• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.331-343
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• 2012

In this study, the site investigation for fish was performed in the 15 km of Hongcheon river including Oancheon stream. The river ecosystem health was evaluated using the field data for fish. The field survey was carried out at 9 sites, 4 times from August to November 2011. The ecological diversity, including dominance, evenness, and richness and the ecological health using IBI and QHEI were evaluated. The result shows that the mean IBI in the 9 sites is in good-common condition, but the downtown section has a common-worse condition. The result evaluated by QHEI shows optimum-good condition. Also, the habitat suitability index for Pseudopuntungia tenuicorpa, which is one of endangered species, was evaluated, and then the environment flow was calculated by using the PHABSIM model. The previous research in the literature reports that Acheilognathus signifer, one of the endangered species, inhabited in Hongchen river. However, the existence of Acheilognathus signifer was not found in the recent research and this study. Thus, the physical habitat condition for Acheilognathus signifer was evaluated using the field data in the previous study. Also, the habitat improvement for Acheilognathus signifer in Hongcheon river was proposed.

• The KIPS Transactions:PartC
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• v.9C no.4
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• pp.489-496
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• 2002

This study proposes a new polling algorithm allowing dynamic change in polling period based on line utilization prediction. Polling is the most important function in network monitoring, but excessive polling data causes rather serious congestion conditions of network when network is In congestion. Therefore, existing multiple polling algorithms decided network congestion or load of agent with previously performed polling Round Trip Time or line utilization, chanced polling period, and controlled polling traffic. But, this algorithm is to change the polling period based on the previous polling and does not reflect network conditions in the current time to be polled. A algorithm proposed in this study is to predict whether polling traffic exceeds threshold of line utilization on polling path based on the past data and to change the polling period with the prediction. In this study, utilization of each line configuring network was predicted with AR model and violation of threshold was presented in probability. In addition, suitability was evaluated by applying the proposed dynamic polling algorithm based on line utilization prediction to the actual network, reasonable level of threshold for line utilization and the violation probability of threshold were decided by experiment. Performance of this algorithm was maximized with these processes.

• Economic and Environmental Geology
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• v.43 no.2
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• pp.177-184
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• 2010

When cement grout is used for waterproofing of grounds, important roles are played by fluidity, particle size and bleeding. The most important element which determines their characteristics is the water/cement ratio of grout. Moreover in order to improve the efficiency of soil permeation, micro cement with a smaller average diameter is used in addition to ordinary portland cement. Besides the mixing ratio and cement diameter, the condition of ground is also of fundamental importance in the efficiency of permeation. In order to evaluate grout in terms of permeation ability into ground, we need a field test of grounting, which is cost and time consuming. In this paper we present a laboratory test method in which the suitability and efficiency of grouts are simply and more practically tested. In Korea neither a test standard nor devices are available to simulate grouting in a laboratory. We devised a grout injection equipment in which grouting was reproduced in the same condition with different materials, and suggested a standard for the production of specimens. Our tests revealed that the efficiency of injection increases with the water/cement ratio. We also found that more efficiently injected is the grout with the order of decreasing size; MS8000, micro cement, and ultra fine cements, and colloidal super cement.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• Geophysics and Geophysical Exploration
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• v.23 no.2
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• pp.97-114
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• 2020

Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.

• Journal of Korean Society of Archives and Records Management
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• v.14 no.3
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• pp.127-151
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• 2014

This study aims to share a methodology for locality reproduction by concretely explaining the theoretical model, procedure, and practice of constructing the Port of Busan Image Digital Archive, based on the photographic and postcard images of the Port of Busan, the representative place of Busan. Among the open-source record management programs, Omeka was chosen in implementing the digital archive because of its suitability for image exhibition. After establishing the principles for archive implementation in accordance with the purpose of the archive, a basic investigation was conducted for the record collection. With the consent of the individuals and institutions that possess the related records on the Port of Busan, such as the National Archives of Korea, the Busan Museum, and the City of Busan, original image artifacts were thus collected. The collected artifacts were then described using the Dublin Core metadata and categorized by time period. The Port of Busan was classified through four distinctive spatial characteristics (transportation, historic, industrial, and living spaces). A total of 11 themes for the exhibition was then suggested. The Busan-Shimonoseki Ferry Boat was chosen as an example exhibition of transportation space.

• Journal of Korea Water Resources Association
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• v.53 no.11
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• pp.929-938
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• 2020

In this study, we estimated missing evapotranspiration (ET) data at a eddy-covariance flux tower in the Cheongmicheon farmland site using the Artificial Neural Network (ANN). The ANN showed excellent performance in numerical analysis and is expanding in various fields. To evaluate the performance the ANN-based gap-filling, ET was calculated using the existing gap-filling methods of Mean Diagnostic Variation (MDV) and Food and Aggregation Organization Penman-Monteith (FAO-PM). Then ET was evaluated by time series method and statistical analysis (coefficient of determination, index of agreement (IOA), root mean squared error (RMSE) and mean absolute error (MAE). For the validation of each gap-filling model, we used 30 minutes of data in 2015. Of the 121 missing values, the ANN method showed the best performance by supplementing 70, 53 and 84 missing values, respectively, in the order of MDV, FAO-PM, and ANN methods. Analysis of the coefficient of determination (MDV, FAO-PM, and ANN methods followed by 0.673, 0.784, and 0.841, respectively.) and the IOA (The MDV, FAO-PM, and ANN methods followed by 0.899, 0.890, and 0.951 respectively.) indicated that, all three methods were highly correlated and considered to be fully utilized, and among them, ANN models showed the highest performance and suitability. Based on this study, it could be used more appropriately in the study of gap-filling method of flux tower data using machine learning method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.478-489
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• 2016

Recently, there has been increasing interest in the remodecycling options of idle spaces around the central city through the urban regeneration. Various studies to create new added value through this way are ongoing. This study aims to analyze the impact relationship and structure on the regeneration of idle space by types affecting the quality of residents' life and local economy revitalization. The hypothesis was verified by a suitability test for setting the hypothesis and statistical significance test from the PLS 3.0 package. The results of this study drew 6 hypotheses from a total of 11 on the 'idle space regeneration of economy based type of PLS-SEM' and 4 hypotheses from a total of 11 on the 'idle space regeneration of neighborhood regeneration type PLS-SEM'. The results can be summarized into several parts. First, if cultural aspects should be considered, the regeneration of idle space (economy-based type and neighborhood-regeneration type) could meet 2 parts, such as the quality of residents' life and local economy revitalization at the same time. Second, improving the 'physical aspects' only affects the 'idle space regeneration of the economy-based type of PLS-SEM'. Third, improving the 'social aspects' only affects the 'idle space regeneration of neighborhood regeneration type of PLS-SEM'. This study has significance in that it provides the empirical analysis for the regeneration of idle space and there are differences according to types of PLS structural model.

• Tunnel and Underground Space
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• v.20 no.2
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• pp.97-104
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• 2010

The materials failure relation $\ddot{\Omega}=A{(\dot{\Omega})}^\alpha$ where $\Omega$ is a measurable quantity such as displacement and the dot superscript is the time derivative, may be used to analyze the accelerating creep of materials. Coefficients, A and $\alpha$, are determined by fitting given data sets. In this study, it is tried to predict the failure time of tunnel using the materials failure relation. Four fitting techniques of applying the materials failure relation are attempted to forecast a failure time. Log velocity versus log acceleration technique, log time versus log velocity technique, inverse velocity technique are based on the linear least squares fits and non-linear least squares technique utilizes the Levenberg-Marquardt algorithm. Since the log velocity versus log acceleration technique utilizes a logarithmic representation of the materials failure relation, it indicates the suitability of the materials failure relation applied to predict a failure time of tunnel. A linear correlation between log velocity and log acceleration appears satisfactory(R=0.84) and this represents that the materials failure relation is a suitable model for predicting a failure time of tunnel. Through comparing the real failure time of tunnel with the predicted failure times from four curve fittings, it is shown that the log time versus log velocity technique results in the best prediction.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.503-508
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• 2010

Recently, the advance of mobile devices has made various services possible beyond simple communication. One of services is the predicting the future path of users and providing the most suitable location based service based on the prediction results. Almost of these prediction methods are based on previous path data. Thus, calculating similarities between current location information and the previous trajectories for path prediction is an important operation. The collected trajectory data have a huge amount of location information generally. These information needs the high computational cost for calculating similarities. For reducing computational cost, the meaningful location based trajectory model approaches are proposed. However, most of the previous researches are considering only the physical information such as stay time and the distance for extracting the meaningful locations. Thus, they will probably ignore the characteristics of users for meaningful location extraction. In this paper, we suggest a meaningful location extracting and trajectory simplification approach considering the stay time, distance, and additionally interaction information of user. The method collects the location information using GPS device and interaction information between the user and the others. Using these data, the proposed method defines the proximity of the people who are related with the user. The system extracts the meaningful locations based on the calculated proximities, stay time and distance. Using the selected meaningful locations the trajectories are simplified. For verifying the usability of the proposed method, we collect the behavioral data of smart phone users. Using these data, we measure the suitability of meaningful location extraction method, and the accuracy of prediction approach based on simplified trajectories. Following these result, we confirmed the usability of proposed method.