• Korean Journal of Agricultural and Forest Meteorology
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• v.4 no.1
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• pp.23-28
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• 2002

Sets of weather variables for estimation of LWD were evaluated using CART(Classification And Regression Tree) models. Input variables were sets of hourly observations of air temperature at 0.3-m and 1.5-m height, relative humidity(RH), and wind speed that were obtained from May to September in 1997, 1998, and 1999 at 15 weather stations in iowa, Illinois, and Nebraska, USA. A model that included air temperature at 0.3-m height, RH, and wind speed showed the lowest misidentification rate for wetness. The model estimated presence or absence of wetness more accurately (85.5%) than the CART/SLD model (84.7%) proposed by Gleason et al. (1994). This slight improvement, however, was insufficient to justify the use of our model, which requires additional measurements, in preference to the CART/SLD model. This study demonstrated that the use of measurements of temperature, humidity, and wind from automated stations was sufficient to make LWD estimations of reasonable accuracy when the CART/SLD model was used. Therefore, implementation of crop disease-warning systems may be facilitated by application of the CART/SLD model that inputs readily obtainable weather observations.

• Korean Journal of Food Science and Technology
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• v.4 no.1
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• pp.6-12
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• 1972

Fay Elberta freestone peaches were harvested at four maturity levels as judged by skin color and firmness. They were ripened at $68^{\circ}F$ under 80 percent relative humidity for 4, 6, 8 and 10 days respectively prior to canning. Results indicate that both harvest maturity and ripening conditions are important factors influencing quality, flavor and composition of canned freestone peaches. Peaches harvested at $18{\sim}24$ pounds on a Magness-Taylor pressure tester with a 7/16' plunger(M1) failed to ripen satisfactorily. Fruits harvested at $13{\sim}17$ pounds (M2) pressure test ripened successfully at $68^{\circ}F$ within 6 to 8 days; and those harvested at 6 to 12 pounds (M3) needed 4 days for ripening at $68^{\circ}F$. Tree-ripened fruits (M4) were undesirable for canning because of the high percentage of bruised fruits. The optimum firmness for canning appears to be in the range of 1.5 to 3.0 pounds. The titratable acidity of peaches decreased during maturation and ripening. The tannin content of peaches at M1 maturity decreased with ripening at $68^{\circ}F$. But no appreciable change was observed in the M2 and M3 series which were ripened at $68^{\circ}F$ for 4 to 10 days. The volatile reducing substances (V.R.S.) increased as the peaches developed on the tree and also during post-harvest ripening. The effect of harvest maturity and post-harvest ripening on color grade of the canned peaches is presented. Little difference was found in the flavor and composition of peaches peeled by the cup-down lye peeling and the steam-peeling methods. The cup-down lye-peeling method might be most advantageous because of its higher peeling efficiency.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.43-52
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• 2024

Medical imaginings assume a important part in the analysis of tumors and cerebrospinal fluid (CSF) leak. Magnetic resonance imaging (MRI) is an image segmentation technology, which shows an angular sectional perspective of the body which provides convenience to medical specialists to examine the patients. The images generated by MRI are detailed, which enable medical specialists to identify affected areas to help them diagnose disease. MRI imaging is usually a basic part of diagnostic and treatment. In this research, we propose new techniques using the 4D-MRI image segmentation process to detect the brain tumor in the skull. We identify the issues related to the quality of cerebrum disease images or CSF leakage (discover fluid inside the brain). The aim of this research is to construct a framework that can identify cancer-damaged areas to be isolated from non-tumor. We use 4D image light field segmentation, which is followed by MATLAB modeling techniques, and measure the size of brain-damaged cells deep inside CSF. Data is usually collected from the support vector machine (SVM) tool using MATLAB's included K-Nearest Neighbor (KNN) algorithm. We propose a 4D light field tool (LFT) modulation method that can be used for the light editing field application. Depending on the input of the user, an objective evaluation of each ray is evaluated using the KNN to maintain the 4D frequency (redundancy). These light fields' approaches can help increase the efficiency of device segmentation and light field composite pipeline editing, as they minimize boundary artefacts.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.2
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• pp.183-189
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• 2010

A localization system for indoor robots is an important technology for robot navigation in a building. Our localization system imports the GPS system and consists of more than 3 satellite beacons and a receiver. Each beacon emits both an ultrasonic wave and radio frequency. The receiver in the robot computes the distance from it to the beacon by measuring the flying time difference between ultrasonic wave and radio frequency. It then computes its position with the distance information from more than 3 beacons whose positions are known. However, the distance information includes errors caused from the ultrasonic sensors; we found it to be limited to within one period of a wave (${\pm}2\;cm$ tolerance). This paper presents a method for predicting the maximum position error due to distance information errors by using Taylor expansion and singular value decomposition (SVD). The paper also proposes a measuring parameter such as sensitivity to represent the accuracy of the indoor robot localization system in determining the robot's position with regards to the distance error.

• Geomechanics and Engineering
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• v.32 no.6
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• pp.583-600
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• 2023

The resilient modulus (M_R) of various pavement materials plays a significant role in the pavement design by a mechanistic-empirical method. The M_R determination is done by experimental tests that need time and money, along with special experimental tools. The present paper suggested a novel hybridized extreme gradient boosting (XGB) structure for forecasting the M_R of modified base materials subject to wet-dry cycles. The models were created by various combinations of input variables called deep learning. Input variables consist of the number of W-D cycles (WDC), the ratio of free lime to SAF (CSAFR), the ratio of maximum dry density to the optimum moisture content (DMR), confining pressure (σ₃), and deviatoric stress (σ_d). Two XGB structures were produced for the estimation aims, where determinative variables were optimized by particle swarm optimization (PSO) and black widow optimization algorithm (BWOA). According to the results' description and outputs of Taylor diagram, M1 model with the combination of WDC, CSAFR, DMR, σ₃, and σ_d is recognized as the most suitable model, with R² and RMSE values of BWOA-XGB for model M1 equal to 0.9991 and 55.19 MPa, respectively. Interestingly, the lowest value of RMSE for literature was at 116.94 MPa, while this study could gain the extremely lower RMSE owned by BWOA-XGB model at 55.198 MPa. At last, the explanations indicate the BWO algorithm's capability in determining the optimal value of XGB determinative parameters in M_R prediction procedure.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.43 no.2
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• pp.113-119
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• 1998

Spatial patterns of soil temperature on sloping lands are related to the amount of solar irradiance at the surface. Since soil temperature is a critical determinant of many biological processes occurring in the soil, an accurate prediction of soil temperature distribution could be beneficial to agricultural and environmental management. However, at least two problems are identified in soil temperature prediction over natural sloped surfaces. One is the complexity of converting solar irradiances to corresponding soil temperatures, and the other, if the first problem could be solved, is the difficulty in handling large volumes of geo-spatial data. Recent developments in geographic information systems (GIS) provide the opportunity and tools to spatially organize and effectively manage data for modeling. In this paper, a simple model for conversion of solar irradiance to soil temperature is developed within a GIS environment. The irradiance-temperature conversion model is based on a geophysical variable consisting of daily short- and long-wave radiation components calculated for any slope. The short-wave component is scaled to accommodate a simplified surface energy balance expression. Linear regression equations are derived for 10 and 50 cm soil temperatures by using this variable as a single determinant and based on a long term observation data set from a horizontal location. Extendability of these equations to sloped surfaces is tested by comparing the calculated data with the monthly mean soil temperature data observed in Iowa and at 12 locations near the Tennessee - Kentucky border with various slope and aspect factors. Calculated soil temperature variations agreed well with the observed data. Finally, this method is applied to a simulation study of daily mean soil temperatures over sloped corn fields on a 30 m by 30 m resolution. The outputs reveal potential effects of topography including shading by neighboring terrain as well as the slope and aspect of the land itself on the soil temperature.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.112-121
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• 1997

In this paper, we study a model parameter compensation method for noise-robust speech recognition. We study model parameter compensation on a sentence by sentence and no other informations are used. Parallel model combination(PMC), well known as a model parameter compensation algorithm, is implemented and used for a reference of performance comparision. We also propose a modified PMC method which tunes model parameter with an association factor that controls average variability of gaussian mixtures and variability of single gaussian mixture per state for more robust modeling. We obtain a re-estimation solution of environmental variables based on the expectation-maximization(EM) algorithm in the cepstral domain. To evaluate the performance of the model compensation methods, we perform experiments on speaker-independent isolated word recognition. Noise sources used are white gaussian and driving car noise. To get corrupted speech we added noise to clean speech at various signal-to-noise ratio(SNR). We use noise mean and variance modeled by 3 frame noise data. Experimental result of the VTS approach is superior to other methods. The scheme of the zero order VTS approach is similar to the modified PMC method in adapting mean vector only. But, the recognition rate of the Zero order VTS approach is higher than PMC and modified PMC method based on log-normal approximation.

• Journal of the Korean GEO-environmental Society
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• v.15 no.7
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• pp.59-66
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• 2014

Nowadays, some studies are performed in order to introduce the Limit State Design method widely used in foreign work sites. LRFD (Load Resistance Factor Design) method is widely used in the fields in which the data accumulation is possible - such as deep foundations, and shallow foundations, etc. The limit state design in the retaining walls is insufficient in the country owing to difficulties applying load tests. The limit state design method for retaining wall structures are studied based upon the National Retaining wall Design Standard legislated in 2008 by Ministry of Land, Transport, and Maritime Affairs. In this paper several retaining walls were calculated according to LRFD design criteria analysis using the general program with limit state design method and the factor of safety for sliding and overturning. Comparing with their results, the Taylor's series simple reliability analysis was performed. In the analysis results of retaining wall section, safety factors calculated by LRFD were found to be lowered than those calculated in current WSD, and it is possibly judged to be economic design by changing wall dimensions. In the future, pre-assessment of the geotechnical data for ensuring the reliability and the studies including reinforced retaining walls with ground anchor are needed.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.164-171
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• 2022

Frankliniella occidentalis is an invasive pest insect, which affects over 500 different species of host plants and transmits viruses (tomato spotted wilt virus; TSWV). Despite their efficiency in controling insect pests, pesticides are limited by residence, cost and environmental burden. Therefore, a fixed-precision level sampling plan was developed. The sampling method for F. occidentalis adults in pepper greenhouses consists of spatial distribution analysis, sampling stop line, and control decision making. For sampling, the plant was divided into the upper part(180 cm above ground), middle part (120-160 cm above ground), and lower part (70-110 cm above ground). Through ANCOVA, the P values of intercept and slope were estimated to be 0.94 and 0.87, respectively, which meant there were no significant differences between values of all the levels of the pepper plant. In spatial distribution analysis, the coefficients were derived from Taylor's power law (TPL) at pooling data of each level in the plant, based on the 3-flowers sampling unit. F. occidentalis adults showed aggregated distribution in greenhouse peppers. TPL coefficients were used to develop a fixed-precision sampling stop line. For control decision making, the pre-referred action thresholds were set at 3 and 18. With two action thresholds, N_max values were calculated at 97 and 1149, respectively. Using the Resampling Validation for Sampling Program (RVSP) and the results gained from the greenhouses, the simulated validation of our sampling method showed a reasonable level of precision.

• KDI Journal of Economic Policy
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• v.34 no.1
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• pp.135-168
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• 2012

This study analyzes ways to detect protest responses (hereafter, PR zero-bid) in the contingent valuation method (CVM). In order to distinguish PR zero-bids from true zero-bids (non-PR zero bids), this study adopts the concept of the implicit willingness to pay employing the Hicksian compensating surplus and the Taylor's 1st order approximation. When a respondent proposes a zero-bid (i.e., WTP=0) and chooses a PR filtering item to indicate that her implicit WTP is not necessary zero, her response is identified as a PR zero bid. PR filtering items falling into the PR zero bids category include the uncertainty of information, distrust in the government and project achievement, disagreement to project plans, discontent with the fairness of public works and their payment method and animosity against the CVM itself. The empirical analysis shows that PR zero bids take place systematically in particular respondent groups: respondents who have never used similar facilities before nor plans to use the facility provided by the public project, the employed, and low income groups. In conclusion, the study suggests that a CVM questionnaire needs to be designed carefully to minimize problems associated with PR zero bids and the potential risks of having sample selection bias should be concerned.