• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.311-319
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• 2006

A bed level change model(SED-FLUX) is introduced based on the realistic sediment transport process including bed load and suspended load behaviours at the bottom boundary layer. The model SED-FLUX includes wave module, hydrodynamic module and sediment transport and diffusion module that calculate suspended sediment concentration, net sediment erosion flux($Q_s$) and bed load flux. Bed load transport rate is evaluated by the van Rijn's TRANSPOR program which has been verified in wave-current fields. The net sediment erosion flux($Q_s$) at the bottom is evaluated as a source/sink term in the numerical sediment diffusion model where the suspended sediment concentration becomes a verification parameter of the $Q_s$. Bed level change module calculates a bed level change amount(${\Delta}h_{i,j}$) and updates a bed level. For the model verification the limit depth of the bed load transport is compared with the field experiment data and some formula on the threshold depth for the bed load movement by waves and currents. This model is applied to the beach profile changes by waves, then the model shows a clear erosion and accumulation profile according to the incident wave characteristics. Finally the beach evolution by waves and wave-induced currents behind the offshore breakwater is calculated, where the model shows a tombolo formation in the landward area of the breakwater.

• Journal of Wetlands Research
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• v.14 no.4
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• pp.715-723
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• 2012

The Hoelyongpo in the Naeseong River as tributary basin of the Nakdong River is broadly well-known a tourist attraction, which is made of sandy beach, and is called "Island of Inland". But Construction of the Dam was planned at upstream of river. In other words, an influx of sediment is blocked from upstream of river. In this situation, through sediment discharge coming from tributary of the Naeseong river, the whether to go ahead of sand beach of the Hoelyongpo is analyzed by using 1-D and 2-D model. The sediment discharge is estimated through ratio raw with basin area, and the instream flow requirement of river coming from dam and the flow rate and sediment coming from tributary are inputted for model. The 1-D model uses HEC-6 and the 2-D model uses SMS(RMA2 and SED2D). The analysis using the HEC-6 is performed from cross section data 10 year ago to the present cross section. Consequently, Yang equation presenting similar result to the present cross section data is determined, using this, the prediction is conducted for the cross section after 20 years. The 2-D analysis is conducted for the present cross section data. The value of distinction between a deposition and erosion with the results presented in the 1, 2-D models is occur, however, the appearance between the deposition and the erosion is similar.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.542-550
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• 2017

The estimations of flow characteristics and river-bed erosion or sedimentation are very important for hydraulic structure design, floodplain management, and especially, river management. The objective of the study is therefore to estimate the change of flow characteristics and river-bed change due to a hydraulic structure construction. With 11.65 km study area of the Geum River which are located in downstream of Daecheong Dam, flow characteristics and river-bed change were estimated based on the RMA2 and SED2D model. As the result of the study, the increase of river-bed sedimentation in upstream and river-bed erosion in downstream were occurred by the construction of hydraulic structure.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.94-104
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• 2004

The purpose of this study is to analyze various hydraulic characteristics using SMS (Surface Water Modeling System) RMA2 model. It is based on 2-D finite element method. River reaches (13.8km) from Gyeongan gauge station to the inlet of Paldang lake was selected. Finite element was made by RIMGIS Data, and the analysis of river-changes was operated by unsteady flow. The sediment concentration and bed change was simulated using SED2D model. This River's velocity was distributed that 0.05~3.85m/s and bed change was changed about 0.0003~0.0135m.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.479-487
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• 2021

In this paper, we propose an Sound Event Detection (SED) model using self-training based on a noisy student model. The proposed SED model consists of two stages. In the first stage, a mean-teacher model based on an Residual Convolutional Recurrent Neural Network (RCRNN) is constructed to provide target labels regarding weakly labeled or unlabeled data. In the second stage, a self-training-based noisy student model is constructed by applying different noise types. That is, feature noises, such as time-frequency shift, mixup, SpecAugment, and dropout-based model noise are used here. In addition, a semi-supervised loss function is applied to train the noisy student model, which acts as label noise injection. The performance of the proposed SED model is evaluated on the validation set of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge Task 4. The experiments show that the single model and ensemble model of the proposed SED based on the noisy student model improve F1-score by 4.6 % and 3.4 % compared to the top-ranked model in DCASE 2020 challenge Task 4, respectively.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Journal of The Korean Astronomical Society
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• v.52 no.5
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• pp.173-180
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• 2019

We present IR flux density measurements, models of the broadband SED, and results of SED modeling for the Pulsar Wind Nebula (PWN) 3C 58. We find that the Herschel flux density seems to be slightly lower than suggested by interpolation of previous measurements in nearby wavebands, implying that there may be multiple electron populations in 3C 58. We model the SED using a simple stationary one-zone and a more realistic time-evolving multi-zone scenario. The latter includes variations of flow properties in the PWN (injected energy, magnetic field, and bulk speed), radiative energy losses, adiabatic expansion, and diffusion, similar to previous PWN models. From the modeling, we find that a PWN age of 2900-5400 yrs is preferred and that there may be excess emission at ${\sim}10^{11}Hz$. The latter may imply multiple populations of electrons in the PWN.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1551-1555
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• 2006

효율적인 댐 운영 및 관리를 위하여 퇴사유입으로 인한 저수용량의 감소에 대한 정량적인 분석이 필수적이다. 본 연구의 대상지인 소양호는 소양강댐이 준공된 1973년을 기준으로 매 10년마다 세부측량을 통한 퇴사량 조사가 실시되고 있다. 기존의 조사에서는 장기적인 퇴사량 예측을 위해 U.S.B.R의 경험적 면적감소법과 90년대 초반부터는 1차원 모형인 HEC-6가 적용되어 왔다. 그러나 기존의 방법은 저수지 내 퇴사의 횡방향 분포는 고려할 수 없다는 단점이 있다. 이를 보완하기 위해 저수지 횡단방향으로의 퇴적과 세굴을 모의할 수 있는 2차원 이상의 모형이 적용되어야 한다. 본 연구에서는 소양호의 장래퇴사분포를 모의하였다. 현재 실무에서 주로 이용되고 있는 HEC-6 모형과 2차원 수치모형인 HSCTM2D(Hydordynamics, Sediment and Contaminant Transport Model)모형 및 SMS-SED2D 모형을 비교한 후 SMS-SED2D 모형을 소양강댐 유역에 적용하였다. 또한 모형의 매개변수 보정을 위하여 퇴사량 조사용역으로 수행된 1983년과 2005년의 실측횡단자료를 이용하였으며, 향후 소양강댐의 관리를 위한 기초자료로의 활용을 위하여 댐 축조후 50년, 100년후의 저수지내 퇴사분포를 모의하였다.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.61-70
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• 2018

This study examined how to determine the optimal sediment level in dam reservoir for efficient plan and operation of dam. Currently, Korea is applying a horizontally accumulated method for sediment level estimation for the safety design of dam and so the method estimated relatively higher level than others. However, the sediment level of dam reservoir should be accurately estimated because it is an important factor in assessing life cycle of a dam. The sediment level in dam reservoir can be determined by SED-2D model linked with RMA-2, horizontally accumulated method, area increment method, and empirical area reduction method. The estimated sediment level from each method was compared with the observed sediment level measured in 2007 in Imha dam reservoir, Korea and then the optimal method was determined. Also, the future sediment level was predicted by each method for the future trend analysis of sediment level. As the results, the most accurate sediment level was estimated by the empirical area reduction method and the future trend of sediment level variation followed the past trend. Therefore, we have found that the empirical area reduction method is a proper one for more accurate estimation of sediment level and it can be validated by the results from a numerical model of SED-2D linked with RMA-2 model.

• Journal of Korea Water Resources Association
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• v.47 no.8
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• pp.729-742
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• 2014

This study predicted long-term sediment distribution for 76 years by using RMA-2 which is two-dimensional numerical model and SED2D which is the sediment transport model to quantitatively analyze sediment distribution in the reservoir based on sediment intrusion and efficiently manage the reservoir. For water level-discharge-sediment data required in boundary conditions of the model, real-time data measured by the Korea Water Resources Corporation were used. The sediment input data was calculated using K-DRUM model. Sedimentation depth was compared with results of model by collecting cross-section core in the reservoir during the dry season. As the result of validation, the sediment depth in the reservoir was similar to actually measured value. For prediction of long-term sediment distribution, terrain data measured in 2012 was used as starting crosssection and simulations for 76 years until 2088 were made. As the results of simulations, sediment distributions of 1.63~1.26 m and 1.45~0.007 m were shown in upstream and downstream of Hapcheon Dam, respectively.