• Journal of Wetlands Research
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• v.8 no.2
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• pp.53-64
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• 2006

A study on the restoration process of a stream ecosystem and the water quality renovation technique by removing algae, vegetation and fish monitoring as evaluating the removal of the algae by dietetic characteristics of fishes were performed on Sangdong stream in the B city after stream restoration it to the artificial stream as the cases, restoring urban stream into close-to-nature stream are being increased domestically with the aim of ecological city. As a result, restoration and rehabilitation of the fundamental stream ecosystem was well maintained 4 years later the reclamation at the moment and total 93 diagnosis which were all vascular plant phylum including 44 families, 73 genuses, 79 species and 14 varieties in flora and vegetation community were observed. 3 families, 8 species and 354 populations in total among Fishes were found and Pseudorasbora Parva, Cyprinus Carpic and Carassius Auratus strongly resistant to water pollution were dominantly appeared in order of 50.5% of Pseudorasbora Parva 21.2% of Cyprinus Carpic, 20.9% of Carassius Auratus, 7.1% of Macropodus chinensis and 0.3% of Misqurnus anguillicaudatus according to relative richness index. It turned out to be that Cyprinus Carpic ingests algae over 90% and Carassius Auratus takes it over 30% according to the analysis about the alimentary object of the fishes as a consequences of algae's excrescent from characteristics of the tested experimental stream. It is reported that a Cyprinus Carpic, about 34 cm in length, ingested wet-weight 43.2g algae on the rough analysis toward the sample which makes us recognize how effective a macro community Cyprinus Carpic is for removing algae.As a consequence of this research, the effect of stream ecosystem characteristics and water quality purification could not be expected by aquatic plants and trees which were eliminated at experimental stream. From now on, a close-to-nature stream should be formed of ecological hydraulic and hydrologic engineered modeling from the beginning so that it can perform the water quality purifying function. It is determined that the structure of food chain will be abundantly influenced by the induction of oversized macro community like Cyprinus Carpic because a biomass of a consumer of higher order is increased. It is estimated that the removal algae by fishes is not effective despite in some cases of dietetic characteristics so much more studies should be executed in the future.

• Maritime Security
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• v.1 no.1
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• pp.273-310
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• 2020

This study aims at empirically analyzing the overall mechanism of the "Gray Zone Strategy", which has begun to be used as one of Chinese major maritime security strategies in maritime conflicts surrounding the South China Sea and East China Sea since early 2010, and comparing the resulting conflict patterns in those reg ions. To this end, I made the following two hypotheses about Chinese gray zone strategy. The hypotheses that I have argued in this study are the first, "The marine gray zone strategy used by China shows different structures of implementation in the South China Sea and the East China Sea, which are major conflict areas.", the second, "Therefore, the patterns of disputes in the South China Sea and the East China Sea also show a difference." In order to examine this, I will classify Chinese gray zone strategy mechanisms multi-dimensionally in large order, 1) conflict trends and frequency of strategy execution, 2) types and strengths of strategy, 3) actors of strategy execution, and 4) response methods of counterparts. So, I tried to collect data related to this based on quantitative modeling to test these. After that, about 10 years of data pertaining to this topic were processed, and a research model was designed with a new categorization and operational definition of gray zone strategies. Based on this, I was able to successfully test all the hypotheses by successfully comparing the comprehensive mechanisms of the gray zone strategy used by China and the conflict patterns between the South China Sea and the East China Sea. In the conclusion, the verified results were rementioned with emphasizing the need to overcome the security vulnerabilities in East Asia that could be caused by China's marine gray zone strategy. This study, which has never been attempted so far, is of great significance in that it clarified the intrinsic structure in which China's gray zone strategy was implemented using empirical case studies, and the correlation between this and maritime conflict patterns was investigated.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.289-308
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• 2021

This study conducts coupled thermo-hydro-mechanical numerical modeling to investigate the maximum temperature and conditions for securing mechanical stability of the high-level radioactive waste repository when temperature criteria of bentonite buffer are 100℃ and 125℃, respectively. In case of temperature criterion of buffer as 100℃, the maximum temperatures at the interface between canister and buffer are calculated to be 99.4℃ and 99.8℃, respectively for a case with disposal tunnel spacing of 40 m and deposition hole spacing of 5.5 m and for the other case with disposal tunnel spacing of 30 m and deposition hole spacing of 6.5 m. In case of temperature criterion of buffer as 125℃, spacings of disposal tunnel and deposition hole could be decreased to 30 m and 4.5 m, respectively, which reduces the disposal area up to 55% compared to the disposal area of KRS⁺. According to analysis of mechanical stability for various disposal spacings, RMR of rock mass for KRS⁺ should be larger than 72.4 which belongs to good rock in RMR classification to prevent failure of rock mass. As disposal spacing is decreased, required RMR of rock mass is increased. In order to prevent failure of rock mass for a case with disposal tunnel spacing of 30 m and deposition hole spacing of 4.5 m, RMR larger than 87.3 is needed. However, mechanical stability of the repository is secured for all cases with RMR over 75 considering the enhancement of rock strength due to confining stress induced by swelling of the bentonite buffer and backfill.

• The Korean Journal of Nuclear Medicine
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• v.37 no.5
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• pp.288-300
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• 2003

Purpose: To obtain regional blood flow and tissue-blood partition coefficient with time-activity curves from ${H_2}^{15}O$ PET, fitting of some parameters in the Kety model is conventionally accomplished by nonlinear least squares (NLS) analysis. However, NLS requires considerable compuation time then is impractical for pixel-by-pixel analysis to generate parametric images of these parameters. In this study, we investigated several fast parameter estimation methods for the parametric image generation and compared their statistical reliability and computational efficiency. Materials and Methods: These methods included linear least squres (LLS), linear weighted least squares (LWLS), linear generalized least squares (GLS), linear generalized weighted least squares (GWLS), weighted Integration (WI), and model-based clustering method (CAKS). ${H_2}^{15}O$ dynamic brain PET with Poisson noise component was simulated using numerical Zubal brain phantom. Error and bias in the estimation of rCBF and partition coefficient, and computation time in various noise environments was estimated and compared. In audition, parametric images from ${H_2}^{15}O$ dynamic brain PET data peformed on 16 healthy volunteers under various physiological conditions was compared to examine the utility of these methods for real human data. Results: These fast algorithms produced parametric images with similar image qualify and statistical reliability. When CAKS and LLS methods were used combinedly, computation time was significantly reduced and less than 30 seconds for $128{\times}128{\times}46$ images on Pentium III processor. Conclusion: Parametric images of rCBF and partition coefficient with good statistical properties can be generated with short computation time which is acceptable in clinical situation.

• Journal of Animal Science and Technology
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• v.55 no.3
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• pp.185-194
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• 2013

Microsatellite markers have been a useful genetic tool in determining diversity, relationships and individual discrimination studies of livestock. The level of genetic diversity, relationships among two Korean indigenous chicken brand populations (Woorimatdag: WR, Hanhyup3: HH) as well as two pure populations (White Leghorn: WL, Rhode Island Red: RIR) were analyzed, based on 26 MS markers. A total of 191 distinct alleles were observed across the four chicken populations, and 47 (24.6%) of these alleles were unique to only one population. The mean $H_{Exp}$ and PIC were estimated as 0.667 and 0.630. Nei's $D_A$ genetic distance and factorial correspondence analysis (FCA) showed that the four populations represented four distinct groups. However, the genetic distance between each Korean indigenous chicken brand (WR, HH) and the pure population (WL, RIR) were threefold that among the WR and HH. For the STRUCTURE analyses, the most appropriate number of clusters for modeling the data was determined to be three. The expected probabilities of identity among genotypes of random individuals (PI) were calculated as $1.17{\times}10^{-49}$ (All 26 markers) and $1.14{\times}10^{-15}$, $7.33{\times}10^{-20}$ (9, 12 with the highest PI value, respectively). The results indicated that the brand chicken breed traceability system employing the own highest PI value 9 to 12 markers, and might be applicable to individual identification of Korean indigenous chicken brand.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.6
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• pp.643-651
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• 2001

Paddlewheel-driven circulation in a culture pond has been simulated based on the depth integrated 2 dimensional hydrodynamic model. Acceleration by paddlewheel is expressed as shaft force divided by water mass discharged by paddlewheel blades. The model has been calibrated and applied to culture ponds as following steps:- i) The model predicted velocities at every 10 m along longitudinal direction from the paddlewheel. The model was calibrated comparing the results with the measured values at mass correction factor $\alpha$ and dimensionless eddy viscosity constant $\gamma$, respectively, in a range $15\~20$ and 6. ii) Wind shear stress was simulated under conditions of direction $0^{\circ}C,\;90^{\circ}C\;and\;180^{\circ}C$ and speed 0.0, 2.5, 5.0 and 7.5 m/s. Change rate of current speed was <$1\%$ at wind in parallel or opposite direction to the paddlewheel-driven jet flow, while $4\%$ at orthogonal angle. iii) The model was then applied to 2 culture ponds located at the Western coast of Korea. The measured and predicted currents for the ponds were compared using the regression analysis. Analysis of flow direction and speed showed correlation coefficients 0.8928 and 0.6782 in pond A, 0.8539 and 0.7071 in pond B, respectively. Hence, the model is concluded to accurately predict circulation driven by paddlewheel such that it can be a useful tool to provide pond management strategy relating to paddlewheel operation and water quality.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.3
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• pp.75-82
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• 2010

This study formed an estimation of the visual characteristics of urban bridges in Yanghwaro in the Gyeongui Railroad Area using a landscape simulation. Existing theses have formerly only suggested directions for design based on visual preference, but there is as yet no research on the practical process of landscape design. As a result, it is difficult to directly apply this to bridge design. This study found a potential bridge site and presented a direction for bridge design in order to improve the image of the surrounding urban landscape by surveying the visual effects and landscape preferences of different bridge types. An urban landscape was produced using a landscape simulation model and was made the background for the survey. Five bridge types--Girder, Arch, Truss, Cable and Suspension--were selected and presented. The shapes of the bridges were selected based on the floor plan. The results of this study are as follows. In a preference analysis, every bridge except Girder was evaluated as a positive influence. When rating the image, 'artificial' was rated significantly higher than other traits when assessing the background image. When the Girder Bridge was introduced, 'stable' and 'orderly' were both rated highly while 'stable', 'beautiful', 'orderly' and 'interesting' were high with the introduction of the Arch Bridge. 'Beautiful', 'stable', and 'orderly' were given a high value in the introduction of the Truss Bridge and every image except 'natural', 'harmony' and 'orderly' were highly rated in the introduction of the Cable Bridge. Further, every image but 'natural' was highly rated with the introduction of the Suspension Bridge. Based on the analysis of the landscape, there is a difference in preference before and after modeling a bridge type, while the bridge itself is an influence when it is the main object of the simulated scene. This study researched only the shape of the bridge as a part of the landscape but other elements such as stability, economics, and construction are also factors in the design of a bridge. Stability, economics, construction and other factors must be considered when selecting a bridge type in the future.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.2
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• pp.183-202
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• 2019

For design and performance assessment of a high-level radioactive waste (HLW) disposal system, it is necessary to understand the characteristics of coupled thermo-hydro-mechanical (THM) behavior. However, in previous studies for the Korean Reference HLW Disposal System (KRS), thermal analysis was performed to determine the spacing of disposal tunnels and interval of disposition holes without consideration of the coupled THM behavior. Therefore, in this study, TOUGH2-MP/FLAC3D is used to conduct THM modeling for performance assessment of the Korean Reference HLW Disposal System (KRS). The peak temperature remains below the temperature limit of $100^{\circ}C$ for the whole period. A rapid rise of temperature caused by decay heat occurs in the early years, and then temperature begins to decrease as decay heat from the waste decreases. The peak temperature at the bentonite buffer is around $96.2^{\circ}C$ after about 3 years, and peak temperature at the rockmass is $68.2^{\circ}C$ after about 17 years. Saturation of the bentonite block near the canister decreases in the early stage, because water evaporation occurs owing to temperature increase. Then, saturation of the bentonite buffer and backfill increases because of water intake from the rockmass, and bentonite buffer and backfill are fully saturated after about 266 years. The stress is calculated to investigate the effect of thermal stress and swelling pressure on the mechanical behavior of the rockmass. The calculated stress is compared to a spalling criterion and the Mohr-Coulumb criterion for investigation of potential failure. The stress at the rockmass remains below the spalling strength and Mohr-Coulumb criterion for the whole period. The methodology of using the TOUGH2-MP/FLAC3D simulator can be applied to predict the long-term behavior of the KRS under various conditions; these methods will be useful for the design and performance assessment of alternative concepts such as multi-layer and multi-canister concepts for geological spent fuel repositories.

• The Journal of Engineering Geology
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• v.16 no.1 s.47
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• pp.69-83
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• 2006

This study aims to evaluate a complex groundwater flow system around the underground oil storage caverns using the concept of hydraulic compartment. For the hydrogeological analysis, the hydraulic testing data, the evolution of groundwater levels in 28 surface monitoring boreholes and pressure variation of 95 horizontal and 63 vertical water curtain holes in the caverns were utilized. At the cavern level, the Hydraulic Conductor Domains(fracture zones) are characterized one local major fracture zone(NE-1)and two local fracture zones between the FZ-1 and FZ-2 fracture zones. The Hydraulic Rock Domain(rock mass) is divided into four compartments by the above local fracture zones. Two Hydraulic Rock Domains(A, B) around the FZ-2 zone have a relatively high initial groundwater pressures up to $15kg/cm^2$ and the differences between the upper and lower groundwater levels, measured from the monitoring holes equipped with double completion, are in the range of 10 and 40 m throughout the construction stage, indicating relatively good hydraulic connection between the near surface and bedrock groundwater systems. On the other hand, two Hydraulic Rock Domains(C, D) adjacent to the FZ-1, the groundwater levels in the upper and lower zones are shown a great difference in the maximum of 120 m and the high water levels in the upper groundwater system were not varied during the construction stage. This might be resulted from the very low hydraulic conductivity$(7.2X10^{-10}m/sec)$ in the zone, six times lower than that of Domain C, D. Groundwater recharge rates obtained from the numerical modeling are 2% of the annual mean precipitation(1,356mm/year) for 20 years.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.