• Journal of Astronomy and Space Sciences
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• v.28 no.1
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• pp.55-62
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• 2011

The precise orbit determination (POD) of low earth orbiter (LEO) has complied with its required positioning accuracy by the double-differencing of observations between International GNSS Service (IGS) and LEO to eliminate the common clock error of the global positioning system (GPS) satellites and receiver. Using this method, we also have achieved the 1 m positioning accuracy of Korea Multi-Purpose Satellite (KOMPSAT)-2. However double-differencing POD has huge load of processing the global network of lots of ground stations because LEO turns around the Earth with rapid velocity. And both the centimeter accuracy and the near real time (NRT) processing have been needed in the LEO POD applications--atmospheric sounding or urgent image processing--as well as the surveying. An alternative to differential GPS for high accuracy NRT POD is precise point positioning (PPP) to use measurements from one satellite receiver only, to replace the broadcast navigation message with precise post processed values from IGS, and to have phase measurements of dual frequency GPS receiver. PPP can obtain positioning accuracy comparable to that of differential positioning. KOMPSAT-5 has a precise dual frequency GPS flight receiver (integrated GPS and occultation receiver, IGOR) to satisfy the accuracy requirements of 20 cm positioning accuracy for highly precise synthetic aperture radar image processing and to collect GPS radio occultation measurements for atmospheric sounding. In this paper we obtained about 3-5 cm positioning accuracies using the real GPS data of the Gravity Recover and Climate Experiment (GRACE) satellites loaded the Blackjack receiver, a predecessor of IGOR. And it is important to reduce the latency of orbit determination processing in the NRT POD. This latency is determined as the volume of GPS measurements. Thus changing the sampling intervals, we show their latency to able to reduce without the precision degradation as the assessment of their precision.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.1
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• pp.9-14
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• 2010

Recent increase in the strength and frequency of typoons due to climate change claims reconsideration of the design wind load in existing design codes for civil engineering structures in which the basic wind speed is estimated based on meteorological data by mid 1990s. In this paper, based on wind speed data at 76 observatories in Korea from 1961 through 2008, the basic wind speeds which can be utilized in designing civil engineering structures including buildings and bridges are estimated using the statistical process. The return period of the wind speed for each location is determined using the Gumbel distribution. The results for considered locations are compared to the existing design codes. Also, for design applications, the wind speed map, which classifies the country into four basic wind speed zones, is proposed using the resulting basic wind speeds.

• KIEAE Journal
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• v.17 no.1
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• pp.23-28
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• 2017

Purpose: Many design index that are using in planning phase have been developed. The most popular things among them are Window to Wall Ratio and Surface to Volume Ratio. However there are some limits. Window to Wall Ratio cannot consider building size and Surface to Volume Ratio cannot do Window to Wall Ratio. Accordingly, in this paper, the Window to Floor Ratio was proposed that it can be considered both building size and Window to Wall Ratio. And analyzed correlation of energy demand. Method: For the test, 16 modules with the size of $6m{\times}6m{\times}4m$ were used to make 35 models with the same volume. The simulation was conducted to 945 cases using the window-to-wall ratio of 30, 50 and 70 % in three areas such as Seoul, Gwangju and Jeju and three kinds of windows. And IES_VE was used. Result: The findings above show that the Window to Floor Ratio that can be considered both building size and Window area have to become as design index. It was found out that design criteria with SHGC is necessary, not with the thermal performance (U-value). It is needed to additional analysis about residential building and the effect of 24-hours heating and cooling condition. It plans to carry out research to establish design indicators for climatic conditions in the country and building applications.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.293-296
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• 2008

Land surface Temperature (LST) is a very useful surface parameter for the wide range of applications, such as agriculture, numerical and climate modelling community. Whereas operational observation of LST is far from the needs of application community in the spatial Itemporal resolution and accuracy. So, we developed split-window type LST retrieval algorithm to estimate the LST from MTSAT-IR data. The coefficients of split-window algorithm were obtained by means of a statistical regression analysis from the radiative transfer simulations using MODTRAN 4 for wide range of atmospheric profiles, satellite zenith angle and lapse rate conditions including the surface inversions. The sensitivity analysis showed that the LST algorithm reproduces the LST with a reasonable quality. However, the LST algorithm overestimates and underestimates for the strong surface inversion and superadiabatic conditions especially for the warm temperature, respectively. And the performance of LST algorithms is superior when satellite zenith angle is small. The accuracy of the retrieved LST has been evaluated with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST data. The validation results showed that the correlation coefficients and RMSE are about 0.83${\sim}$0.98 and 1.38${\sim}$4.06, respectively. And the quality of LST is significantly better during night and winter time than during day and summer. The validation results showed that the LST retrieval algorithm could be used for the operational retrieval of LST from MTSAT-IR and COMS(Communication, Ocean and Meteorological Satellite) data with some modifications.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1205-1216
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• 2015

Since concentration of greenhouse gas increases continuously from human's fossil fuel use, urbanization, and cultivation, it is trend that climate change is appearing. In Addition, in 20th century, occurrence of disaster is accidental and huge, and damage level also increases gradually. Therefore, in order to preserve the territory and to protect people's life and property against new type disasters, disaster detection satellite (payloads) development is required urgently. In this paper, we conduct a research and development for the prompt preemptive action when occurred a disaster, in particularly, about the disaster observation optimized at Korea's geographical features for the irregular future disasters. For the payload design which is specialized detect disasters, we create a tech tree of satellite imagery applications based 10 disaster types, and analyze the satellite sensor technologies referred to Landsat-8, Worldview-3 and ALOS-2.

• Membrane Journal
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• v.30 no.5
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• pp.293-306
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• 2020

Increasing harmful effects of climate change, such as its effect on water scarcity, has led to a focus on developing effective water purification methods to obtain pure water. Additionally, rising levels of water pollution is increasing levels of environmental degradation, calling for sources of water treatment to remove contaminants. To purify water, osmotic processes across a semipermeable membrane can take place, and recent studies are showing that incorporating nanoparticles, including carbon quantum dots (CQDs), graphene carbon dots (GQDs), and graphene oxide quantum dots (GOQDs) are making thin film composite (TFC) membranes more effective by increasing water flux while maintaining similar levels of salt rejection, increasing the hydrophilicity of the membrane surface, showing bactericidal properties, exhibiting antifouling properties to prevent accumulation of bacteria or other microorganisms from reducing the effectiveness of the membrane, and more. In the review, the synthesis process, applications, functionality, properties, and the role of several types of quantum dots are discussed in the composite membrane for water purification.

• Ocean and Polar Research
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• v.38 no.4
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• pp.339-345
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• 2016

Stable water vapor isotopes have been utilized as a tracer for studying atmospheric global circulations, climate change and paleoclimate with ice cores. Recently, since laser spectroscopy has been available, water vapor isotopes can be measured more precisely and continuously. Studies of water vapor isotopes have been conducted over the world, but it is the early stage in south Korea. For vapor isotopes study, a cryogenic sampling device for water vapor isotopes has been developed. The cryogenic sampling device consists of the dewar bottle, filled with extremely low temperature material and impinger connected with a vacuum pump. Impinger stays put in the dewar bottle to change the water vapor which passes through the inside of impinger into the solid phase as ice. The fact that water vapor has not sampled completely leads to isotopic fractionation in the impinger. To minimize the isotopic fractionation during sampling water vapor, we have tested the method using a serial connection with two sets of impinger device in the laboratory. We trapped 98.02% of water vapor in the first trap and the isotopic difference of the trapped water vapor between two impinger were about 20‰ and 6‰ for hydrogen and oxygen, respectively. Considering the amount of water vapor trapped in each impinger, the isotopic differences for hydrogen and oxygen were 0.33‰ and 0.06‰, respectively, which is significantly smaller than the precision of isotopic measurements. This work can conclude that there is no significant fractionation during water vapor trapping.

• Tunnel and Underground Space
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• v.25 no.2
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• pp.115-124
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• 2015

Thermal energy storage (TES) is a technology that stores surplus thermal energy at high or low temperatures for later use when the customer needs it, not just when it is available. TES systems can help balance energy demand and supply and thus improve the overall efficiency of energy systems. Furthermore, the conversion and storage of intermittent renewable resources in the form of thermal energy can help increase the share of renewable resources in the energy mix which refers to the distribution of energy consumption from different sources, and to achieve this, it is essential to combine renewable resources with TES systems. Underground TES using rock caverns, known as cavern thermal energy storage (CTES), is a viable option for large-scale, long-term TES utilization although its applications are limited because of the high construction costs. Furthermore, the heat loss in CTES can significantly be reduced due to the heating of the surrounding rock occurred during long-term TES, which is a distinctive advantage over aboveground TES, in which the heat loss to the surroundings is significantly influenced by climate conditions. In this paper, we introduced important factors that should be considered in the shape and multiple layout design of TES caverns, and proposed guidelines for storage space design.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1007-1011
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• 2020

Recently, natural and anthropogenic disasters have rapidly increased due to the on-going climate change and various human activities. Remote sensing (RS) technology enables the continuous monitoring and rapid detection of disastrous events thanks to its advantages covering vast areas at high temporal resolution. Moreover, RS technology has been very actively used in disaster monitoring and assessment since cluster- and micro-satellites and drones were introduced and became popular. In this special issue, nine papers were introduced, including the processing and applications of remote sensing data for monitoring, assessment, and prediction of various natural disasters. These papers are expected to serve as useful references for disaster management in the future.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.326-333
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• 2017

The lakes and reservoirs have been reported as important sources of carbon emissions to the atmosphere in many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed the quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there are still large uncertainties at the global scale estimation. Mechanistic models can be used for understanding and estimating the temporal and spatial variations of the NAFs considering complicated hydrodynamic and biogeochemical processes in a reservoir, but these models require extensive and expensive datasets and model parameters. On the other hand, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate the NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily $CO_2$ NAFs in Daecheong Reservoir located in Geum River of Korea, and compare the models performance against the multiple linear regression (MLR) model that proposed in the previous study (Chung et al., 2016). As a result, the RF and ANN models showed much enhanced performance in the estimation of the high NAF values, while MLR model significantly under estimated them. Across validation with 10-fold random samplings was applied to evaluate the performance of three models, and indicated that the ANN model is best, and followed by RF and MLR models.