• Journal of Environmental Impact Assessment
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• v.20 no.5
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• pp.663-673
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• 2011

In the face of accelerating biodiversity loss and its significance in our coexistence with nature, biodiversity is becoming more crucial in sustainable development perspective. To estimate biodiversity in the future which provides valuable information for decision making system especially in the national level, a quantitative approach must be studied forehand as a baseline of the present status. In this study, we developed a large-scale map of Plant Species Richness (PSR, typical indicator of biodiversity) for Young-dong and Pyung-chang provinces. Due to the accessibility of appropriate data and advance of modelling techniques, reduction of variables without deteriorating the predictive power is considered by applying Genetic algorithm. In addition, a number of Correctly Classified Instances (CCI) with 10-fold cross validation which indicates the predictive power, was carried out for evaluation. This study, as a fundamental baseline, will be beneficial in future land work as well as ecosystem restoration business or other relevant decision making agenda.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.548-551
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• 2007

Among components of digital topographic maps used officially in Korea, only contours have 3D values except buildings and trees that are demanded in landscape planning. This study presented a series of processes for 3Dreconstructing landscape features such as terrain, buildings and standing trees using LiDAR (Light Detection And Ranging) data and aerial digital photo graphs. The 3D reconstructing processes contain 1) building terrain model, 2) delineating outline of landscape features, 3) extracting height values, and 4) shaping and coloring landscape features using aerial photograph and 3-D virtual data base. LiDAR data and aerial photograph was taken in November 2006 for $50km^{2}$ area in Sorak National Park located in eastern part of Korea. The average scanning density of LiDAR pulse was 1.32 points per square meter, and the aerial photograph with RGB bands has $0.35m{\times}0.35m$ spatial resolution. Using reconstructed 3D landscape features, visibility with the growing trees with time and at different viewpoints was analyzed. Visible area from viewpoint could be effectively estimated considering 3D information of landscape features. This process could be applied for landscape planning like building scale with the consideration of surrounding landscape features.

• Journal of environmental and Sanitary engineering
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• v.13 no.1
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• pp.9-15
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• 1998

Microwave heating and drying processes have been well established in various industrial applications. Feasibilities of successful application of microwave drying to many material have been shown on the laboratory or pilot-plant scale. The microwave drying behavior of plating sludge are considered in this paper. The plating sludge containing 70%, 80% and 90% water exposed to microwave power at 2,450 MHz, 700W. An experimental microwave drying apparatus was designed and constructed to monitor weight loss during drying. By studying the drying characteristic curve, the moisture in sludge was almost classified into two categories : free moisture and intestinal moisture. And the critical moisture contents at which the drying rate ceases to be constant were from 10.1 to 10.5%. A simple drying model is proposed which may be used to describe drying behavior of plating sludge. The constant rate and the falling rate periods in microwave drying were addressed separately. From the eqation of constant rate period the drying rate constants decreased exponentially with increasing depth. Microwave heating compared with conventional heating offered higher heating rates from 9 to 16 times. Therefore, microwave drying process can be effective in removing moisture from plating sludge.

• Journal of Korean Society of Transportation
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• v.28 no.1
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• pp.7-14
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• 2010

As globalization is making rapid progress, place of international trade based on seaports is changing to airports, which make logistic function in airport getting more important. Airports are required to serve as social overhead capital representing economies of scale as well as a logistic hub for integrating production, sales and transport for multinational corporations. In order to keep regional airport hub, many strategies are required such as development of hinterland and competitive advantage strategies. This paper tried to find determining factors to be a hub airport and competitiveness for hubbing, using the data from Incheon, Narita, Kansai, Nagoya, Singapore-Changi and Taipei airports. As the result of making an analysis of competitiveness of airports and competitive ranking excluding hinterland factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.08a
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• pp.172-172
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• 2010

$MgB_2$ doped with $TiO_2$ was prepared by the in-situ solid state reaction to study the effects of $TiO_2$ dopant on the flux pinning behavior of $MgB_2$ superconductor. From the field-cooled and the zero-field-cooled temperature dependences of magnetization, the realms of vortex-glass and vortex-liquid states of $TiO_2$-doped $MgB_2$ were determined in the H-T diagram (the temperature dependence of upper critical magnetic field and irreversibility line). The critical current density was estimated from the width of hysteresis loops in the framework of Beam's model at different temperatures. The results indicate that nano-scale $TiO_2$ inclusions play a role of the effective pinning centers and lead to the enhanced upper critical field and critical current density. It is suggested that the grain-boundary pinning mechanism is realized in $TiO_2$-doped $MgB_2$ superconductor.

• Journal of Korean Society on Water Environment
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• v.25 no.6
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• pp.863-871
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• 2009

For the assessment of climate change impacts on river flow condition, CGCM 3.1 T63 is selected as future climate information. The projections come from CGCM used to simulate the GHG emission scenario known as A2. Air temperature and precipitation information from the GCM simulations are converted to regional scale data using the statistical downscaling method known as MSPG. Downscaled climate data from GCM are then used as the input data for the modified TANK model to generate regional runoff estimates for 44 river locations in Nakdong river basin. Climate change is expected to reduce the reliability of water supplies in the period of 2021~2030. In the period of 2051~2060, stream flow is expected to be reduced in spring season and increased in summer season. However, it should be noted that there are a lot of uncertainties in such multiple-step analysis used to convert climate information from GCM-based future climate projections into hydrologic information.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.581-586
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• 2009

Knowledge of ground thermal properties is most important for the proper design of large scale BHE(borehole heat exchanger) systems. The type, pipe size and thermal performance of the BHE is highly dependent on the ground source heatpump system-efficiency and instruction cost. Thermal response tests with mobile measurement devices were developed primarily for insitu determination of design data for large diameter BHE for triple-U spacer apply. The main purpose has been to determine insitu values of effective ground thermal conductivity and thermal resistance, including the effect of ground-water flow and natural convection in the boreholes. The test rig is set up on a some trailer, and contains a circulation pump, a inline heater, temperature sensors, flow meter, power analysis meter and a data logger for recording the temperature, fluid flow data. A constant heat power is injected into the borehole through the tripl-U pipes system of test rig and the resulting temperature change in the borehole is recorded. The recorded temperature data are analysed with a line-source model, which gives the effective insitu values of rock thermal conductivity and borehole thermal resistance of large diameter BHE for spacer apply.

• Journal of Food Hygiene and Safety
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• v.14 no.1
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• pp.104-114
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• 1999

This study was conducted to find out the proper ways of implementation of Hazard Analysis Critical Control Point (HACCP) concepts applicable to the current Korean food inspection system. The following recommendations are based on an in-depth review of the Canadian Food Safety Enhancement Program (FSEP), which is one of the leading HACCP programs adapted to the food industry. Since 1997, the HACCP system has been voluntarily applied to meat processing plants in Korea in accordance with the Food Protection Law. But the guidelines are obscure and inadequate to expand to the diversity of food plants, and are therefore only applied to a limited number of plants of small scale enterprise. For these reasons, it is necessary to prepare an enhanced food safety control program focused not only on the HACCP plants but also on the non-HACCP plants. The national program should be the fundamental framework of a food safety control policy enforced by all the relevant authorities. The Prerequiste Program of Canadian Food Inspection Agency and Sanitation Standard Operating Procedures (SSOP) of FSIS are good example programs for the non-HACCP plants. These programs, which are a major part of the HACCP system, could easily be adapted to the Korean food industry. To improve the current HACCP implementation guideline, it is necessary to develop a detailed implementation manual, generic HACCP model, training program, and an audit program.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.326-337
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• 2010

This work addresses problems regarding trajectory planning for unmanned aerial vehicle sensors. Such sensors are used for taking measurements of large nonlinear systems. The sensor investigations presented here entails methods for improving estimations and predictions of large nonlinear systems. Thoroughly understanding the global system state typically requires probabilistic state estimation. Thus, in order to meet this requirement, the goal is to find trajectories such that the measurements along each trajectory minimize the expected error of the predicted state of the system. The considerable nonlinearity of the dynamics governing these systems necessitates the use of computationally costly Monte-Carlo estimation techniques, which are needed to update the state distribution over time. This computational burden renders planning to be infeasible since the search process must calculate the covariance of the posterior state estimate for each candidate path. To resolve this challenge, this work proposes to replace the computationally intensive numerical prediction process with an approximate covariance dynamics model learned using a nonlinear time-series regression. The use of autoregressive time-series featuring a regularized least squares algorithm facilitates the learning of accurate and efficient parametric models. The learned covariance dynamics are demonstrated to outperform other approximation strategies, such as linearization and partial ensemble propagation, when used for trajectory optimization, in terms of accuracy and speed, with examples of simplified weather forecasting.