• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.102-107
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• 2021

This paper discusses the containment control problem for multi-agent systems with input saturations. The goal of the containment control is to obtain swarming behavior by driving follower agents into the convex hull which is spanned by multiple leader agents. This paper considers multiple leader agents moving at the same constant speed. Then, to solve the containment problem for moving leaders, we propose a PI-based distributed control algorithm. We next analyze the convergence of follower agents to the desired positions. Specifically, we apply the integral-type Lyapunov function to take into account the saturation nonlinearity. Then, based on Lasalle's Invariance Principle, we show that the asymptotic convergence of error states to zero for any positive constant gains. Finally, numerical examples with the static and moving leaders are provided to validate the theoretical results.

• Journal of the Korean GEO-environmental Society
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• v.12 no.1
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• pp.5-12
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• 2011

In this study, correlation between measured deformation modulus using pressuremeter and RMR value conducted in 10 sites is analyzed, and applicability of the conventional empirical formulas to the rock masses in Korea are analyzed, It is found that if RMR is below 40, the correlation between deformation modulus and RMR accords Kim Gyo-won's formula and Aydan, Serafim and Pereira's one well, but if the RMR exceeds 40, the correlation was lower than those from the formula. Such results may be attribute to the fact that during classification of RMR, scores are weighed relatively more in joint conditions and apertures than such highly correlational items as uniaxial compression strength or RQD, and RMR would not be evaluated qualitatively due to different weathering degrees and rock mass types as well as engineers' personal errors. Sandstone among sedimentary rocks are quite well accord with suggested equation, but correlation of other rocks are due to large variance. In this study, correlation expressions of various rocks are proposed as the function of exponential based on the field test data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.2
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• pp.33-38
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• 2008

Biometric based authentication can provide strong security guarantee about the identity of users. However, security of biometric data is particularly important as compromise of the data will be permanent. Cancelable biometrics stores a non - invertible transformed version of the biometric data. Thus, even if the storage is compromised, the biometric data remains safe. Cancelable biometrics also provide a higher level of privacy by allowing many templates for the same biometric data and hence non-linkability of user's data stored in different databases. In this paper, we proposed the fast polynomial reconstruction algorithm for fuzzy fingerprint vault. The proposed method needs (k+1) real points to reconstruct the polynomial of degree (k-1). It enhances the speed, however, by $300{\sim}1500$ times according to the degree of polynomial compared with the exhaust search.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.1
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• pp.125-133
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• 2009

Security of biometric data is particularly important as the compromise of the data will be permanent. To protect the biometric data, we need to store it in a non.invertible transformed version. Thus, even if the transformed version is compromised, its valid biometric data are securely remained. Fuzzy vault mechanism was proposed to provide cryptographic secure protection of critical data(e.g., encryption key) with the fingerprint data in a way that only the authorized user can access the critical data by providing the valid fingerprint. However, all the previous results cannot operate on the fingerprint image with a few minutiae, because they use fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use adaptive degree of polynomial considering the number of minutiae. Also, we apply multiple polynomials to operate the fingerprint with a few minutiae. Based on the experimental results, we confirm that the proposed approach can enhance the security level and verification accuracy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.751-758
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• 2021

Munitions must be analyzed to identify any risks for quality assurance in development and mass production. Risk identification for parts, compositions, and systems is carried out through failure mode effects analysis (FMEA) as one of the most reliable methods. FMEA is a design tool for the failure mode of risk identification and relies on the RPN (risk priority number). FMEA has disadvantages because its severity, occurrence, and detectability are rated at the same level. Fuzzy FMEA applies fuzzy logic to compensate for the shortcomings of FMEA. The fuzzy logic of Fuzzy FMEA is to express uncertainties about the phenomenon and provides quantitative values. In this paper, Fuzzy FMEA is applied to the failure mode of a rotorcraft landing system. The Fuzzy rule and membership functions were conducted in the Fuzzy model to study the RPN in the failure mode of a landing system. This method was selected to demonstrate crisp values of severity, occurrence, and detectability. In addition, the RPN was obtained. The results of Fuzzy FMEA for the landing system were analyzed for the RPN and ranking by fuzzy logic. Finally, Fuzzy FMEA confirmed that it could use the data in quality assurance activities for rotorcraft.

• Journal of the Korea Computer Graphics Society
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• v.26 no.5
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• pp.1-13
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• 2020

In this paper, we propose a new method to stable simulation the directional ice shape by coupling of freezing solver and viscous water flow. The proposed ice modeling framework considers viscous fluid flow in the direction of ice growth, which is important in freezing simulation. The water simulation solution uses the method of applying a new viscous technique to the IISPH(Implicit incompressible SPH) simulation, and the ice direction and the glaze effect use the proposed anisotropic freezing solution. The condition in which water particles change state to ice particles is calculated as a function of humidity and new energy with water flow. Humidity approximates a virtual water film on the surface of the object, and fluid flow is incorporated into our anisotropic freezing solution to guide the growth direction of ice. As a result, the results of the glaze and directional freezing simulations are shown stably according to the flow direction of viscous water.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.165-170
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• 2021

Machine learning has recently been applied to research in most areas. This is because the results of machine learning are not determined, but the learning of input data creates the objective function, which enables the determination of new data. In addition, the increase in accumulated data affects the accuracy of machine learning results. The data collected here is an important factor in machine learning. The proposed system is a convergence system of cloud systems and local fog systems for service delivery. Thus, the cloud system provides machine learning and infrastructure for services, while the fog system is located in the middle of the cloud and the user to collect and refine data. The data for this application shall be based on the Sensitive data generated by smart devices. The machine learning technique applied to this system uses SVM algorithm for classification and RNN algorithm for status recognition.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Journal of Advanced Navigation Technology
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• v.26 no.2
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• pp.72-77
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• 2022

Among the techniques of reinforcement learning, Q-Learning means learning optimal policies by learning Q functions that perform actionsin a given state and predict future efficient expectations. Q-Learning is widely used as a basic algorithm for reinforcement learning. In this paper, we studied the effectiveness of selecting and learning efficient paths by designing policies and rewards based on Q-Learning. In addition, the results of the existing algorithm and punishment compensation policy and the proposed punishment reinforcement policy were compared by applying the same number of times of learning to the 8x8 grid environment of the Frozen Lake game. Through this comparison, it was analyzed that the Q-Learning punishment reinforcement policy proposed in this paper can significantly increase the learning speed compared to the application of conventional algorithms.

• Journal of Software Assessment and Valuation
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• v.17 no.2
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• pp.31-38
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• 2021

In order to analyze the similarity of the source code object material, the source code on both sides must be able to be compiled and executed. In particular, in the case of hardware-integrated software, it is necessary to check whether the hardware interface matches. However, currently, the source code is provided in an incomplete state which is not original of source code used in developing steps. The complainant confirms that the executing characteristics are similar to their own in the expression and function of the output, and request an evaluation. When a source code compilation error occurs during the evaluation process, the experts draw a flowchart of the source code and applies the method of tracing the code flow for each function as indirect method. However, this method is indirect and the subjective judgment is applied, so there is concern about the contention of objectivity in the similarity evaluation result. In this paper, the problems of unverified source code similarity analysis and improvement directions are dealt with, through the analysis cases of source code disputes applied to embedded systems.