• Journal of Internet Computing and Services
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• v.24 no.2
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• pp.57-66
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• 2023

Currently, a new energy system is emerging that implements consumption reduction by improving energy efficiency. Accordingly, as smart grids spread, the rate system by timing is expanding. The rate system by timing is a rate system that applies different rates by season/hour to pay according to usage. In this study, external factors such as temperature/day/time/season are considered and the time series prediction model, LSTM, is used to predict energy power usage data. Based on this energy usage prediction model, energy usage charges are reduced by analyzing usage patterns for each device and transferring power energy from the maximum load time to the light load time. In order to analyze the usage pattern for each device, a clustering technique is used to learn and classify the usage pattern of the device by time. In summary, this study predicts usage and usage fees based on the user's power data usage, analyzes usage patterns by device, and provides customized demand transfer services based on analysis, resulting in cost reduction for users.

• Korean Journal of Remote Sensing
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• v.36 no.5_2
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• pp.867-879
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• 2020

As the era of space technology utilization is approaching, the launch of CAS (Compact Advanced Satellite) 500-1/2 satellites is scheduled during 2021 for acquisition of high-resolution images. Accordingly, the increase of image usability and processing efficiency has been emphasized as key design concepts of the CAS 500-1/2 ground station. In this regard, "CAS 500-1/2 Image Acquisition and Utilization Technology Development" project has been carried out to develop core technologies and processing systems for CAS 500-1/2 data collecting, processing, managing and distributing. In this paper, we introduce the results of the above project. We developed an operation system to generate precision images automatically with GCP (Ground Control Point) chip DB (Database) and DEM (Digital Elevation Model) DB over the entire Korean peninsula. We also developed the system to produce ortho-rectified images indexed to 1:5,000 map grids, and hence set a foundation for ARD (Analysis Ready Data)system. In addition, we linked various application software to the operation system and systematically produce mosaic images, DSM (Digital Surface Model)/DTM (Digital Terrain Model), spatial feature thematic map, and change detection thematic map. The major contribution of the developed system and technologies includes that precision images are to be automatically generated using GCP chip DB for the first time in Korea and the various utilization product technologies incorporated into the operation system of a satellite ground station. The developed operation system has been installed on Korea Land Observation Satellite Information Center of the NGII (National Geographic Information Institute). We expect the system to contribute greatly to the center's work and provide a standard for future ground station systems of earth observation satellites.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.6
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• pp.1-8
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• 2016

Current sensors are used widely in the fields of current control, monitoring, and measuring. They have become more popular with the increasing demand for smart grids in a power network, generation of renewable energy, electric cars, and hybrid cars. Although open loop Hall effect current sensors have merits, such as low cost, small size, and weight, they have low accuracy. This paper describes the design and fabrication of a 300A open loop current sensor that has high accuracy and temperature performance. The core of the current sensor was calculated numerically and the signal conditioning circuits were designed using circuit analysis software. The characteristics of the manufactured open loop current sensor of 300 A class was measured at currents up to 300 A. According to the test of the current sensor, the accuracy error and linearity error were 0.75% and 0.19%, respectively. When the temperature compensation was carried out with the relevant circuit, the temperature coefficients were less than $0.012%/^{\circ}C$ at temperatures between $-25^{\circ}C$ and $85^{\circ}C$.

• Journal of Wetlands Research
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• v.22 no.1
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• pp.15-23
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• 2020

The purpose of this study is to investigate how the degree of distribution influences the calibration of snow and runoff in distributed hydrological models using a multi-criteria calibration method. The Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) developed by NOAA-National Weather Service (NWS) is employed to estimate optimized parameter sets. We have 3 scenarios depended on the model complexity for estimating best parameter sets: Lumped, Semi-Distributed, and Fully-Distributed. For the case study, the Durango River Basin, Colorado is selected as a study basin to consider both snow and water balance components. This study basin is in the mountainous western U.S. area and consists of 108 Hydrologic Rainfall Analysis Project (HRAP) grid cells. 5 and 13 parameters of snow and water balance models are calibrated with the Multi-Objective Shuffled Complex Evolution Metropolis (MOSCEM) algorithm. Model calibration and validation are conducted on 4km HRAP grids with 5 years (2001-2005) meteorological data and observations. Through case study, we show that snow and streamflow simulations are improved with multiple criteria calibrations without considering model complexity. In particular, we confirm that semi- and fully distributed models are better performances than those of lumped model. In case of lumped model, the Root Mean Square Error (RMSE) values improve by 35% on snow average and 42% on runoff from a priori parameter set through multi-criteria calibrations. On the other hand, the RMSE values are improved by 40% and 43% for snow and runoff on semi- and fully-distributed models.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.8
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• pp.195-202
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• 2018

With the development of location-based applications such as smart phones and GPS navigation, active research is being conducted to protect location and trajectory privacy. To receive location-related services, users must disclose their exact location to the server. However, disclosure of users' location exposes not only their locations but also their trajectory to the server, which can lead to concerns of privacy violation. Furthermore, users request from the server not only location information but also multimedia information (photographs, reviews, etc. of the location), and this increases the processing cost of the server and the information to be received by the user. To solve these problems, this study proposes the EGTC (Enhanced Grid-based Trajectory Cloaking) technique. As with the existing GTC (Grid-based Trajectory Cloaking) technique, EGTC method divides the user trajectory into grids at the user privacy level (UPL) and creates a cloaking region in which a random query sequence is determined. In the next step, the necessary information is received as index by considering the sub-grid cell corresponding to the path through which the user wishes to move as c(x,y). The proposed method ensures the trajectory privacy as with the existing GTC method while reducing the amount of information the user must listen to. The excellence of the proposed method has been proven through experimental results.

• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.328-335
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• 2014

Numerical prediction methods were applied to investigate the turbulent air currents and air-conditioning efficiency in an underground subway station, and the results compared to experimental data. The Shin-gumho Station($8^{th}$ floor underground and 43.6m in depth) in Seoul was selected for the analysis. The entire station was covered for simulation and the ventilation mode was ordinary. The ventilation diffusers were modeled as 95 square shapes of $0.6m{\times}0.6m$ in the lobby and as 222 square shapes in the platform. Cooling air of $47,316m^3/h$ was supplied and the returned air of $33,980m^3/h$ is exhausted in the lobby and the cooling air of $33,968m^3/h$ is supplied and the returned air of $76,190m^3/h$ was exhausted in the platform which is the same as the experimental data. The cases of the screen-door-closed and open were respectively investigated. A total of 7.5million grids were generated and the whole domain divided into 22 blocks for MPI efficiency of calculation. Large eddy simulation (LES) was applied to solve the momentum and energy equation.

• Clean Technology
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• v.27 no.4
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• pp.277-290
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• 2021

A supercapacitor, also called an ultracapacitor or an electrochemical capacitor, stores electrochemical energy by the adsorption/desorption of electrolytic ions or a fast and reversible redox reaction at the electrode surface, which is distinct from the chemical reaction of a battery. A supercapacitor features high specific power, high capacitance, almost infinite cyclability (~ 100,000 cycle), short charging time, good stability, low maintenance cost, and fast frequency response. Supercapacitors have been used in electronic devices to meet the requirements of rapid charging/discharging, such as for memory back-up, and uninterruptible power supply (UPS). Also, their use is being extended to transportation and large industry applications that require high power/energy density, such as for electric vehicles and power quality systems of smart grids. In power generation using intermittent power sources such as solar and wind, a supercapacitor is configured in the energy storage system together with a battery to compensate for the relatively slow charging/discharging time of the battery, to contribute to extending the lifecycle of the battery, and to improve the system power quality. This article provides a concise overview of the principles, mechanisms, and classification of energy storage of supercapacitors in accordance with the electrode materials. Also, it provides a review of the status of recent research and patent, product, and market trends in supercapacitor technology. There are many challenges to be solved to meet industrial demands such as for high voltage module technologies, high efficiency charging, safety, performance improvement, and competitive prices.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.42-48
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• 2019

The significance of PNT information in the fourth industrial revolution is viewed differently in relation to the past. Autonomous vehicles, autonomous vessels, smart grids, and national infrastructure require sustainable and reliable services in addition to their high precision service. Satellite navigation system, which is the most representative system for providing PNT information, receive signals from satellites outside the earth so signal reception power is low and signal structures for civilian use are open to the public. Therefore, it is vulnerable to intentional and unintentional interference or hacking. Satellite navigation systems, which can easily acquire high performance of PNT information at low cost, require alternatives due to its vulnerability to the hacking. This paper proposed R-Mode (Ranging Mode) technology that utilizes currently operated navigation and communication infrastructure in terms of Signals of OPportunity (SoOP). For this, the Nationwide Differential Global Navigation Satellite System (NDGNSS), which currently gives a service of Medium Frequency (MF) navigation signal broadcasting, was used to validate the feasibility of a backup infrastructure in domestic maritime areas through simulation analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.78-95
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• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.