• Korean Journal of Remote Sensing
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• v.21 no.6
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• pp.445-456
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• 2005

The land surface parameters should be determined with sufficient accuracy, because these play an important role in climate change near the ground. As the surface reflectance presents strong anisotropy, off-nadir viewing results a strong dependency of observations on the Sun - target - sensor geometry. They contribute to the random noise which is produced by surface angular effects. The principal objective of the study is to provide a database of accurate surface reflectance eliminated the angular effects from MODIS 250m reflective channel data over Korea. The MODIS (Moderate Resolution Imaging Spectroradiometer) sensor has provided visible and near infrared channel reflectance at 250m resolution on a daily basis. The successive analytic processing steps were firstly performed on a per-pixel basis to remove cloudy pixels. And for the geometric distortion, the correction process were performed by the nearest neighbor resampling using 2nd-order polynomial obtained from the geolocation information of MODIS Data set. In order to correct the surface anisotropy effects, this paper attempted the semiempirical kernel-driven Bi- directional Reflectance Distribution Function(BRDF) model. The algorithm yields an inversion of the kernel-driven model to the angular components, such as viewing zenith angle, solar zenith angle, viewing azimuth angle, solar azimuth angle from reflectance observed by satellite. First we consider sets of the model observations comprised with a 31-day period to perform the BRDF model. In the next step, Nadir view reflectance normalization is carried out through the modification of the angular components, separated by BRDF model for each spectral band and each pixel. Modeled reflectance values show a good agreement with measured reflectance values and their RMSE(Root Mean Square Error) was totally about 0.01(maximum=0.03). Finally, we provide a normalized surface reflectance database consisted of 36 images for 2001 over Korea.

• Journal of Korea Port Economic Association
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• v.32 no.3
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• pp.95-108
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• 2016

China has recently advocated a national strategy called "One Belt One Road" and transferred to execution to refine it into detailed action plans and has continued to fix the complement. However, the Korean Peninsula, including the North Korea remains could not be included at all in the Chinese development policy and framework in terms of the International Logistics. Currently it is raised between Korea-China rail ferry system again and that is when we need to make effective policy development on international multimodal transport system in Northeast Asia. This paper introduces the K-LB (Korea LandBridge) as its execution plan and conducted a feasibility study on this. K-LB consists of a Korea-Russian train ferry system based in Pohang Yeongil New Port(light-wing) and a Korea-China train ferry system based in Saemangeum New Port(left-wing). These two wings are linked to the existing rail system in Korea. This study is convinced that the K-LB is an effective international logistics system in the current terms and conditions and also demonstrated that it is feasible to introduce th K-LB on the peninsula. More strictly speaking, through a linear programming under objective function that minimize the transport cost quantified prior to demonstrate the feasibility, the available ranges and conditions for the transportation costs that are ensured the effectiveness of the K-LB are presented as results. According to the results, if the transport cost of K-LB is cheaper about 34.5% than that of sea transport such as container transport, the object goods may be transported by K-LB on this route. It means that the K-LB system has a competitive advantage due to more rapid customs clearance as well as omitted loading and unloading procedures over container transportation system. It also noted that the threshold level may not be large. Therefore, K-LB has competitive enough to prove its introduction in the Northeast Asian logistics system.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.1
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• pp.55-64
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• 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 agriculture & life science
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• v.50 no.2
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• pp.73-82
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• 2016

Best drought tolerance index was determined through statistics analysis and growth appearance of drought tolerant plants was determined by cultivation in pot and sloping land. For determination of best drought tolerant indicators, RD(Resistant dry days), LD(Leaf area), UTR(Unit transpiration), RWC(Relative water content), RWL(Relative water loss), LA(Leaf area), SN(Stoma unmber) and SA(Stoma area) were carried out by correlation and PCA analysis. RWL and UTR were affected on plant drought tolerance according to comparison among six indices for resistant dry days. The PCs axes separated SA, LA, RD and RWC and SN. UTR was negatively correlated with SA, RWL were also negatively correlated with RWC and SN. RWL and UTR were proved best selection indicator for the selection of drought tolerant species. Ulmus parvifolia, Bidens bipinnata, Patrinia villosa, Kummerowia striata, Arundinella hirta, Artemisia gmelini etc. were selected drought tolerant plants. Shoot growth appearance of drought resistant plants was differed pot and sloping land. Shoot growth and leaf number was no significant differences between the pot and sloping land. However, root growth of drought tolerant plants was all the difference between two cultivation. T/R ratio of drought tolerant plants was also found a big difference. T/R ratio of drought tolerant plants in sloping land was lower than that of pot. These results will be served efficiently plant breeding.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.419-430
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• 2023

In response to the periodic occurrence of cyanobacterial blooms in Korean freshwaters, various types of cyanobacteria removal technologies are being developed and implemented. Due to the differing principles behind these technologies, it is difficult to compare and evaluate their removal efficiencies. In this study, a standardized method for evaluating cyanobacteria removal efficiency was proposed by utilizing the results of removal operations using a mobile cyanobacteria removal device in the Seohwacheon area of Daechung Reservoir. During removal operations, the decrease in chlorophyll-a (chl-a) concentration (ΔChl-a) in the working area was calculated based on the amount of collected sludge, the efficiency rate, and the concentration of chl-a. Additionally, the required working days (WD) to reduce the chl-a concentration to 1 mg/m³ in the target area was calculated based on the area of the target zone, the maximum daily working area, and the efficiency rate. A method for calculating the cyanobacteria removal capacity was proposed based on the reduction rate of chl-a concentration in the water before and after the operation, the treatment capacity of the removal technology, and the water volume of the target area. The cyanobacteria removal capacity of the mobile cyanobacteria removal device used in this study was 6.64%/day (targeting the Seohwacheon area of Daechung Reservoir, approximately 500,000 m²), which was higher compared to other physical or physicochemical cyanobacteria removal technologies (0.02~4.72%/day). Utilizing the evaluation method of cyanobacteria removal efficiency presented in this study, it will be possible to compare and evaluate the cyanobacteria removal technologies currently being applied in Korea. This method could also be used to assess the performance and efficiency of physical or physicochemical combined cyanobacteria removal techniques in the "Guidelines for the Installation and Operation of Algae Removal Facilities and the Use of Algae Removal Agents" operated by the National Institute of Environmental Research.

• Journal of Nutrition and Health
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• v.46 no.1
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• pp.50-60
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• 2013

The aims of this study were to estimate daily intake of macrominerals from beverages, liquid teas, and liquid coffees and to evaluate their potential health risks for Korean children and adolescents (1-to 19 years old). Assessment of dietary intake was conducted using the actual level of sodium, calcium, phosphorus, potassium, and magnesium in non-alcoholic beverages and (207 beverages, 19 liquid teas, and 24 liquid coffees) the food consumption amount drawn from "The Fourth Korea National Health and Nutrition Examination Survey (2007-2009)". To estimate the dietary intake of non-alcoholic beverages, 6,082 children and adolescents (Scenario I) were compared with 1,704 non-alcoholic beverage consumption subjects among them (Scenario II). Calculation of the estimated daily intake of macrominerals was based on point estimates and probabilistic estimates. The values of probabilistic macromineral intake, which is a Monte-Carlo approach considering probabilistic density functions of variables, were presented using the probabilistic model. The level of safety for macrominerals was evaluated by comparison with population nutrient intake goal (Goal, 2.0 g/day) for sodium, tolerable upper intake level (UL) for calcium (2,500 mg/day) and phosphorus (3,000-3,500 mg/day) set by the Korean Nutrition Society (Dietary Reference Intakes for Koreans, KDRI). For total children and adolescents (Scenario I), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 7.93, 10.92, 6.73, 23.41, and 1.11, and 95th percentile daily intake of those was, respectively, 28.02, 44.86, 27.43, 98.14, and 3.87 mg/day. For consumers-only (Scenario II), mean daily intake of sodium, calcium, phosphorus, potassium, and magnesium estimated by probabilistic estimates using Monte Carlo simulation was, respectively, 19.10, 25.77, 15.83, 56.56, and 2.86 mg/day, and 95th percentile daily intake of those was, respectively, 62.67, 101.95, 62.09, 227.92, and 8.67 mg/day. For Scenarios I II, sodium, calcium, and phosphorus did not have a mean an 95th percentile intake that met or exceeded the 5% of Goal and UL.

• Explosives and Blasting
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• v.9 no.1
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• pp.3-13
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• 1991

The cautious blasting works had been used with emulsion explosion electric M/S delay caps. Drill depth was from 3m to 6m with Crawler Drill ${\phi}70mm$ on the calcalious sand stone (soft -modelate -semi hard Rock). The total numbers of test blast were 88. Scale distance were induced 15.52-60.32. It was applied to propagation Law in blasting vibration as follows. Propagtion Law in Blasting Vibration $V=K(\frac{D}{W^b})^n$ were V : Peak partical velocity(cm/sec) D : Distance between explosion and recording sites(m) W : Maximum charge per delay-period of eight milliseconds or more (kg) K : Ground transmission constant, empirically determind on the Rocks, Explosive and drilling pattern ets. b : Charge exponents n : Reduced exponents where the quantity $\frac{D}{W^b}$ is known as the scale distance. Above equation is worked by the U.S Bureau of Mines to determine peak particle velocity. The propagation Law can be catagorized in three groups. Cubic root Scaling charge per delay Square root Scaling of charge per delay Site-specific Scaling of charge Per delay Plots of peak particle velocity versus distoance were made on log-log coordinates. The data are grouped by test and P.P.V. The linear grouping of the data permits their representation by an equation of the form ; $V=K(\frac{D}{W^{\frac{1}{3}})^{-n}$ The value of K(41 or 124) and n(1.41 or 1.66) were determined for each set of data by the method of least squores. Statistical tests showed that a common slope, n, could be used for all data of a given components. Charge and reduction exponents carried out by multiple regressional analysis. It's divided into under loom over loom distance because the frequency is verified by the distance from blast site. Empirical equation of cautious blasting vibration is as follows. Over 30m ------- under l00m ${\cdots\cdots\cdots}{\;}41(D/sqrt[2]{W})^{-1.41}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}A$ Over 100m ${\cdots\cdots\cdots\cdots\cdots}{\;}121(D/sqrt[3]{W})^{-1.66}{\;}{\cdots\cdots\cdots\cdots\cdots}{\;}B$ where ; V is peak particle velocity In cm / sec D is distance in m and W, maximLlm charge weight per day in kg K value on the above equation has to be more specified for further understaring about the effect of explosives, Rock strength. And Drilling pattern on the vibration levels, it is necessary to carry out more tests.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.