
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• 2012

This study has compared the different types of forest fires(unburned, crown fire, ground fire) and the degree of vegetation recovery at Samcheuk-si, Gangwon-do by assessing the biomass and net primary production from July 2007 through July 2010. The research showed that the average biomass of unburned site(Un), crown fire site(C-1), crown fire site(C-3), ground fire site(G-2) were $181.20{\pm}5.39$, $62.04{\pm}4.38$, $131.09{\pm}14.38$, $63.39{\pm}2.72ton{\cdot}ha^{-1}$, respectively. And the research showed that the average net primary production of unburned site(Un), crown fire site(C-1), crown fire site(C-3), ground fire site(G-2) were $4.17{\pm}0.56$, $3.27{\pm}1.56$, $11.51{\pm}0.53$, $2.10{\pm}0.31ton{\cdot}ha^{-1}{\cdot}yr^{-1}$, respectively. Quercus mongolica $DH_{10}$(Diameter at the 10cm tree height) growth rate at each plot was compared to the crown fire site(C-1) in the annual average $1.21{\pm}0.55mm{\cdot}yr^{-1}$ at the speed of the fastest growth follows; showed crown fire site(C-3), ground fire site(G-2), unburned site(Un) appeared in the order. And that showed the growth rate of height was highest in the $15.43{\pm}4.57cm{\cdot}yr^{-1}$ at crown fire site(C-3), then the crown fire site(C-1), and ground fire site(G-2), and lowest in the unburned site(Un).

• Horticultural Science & Technology
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• v.35 no.4
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• pp.418-430
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• 2017

The objective of this study was to understand the combined effect of shading treatment and harvest time on pungency, ascorbic acid content, market-quality pepper yield, and photosynthetic activity in a yellow 'Star Flame' and 'Fire Flame' F1 hybrid pepper cultivar (Capsicum annuum). Plants were cultivated in a greenhouse under white, red, and green shading nets and compared to those grown under unshaded control conditions. The ascorbic acid and pungency parameters were analyzed by high-performance liquid chromatographic methods. Ascorbic acid, a compound of high nutritive value in pepper, was highest in fruits gathered during the first summer harvest in both hybrids. The ascorbic acid content was found to be further increased in fruits from plants grown under white net shading in both 'Star Flame' and 'Fire Flame'. Total capsaicinoid contents in 'Star Flame' were influenced by the interaction of shading treatment and harvest time (p = 0.004), with the lowest amounts ($241.2-251.5mg{\cdot}kg^{-1}$ fresh weight) resulting from white and red shading treatments at the early autumn harvest. In 'Fire Flame', both shading treatment (p = 0.009) and harvest time (p < 0.001) affected total capsaicinoid contents. We observed significantly higher total capsaicinoid contents in control fruits compared to that resulting from red and green shading treatments at the second harvest, and that resulting from red shading treatment at the third harvest. Analysis of photosynthetic activity revealed a significant and negative correlation between Fv/Fm values and total capsaicinoid contents in both hybrids (p < 0.001). Based on the obtained results, the harvest of peppers during summer should be promoted to produce fruits with high pungency.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1765-1775
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• 2019

Multiple spurious operations (MSOs) mean multiple fire induced circuit faults causing an undesired operation of one or more systems or components. The Nuclear Energy Institute (NEI) of the United States published NEI 00-01 as guidelines for solving MSOs. And this guideline includes MSO scenarios of pressurized water reactor (PWR) and boiling water reactor (BWR). Nuclear power plant operators in U.S. analyzed MSOs under MSO scenarios included in NEI 00-01 and operators of PWRs in Korea also analyzed MSOs under the scenarios of NEI 00-01. As there are no pressurized heavy water reactors (PHWRs) in the United States, MSO scenarios of PHWRs are not included in the NEI 00-01 and any feasible scenarios have not been developed. This paper developed MSO scenarios which can be applied to PHWRs by reviewing the 63 MSO scenarios included in NEI 00-01. This study found that seven scenarios out of the 63 MSO scenarios can be applied and three more scenarios need to be developed.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.671-680
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• 2006

As a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the initial marking in a timed net, the minimum cycle time method has been widely used in computer system analysis. A timed net is a modified version of a Petri net where a transition is associated with a delay time. A delay time used in a timed net is a constant even though the duration time associated with an event in the world is a stochastic number in general. In the consequence, the result of minimum cycle time analysis is not realistic. Therefore, we propose ‘Stochastic Timed Net' where a transition can be associated with a stochastic number and introduce a minimum cycle time analysis method for ‘Stochastic Timed Net’ As an example of the application of ‘Stochastic Timed Net’, we introduce a ‘Stochastic Timed Net' model of a Location Based Service Providing Multimedia System and the result of minimum cycle time analysis of it. Whereas the typical form of the result of the existing minimum cycle time analysis is 'It takes at least 10 time units', the typical form of the result of minimum cycle time analysis of a ‘Stochastic Timed Net' is in the probability form such as "The probability of the events in which it finishes its job within 10 time units is 85%."

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.12
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• pp.1596-1603
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• 2018

Rapidly detecting and warning of fires is necessary for minimizing human injury and property damage. Generally, when fires occur, both the smoke and the flames are generated, so fire detection systems need to detect both the smoke and the flames. However, most fire detection systems only detect flames or smoke and have the disadvantage of slower processing speed due to additional preprocessing task. In this paper, we implemented a fire detection system which predicts the flames and the smoke at the same time by constructing a CNN model that supports multi-labeled classification. Also, the system can monitor the fire status in real time by using Grad-CAM which visualizes the position of classes based on the characteristics of CNN. Also, we tested our proposed system with 13 fire videos and got an average accuracy of 98.73% and 95.77% respectively for the flames and the smoke.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4195-4208
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• 2022

In this study, operator habitability was numerically evaluated in the event of a fire at the main control bench board (MCB) in a reference main control room (MCR). It was investigated if evacuation variables including hot gas layer temperature (HGLT), heat flux (HF), and optical density (OD) at 1.8 m from the MCR floor exceed the reference evacuation criteria provided in NUREG/CR-6850. For a fire model validation, the simulation results of the reference MCR were compared with existing experimental results on the same reference MCR. In the simulation, various input parameters were applied to the MCB panel fire scenario: MCR height, peak heat release rate (HRR) of a panel, number of panels where fire propagation occurs, fire propagation time, door open/close conditions, and mechanical ventilation operation. A specialized-average HRR (SAHRR) concept was newly devised to comprehensively investigate how the various input parameters affect the operator's habitability. Peak values of the evacuation variables normalized by evacuation criteria of NUREG/CR-6850 were well-correlated as the power function of the SAHRR for the various input parameters. In addition, the evacuation time map was newly utilized to investigate how the evacuation time for different SAHRR was affected by changing the various input parameters. In the previous studies, it was found that the OD is the most dominant variable to determine the MCR evacuation time. In this study, however, the evacuation time map showed that the HF is the most dominant factor at the condition of without-mechanical ventilation for the MCR with a partially-open false ceiling, but the OD is the most dominant factor for all the other conditions. Therefore, the method using the SAHRR and the evacuation time map was very useful to effectively and comprehensively evaluate the operator habitability for the various input parameters in the event of MCB fires for the reference MCR.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1503-1514
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• 2006

Today, consumers can access Internet from everywhere, therefore most commercial and other organizations provide their services on the Web. As the result, countless Web service systems are already on the Internet and more systems are under construction. Therefore, many researches of verifying that the system to be constructed will not have any deadlock and will run successfully without any problem at the early stage of design have been performed. Several Petri net based verification methods have also been published. However, they have focused on building Petri net models of Web service systems and none of them introduces efficient analysis methods. As a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the initial marking in a timed net, the minimum cycle time method has been widely used in computer system analysis. A timed net is a modified version of a Petri net where a transition is associated with a delay time. A delay time used in a timed net is a constant even though the duration time associated with an event in the real world is a stochastic number in general. Therefore, this paper proposes 'Mixedly Distributed Stochastic Timed Net' where a transition can be associated with a stochastic number and introduce a minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net'. We also introduce a method of analysing a Web service system's response time with the minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net.'.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.301-309
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• 2021

In this study, we tried to improve the performance of the existing U-net-based deep learning rainfall prediction model, which can weaken the meaning of time series order. For this, ConvLSTM2D U-Net structure model considering temporal consistency of data was applied, and we evaluated accuracy of the ConvLSTM2D U-Net model using a RainNet model and an extrapolation-based advection model. In addition, we tried to improve the uncertainty in the model training process by performing learning not only with a single model but also with 10 ensemble models. The trained neural network rainfall prediction model was optimized to generate 10-minute advance prediction data using four consecutive data of the past 30 minutes from the present. The results of deep learning rainfall prediction models are difficult to identify schematically distinct differences, but with ConvLSTM2D U-Net, the magnitude of the prediction error is the smallest and the location of rainfall is relatively accurate. In particular, the ensemble ConvLSTM2D U-Net showed high CSI, low MAE, and a narrow error range, and predicted rainfall more accurately and stable prediction performance than other models. However, the prediction performance for a specific point was very low compared to the prediction performance for the entire area, and the deep learning rainfall prediction model also had limitations. Through this study, it was confirmed that the ConvLSTM2D U-Net neural network structure to account for the change of time could increase the prediction accuracy, but there is still a limitation of the convolution deep neural network model due to spatial smoothing in the strong rainfall region or detailed rainfall prediction.

• Advances in concrete construction
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• v.6 no.2
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• pp.177-197
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• 2018

This paper presents a case study about the damages on the structural elements of a cast in place reinforced concrete (RC) building after a big fire which was able to be controlled after six hours. The fire broke off at the $2^{nd}$ basement floor of the building, which has five basements, one ground, and two normal floors. As a result of intensely stocked ignitable materials, it spread out to the all of the upstairs. In visual inspection, most of the typical fire damages were observed (such as spalling, net-like cracks, crumbled plasters, bared or visible reinforcement). Also, failures of the $2^{nd}$ basement columns were encountered. It has been concluded that the severity failures of the columns at the $2^{nd}$ basement caused utterly deformation of the building, which is responsible for the massive damages on the beam-column connections. All of the observed damages were categorized related to the types and presented separated regarding the floors. Besides to the visual inspection, the numerical analysis was run to verify the observed damaged on the building for columns, beams, and the connection regions. It is concluded from the study that several parameters such as duration of the fire, level of the temperature influence on the damages to the RC building. Also, it is highlighted by the study that if the damaged building is considered on the overall structural system, it is not able to satisfy the minimum service requirements neither gravity loads nor earthquake conditions.