• KIPS Transactions on Software and Data Engineering
• /
• v.5 no.11
• /
• pp.593-606
• /
• 2016

Computer simulation is widely used in a variety of computational science and engineering fields, including computational fluid dynamics, nano physics, computational chemistry, structural dynamics, and computer-aided optimal design, to simulate the behavior of a system. As the demand for the accuracy and complexity of the simulation grows, however, the cost of executing the simulation is rapidly increasing. It, therefore, is very important to lower the total execution time of the simulation especially when that simulation makes a huge number of repetitions with varying values of input parameters. In this paper we develop a simulation service system that provides the ability to predict the result of the requested simulation without actual execution for that simulation: by recording and then returning previously obtained or predicted results of that simulation. To achieve the goal of avoiding repetitive simulation, the system provides two main functionalities: (1) storing simulation-result records into database and (2) predicting from the database the result of a requested simulation using statistical machine learning techniques. In our experiments we evaluate the prediction performance of the system using real airfoil simulation result data. Our system on average showed a very low error rate at a minimum of 0.9% for a certain output variable. Using the system any user can receive the predicted outcome of her simulation promptly without actually running it, which would otherwise impose a heavy burden on computing and storage resources.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.289-299
• /
• 2016

Weapon systems require reliability in the development phase for efficient combat readiness. Improved reliability in various manufacturing processes have been achieved using data analysis. However, data analysis in the development phase is difficult due to problems such as the lack of data, high cost, and the importance of security. Therefore, Post Logistics Support (PLS) data collected following integration is analyzed for long-term quality improvement of weapon systems. In this study, we propose a methodology for examining the correlation between the failure rate and PLS data as follows: First, key variables affecting reliability were identified the correlation between variables on the failure rate examined. Second, corresponding analysis was conducted for determining the correlation between patterns of categorical data. Third, extract categories with the higher contribution and quality of representation, and find the highest variable correlated with failure period through visualization. Then, after selecting patterns which have shorter failure period, the cause of decreased reliability was confirmed through frequency analysis. This study will contribute to improving reliability when developing new weapon systems and will help to strengthen the combat readiness of military.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.2
• /
• pp.127-136
• /
• 2012

Many research of hand gesture recognition based on vision system have been conducted which enable user operate various electronic devices more easily. 3D position calculation and meaningful gesture classification from similar gestures should be executed to recognize hand gesture accurately. A simple and cost effective method of 3D position calculation and gesture spotting (a task to recognize meaningful gesture from other similar meaningless gestures) is described in this paper. 3D position is achieved by calculation of two cameras relative position through pan/tilt module and a marker regardless with the placed position. Fuzzy garbage model is proposed to provide a variable reference value to decide whether the user gesture is the command gesture or not. The reference is achieved from fuzzy command gesture model and fuzzy garbage model which returns the score that shows the degree of belonging to command gesture and garbage gesture respectively. Two-stage user adaptation is proposed that off-line (batch) adaptation for inter-personal difference and on-line (incremental) adaptation for intra-difference to enhance the performance. Experiment is conducted for 5 different users. The recognition rate of command (discriminate command gesture) is more than 95% when only one command like meaningless gesture exists and more than 85% when the command is mixed with many other similar gestures.

• Journal of the Korean Recycled Construction Resources Institute
• /
• v.9 no.4
• /
• pp.433-442
• /
• 2021

In this study, the properties of no-fines polymer concrete with different polymer binder contents were evaluated. The polymer concrete was formulated using a polymeric binder (unsaturated polyester resin), fly ash, and recycled coarse aggregate (60%) and crushed coarse aggregate (40%). The polymeric binder content (4.0-6.0wt.%) was used as an experimental variable because it dramatically affects both the cost-effectiveness and material properties. The results showed that the density, compressive strength, flexural strength both before and after exposure to freezing and thawing increased as the polymer binder content increased, while the absorption, void ratio, permeable voids, coefficient of permeability, and acid resistance (mass loss by acid attack) decreased as the polymeric binder content increased. In particular, even though the void ratio was 18.4% and the water permeability coefficient was 7.3mm/sec, the compressive strength and flexural strength were as high as 38.0MPa and 10.0MPa, respectively, much more significant than those of previous studies. Other properties such as absorption and acid resistance were also found to be excellent. The results appear to be rooted in the increased adhesion of the binder by adding a cross-linking agent and the surface hydrophobicity of the polymer.

• International Area Studies Review
• /
• v.15 no.2
• /
• pp.247-273
• /
• 2011

This study analyzes the impacts on the M&A and greenfield of macroeconomic variables of home and host countries, after identifying current status and characteristics of the M&A and greenfield related to the entering way of Korean firms in China. Main empirical results are summarize as follows. First, as for foreign exchange variable, the decreased value of Korea won shows the negative correlations with both of the greenfield and M&A. Second, the real interest rate of Korea to measure the cost of capital is not significant statistically. Third, while the host country's stock market index, Shanghai Comprehensive Index, shows the expected negative correlations with the investment in the case of small & medium firm and light industry, it shows the positive correlations which is not consistent with general expectation in the case of large firm and heavy industry. Fourth, the openness of host country shows the positive correlations with both of the greenfield and M&A. Finally, in regard to the M&A, China's GDP to measure the market size of host country is not significant statistically while it shows the strong positive relationship with the greenfield investment.

• Journal of Navigation and Port Research
• /
• v.43 no.4
• /
• pp.264-272
• /
• 2019

In this study, the rate of return on investment used as a proxy variable for the entity's value and financial structure (liability ratio) is related to positive balance. This is consistent with the Static Tradeoff Theory (STT) that the entity's value and financial structure are related to a positive balance because the capital expense of a debt (tax-saving effects) that is less than its equity cost before it is in financial difficulty. Also, operating profitability (EBITDA/Sales), investment safety, total asset growth, net working capital and depreciation expenses are related to negative (-) with financial structure (liability ratio). This is the result of an analysis consistent with the Pecking Order Theory (POT). Fuel costs, borrowing, total asset turnover, financial costs, and tangible asset ratios have a significant positive relationship with the debt ratio. This is consistent with the agency theory and confirms that excessive chartering expenses, such as the bankrupt H company, are the main factors that pressure the financial structure of Korean ocean carriers.

• Environmental and Resource Economics Review
• /
• v.28 no.3
• /
• pp.355-383
• /
• 2019

This study is to investigate whether averting costs for wearing $anti-PM_{10}$ masks and using air purifiers at home to reduce exposure from $PM_{10}$ are influenced by subjective risk perceptions and/or objective $PM_{10}$ concentration levels, whose estimates will be used to measure the willingness to pay for $PM_{10}$ risk reduction. An empirical analysis was conducted on a sample of 1,224 respondents who participated in the web-based survey in the late October of 2017. As we reflect the potential endogeniety bias in the estimation of averting cost functions of using air purifiers, the coefficients of risk perception were differed by 6~7 times. Respondents. subjective risk perceptions were influenced by individuals' knowledge, attitudes and demographic variables, as well as the levels of $PM_{10}$ concentrations in their residential region. The marginal willingness to pay for risk reductions at the mean levels of their risk perceptions were measured at 1,000 won per month from wearing $anti-PM_{10}$ masks and 6,000 won for using air purifiers respectively.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.4
• /
• pp.1-9
• /
• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.6
• /
• pp.27-32
• /
• 2020

This paper compare the adaptive equalization performance according to the values of adaptive step variation speed for adapting in VS-CCA (Variable Stepsize-Compact Constellation Algorithm) based on nonlinear function function of error signal. The VS-CCA algorithm compacts the 16-QAM nonconstant modulus signal into the 4 groups of 4-QAM constant modulus signal constellation in quadature plane, then the error signal is generated using the constant modulus of transmitted signal statistics. The adaptive equalizer coefficient were updated in order to achieve the minimum cost function by varying step based on the nonlinear function of error signal. In this time, the instantaneous adaptive step is determined according to the value of step variation speed of nonlinear function and the different equalization performance were obtained according to the step variation speed value. The equalizer internal index and external index which represents the robustness of external noise were used for the performance comparison index. As a result of computer simulation, it was confirmed that the value of variation speed less than 1.0 give more superior in every performance index compared to the greater than 1.0 in steady state.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.1-8
• /
• 2021

This study developed low-cost and high-efficiency pavement condition monitoring technology to produce the key information required for pavement management. A noise and artificial intelligence-based monitoring system was devised to compensate for the shortcomings of existing high-end equipment that relies on visual information and high-end sensors. From idea establishment to system development, functional definition, information flow, architecture design, and finally, on-site field evaluations were carried out. As a result, confidence in the high level of artificial intelligence evaluation was secured. In addition, hardware and software elements and well-organized guidelines on system utilization were developed. The on-site evaluation process confirmed that non-experts could easily and quickly investigate and visualized the data. The evaluation results could support the management works of road managers. Furthermore, it could improve the completeness of the technologies, such as prior discriminating techniques for external conditions that are not considered in AI learning, system simplification, and variable speed response techniques. This paper presents a new paradigm for pavement monitoring technology that has lasted since the 1960s.