• Journal of Convergence for Information Technology
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• v.9 no.10
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• pp.9-15
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• 2019

Recently, in the field of next-generation e-commerce and finance, interest in blockchain-based technologies such as Bitcoin and Ethereum is great. Although the security of blockchain technology is known to be secure, hacking incidents / accidents related to cryptocurrencies are being issued. The main causes were vulnerabilities in the external environment, such as taking over login sessions on cryptocurrency wallets, exposing private keys due to malware infection, and using simple passwords. However, private key management recommends general methods such as utilizing a dedicated application or local backup and physical archiving through document printing. In this paper, we propose a white box password-based private key protection scheme. As a result of safety and performance analysis, we strengthened the security against vulnerability of private key exposure and proved the processing efficiency of existing protocol.

• Journal of Applied Reliability
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• v.9 no.2
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• pp.107-119
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• 2009

Reliability tests should be designed to verify whether reliability requirements are satisfied or not effectively and efficiently. The portion of reliability requirements that a reliability test scheme composed of different types of tests can cover is defined as test coverage in software engineering. For the cases of hardwares, to be effective, a reliability test scheme should enhance the test coverage. This study is to develop an evaluation method of test coverage for a reliability test scheme proposed for new products. Case studies are also given.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.495-497
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• 2012

Development of application risk management for medical device software test. First, Through questionnaires, Medical device manufacturers, Analysis of software validation and risk management status. Second, Analyzed by comparing the difference between black box testing and white box testing. Third, After analyzing the potential for software analysis tools using code derived factors were quantified, Finally, Medical device risk management process so that it can be applied to build the framework by FMEA(Failure Mode and Effect Analysis) technique. Through this Difficult to build software validation and risk management processes for manufacturers to take advantage of support in medical device GMP(Good Manufacture Practice).

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.3
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• pp.14-26
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• 2015

A wind speed forecast is a crucial and sophisticated task in a wind farm for planning turbines and corresponds to an estimate of the expected production of one or more wind turbines in the near future. By production is often meant available power for wind farm considered (with units KW or MW depending on both the wind speed and direction. Such forecasts can also be expressed in terms of energy, by integrating power production over each time interval. In this study, we technically focused on mathematical modeling of wind speed and direction forecast based on locally data set gathered from Aghdasiyeh station in Tehran. The methodology is set on using most common techniques derived from literature review. Hence we applied the most sophisticated forecasting methods to embed seasonality, trend, and irregular pattern for wind speed as an angular variables. Through this research, we carried out the most common techniques such as the Box and Jenkins family, VARMA, the component method, the Weibull function and the Fourier series. Finally, the best fit for each forecasting method validated statistically based on white noise properties and the final comparisons using residual standard errors and mean absolute deviation from real data.

• Smart Structures and Systems
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• v.21 no.2
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• pp.207-223
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• 2018

In this inquisition, a passive damper namely Stockbridge Damper (SBD) has been introduced to the field of vibration control of Offshore Wind Turbine (OWT) to reduce the earthquake excitations. The dynamic responses of the structure have been analyzed for three recorded earthquakes and the responses have been assessed. To find an optimum SBD, the parameters of damper have been optimized using Response Surface Methodology (RSM) based on Box-Behnken Design (BBD) and Particle Swarm Optimization (PSO). The influence of the design variables of SBD such as the diameter of messenger cable, the length of messenger cable and logarithmic decrement of the damping has been investigated through response variables such as maximum displacement, RMS displacement and frequency amplitude of structure under an artificially generated white noise. After that, the structure with optimized and non-optimized damper has been analyzed with under the same earthquakes. Moreover, the comparative results show that the structure with optimized damper is 11.78%, 18.71%, 11.6% and 7.77%, 7.01%, 10.23% more effective than the structure with non-optimized damper with respect to the displacement and frequency response under the earthquakes. The results show that the SBD can obviously affect the characteristics of the vibration of the OWT and RSM based on BBD and PSO approach can provide an optimum damper.

• Journal of Broadcast Engineering
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• v.27 no.7
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• pp.999-1010
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• 2022

The increase in vehicle purchases worldwide is having a very significant impact on the availability of parking spaces. In particular, since it is difficult to secure a parking space in an urban area, it may be of great help to the driver to check vehicle parking information in advance. However, the current parking lot information is still operated semi-manually, such as notifications. Therefore, in this study, we propose a system for detecting a parking space using a relatively simple image processing method based on an image taken from the sky and evaluate its performance. The proposed method first converts the captured RGB image into a black-and-white binary image. This is to simplify the calculation for detection using discrete information. Next, a morphological operation is applied to increase the clarity of the binary image, and a template mask in the form of a bounding box indicating a parking space is applied to check the parking state. Twelve image samples and 2181 total of test, were used for the experiment, and a threshold of 40% was used to detect each parking space. The experimental results showed that information on the availability of parking spaces for parking users was provided with an accuracy of 95%. Although the number of experimental images is somewhat insufficient to address the generality of accuracy, it is possible to confirm the possibility of parking space detection with a simple image processing method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1689-1705
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• 2023

To deal with the potential XSS vulnerabilities in the source code of the power communication network, an XSS vulnerability detection method combining the static analysis method with the dynamic testing method is proposed. The static analysis method aims to analyze the structure and content of the source code. We construct a set of feature expressions to match malignant content and set a "variable conversion" method to analyze the data flow of the code that implements interactive functions. The static analysis method explores the vulnerabilities existing in the source code structure and code content. Dynamic testing aims to simulate network attacks to reflect whether there are vulnerabilities in web pages. We construct many attack vectors and implemented the test in the Selenium tool. Due to the combination of the two analysis methods, XSS vulnerability discovery research could be conducted from two aspects: "white-box testing" and "black-box testing". Tests show that this method can effectively detect XSS vulnerabilities in the source code of the power communication network.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.35-41
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• 2002

There are many image segmentation methods having been published as the results of research so far, but it is difficult to be partitioned to each similar range that should be extracted into the accurate parameters of image information on the images with noises. Also if it is used to fractal coding, according to amount of noise in image, the image segmentation leads to decreasing of the compression ratio. In this paper, we propose the new quad-tree image segmentation using the box-counting dimension which can estimate the effective image information parameters against the noise properties and apply this method to fractal image coding. As the result of simulation, we confirm that the image segmentation is improved to 31.10% for parameter detection of image information and compression ratio is enhanced to 38.93% for fractal image coding when tested on 10% Gaussian white noise image by the proposed quad-tree method compared with method using existing quad-tree. 

• School Mathematics
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• v.10 no.2
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• pp.297-317
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• 2008

This study was designed to gain insight to adopt CAS into secondary level algebra education in Korea. Most inactive usage of calculators in math and most negative effects of calculators on their achievements of Korean students were shown in International studies such as TIMSS-R. A comparative study was carried out with consideration of mathematical backgrounds and technological environments. 8 Korean students and 26 US students in Grade 11 were participated in this study. Subjects' Problem solving process and their strategies of CAS usage in classical Box-problem with CAS were analyzed. CAS helped modeling by providing symbolic manipulation commands and graphs with students' mathematical knowledge. Results indicates that CAS requires shifts focus in algebraic contents: recognition of decimal & algebraic presentations of numbers; linking various presentations, etc. The extent of instrumentation effects on the selection of problem solving strategies among Korea and US students. Instrumentation

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.