• Communications for Statistical Applications and Methods
• /
• v.17 no.5
• /
• pp.713-724
• /
• 2010

Calculating or estimating the proper insurance premium is very important decision making process for both the policyholder and the insurance company. The credibility theory is one of the most important theories in actuarial science to get the proper premium. In this research, we introduce the rule of relative exposure volume, the square root rule and the B$\ddot{u}$hlmann credibility, and estimate the new premiums based on these methods. By real data analysis, the accuracy of these credibility methods are compared.

• The Korean Journal of Applied Statistics
• /
• v.24 no.2
• /
• pp.279-292
• /
• 2011

Credibility theory is one of the most important theories of actuarial science to calculate the proper insurance premium. In this paper, the rule of relative exposure volume, the square root rule, the B$\"{u}$hlmann credibility and B$\"{u}$hlmann-Straub credibility with the basic concept of credibility have been introduced, Also, we estimate new premiums based on these methods for real data. As a result, the rule of relative exposure volume provides the highest accuracy.

• Journal of Ocean Engineering and Technology
• /
• v.34 no.3
• /
• pp.167-179
• /
• 2020

Recently, the increasing importance of artificial intelligence (AI) technology has led to its increased use in various fields in the shipbuilding and marine industries. For example, typical scenarios for AI include production management, analyses of ships on a voyage, and motion prediction. Therefore, this study was conducted to predict a response amplitude operator (RAO) through AI technology. It used a neural network based on one of the types of AI methods. The data used in the neural network consisted of the properties of the vessel and RAO values, based on simulating the in-house code. The learning model consisted of an input layer, hidden layer, and output layer. The input layer comprised eight neurons, the hidden layer comprised the variables, and the output layer comprised 20 neurons. The RAO predicted with the neural network and an RAO created with the in-house code were compared. The accuracy was assessed and reviewed based on the root mean square error (RMSE), standard deviation (SD), random number change, correlation coefficient, and scatter plot. Finally, the optimal model was selected, and the conclusion was drawn. The ultimate goals of this study were to reduce the difficulty in the modeling work required to obtain the RAO, to reduce the difficulty in using commercial tools, and to enable an assessment of the stability of medium/small vessels in waves.

• Korean Journal of Poultry Science
• /
• v.47 no.2
• /
• pp.107-114
• /
• 2020

This study was conducted to investigate the variation in nutrient composition of oilseed meals and to develop prediction equations for amino acid concentrations. Energy and nutrient contents were determined in a total of 1,380 feed ingredient samples including copra byproducts, corn distillers, dried grains with solubles, palm kernel byproducts, and soybean meal. The ingredient samples were imported to the Republic of Korea between 2006 and 2015. Data were analyzed using the MIXED procedure of SAS. The regression procedure of SAS was used to generate the prediction equation for the lysine concentration using the crude protein (CP) concentration as an independent variable. The concentrations of moisture, gross energy, CP, ether extract, crude fiber, ash, calcium, phosphorus, lysine, methionine, cysteine, and threonine in tested oilseed meals differed (P<0.05) depending on producing countries. The prediction equations for amino acid concentrations (% as-is basis) in the oilseed meals are: lysine = -1.08 + 0.080 × CP (root mean square error = 0.244, R² = 0.924, and P<0.001); threonine = -0.297 + 0.044 × CP (root mean square error = 0.099, R² = 0.958, and P<0.001). In conclusion, energy and nutrient compositions vary in the oilseed meals depending on the producing countries. Moreover, the crude protein concentration can be used as a suitable independent variable for estimating lysine and threonine concentrations in the oilseed meals.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.5
• /
• pp.123-128
• /
• 2011

In this paper, we design the CA-CFAR processor using a root-square approximation approach and a fixed-point operation to improve hardware complexity and reduce computational effort. We also propose CA-CFAR processor with multi-window, which is capable of concurrent parallel processing. The proposed architecture is synthesized and implemented into the FPGA and the performance is compared with the conventional processor designed by root-square libarary licensed by FPGA corporation.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.5
• /
• pp.135-142
• /
• 2018

This paper compares and analyzes advantages and disadvantages of CDMA(code division multiple access) and OFDM(orthogonal frequency division multiplexing) transmission techniques for underwater acoustic channel environments. Computer simulations were carried out in various underwater acoustic channels with varying r.m.s.(root mean square) delay, doppler frequency and the number of multipaths. When r.m.s. delay and doppler frequency are within the tolerance of designed transmission schemes, the computer simulations show that CDMA has better BER performance than that of the OFDM. However, when the doppler frequency exceeds the tolerance, BER performance of the CDMA decreases.

• Child Health Nursing Research
• /
• v.26 no.1
• /
• pp.35-46
• /
• 2020

Purpose: The purpose of this study was to test a model for intention to discontinuation drinking high caffeinated beverages among undergraduate students. This model was based on the Ajzen's theory of planned behavior and Becker's health belief model. Methods: Participants consisted of 201 undergraduate students. Data were collected by questionnaires from March 11 to May 24, 2019. Collected data were analyzed using SPSS/WIN 22.0, AMOS 22.0 program. Results: The assessment of the model indicated an acceptable fit (normed x²=1.65, goodness-of-fit index [GFI]=.83, adjusted GFI=.79, comparative fit index [CFI]=.92, standardized root mean square residual [SRMR]=.05, Tucker-Lewis index [TLI]=.91, normed fit index [NFI]=.87, root mean square error of approximation [RMSEA]=.07). Perceived behavior control, subjective norm, the subjective attitude was found to have a significant direct effect on the intention to discontinuation of drinking a high caffeinated beverage. The variances of this model explained 45.3% of the variance in intention to discontinuation of drinking a high caffeinated beverage. Conclusion: These results suggest that a need to increase awareness of adverse effects and potential risks of high caffeinated beverage consumption in undergraduate students. Besides, the university and government should provide education and campaigns to prevent excessive high-caffeinated beverage consumption.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.5
• /
• pp.75-84
• /
• 2015

A data allocation technique is essential to improve the performance of data broadcast systems. This paper explores the issues for allocating data items on broadcast channels to process multiple-data queries in the environment where query profiles and query request rates are given, and proposes a new data allocation scheme named IDAS. The proposed scheme employs the strategy that the broadcast frequency of each data is determined by the square root value of its relative access probability. IDAS could enhance the performance of query response time since it can process queries of high request rate fast and show a resonable degree of query data adjacency. Simulation is performed to evaluate the performance of the proposed scheme. The simulation results show that IDAS outperforms other schemes in terms of the average response time.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.25 no.11
• /
• pp.1705-1712
• /
• 2001

Mechanical component has striation with constant width and SEM can estimate fracture type and loading condition. SEM has benefit to fatigue fracture analysis but striation can be observed according to the kind of material and range of crack growth rate and can't. In this case, it needs AFM that can measure 3-dimensional surface profile with resolution of atomic size. In this study. to find fracture reason of torsion-mounted blade in nuclear plant, we estimate the relation between stress intensity factor range and root mean square roughness in 12% Cr steel by AFM and predict in-service loading condition of turbine blade. failure analysis is performed by finite element method and Goodman diagram on torsion-mounted blade.

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