• Korean Journal of Organic Agriculture
• /
• v.29 no.2
• /
• pp.159-171
• /
• 2021

The purpose of this paper is to analyze the relationship between the level of satisfaction of domestic Environment-friendly agricultural products and purchase intent of imported organic products. To accomplish the objective of the study a consumer survey was administered for quantitative analysis regarding consumption patterns. The bivariate probit with sample selection model was employed for empirical analysis on the relationship. The estimation results showed that to increase continuously the consumption, it is necessary to improve the quality satisfaction compared to the price, and that it is also necessary to increase the reliability of the certification system and the awareness that the consumption is helpful for health promotion to increase the quality satisfaction compared to price. In addition, it was concluded that in order to induce the purchase of domestic organic products rather than imported organic products, efforts to improve the safety of domestic products, remove the risk of residual pesticides, and increase the reliability of domestic products compared to imported products are needed. Therefore, to reduce the proportion of purchases of imported organic products and increase the consumption of domestic products, raising awareness that the consumption is conducive to health promotion, enhancing the safety of domestic products, and providing accurate information on the safety of imported products are required.

• International Journal of Highway Engineering
• /
• v.16 no.5
• /
• pp.173-182
• /
• 2014

PURPOSES : The purpose of the study is to a) explore the operating speed of trucks on rural highways affected by road geometry, and thereby b) develop a predictive model for the operating speed of trucks on rural highways. METHODS : Considering that most of the existing studies have focused on cars, the current study aimed to predict the operating speed of trucks by conducting linear regression analysis on the speed data of trucks operating on the linear-curved-linear portions of the road as a single set. RESULTS : The operating speed in the plane curve portion increased with the length of the curve, and decreased with a lower vertical grade and a smaller curve radius. In the straight plane portion, the operating speed increased with a larger curve radius(upstream), and decreased with an increase in the change of the vertical grade, depending on the length of the vertical curve. CONCLUSIONS : This study developed estimation models of truck for operational speed and evaluated the degree of safety for horizontal and vertical alignments simultaneous. In order to represent whole area of the rural highway, the models should be ew-analyzed with vast data related with road alignment factor in the near future.

• International Journal of Highway Engineering
• /
• v.19 no.4
• /
• pp.1-7
• /
• 2017

PURPOSES : This study aims to improve complex modeling of multivariable, nonlinear, and overdispersion data with an artificial neural network that has been a problem in the civil and transport sectors. METHODS: Deep learning, which is a technique employing artificial neural networks, was applied for developing a large bus fuel consumption model as a case study. Estimation characteristics and accuracy were compared with the results of conventional multiple regression modeling. RESULTS : The deep learning model remarkably improved estimation accuracy of regression modeling, from R-sq. 18.76% to 72.22%. In addition, it was very flexible in reflecting large variance and complex relationships between dependent and independent variables. CONCLUSIONS : Deep learning could be a new alternative that solves general problems inherent in conventional statistical methods and it is highly promising in planning and optimizing issues in the civil and transport sectors. Extended applications to other fields, such as pavement management, structure safety, operation of intelligent transport systems, and traffic noise estimation are highly recommended.

• Geomechanics and Engineering
• /
• v.13 no.2
• /
• pp.237-254
• /
• 2017

Estimation of slope stability is a very important task in geotechnical engineering. However, its estimation using conventional and soft computing methods has several drawbacks. Use of conventional limit equilibrium methods for the evaluation of slope stability is very tedious and time consuming, while the use of soft computing approaches like Artificial Neural Networks and Fuzzy Logic are black box approaches. Multiple Regression (MR) analysis provides an alternative to conventional and soft computing methods, for the evaluation of slope stability. MR models provide a simplified equation, which can be used to calculate critical factor of safety of slopes without adopting any iterative procedure, thereby reducing the time and complexity involved in the evaluation of slope stability. In the present study, a multiple regression model has been developed and tested its accuracy in the estimation of slope stability using real field data. Here, two separate multiple regression models have been developed for dry and wet slopes. Further, the accuracy of these developed models have been compared and validated with respect to conventional limit equilibrium methods in terms of Mean Square Error (MSE) & Coefficient of determination ($R^2$). As the developed MR models here are not based on any region specific data and covers wide range of parametric variations, they can be directly applied to any real slopes.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.11 no.8
• /
• pp.3012-3020
• /
• 2010

VPN can give safety in connection in Timbuc-too, by corporation's basis communication means today that transfer user support in Timbuc-too is required compulsorily, VPN is activated. This research wishes to investigate base technology of VPN software field and investigate VPN software market trend and standard and develop estimation model of VPN software. For this special quality of VPN software investigation / analyze and investigate or analyze market trend and standard this to VPN software to base deduction of estimation item and estimation model develop.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.6
• /
• pp.1085-1091
• /
• 2012

Phase I clinical trials are designed to identify an appropriate dose; the maximum tolerated dose, which assures safety of a new drug by evaluating the toxicity at each dose-level. The adjusted maximum tolerated dose estimation is presented by stopping rule in phase I clinical trial on this research. The suggested maximum tolerated dose estimation is compared to the standard method3 and NM method using a Monte Carlo simulation study.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.6
• /
• pp.609-617
• /
• 2011

There is a trend towards the progressive use of higher operating temperatures and stresses to achieve improved efficiencies in power-generation equipment. It is important to perform the crack assessment under hightemperature and high-pressure conditions. The C(t)-integral is a key parameter in crack assessment for transient creep states. The estimation of the C(t)-integral is complex when considering the mechanical and thermal loads simultaneously. In this paper, we study estimation of C(t)-integral under combined mechanical and thermal load depending on loading conditions.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.24 no.10 s.181
• /
• pp.2654-2663
• /
• 2000

Steam turbine rotors are the most critical and highly stressed components of a steam power plant; therefore, the life expectancy of the turbine rotor is an important consideration for the safety of a steam power plant. The objective of this paper is to develop a life estimation program for turbine rotors for all possible operating conditions. For this purpose, finite element analysis was carried out for four normal operating modes (cold, warm, hot and very hot starts) using ABAQUS codes. The results are made into databases to evaluate the life expenditure for an actual operating condition. For any other possible abnormal operating condition, the operating data are transmitted to the server (workstation) through a network to carry out finite element analysis. Damage estimation is carried out by transmitting the finite element analysis results to the personal computer, and then the life expectancy is calculated.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.209-213
• /
• 1997

This paper deals with sensing ability of $2^{nd}$ smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the $2^{nd}$ smart sensor for experiment. The second type of smart sensor is HH type. We have developed a new signal processing method that can distinguish among different materials. The estimation method (RSAIIn dex) is developed for $2^{nd}$ smart sensor(HH smart sensor). Experiment and analysis are executed for estimation the new method. We estimated sensing ability of $2^{nd}$ smart sensor with RsA, method. Sensing Ability of the $2^{nd}$ smart sensor were evaluated relatively through a new RsAl method. According to frequency changing, influences of the $2^{nd}$ smart sensor are evaluated through a new recognition index RSAI. Applications of this method are for finding abnormal conditions of objects (automanufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.6 no.9
• /
• pp.2170-2190
• /
• 2012

There are nowadays strong demands for intelligent surveillance systems, which can infer or understand more complex behavior. The application of crowd density estimation methods could lead to a better understanding of crowd behavior, improved design of the built environment, and increased pedestrian safety. In this paper, we propose a new crowd density estimation method, which aims at estimating not only a moving crowd, but also a stationary crowd, using images captured from surveillance cameras situated in various public locations. The crowd density of the moving people is measured, based on the moving area during a specified time period. The moving area is defined as the area where the magnitude of the accumulated optical flow exceeds a predefined threshold. In contrast, the stationary crowd density is estimated from the coarseness of textures, under the assumption that each person can be regarded as a textural unit. A multilayer neural network is designed, to classify crowd density levels into 5 classes. Finally, the proposed method is experimented with PETS 2009 and the platform of Gangnam subway station image sequences.