• Korean Journal of Remote Sensing
• /
• v.14 no.1
• /
• pp.53-68
• /
• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Journal of Bio-Environment Control
• /
• v.28 no.4
• /
• pp.279-285
• /
• 2019

To estimate daily canopy photosynthesis, accurate estimation of canopy light interception according to a daily solar position is needed. However, this process needs a lot of cost, time, manpower, and difficulty when measuring manually. Various modeling approaches have been applied so far, but it was difficult to accurately estimate light interception by conventional methods. The objective of this study is to estimate the spatial distributions of light interception and photosynthetic rate of paprika with time by using 3D-scanned plant models and optical simulation. Structural models of greenhouse paprika were constructed with a portable 3D scanner. To investigate the change in canopy light interception by surrounding plants, the 3D paprika models were arranged at $1{\times}1$ and $9{\times}9$ isotropic forms with a distance of 60 cm between plants. The light interception was obtained by optical simulation, and the photosynthetic rate was calculated by a rectangular hyperbola model. The spatial distributions of canopy light interception of the 3D paprika model showed different patterns with solar altitude at 9:00, 12:00, and 15:00. The total canopy light interception decreased with an increase of surrounding plants like an arrangement of $9{\times}9$, and the decreasing rate was lowest at 12:00. The canopy photosynthetic rate showed a similar tendency with the canopy light interception, but its decreasing rate was lower than that of the light interception due to the saturation of photosynthetic rate of upper leaves of the plants. In this study, by using the 3D-scanned plant model and optical simulation, it was possible to analyze the light interception and photosynthesis of plant canopy under various conditions, and it can be an effective way to estimate accurate light interception and photosynthesis of plants.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.24 no.7
• /
• pp.848-857
• /
• 2018

Recently, around the world, active development of new renewable energy sources including solar power, waves, and fuel cells, etc. has taken place. Particularly, floating offshore wind farms have been developed for saving costs through large scale production, using high-quality wind power and minimizing noise damage in the ocean area. The development of floating wind farms requires an evaluation of the Maritime Safety Audit Scheme under the Maritime Safety Act in Korea. Floating wind farms shall be assessed by applying the line and area concept for systematic development, management and utilization of specified sea water. The development of appropriate evaluation methods and standards is also required. In this study, proper standards for marine traffic surveys and assessments were established and a systemic treatment was studied for assessing marine spatial area. First, a marine traffic data collector using AIS or radar was designed to conduct marine traffic surveys. In addition, assessment methods were proposed such as historical tracks, traffic density and marine traffic pattern analysis applying the line and area concept. Marine traffic density can be evaluated by spatial and temporal means, with an adjusted grid-cell scale. Marine traffic pattern analysis was proposed for assessing ship movement patterns for transit or work in sea areas. Finally, conceptual design of a Marine Traffic and Safety Assessment Solution (MaTSAS) was competed that can be analyzed automatically to collect and assess the marine traffic data. It could be possible to minimize inaccurate estimation due to human errors such as data omission or misprints through automated and systematic collection, analysis and retrieval of marine traffic data. This study could provides reliable assessment results, reflecting the line and area concept, according to sea area usage.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.31 no.3
• /
• pp.158-169
• /
• 2019

A probabilistic model that can predict the residual useful lifetime of structure is formulated by using the gamma process which is one of the stochastic processes. The formulated stochastic model can take into account both the sampling uncertainty associated with damages measured up to now and the temporal uncertainty of cumulative damage over time. A method estimating several parameters of stochastic model is additionally proposed by introducing of the least square method and the method of moments, so that the age of a structure, the operational environment, and the evolution of damage with time can be considered. Some features related to the residual useful lifetime are firstly investigated into through the sensitivity analysis on parameters under a simple setting of single damage data measured at the current age. The stochastic model are then applied to the rubble-mound breakwater straightforwardly. The parameters of gamma process can be estimated for several experimental data on the damage processes of armor rocks of rubble-mound breakwater. The expected damage levels over time, which are numerically simulated with the estimated parameters, are in very good agreement with those from the flume testing. It has been found from various numerical calculations that the probabilities exceeding the failure limit are converged to the constraint that the model must be satisfied after lasting for a long time from now. Meanwhile, the expected residual useful lifetimes evaluated from the failure probabilities are seen to be different with respect to the behavior of damage history. As the coefficient of variation of cumulative damage is becoming large, in particular, it has been shown that the expected residual useful lifetimes have significant discrepancies from those of the deterministic regression model. This is mainly due to the effect of sampling and temporal uncertainties associated with damage, by which the first time to failure tends to be widely distributed. Therefore, the stochastic model presented in this paper for predicting the residual useful lifetime of structure can properly implement the probabilistic assessment on current damage state of structure as well as take account of the temporal uncertainty of future cumulative damage.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.17 no.3
• /
• pp.339-346
• /
• 2019

Based on the $8^{th}$ Basic Plan for Electric Power Demand and Supply, an estimation has been made for inventories and characteristics of spent fuel (SF) to be generated from existing and planned nuclear power plants. The characteristics under consideration in this study are dimensions, fuel array, $^{235}U$ enrichment, discharge burnup, and cooling time for each fuel assembly. These are essentially needed for designing a disposal facility for SFs. It appears that the anticipated quantity by the end of 2082 is about 62,500 assemblies for PWR SFs. The inventories of Westinghouse-type and Korean-type SFs were revealed to be 60% and 40%, respectively as of the end of 2018. The proportion of SFs with initial $^{235}U$ enrichment below 4.5 weight percent (wt%) was shown to be approximately 90% in total as of the end of 2018. As of 2077, more than 97% of SFs generated from Westinghouse-type nuclear reactors were shown to have cooling time of over 50 years. As of 2125, more than 98% of SFs generated from Korean-type nuclear reactors were shown to have cooling time of over 45 years. Based on these results, for the efficient design of a disposal system, it is reasonable to adopt two types of reference spent fuel. SF of KSFA with $^{235}U$ enrichment of 4.5 wt%, discharge burnup of 55 GWd/tU, and cooling time of 50 years was determined as reference fuel for Westinghouse-type SFs; SF of PLUS7 with $^{235}U$ enrichment of 4.5 wt%, discharge burnup of 55 GWd/tU, and cooling time of 45 years was determined as reference fuel for Korean-type SFs.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.21 no.1
• /
• pp.55-64
• /
• 2019

The flowering seasons can be advanced due to climate change that would cause an abnormally warm winter. Such warm winter would increase the frequency of crop damages resulted from sudden occurrences of low temperature before and after the vegetative growth stages, e.g., the period from germination to flowering. The degree and pattern of freezing damage would differ by the development stage of each individual fruit tree even in an orchard. A critical temperature, e.g., killing temperature, has been used to predict freeze damage by low-temperature conditions under the assumption that such damage would be associated with the development stage of a fruit flower bud. However, it would be challenging to apply the critical temperature to a region where spatial variation in temperature would be considerably high. In the present study, a phenological model was used to estimate major bud development stages, which would be useful for prediction of regional risks for the freeze damages. We also derived a linear function to calculate a probabilistic freeze risk in spring, which can quantitatively evaluate the risk level based solely on forecasted weather data. We calculated the dates of freeze damage occurrences and spatial risk distribution according to main production areas by applying the spring freeze risk function to apple, peach, and pear crops in 2018. It was predicted that the most extensive low-temperature associated freeze damage could have occurred on April 8. It was also found that the risk function was useful to identify the main production areas where the greatest damage to a given crop could occur. These results suggest that the freezing damage associated with the occurrence of low-temperature events could decrease providing early warning for growers to respond abnormal weather conditions for their farm.

• Journal of the Korean Wood Science and Technology
• /
• v.49 no.5
• /
• pp.399-415
• /
• 2021

This study was conducted to suggest the optimal periods for planting and felling Larix kaempferi tree by monitoring its cambial activity period. In addition, the heat summation to induce the cambial activity of Larix kaempferi was investigated. The study sites were at Mt. Worak and Mt. Midong. After selecting 5 trees at Mt. Worak and Mt. Midong, the cambium samples were collected using a mini trephor with 2 mm diameter from April 7 to October 6, 2017 at Mt. Worak, and from April 7 to September 29, 2017 at Mt. Midong. After the collected cambium samples were embedded in PEG2000, transverse thin sections with a thickness of 10 to 15 ㎛ were prepared using a microtome. One Larix kaempferi sample from each site, Mt. Worak and Mt. Midong, in which the accurate monitoring of cambial activity was impossible due to the formation of traumatic resin canal, was excluded from the study. The observation of the initiation date of cambial activity under a light microscopy revealed that 2 specimens from Mt. Worak and 3 from Mt. Midong showed the initiation on April 28. The remaining 2 specimens of Mt. Worak and 1 specimen of Mt. Midong were initiated on May 4, which was a week later than the others. The heat summation that induced the initiation of cambial activity was 196.4-271.8 at Mt. Worak and 204.7-277.3 at Mt. Midong, which was similar. The termination of cambial activity occurred between August 4 and 25 at Mt. Worak, and between August 4 and September 1 at Mt. Midong. Based on the above results, it was found that the optimal planting period for Larix kaempferi in Mt. Worak and Mt. Midong was before April, about a month before the cambium activity, and the felling period was from October when the cambial activity was completely terminated.

• Journal of Intelligence and Information Systems
• /
• v.27 no.1
• /
• pp.65-82
• /
• 2021

Stock market investors are generally split into foreign investors, institutional investors, and individual investors. Compared to individual investor groups, professional investor groups such as foreign investors have an advantage in information and financial power and, as a result, foreign investors are known to show good investment performance among market participants. The purpose of this study is to propose an investment strategy that combines investor-specific transaction information and machine learning, and to analyze the portfolio investment performance of the proposed model using actual stock price and investor-specific transaction data. The Korea Exchange offers daily information on the volume of purchase and sale of each investor to securities firms. We developed a data collection program in C# programming language using an API provided by Daishin Securities Cybosplus, and collected 151 out of 200 KOSPI stocks with daily opening price, closing price and investor-specific net purchase data from January 2, 2007 to July 31, 2017. The self-organizing map model is an artificial neural network that performs clustering by unsupervised learning and has been introduced by Teuvo Kohonen since 1984. We implement competition among intra-surface artificial neurons, and all connections are non-recursive artificial neural networks that go from bottom to top. It can also be expanded to multiple layers, although many fault layers are commonly used. Linear functions are used by active functions of artificial nerve cells, and learning rules use Instar rules as well as general competitive learning. The core of the backpropagation model is the model that performs classification by supervised learning as an artificial neural network. We grouped and transformed investor-specific transaction volume data to learn backpropagation models through the self-organizing map model of artificial neural networks. As a result of the estimation of verification data through training, the portfolios were rebalanced monthly. For performance analysis, a passive portfolio was designated and the KOSPI 200 and KOSPI index returns for proxies on market returns were also obtained. Performance analysis was conducted using the equally-weighted portfolio return, compound interest rate, annual return, Maximum Draw Down, standard deviation, and Sharpe Ratio. Buy and hold returns of the top 10 market capitalization stocks are designated as a benchmark. Buy and hold strategy is the best strategy under the efficient market hypothesis. The prediction rate of learning data using backpropagation model was significantly high at 96.61%, while the prediction rate of verification data was also relatively high in the results of the 57.1% verification data. The performance evaluation of self-organizing map grouping can be determined as a result of a backpropagation model. This is because if the grouping results of the self-organizing map model had been poor, the learning results of the backpropagation model would have been poor. In this way, the performance assessment of machine learning is judged to be better learned than previous studies. Our portfolio doubled the return on the benchmark and performed better than the market returns on the KOSPI and KOSPI 200 indexes. In contrast to the benchmark, the MDD and standard deviation for portfolio risk indicators also showed better results. The Sharpe Ratio performed higher than benchmarks and stock market indexes. Through this, we presented the direction of portfolio composition program using machine learning and investor-specific transaction information and showed that it can be used to develop programs for real stock investment. The return is the result of monthly portfolio composition and asset rebalancing to the same proportion. Better outcomes are predicted when forming a monthly portfolio if the system is enforced by rebalancing the suggested stocks continuously without selling and re-buying it. Therefore, real transactions appear to be relevant.

• Journal of Korea Water Resources Association
• /
• v.55 no.12
• /
• pp.1041-1052
• /
• 2022

This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km²) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m³/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m²/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q₃₅₅ condition.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.50 no.4
• /
• pp.20-36
• /
• 2022

This study aims to provide basic data for high-quality street tree management by setting reasonable management items and appropriate unit prices by reviewing the adequacy of current street tree management. Currently, street tree management items, except for street tree pruning, use general landscape tree quantity per unit for the street tree management quantity per unit. KEPCO (Korea Electric Power Corporation) applied pruning items from standard electric production infrastructure and carried out the activities at an average unit price of 51% lower for heavy pruning and 39% lower for light pruning than the standard estimate. This was judged to be a level that could not maintain or increase the quality of street tree management. It was determined that an appropriate standard unit price for street tree management was necessary. To improve the quantity per unit for the proper management of street trees, it was necessary to review costs in the field. However, due to the absence of data on actual construction costs in the domestic landscape field, detailed items of the US RSMeans Building Construction Cost Data (RSMeans) were reviewed, and the actual construction costs were calculated by applying personal domestic expenses. As a result, the standard of the estimated unit showed a good ratio of 107% for heavy pruning of street tree pruning compared to the actual construction cost, but light pruning was underestimated with a 59% ratio. Shrub pruning was 82%, weeding was 92%, tree fertilization was 87%, and windbreak wall installation was 91% under-engineered. In addition, it was also confirmed that the watering by sprinkler trucks and chemical spraying were over-designed compared to the actual construction cost at the rates of 118% and 124%, respectively. Due to the specificity of the street trees, the increase in personal expenses and the input cost of equipment, such as road safety controls, were judged to be the main cause of the underestimation of items. Therefore, it is necessary to add items related to street trees and general landscape trees to the landscape maintenance items of the standard of the estimated unit.