• Geotechnical Engineering
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• v.14 no.3
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• pp.25-46
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• 1998

This paper shows that there are the results of a series of model tests on the behavior of single pipe pile which is subjected to lateral load in, Nak-dong River sand. The purpose of the present paper is to estimate the effect of Non-homogeneity. constraint condition of pile head, lateral load velocity, relative density, and embedded length of pile on the behavior of single pile. These effects can be quantified only by the results of model tests. Also, these are compared with the results of the numerical methods (p-y method, modified Vlasov method; new ${\gamma}$ parameter, Characteristic Load Method'CLM). In this study, a new ${\gamma}$ parameter equation based on the Vlasov method was developed to calculate the modulus of subgrade reaction (E. : nhz.) proportional to the depth. The p-y method of analysis is characterized by nonlinear behavior. and is an effective method of designing deep foundations subjected to lateral loads. The new method, which is called the characteristic load method (CLM). is simpler than p-y analysis. but its results closely approximates p-y analysis results. The method uses dimensional analysis to characterize the nonlinear behavior of laterally loaded piles with respect to be relationships among dimensionless variables. The modulus of subgrade reaction used in p-y analysis and modified Vlasov method obtained from back analysis using direct shear test (DST) results. The coefficients obtained from DST and the modified ones used for the prediction of lateral behavior of ultimate soil reaction range from 0.014 to 0.05. and from 0.2 to 0.4 respectively. It is shown that the predicted numerical results by the new method (CLM), p-y analysis, and modified Vlasov method (new parameter) agree well with measured results as the relative density increases. Also, the characteristic load method established applicability on the Q-Mnu. relationship below y/D=0.2.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.2 no.1
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• pp.47-62
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• 1969

A goby, Synechogobius hasta (Temminck et Schlegel) was studied to investigate the food consumed and the biological change of the food organisms, and the fish were sampled from the closed tributary and the lower Part of the Naktong River, near Pusan, during the period from November of 1967 to December of 1968. The fish were sampled from four stations (Fig. 1), the total number of fish being 1,295 and they were grouped and analysed monthly. The content of the alimentary canal was analysed in three categories according to modified Nilsson's method (Dahl 1962) with a slight alteration: 1) The number of each item of stomach contents was counted and the percentage of each item in proportion to the total number of food organisms is indicated by the letter 'N' representing numerical percentage in Table 2. 2) The percentage of fish which contained any items of food organisms in proportion to the total number of fish caught in a given season is indicated by the letter 'O' representing frequency of occurrence. 3) Dominant groups of food items were selected and the percentage of the number of each dominant item in proportion to the number of the food organisms belonging to the dominant groups is indicated by the letter 'D' representing dominance. All food organisms were classified in 50 food item categories and then they were grouped in 13 main groups (Fig. 2-1), and they were further divided into 1) obligatory bottom animals, 2) organic drifts and 3) actively swimming forms; according to the conditions of the animal communities within the habitat. Since the majority of its food was composed of the obligatory bottom animals ($94.6\%$), the fish appeard to be a typical bottom feeder. And the dominant food organisms of the fish is generally determined by the local composition of the benthic fauna within the fish habitat. And their seasonal rhythm occurs among the food organisms in the stomach by the biological interaction. Locality variation in the population of the same food organism occurs due to the difference of food organisms in the habitat of the fish at Seonam and Garak, and at Seongsan and Hadan the condition of the niche for the fish in the both regions seems to be the same since the composition and the seasonal variation of the organisms were the same. The results may be summarized as follows: 1) The goby mainly feed on the animals of bottom fauna, and the food organisms are deter-mined by the food compositions within the habitat. 2) Seasonal variation of the stomach content shows the seasonal rhythm due to the biological variation of the population and their interaction. 3) The goby shows no preference on specific food, and the food is composed of a variety of animals. 4) Major food items of the goby are Polychaeta, Palaemon modestus, Isopoda, Gammaridea, Insecta (nymphs and larvae), Ilyoplax deschampsi, and Paratye compressa. 5) Logitudinal succession oil the population of the food organisms is apparently recognized within the community of Seongsan, Garak and Seonam. 6) The goby begins to descend toward the estuary and sea around April when the water temperature reaches $20^{\circ}C$, and they begin to return to river waters in September.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.613-623
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• 2011

This study assessed the feasibility to apply Two-band and Three-band reflectance models for chlorophyll-a estimation in turbid productive waters whose scale is smaller and narrower than ocean using a high spatial resolution image. Those band ratio models were successfully applied to analyzing chlorophyll-a concentrations of ocean or coastal water using Moderate Imaging Spectroradiometer(MODIS), Sea-viewing Wide Field-fo-view Sensor(SeaWiFS), Medium Resolution Imaging Spectrometer(MERIS), etc. Two-band and Three-band models based on band ratio such as Red and NIR band were generally used for the Chl-a in turbid waters. Two-band modes using Red and NIR bands of RapidEye image showed no significant results with $R^2$ 0.38. To enhance a band ratio between absorption and reflection peak, We used red-edge band(710 nm) of RapidEye image for Twoband and Three-band models. Red-RE Two-band and Red-RE-NIR Three-band reflectance model (with cubic equation) for the RapidEye image provided significance performances with $R^2$ 0.66 and 0.73, respectively. Their performance showed the 'Approximate Prediction' with RPD, 1.39 and 1.29 and RMSE, 24.8, 22.4, respectively. Another three-band model with quadratic equation showed similar performances to Red-RE two-band model. The findings in this study demonstrated that Two-band and Three-band reflectance models using a red-edge band can approximately estimate chlorophyll-a concentrations in a turbid river water using high-resolution satellite image. In the distribution map of estimated Chl-a concentrations, three-band model with cubic equation showed lower values than twoband model. In the further works, quantification and correction of spectral interferences caused by suspended sediments and colored dissolved organic matters will improve the accuracy of chlorophyll-a estimation in turbid waters.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.