• KOREAN JOURNAL OF CROP SCIENCE
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• v.28 no.3
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• pp.285-290
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• 1983

Two methods were tested to establish the cropping period for rice cultivation using the meteorological data. The Hanyu-Uchijima method was based on the normal average temperature to select the earliest possible transplanting date (ETD), the earliest heading date (EHD), the optimum heading date (OHD) and the latest maturing date (LMD). The probability method was based on the temperature occurrence probability. The cropping period based on the probability method gave higher stability than H-U method for year variability. The ETD by the probability of 75 to 90 percents was May 12 to 22 for northern part of Korea, May 15 to 25 for east coastal area and May 4 to 16 for southern part, respectively. In Chuncheon area, the rice varieties requiring more than 1700 degree-days from transplanting to heading might not be appropriate due to low temperature condition and those requiring 1900 degree days were not allowable in Kangreung area. The OHD was July 30 to August 8 in northern part of the country and August 11 to 16 in southern part for Tongil varieties which demand higher temperature than common Japonica varieties. The OHD for Japonica varieties were 5 to 7 days later than Tongil varieties. The LMD was September 30 to October 2 in northern part, October 13 to 14 in east costal area and October 7 to 14 in southern part, and was earlier than the first frost date.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.403-413
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• 2022

Classification and analysis are improved factors for the realtime automation system. In the field of agriculture, the cultivation of different paddy crop depends on the atmosphere and the soil nature. We need to analyze the moisture level in the area to predict the type of paddy that can be cultivated. For this process, Ensemble Modulation Pattern system and Block Probability Neural Network based classification models are used to analyze the moisture and temperature of land area. The dataset consists of the collections of moisture and temperature at various data samples for a land. The Ensemble Modulation Pattern based feature analysis method, the extract of the moisture and temperature in various day patterns are analyzed and framed as the pattern for given dataset. Then from that, an improved neural network architecture based on the block probability analysis are used to classify the data pattern to predict the class of paddy crop according to the features of dataset. From that classification result, the measurement of data represents the type of paddy according to the weather condition and other features. This type of classification model assists where to plant the crop and also prevents the damage to crop due to the excess of water or excess of temperature. The result analysis presents the comparison result of proposed work with the other state-of-art methods of data classification.

• Journal of the military operations research society of Korea
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• v.22 no.2
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• pp.166-181
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• 1996

Aircraft survivability is determined by the susceptibility and the vulnerability. The aircraft susceptibility and vulnerability depend upon the hardware and software factors. Each of the hardware and software factors consisted of the qualitative and quantitative attributes varies according to the time of the mission. In order to establish the mathermatical model to analyze and evaluate the aircraft survivability, qualitative factors have to be transformed into quantitative factors. Even if many researches in the area of dynamic concept analysis and conversion of qualitative factors into the quantitative factors has been insufficient. This research enhances these insufficient area by developing a reliable aircarft survivability analysis method. The major areas of this research are as follows. First, a method for the conversion of the qualitative factors into the quantitative factors is developed by combining the Fuzzy Set Theory concept and the Delphi Technique. Second, by using the stochastic network diagram for the dynamic survivability analysis, the aircraft survivability and the probability of kill are calculated from the state probability for the situation during mission. The advantage of the analysis technique developed in this research includes ease of use and flexibility. In other words, in any given aircraft's mission execution under any variable probability density function, the developed computer program is able to analyze and evaluate the aircraft survivability.

• Structural Engineering and Mechanics
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• v.42 no.1
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• pp.121-129
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• 2012

All contemporary seismic Codes have adopted smooth design acceleration response spectra, which have derived by statistical analysis of many elastic response spectra of natural accelerograms. The above smooth design spectra are characterized by two main branches, an horizontal branch that is 2.5 times higher than the peak ground acceleration, and a declining parabolic branch. According to Eurocode EN/1998, the period range of the horizontal, flat branch is extended from 0.1 s, for rock soils, up to 0.8 s for softer ones. However, from many natural recorded accelerograms of important earthquakes, the real spectral amplification factor appears to be much higher than 2.5 and this means that the spectrum leads to an unsafe seismic design of the structures. This point is an issue open to question and it is the object of the present study. In the present paper, the spectral amplification factor of the smooth design acceleration spectra is re-calculated on the grounds of a known "reliability index" for a desired probability of exceedance. As a pilot scheme, the seismic area of Greece is chosen, as it is the most seismically hazardous area in Europe. The accelerograms of the 82 most important earthquakes, which have occurred in Greece during the last 38 years, are used. The soil categories are taken into account according to EN/1998. The results that have been concluded from these data are compared with the results obtained from other strong earthquakes reported in the World literature.

• Journal of Environmental Impact Assessment
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• v.30 no.1
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• pp.13-23
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• 2021

In this study, we performed a Random Walker analysis to predict the Major Movement Paths of otters. The scope of the research was a simulation analysis with a radius of 7.5 km set as the final range centered on the Ansim-wetland in Daegu City, and a field survey was used to verify the model. The number of virtual otters was set to 1,000, the number of moving steps was set to 1,000 steps per grid, and simulations were performed on a total of 841 grids. As a result of the analysis, an average of 147.6 objects arrived at the boundary point under the condition of an interval of 50 m. As a result of the simulation verification, 8 points (13.1%) were found in the area where the movement probability was very high, and 9 points (14.8%) were found in the area where the movement probability was high. On the other hand, in areas with low movement paths probabilities, there were 8 points (13.1%) in low areas and 4 points (6.6%) in very low areas. Simulation verification results In areas with high otter values, the actual otter format probability was particularly high. In addition, as a result of investigating the correlation with the otter appearance point according to the unit area of the evaluation star of the movement probability, it seems that 6.8 traces were found per unit area in the area where the movement probability is the highest. In areas where the probability of movement is low, analysis was performed at 0.1 points. On the side where otters use the major movement paths of the river area, the normal level was exceeded, and as a result, in the area, 23 (63.9%), many form traces were found, along the major movement paths of the simulation. It turned out that the actual otter inhabits. The EN-Simulator analysis can predict how spatial properties affect the likelihood of major movement paths selection, and the analytical values are used to utilize additional habitats within the major movement paths. It is judged that it can be used as basic data such as to grasp the danger area of road kill in advance and prevent it.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.

• Journal of Ocean Engineering and Technology
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• v.28 no.1
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• pp.69-76
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• 2014

Survivability assessments and vulnerability reductions are required in warship design. A warship's survivability is assessed by its susceptibility, vulnerability, and recoverability. In this paper, an integrated survivability assessment for a warship subjected to multiple hits is introduced. The methodology aims at integrating a survivability assessment into an early stage of warship design. The hull surface is idealized using typical geometries for RCS (Radar Cross Section) detection probability and susceptibility. The Vulnerability is evaluated by using the shot-line. The recoverability is estimated using a survival time analysis. This enables the variation of survivability to be assessed. Several parameters may be varied to determine their effects on the survivability. The susceptibility is assessed by the probability of detecting the radar cross section of the subject and the probability of being hit based on a probability density function. The vulnerability is assessed by the kill probability based on the vulnerable area of critical components, according to the component's layout and redundancy. Recoverability is assessed by the recovery time for damaged critical components.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.301-309
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• 2006

In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.04a
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• pp.157-164
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• 1998

An elasto-plastic stochastic finite element method is developed to evaluate the probability of failure of the underground structure. The Mohr-Coulomb failure criteria is adopted for yield condition. The material properties such as the elastic modulus and the cohesion are assumed to be statistically independent random variables which are modeled as spatial stochastic fields. The displacements around the excavated area and the probability of the failure are examined by varying the coefficient of variance for each variables. It is found that the developed procedure can provide the proper probabilistic information about the failure of the underground structure

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.4
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• pp.72-85
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• 2019

The goal of this study is to predict sexual violence crimes, which is an routine risk. The study used to the Weight of Evidence on sexual violence crimes that occurred in partly Cheongju-si for five years from 2011 to 2015. The results are as follows. First, application and analysis of the Weight of Evidence that considers the weight of evidence characteristics showed 8 out of total 26 evidences that are used for a sexual violence crimes risk prediction. The evidences were residential area, date of use permission for building, individual housing price, floor area ratio, number of basement floor, lot area, security light and recreational facility; which satisfied credibility in the process of calculating weight. Second, The weight calculated 8 evidences were combined to create the prediction map in the end. The map showed that 16.5% of sexual violence crimes probability occurs in 0.3㎢, which is 3.3% of the map. The area of probability of 34.5% is 1.8㎢, which is 19.0% of the map and the area of probability of 75.5% is 2.0㎢, which is 20.7% of the map. This study derived the probability of occurrence of sexual violence crime risk and environmental factors or conditions that could reduce it. Such results could be used as basic data for devising preemptive measures to minimize sexual violence, such as police activities to prevent crimes.