• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.5
• /
• pp.93-99
• /
• 2019

In this paper, we propose a smart meter that uses GRU model, which is one of artificial neural networks, for the efficient energy management. We collected power consumption data that train GRU model through the proposed smart meter. The implemented smart meter has automatic power measurement and real-time observation function and load control function through power consumption prediction. We determined a reference value to control the load by using Root Mean Squared Error (RMS), which is one of performance evaluation indexes, with 20% margin. We confirmed that the smart meter with automatic load control increases the efficiency of energy management.

• Journal of Ocean Engineering and Technology
• /
• v.35 no.1
• /
• pp.82-90
• /
• 2021

Owing to the advantages of assuring the best views and seawater exchange, submerged breakwaters have been widely installed along the eastern coast of Korea in recent years. It significantly contributes to promoting the advancement of shorelines by partially inhibiting incident wave energy. Observations were carried out by a pressure-type wave gauge in the Bongpo Beach to evaluate the coefficients of wave transmission via a submerged breakwater, and the results obtained were compared with those of existing conventional equations on the transmission coefficient derived from hydraulic experiments. After reviewing the existing equations, we proposed a transmission coefficient equation in terms of an error function. Although it exhibited robust relationships with the crest height and breaking coefficient, deviations from the observed data were evident and considered to be triggered by the difference in the incident wave climate. Therefore, in this study, we conducted a numerical experiment to verify the influence of wave period on the coefficients of wave transmission, in which we adopted a parabolic-type mild-slope equation model. Consequently, the deviation from calculated results appears to practically cover all deviation range in the observed data. The wave period and direction of the incident wave increased, the transmission coefficient decreased, and the wave direction was determined to demonstrate a relatively significant influence on the transmission coefficient. It was inferred that this numerical study is expected to be used practically in evaluating the design achievement of the submerged breakwater, which is adopted as a countermeasure to coastal beach erosion.

• Atmosphere
• /
• v.22 no.4
• /
• pp.429-436
• /
• 2012

The performances of the Seoul National University Urban Canopy Model (SNUUCM) under different meteorological conditions (clear, cloudy, and rainy conditions) in summertime are compared using observation dataset obtained at an urban site. The daily-averaged net radiation, sensible heat flux, and storage heat flux are largest in clear days and smallest in rainy days, but the daily-averaged latent heat flux is similar among clear, cloudy, and rainy days. That is, the ratio of latent heat flux to net radiation increases in order of clear, cloudy, and rainy conditions. In general, the performance of the SNUUCM is better in clear days than in cloudy or rainy days. However, the performance in simulating sensible heat flux in clear days is as poor as that in rainy days. For all the meteorological conditions, the performance in simulating latent heat flux is worst among the performances in simulating net radiation, sensible heat flux, and latent heat flux. The normalized mean error for latent heat flux is largest in rainy days in which the relative importance of latent heat flux in the surface energy balance becomes greatest among the three conditions. This study suggests that improvements to the parameterization of processes that are related to latent heat flux are particularly needed.

• Bulletin of the Korean Space Science Society
• /
• 2009.10a
• /
• pp.49.3-49.3
• /
• 2009

Geostationary Ocean Colour Imager (GOCI) is the first ocean color instrument that will be operating in a geostationary orbit from 2010. GOCI will provide the crucial information of ocean environment around the Korean peninsula in high spatial and temporal resolutions at eight visible bands. We report an on-going development of imaging and radiometric performance prediction model for GOCI with realistic data for reflectance, transmittance, absorption, wave-front error and scattering properties for its optical elements. For performance simulation, Monte Carlo based ray tracing technique was used along the optical path starting from the Sun to the final detector plane for a fixed solar zenith angle. This was then followed by simulation of red-tide evolution detection and their radiance estimation, following the in-orbit operational sequence. The simulation results proves the GOCI flight model is capable of detecting both image and radiance originated from the key ocean phenomena including red tide. The model details and computational process are discussed with implications to other earth observation instruments.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.2 no.4
• /
• pp.175-182
• /
• 2000

Spatial interpolation of daily temperature forecasts and observations issued by public weather services is frequently required to make them applicable to agricultural activities and modeling tasks. In contrast to the long term averages like monthly normals, terrain effects are not considered in most spatial interpolations for short term temperatures. This may cause erroneous results in mountainous regions where the observation network hardly covers full features of the complicated terrain. We developed a spatial interpolation model for daily minimum temperature which combines inverse distance squared weighting and elevation difference correction. This model uses a time dependent function for 'mountain slope lapse rate', which can be derived from regression analyses of the station observations with respect to the geographical and topographical features of the surroundings including the station elevation. We applied this model to interpolation of daily minimum temperature over the mountainous Korean Peninsula using 63 standard weather station data. For the first step, a primitive temperature surface was interpolated by inverse distance squared weighting of the 63 point data. Next, a virtual elevation surface was reconstructed by spatially interpolating the 63 station elevation data and subtracted from the elevation surface of a digital elevation model with 1 km grid spacing to obtain the elevation difference at each grid cell. Final estimates of daily minimum temperature at all the grid cells were obtained by applying the calculated daily lapse rate to the elevation difference and adjusting the inverse distance weighted estimates. Independent, measured data sets from 267 automated weather station locations were used to calculate the estimation errors on 12 dates, randomly selected one for each month in 1999. Analysis of 3 terms of estimation errors (mean error, mean absolute error, and root mean squared error) indicates a substantial improvement over the inverse distance squared weighting.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.4
• /
• pp.109-118
• /
• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

• Spatial Information Research
• /
• v.23 no.4
• /
• pp.79-89
• /
• 2015

This study aims to design and implement a traffic model that can simulate the traffic behavior on the microscopic level by using the GIS. In the design of the model, the vehicle in the simulation environment recognizes the GIS road centerline data as road network data reflecting number of lanes, speed limit and so on. In addition, the behavior model was designed by dividing functions into the environmental perception model, time headway distribution model, car following model, and lane changing model. The implemented model was applied to Jahamun-road of Jongno-gu district to verify the accuracy of the model. As a result, the simulation results on the Jahamun-road had no great error compared with the actual observation data. In the aspect of usability of model, it is judged that this model will be able to effectively contribute to analysis of amount of carbon emission by traffic, evaluation of traffic flow, plans for location of urban infrastructure and so on.

• The Korean Journal of Physiology and Pharmacology
• /
• v.22 no.6
• /
• pp.705-712
• /
• 2018

The tube formation assay is a widely used in vitro experiment model to evaluate angiogenic properties by measuring the formation of tubular structures from vascular endothelial cells (ECs). In vitro experimental results are crucial when considered the advisability of moving forward to in vivo studies. Thus, the additional attentions to the in vitro assay is necessary to improve the quality of the pre-clinical data, leading to better decision-making for successful drug discovery. In this study, we improved the tube formation assay system in three aspects. First, we used human endothelial colony forming cells (ECFCs), which are endothelial precursors that have a robust proliferative capacity and more defined angiogenic characteristics compared to mature ECs. Second, we utilized a real-time cell recorder to track the progression of tube formation for 48 hours. Third, to minimize analysis error due to the limited observation area, we used image-stitching software to increase the microscope field of view to a $2{\times}2$ stitched area from the $4{\times}$ object lens. Our advanced tube formation assay system successfully demonstrated the time-dependent dynamic progression of tube formation in the presence and absence of VEGF and FGF-2. Vatalanib, VEGF inhibitor, was tested by our assay system. Of note, $IC_{50}$ values of vatalanib was different at each observation time point. Collectively, these results indicate that our advanced tube formation assay system replicates the dynamic progression of tube formation in response to angiogenic modulators. Therefore, this new system provides a sensitive and versatile assay model for evaluating pro- or anti-angiogenic drugs.

• Atmosphere
• /
• v.32 no.1
• /
• pp.27-37
• /
• 2022

The Korean Integrated Model (KIM) forecast system was extended to assimilate Horizontal Line-Of-Sight (HLOS) wind observations from the Atmospheric Laser Doppler Instrument (ALADIN) on board the Atmospheric Dynamic Mission (ADM)-Aeolus satellite. Quality control procedures were developed to assess the HLOS wind data quality, and observation operators added to the KIM three-dimensional variational data assimilation system to support the new observed variables. In a global cycling experiment, assimilation of ALADIN observations led to reductions in average root-mean-square error of 2.1% and 1.3% for the zonal and meridional wind analyses when compared against European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analyses. Even though the observable variable is wind, the assimilation of ALADIN observation had an overall positive impact on the analyses of other variables, such as temperature and specific humidity. As a result, the KIM 72-hour wind forecast fields were improved in the Southern Hemisphere poleward of 30 degrees.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
• /
• 2004.04a
• /
• pp.507-512
• /
• 2004

Research that establish new cadastral survey model that use GPS to introduce GPS observation technique in cadastral survey and research that develop connection technologies are gone abuzz. The purpose of this research is to keep in step in such trend and grasp present condition and performance of surveying connection to common use GPS data processing software, and analyze data processing algorithm, and develop suitable GPS data processing software in our real condition regarding GPS data processing and result of control point calculation. This research studies analysis common use software and error occurrence by data processing method that college and company have. Also, It analyzes algorithm that is applied to existing GPS data processing software. After that we study algorithm that is most suitable with cadastral survey and then develop cadastral survey calculation software for new cadastral control points