• Journal of Wetlands Research
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• v.23 no.4
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• pp.287-295
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• 2021

As facilities such as dam reservoir wetlands and agricultural irrigation reservoir wetlands are built, sedimentation occurs over time through erosion, sedimentation transport, and sediment deposition. Sedimentation issues are very important for the maintenance of reservoir wetlands because long-term sedimentation of sediments affects flood and drought control functions. However, research on resignation has been estimated mainly by empirical formulas due to the lack of available data. The purpose of this study was to calculate and compare the sediment deposition rate by developing a multiple regression model along with actual data and empirical formulas. In addition, it was attempted to identify potential causes of collapse by applying it to 64 reservoir wetlands that suffered flood damage due to the long rainy season in 2020 due to reservoir wetland sedimentation and aging. For the target reservoir, 10 locations including the GaGog reservoir located in Miryang city, Gyeongsangnam province in South Korea, where there is actual survey information, were selected. A multiple regression model was developed in consideration of physical and climatic characteristics, and a total of four empirical formulas and sediment deposition rate were calculated. Using this, the error of the sediment deposition rate was compared. As a result of calculating the sediment deposition rate using the multiple regression model, the error was the lowest from 0.21(m³km²/yr) to 2.13(m³km²/yr). Therefore, based on the sediment deposition rate estimated by the multi-regression model, the change in the available capacity of reservoir wetlands was analyzed, and the effective storage capacity was found to have decreased from 0.21(%) to 16.56(%). In addition, the sediment deposition rate of the reservoir where the overflow damage occurred was relatively higher than that of the reservoir where the piping damage occurred. In other words, accumulating sediment deposition rate at the bottom of the reservoir would result in a lack of acceptable effective water capacity and reduced reservoir flood and drought control capabilities, resulting in reservoir collapse damage.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.6
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• pp.804-811
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• 2018

Objective: Complete mtDNA D-loop sequences of four Thai indigenous chicken varieties, including Pra-dhu-hang-dam (PD), Leung-hang-khao (LK), Chee (CH), and Dang (DA) were explored for genetic diversity and relationships with their potential ancestor and possible associates to address chicken domestication in Thailand. Methods: A total of 220 complete mtDNA D-loop sequences of the four Thai indigenous chicken varieties were obtained by Sanger direct sequencing of polymerase chain reaction amplicons of 1,231 to 1,232 base pair in size. A neighbor-joining dendrogram was constructed with reference complete mtDNA D-loop sequences of Red Junglefowl (RJF) and those different chicken breeds available on National Center for Biotechnology Information database. Genetic diversity indices and neutrality test by Tajima's D test were performed. Genetic differences both within and among populations were estimated using analysis of molecular variance (AMOVA). Pairwise fixation index ($F_{ST}$) was conducted to evaluated genetic relationships between these varieties. Results: Twenty-three identified haplotypes were classified in six haplogroups (A-E and H) with the majority clustered in haplogroup A and B. Each variety was in multiple haplogroups with haplogroups A, B, D, and E being shared by all studied varieties. The averaged haplotype and nucleotide diversities were, respectively 0.8607 and 0.00579 with non-significant Tajima's D values being observed in all populations. Haplogroup distribution was closely related to that of RJF particularly Gallus gallus gallus (G. g. gallus) and G. g. spadiceus. As denoted by AMOVA, the mean diversity was mostly due to within-population variation (90.53%) while between-population variation (9.47%) accounted for much less. By pairwise $F_{ST}$, LK was most closely related to DA ($F_{ST}=0.00879$) while DA was farthest from CH ($F_{ST}=0.24882$). Conclusion: All 4 Thai indigenous chickens are in close relationship with their potential ancestor, the RJF. A contribution of shared, multiple maternal lineages was in the nature of these varieties, which have been domesticated under neutral selection.

• Journal of Korea Game Society
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• v.11 no.4
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• pp.143-149
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• 2011

This paper presents a novel camera tracking method based on model with multiple planes. The proposed algorithm detects QR code that is one of the most popular types of two-dimensional barcodes. A 3D model is imported from the detected QR code for augmented reality application. Based on the geometric property of the model, the vertices are detected and tracked using optical flow. A clipping algorithm is applied to identify each plane from model surfaces. The proposed method estimates the homography from coplanar feature correspondences, which is used to obtain the initial camera motion parameters. After deriving a linear equation from many feature points on the model and their 3D information, we employ DLT(Direct Linear Transform) to compute camera information. In the final step, the error of camera poses in every frame are minimized with local Bundle Adjustment algorithm in real-time.

• Computers and Concrete
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• v.20 no.3
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• pp.275-282
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• 2017

Grouting is an operation often carried out to consolidate and seal the rock mass in dam sites and tunnels. One of the important parameters in this operation is grouting pressure. In this paper, analytical models used to estimate pressure are investigated. To validate these models, grouting data obtained from Seymareh and Aghbolagh dams were used. Calculations showed that P-3 model from Groundy and P-25 model obtained from the results of grouting in Iran yield the most accurate predictions of the pressure and measurement errors compared to the real values in P-25 model in this dams are 12 and 14.33 Percent and in p-3 model are 12.25 and 16.66 respectively. Also, SPSS software was applied to define the optimum relation for pressure estimation. The results showed a high correlation between the pressure with the depth of the section, the amount of water take, rock quality degree and grout volume, so that the square of the multiple correlation coefficient among the parameters in this dams were 0.932 and 0.864, respectively. This indicates that regression results can be used to predict the amount of pressure. Eventually, the relationship between the parameters was obtained with the correlation coefficient equal to 0.916 based on the data from both dams generally and shows that there is a desirable correlation between the parameters. The outputs of the program led to the multiple linear regression equation of P=0.403 Depth+0.013 RQD+0.011 LU-0.109 V+0.31 that can be used in estimating the pressure.

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.365-377
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• 2008

Large artificial dam reservoirs and associated downstream ecosystems are under increased pressure from long-term negative impacts of turbid flood runoff. Despite various emerging issues of reservoir turbidity flow, turbidity modeling studies have been rare due to lack of experimental data that can support scientific interpretation. Modeling suspended sediment (SS) dynamics, and therefore turbidity ($C_T$), requires provision of constitutive relationships ($SS-C_T$) and accounting for deposition of different SS size fractions/types distribution in order to display this complicated dynamic behavior. This study explored the performance of a coupled two-dimensional (2D) hydrodynamic and particle dynamics model that simulates the fate and transport of a turbid density flow in a negatively buoyant density flow regime. Multiple groups of suspended sediment (SS), classified by the particle size and their site-specific $SS-C_T$ relationships, were used for the conversion between field measurements ($C_T$) and model state variables (SS). The 2D model showed, in overall, good performance in reproducing the reservoir thermal structure, flood propagation dynamics and the magnitude and distribution of turbidity in the stratified reservoir. Some significant errors were noticed in the transitional zone due to the inherent lateral averaging assumption of the 2D hydrodynamic model, and in the lacustrine zone possibly due to long-term decay of particulate organic matters induced during flood runoffs.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.5-11
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• 1997

In this paper, we investigate the performance of the direct sequence/spread spectrum multiple access (DS/SSMA) system using the Trellis coded modulation (TCM) technique in both multipath fading and multi-user channel environments. For this, an expression that represents the pairwise bit error probability of the system is derived. Unlike the existing results that were performed in a more restrictive condition considering only the multi-user effect, the effects of the multipath fading as well as the multi-user environments are compositely taken into account. In order to check the validity of our analysis, although not direct, computer simulations are carried out, and they show that our expression matches exactly with the previous work for which the TCM and the multipath effects were disregarded. Moreover, it is observed that the performance of the Trellis coded DS/SSMA system can be improved dramatically comparing to the uncoded QPSK system in the multipath fading and multi-user channel environments.

• Water for future
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• v.25 no.3
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• pp.115-124
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• 1992

The peak flood discharge at a downstream station and the flood travel time between a pair of dams due to a specific flood release from the upper reservoir are computed using a hydraulic river channel routing method. The study covered the whole reservoir system in the Han River. The computed peak flood discharges and the travel times between dams were correlated with the duration and the magnitude of flood release rate at the upstream reservoir, and hence a multiple regression model is proposed for each river reach between a pair of dams. The peak flood discharge at a downstream location can be converted to the peak flood stage by rating curve. Hence, the proposed regression model could be used to forecast the peak flood stage at a downstream location and the flood travel time between dams using the information on the flood release rate and duration from the upper dam.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.787-793
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• 2017

This paper proposes the IoT based monitoring system to reservoir and erosion control dam that measure amount of contained water and amount of sediment by real time through unit volume block object modeling and support the related image. The proposed system is more effective in establishing a more accurate dredging plan and effectively managing efficient water management plans, and effectively preventing accidents such as landslides, etc.

• Magazine of the Korean Society of Agricultural Engineers
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• v.38 no.3
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• pp.127-136
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• 1996

The purpose of this study is to provide with information for the water resources development and management in stream management planning, such as information on the sediment trensport, design of dam and water facilities, river improvement and flood plains management. The major results obtained from the field measurement and analysis of the watershed characteristics, hydraulic and sediment characteristics are as follows ; 1. The rating curve formulas obtained from the analysis of the hydraulic characteristics data collected are ; Q-=110.563 $(H-0.474)^2$ for 0.7m$(H-0.146)^2$ for 0.4m$Sr=aX{^2} {_1} X^{c}{_2}$, in the experimental watershed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.3
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• pp.166-171
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• 2009

In recent years, video detection systems have been implemented in various infrastructures such as airport, public transportation, power generation system, water dam and so on. Recognizing moving objects in video sequence is an important problem in computer vision, with applications in several fields, such as video surveillance and target tracking. Segmentation and tracking of multiple vehicles in crowded situations is made difficult by inter-object occlusion. In the system described in this paper, the mean shift algorithm is firstly used to filter and segment a color vehicle image in order to get candidate regions. These candidate regions are then analyzed and classified in order to decide whether a candidate region contains a license plate or not. And then some characters in the license plate is recognized by using the fuzzy ARTMAP neural network, which is a relatively new architecture of the neural network family and has the capability to learn incrementally unlike the conventional BP network. We finally design a license plate recognition system using the mean shift algorithm and fuzzy ARTMAP neural network and show its performance via some computer simulations.