• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.3
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• pp.34-44
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• 2020

In order to suggest performance analysis directions of ecological components based on a vegetation-based LID system model, this study seeks to analyze the statistical significance between monitoring results by using SWMM computer simulation and rainfall and run-off simulation devices and provide basic data required for a preliminary system design. Also, the study aims to comprehensively review a vegetation-based LID system's soil, a vegetation model, and analysis plans, which were less addressed in previous studies, and suggest a performance quantification direction that could act as a substitute device-type LID system. After monitoring artificial rainfall for 40 minutes, the test group zone and the control group zone recorded maximum rainfall intensity of 142.91mm/hr. (n=3, sd=0.34) and 142.24mm/hr. (n=3, sd=0.90), respectively. Compared to a hyetograph, low rainfall intensity was re-produced in 10-minute and 50-minute sections, and high rainfall intensity was confirmed in 20-minute, 30-minute, and 40-minute sections. As for rainwater run-off delay effects, run-off intensity in the test group zone was reduced by 79.8% as it recorded 0.46mm/min at the 50-minute point when the run-off intensity was highest in the control group zone. In the case of computer simulation, run-off intensity in the test group zone was reduced by 99.1% as it recorded 0.05mm/min at the 50-minute point when the run-off intensity was highest. The maximum rainfall run-off intensity in the test group zone (Dv=30.35, NSE=0.36) recorded 0.77mm/min and 1.06mm/min in artificial rainfall monitoring and SWMM computer simulation, respectively, at the 70-minute point in both cases. Likewise, the control group zone (Dv=17.27, NSE=0.78) recorded 2.26mm/min and 2.38mm/min, respectively, at the 50-minutes point. Through statistical assessing the significance between the rainfall & run-off simulating systems and the SWMM computer simulations, this study was able to suggest a preliminary design direction for the rainwater run-off reduction performance of the LID system applied with single vegetation. Also, by comprehensively examining the LID system's soil and vegetation models, and analysis methods, this study was able to compile parameter quantification plans for vegetation and soil sectors that can be aligned with a preliminary design. However, physical variables were caused by the use of a single vegetation-based LID system, and follow-up studies are required on algorithms for calibrating the statistical significance between monitoring and computer simulation results.

• KIEAE Journal
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• v.8 no.5
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• pp.49-54
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• 2008

The experimental of temperature, humidity and velocity was taken from the underground pit which utilized the system of ground heat source quite similar to the cool-pit system. Also, through CFD analysis, one could review the effectiveness of analysis of future alternatives. Furthermore, the temperature range of mock up cool-pit system was analyzed by inputting the weather data of annual average soil temperature provided by KMA(Korea Meteorological Administration) into the fluid simulation of anticipated heat distribution. Firstly, the difference between the temperature of air exhaust of the pit or the temperature of air supply of the compressor room and the experimental data for the month of May from the CFD analysis came out to be $0.6^{\circ}C$ and $0.9^{\circ}C$ respectively with tolerance of 3.1% and 4.7%. Secondly, the difference between the temperature of air exhaust of the Pit or the temperature of air supply of the compressor room and the experimental data for the month of July from the CFD analysis came out to be $0.8^{\circ}C$ and $1.1^{\circ}C$ respectively with tolerance of 3.3% and 4.5%. Thirdly, for the month of May, the difference between the experimental data taken for the air exhaust of the Pit or the air supply of the compressor room and soil temperature provided by KMA for monthly and yearly average temperature of Jeonju region came out be $1.9^{\circ}C$ and $1.8^{\circ}C$ respectively with tolerance of 10.7% and 9.8%. Fourthly, for the month of July, the difference between the experimental data taken for the air exhaust of the Pit or the air supply of the compressor room and soil temperature provided by KMA for monthly and yearly average temperature of Jeonju region came out be $1.1^{\circ}C$ and $1.4^{\circ}C$ respectively with tolerance of 4.5% and 5.8%. The result of above experiments allowed us to establish CFD model set up as a verification tool that is based on experimental data collected within the Pit area. Also, one could confirm the possibility to apply weather data of soil temperature provided by KMA in order to anticipate proper value for CFD analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.spc4_2
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• pp.401-412
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• 2014

This study is purposed on showing an effective process for coordinate transformation of cadastral maps, based on the local datum, in the World Geodetic System (WGS) for Cadastral Reform Project (CRP). The process follows three steps: coordinate adjustment, datum transformation and distortion modeling. The first procedure is that point coordinates on local datum has to be adjusted by those GPS observed point-to-point distances, using trilateration. Secondly, the adjusted coordinates need to be transformed to WGS by applying the Affine model, while the verification of the methodology is implemented under numerical experiments. To conduct this procedure, 195 points in the same coordinate origins in Seoul and 61 points in several different origins in Incheon are used in the estimation. As a result, there are less than 2cm coordinate differences between transformed coordinates and measured ones at everywhere. Also, it is remarkable that the transformation does not depend on either of the particular common points or the sizes of computed region. Therefore, this suggested methodology is expected to easily provide identifications and corrections for points-deviations for improved quality of the cadastral map by distortion modeling through CRP.

• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.5
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• pp.608-616
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• 2015

In this study, we have estimated the storm surge heights using numerical modeling on coastal area, and then evaluated the vulnerability index by applying the vulnerability assessment techniques. Surge modelling for 27 typhoons affected from 2000 to 2014 were simulated by applying the ADCIRC model. The results of validation and verification was in significant agreement as compared with observations for the top 6 ranking typhoons affected. As results, the storm surge heights in Jinhae Bay, Sacheon Bay, Gwangyang Bay, Cheonsu Bay and Gyeonggi Bay were higher than other inner coastal areas, then storm surge vulnerability assessment was performed using a standardization, normalization and gradation of storm surge heights. According to results of storm surge vulnerability assessment, index of Jinhae Bay, Sacheon Bay, Gwangyang Bay etc. are estimated to be vulnerable(4~5) because of the characteristics of storm surge such as inner bay are vulnerable compared with exposed to the open sea areas. However, index in the inner bay of western Jeonnam are not vulnerable(1~3) relatively. It may not appear the typhoons affected significantly for the past 15 years. So, the long-term vulnerability assessment with the sensitivity of geomorphology are necessary to reduce the uncertainty.

• Korean Journal of Environmental Biology
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• v.40 no.3
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• pp.307-315
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• 2022

In terms of habitat conservation, it is essential to develop a habitat assessment system that can evaluate not only the suitability of the current habitat, but also the health and stability of the habitat. This study aimed to develop a methodology of habitat quality assessment for endangered species by analyzing various existing habitat assessment methods. The habitat quality assessment consisted of selecting targeted species, planning of assessment, selecting targeted sites, assessing performance, calculating grade, and expert verification. Target sites were selected separately from core and potential habitats using a species distribution model or habitat suitability index. Habitat assessment factors were classified into ecological characteristic, landscape characteristic, and species-habitat characteristic. Ecological characteristic consisted of thirteen factors related to health of tree, vegetation, and soil. Landscape characteristic consisted of five factors related to fragment and connectivity of habitat. Species-habitat characteristic consisted of factors for evaluating habitat suitability depending on target species. Since meanings are different depending on characteristics, habitat quality assessment of this study could be used by classifying results for each characteristic according to various assessment purposes, such as designation of alternative habitats, assessment of restoration project, and protected area valuation for endangered species. Forest habitat quality assessment is expected to play an important role in conservation acts of endangered species in the future through continuous supplementation of this system in regard to quantitative assessment criteria and weighting for each factor with an influence.

• Tunnel and Underground Space
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• v.30 no.4
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• pp.382-393
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• 2020

The engineered barrier system of high-level radioactive waste disposal must maintain its performance in the long term, because it must play a role in slowing the rate of leakage to the surrounding rock mass even if a radionuclide leak occurs from the canister. In particular, it is very important to clarify gas dilation flow phenomenon clearly, that occurs only in a medium containing a large amount of clay material such as a bentonite buffer, which can affect the long-term performance of the bentonite buffer. Accordingly, DECOVALEX-2019 Task A was conducted to identify the hydraulic-mechanical mechanism for the dilation flow, and to develop and verify a new numerical analysis technique for quantitative evaluation of gas migration phenomena. In this study, based on the conventional two-phase flow and mechanical behavior with effective stresses in the porous medium, the hydraulic-mechanical model was developed considering the concept of damage to simulate the formation of micro-cracks and expansion of the medium and the corresponding change in the hydraulic properties. Model verification and validation were conducted through comparison with the results of 1D and 3D gas injection tests. As a result of the numerical analysis, it was possible to model the sudden increase in pore water pressure, stress, gas inflow and outflow rate due to the dilation flow induced by gas pressure, however, the influence of the hydraulic-mechanical interaction was underestimated. Nevertheless, this study can provide a preliminary model for the dilation flow and a basis for developing an advanced model. It is believed that it can be used not only for analyzing data from laboratory and field tests, but also for long-term performance evaluation of the high-level radioactive waste disposal system.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.2
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• pp.109-120
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• 2017

A discounted cost model for preventive maintenance of armor units of rubble-mound breakwaters is mathematically derived by combining the deterioration model based on a discrete-time stochastic process of shock occurrence with the cost model of renewal process together. The discounted cost model of condition-based maintenance proposed in this paper can take into account the nonlinearity of cumulative damage process as well as the discounting effect of cost. By comparing the present results with the previous other results, the verification is carried out satisfactorily. In addition, it is known from the sensitivity analysis on variables related to the model that the more often preventive maintenance should be implemented, the more crucial the level of importance of system is. However, the tendency is shown in reverse as the interest rate is increased. Meanwhile, the present model has been applied to the armor units of rubble-mound breakwaters. The parameters of damage intensity function have been estimated through the time-dependent prediction of the expected cumulative damage level obtained from the sample path method. In particular, it is confirmed that the shock occurrences can be considered to be a discrete-time stochastic process by investigating the effects of uncertainty of the shock occurrences on the expected cumulative damage level with homogeneous Poisson process and doubly stochastic Poisson process that are the continuous-time stochastic processes. It can be also seen that the stochastic process of cumulative damage would depend directly on the design conditions, thus the preventive maintenance would be varied due to those. Finally, the optimal periods and scale for the preventive maintenance of armor units of rubble-mound breakwaters can be quantitatively determined with the failure limits, the levels of importance of structure, and the interest rates.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.93-101
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• 2001

In this paper, we propose an image downscaler used in multimedia video applications, such as DTV, TV-PIP, PC-video, camcorder, videophone and so on. The proposed image downscaler provides a scaled image of high-quality and high-performance. This paper will explain the scaling theory using two-dimensional digital filters. It is the method that removes an aliasing noise and decreases the hardware complexity, compared with Pixel-drop and Upsamling. Also, this paper will prove it improves scaling precisians and decreases the loss of data, compared with the Scaler32, the Bt829 of Brooktree, and the SAA7114H of Philips. The proposed downscaler consists of the following four blocks: line memory, vertical scaler, horizontal scaler, and FIFO memory. In order to reduce the hardware complexity, the using digital filters are implemented by the multiplexer-adder type scheme and their all the coefficients can be simply implemented by using shifters and adders. It also decreases the loss of high frequency data because it provides the wider BW of 6MHz as adding the compensation filter. The proposed downscaler is modeled by using the Verilog-HDL and the model is verified by using the Cadence simulator. After the verification is done, the model is synthesized into gates by using the Synopsys. The synthesized downscaler is Placed and routed by the Mentor with the IDEC-C632 0.65${\mu}{\textrm}{m}$ library for further IC implementation. The IC master is fixed in size by 4,500${\mu}{\textrm}{m}$$\times$4,500${\mu}{\textrm}{m}$. The active layout size of the proposed downscaler is 2,528${\mu}{\textrm}{m}$$\times$3,237${\mu}{\textrm}{m}$.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.19-30
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• 2012

The majority of daily travel demands concentrate at particular time-periods, which causes the difficulties in the travel demand analysis and the corresponding benefit estimation. Thus, it is necessary to consider time-specific traffic characteristics to yield more reliable results. Traditionally, na$\ddot{i}$ve, heuristic, and statistical approaches have been applied to address the peak-hour ratio. In this study, a hybrid clustering model which is one of the statistical methods is applied to calculate the peak-hour ratio and its duration. The 2009 national 24-hour traffic data provided by the Korea institute of Construction Technology are used. The analysis is conducted dividing vehicle types into passenger cars and trucks. For the verification for the usefulness of the methodology, the toll collection system data by the Korea Express Corporation are collected. The result of the research shows lower errors during the off-peak hours and night times and increasing error ratios as the travel distance increases. Since the method proposed can reduce the arbitrariness of analysts and can accommodate the statistical significance test, the model could be considered as a more robust and stable methodology. It is hoped that the result of this paper could contribute to the enhancement of the reliability for the travel demand analysis.