• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.6
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• pp.579-589
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• 2004

The radar signals are generally very sensitive to relative orientations between radar and target. Thus, the performance of a target recognition system significantly deteriorates as the region of aspect angles becomes broader. To address this difficulty, in this paper, we propose a method based on the multi-aspect information in order to improve the classification capability ever for a wide angular region. First, range profiles are used to extract feature vectors based on the central moments and principal component analysis(PCA). Then, a classifier with the use of multi-aspect information is applied to them, yielding an additional improvement of target recognition capability. There are two different strategies among the classifiers that can fuse the information from multi-aspect radar signals: independent methodology and dependent methodology. In this study, the performances of the two strategies are compared within the frame work of target recognition. The radar cross section(RCS) data of six aircraft models measured at compact range of Pohang University of Science and Technology are used to demonstrate and compare the performances of the two strategies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.6
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• pp.72-79
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• 2015

An efficient and practical reliability evaluation method is proposed for the coastal structures in this paper. It is capable of evaluating reliability of real complicated coastal structures considering uncertainties in various sources of design parameters, such as wave and current loads, resistance-related design variables including Young's modulus and compressive strength of the reinforced concrete, soil parameters, and boundary conditions. It is developed by intelligently integrating the Latin Hypercube sampling (LHS), Monte Carlo simulation (MCS) and the finite element method (FEM). The LHS-based MCS is used to significantly reduce the computational effort by limiting the number of simulation cycles required for the reliability evaluation. The applicability and efficiency of the proposed method were verified using a caisson-type breakwater structure in the numerical example.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.535-543
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• 2002

In this paper, we propose a new gaze detection method using 2-D facial images captured by a camera on top of the monitor. We consider only the facial rotation and translation and not the eyes' movements. The proposed method computes the gaze point caused by the facial rotation and the amount of the facial translation respectively, and by combining these two the final gaze point on a monitor screen can be obtained. We detected the gaze point caused by the facial rotation by using a neural network(a multi-layered perceptron) whose inputs are the 2-D geometric changes of the facial features' points and estimated the amount of the facial translation by image processing algorithms in real time. Experimental results show that the gaze point detection accuracy between the computed positions and the real ones is about 2.11 inches in RMS error when the distance between the user and a 19-inch monitor is about 50~70cm. The processing time is about 0.7 second with a Pentium PC(233MHz) and 320${\times}$240 pixel-size images.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.1
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• pp.87-100
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• 2020

Researches on Post-quantum blockchain, which is a synthesis of blockchain and post-quantum cryptography[1], are relatively unrevealed areas but have needs to be studied with the regard to the quantum computers. However there could be several fundamental problems, e.g. unsustainably large size of public key and signature, or too lengthy time for sign and verification, if any post-quantum cryptography is adopted to the existing blockchain to implement post-quantum blockchain. Thus, a new method was proposed in this paper that produces fixed length of references for massive signatures and corresponding public keys to enable relatively lightweight transactions. This paper proposed the mechanism that included a new transaction structure and protocols, and demonstrated a post-quantum blockchain that the proposed mechanism was adopted. Through this research, it could enhance compatibility of blockchain regarding post-quantum digital signature, possibly reducing weights of the whole blockchain.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1634-1642
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• 2014

Mobile RFID system, that consists of the existing RFID reader mounted on the mobile devices such as smartphones, is able to provide the users a variety of services and convenience. But security of mobile RFID system is too weak like the existing RFID system. In this paper, the mobile RFID mutual authentication protocol with high level of security is proposed to overcome the troubles such as cryptographic protocols in the existing RFID system responding with the same value in every authentication procedure and the exposure in the exchange of messages. The proposed protocol exchanges messages unexposed by using the random numbers generated in the mutual authentication between the tag and the reader and making numbers coded with the symmetric key. Besides, the protocol uses the mutual authentication utilizing OTP by considering the characteristics of the reader embedded in mobile devices in the mutual authentication process between the reader and the server. Because changed message in every authentication, which produces safe from spoofing attacks and replay attacks, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1015-1017
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• 2013

Object tracking, in general, is a challenging problem. Difficulties in tracking objects can arise due to abrupt object motion, changing appearance patterns of both the object and the scene, non-rigid object structures, object-to-object and object-to-scene occlusions, and camera motion. Tracking is usually performed in the context of higher-level applications that require the location or the shape of the object in every frame. This paper describes an object tracking system based on active vision with two cameras, into algorithm of single camera tracking system an object active visual tracking and object locked system based on Extend Kalman Filter (EKF) is introduced, by analyzing data from which the next running state of the object can be figured out and after the tracking is performed at each of the cameras, the individual tracks are to be fused (combined) to obtain the final system object track.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1049-1054
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• 2018

Keyword searching used in the past as a method of finding similar patents, and automated classification by machine learning is using in recently. Keyword searching is a method of analyzing data that is formalized through data refinement. While the accuracy for short text is high, long one consisted of several words like as document that is not able to analyze the meaning contained in sentences. In semantic analysis level, the method of automatic classification is used to classify sentences composed of several words by unstructured data analysis. There was an attempt to find similar documents by combining the two methods. However, it have a problem in the algorithm w the methods of analysis are different ways to use simultaneous unstructured data and regular data. In this paper, we study the method of extracting keywords implied in the document and using the LDA(Latent Semantic Analysis) method to classify documents efficiently without human intervention and finding similar patents.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.348-354
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• 2003

This proposes a new algorithm for advanced personal identification system using iris pattern and speech signal. Since the proposed algorithm adopts a fusion scheme to take advantage of iris recognition and speaker identification, it shows robustness for noisy environments. For evaluating the performance of the proposed scheme, we compare it with the iris pattern recognition and speaker identification respectively. In the experiments, the proposed method showed more 56.7% improvements than the iris recognition method and more 10% improvements than the speaker identification method for high quality security level. Also, in noisy environments, the proposed method showed more 30% improvements than the iris recognition method and more 60% improvements than the speaker identification method for high quality security level.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.417-424
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• 2010

In this paper the real-time face region was detected by suggesting the rectangular feature-based classifier and the robust detection algorithm that satisfied the efficiency of computation and detection performance was suggested. By using the detected face region as a recognition input image, in this paper the face recognition method combined with PCA and the multi-layer network which is one of the intelligent classification was suggested and its performance was evaluated. As a pre-processing algorithm of input face image, this method computes the eigenface through PCA and expresses the training images with it as a fundamental vector. Each image takes the set of weights for the fundamental vector as a feature vector and it reduces the dimension of image at the same time, and then the face recognition is performed by inputting the multi-layer neural network.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.243-248
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• 2014

Recently, solar energy is expanding to combination of computing in real time by tracking the position of the sun to estimate the angle of inclination and make up freshly correcting a part of the solar radiation. Solar power is need that reliably linked technology to power generation system renewable energy in order to efficient power production that is difficult to output predict based on the position of the sun rise. In this paper, we analysis of prediction model for solar power generation to estimate the predictive value of solar power generation in the development of real-time weather data. Photovoltaic power generation input the correction factor such as temperature, module characteristics by the solar generator module and the location of the local angle of inclination to analyze the predictive power generation algorithm for the prediction calculation to predict the final generation. In addition, the proposed model in real-time national weather service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.