• Journal of the Korean Society for information Management
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• v.28 no.2
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• pp.79-96
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• 2011

Despite the widespread use, critics claim that citation analysis has serious limitations in evaluating the research performance of scholars. First, conventional citation analysis methods yield one-dimensional and sometimes misleading evaluation as a result of not taking into account differences in citation quality, not filtering out citation noise such as self-citations, and not considering non-numeric aspects of citations such as language, culture, and time. Second, the citation database coverage of today is disjoint and incomplete, which can result in conflicting quality assessment outcomes across different data sources. This paper discuss the findings from a citation analysis study that measured the impact of scholarly publications based on the data mined from Web of Science, Scopus, and Google Scholar, and briefly describes a work-in-progress prototype system called CiteSearch, which is designed to overcome the weaknesses of existing citation analysis methods with a robust citation-based quality assessment approach.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.230-237
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• 2001

Adaptive filters are widely used for acoustic echo canceler, adaptive equalizer and adaptive noise canceler. Coefficients of adaptive filters are updated by NLMS algorithm. However, Coefficients are misaligned by ambient noises when they are adapted by NLMS algorithm. In this Paper, a method determined the adaptation constant by low-pass filtered instantaneous gradient vector of LMS algorithm using orthognality principles of optimal filter is proposed. At initial states, instantaneous gradient vector, that is the cross-correlation of input signals and estimation error signals, has large value because input signals are remained in estimation error signals. When an adaptive filter is conversed, the cross-correlation will be close to zero. It isn's affected by ambient noises because ambient noises are uncorrelated with input signals. Determining adaptation constant with the cross-correlation, adaptive filters can be robust to ambient noises and the convergence rate doesn't slower As results of computer simulations, it is shown that the performance of proposed algorithm is betted than that of conventional algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.8
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.

• Journal of Korea Multimedia Society
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• v.12 no.11
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• pp.1692-1700
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• 2009

This paper proposes the direction distribution of surface normal vectors as a feature descriptor of three-dimensional models. Proposed the feature descriptor handles rotation invariance using a principal component analysis(PCA) method, and performs mesh simplification to make it robust and nonsensitive against noise addition. Our method picks samples for the distribution of normal vectors to be proportional to the area of each polygon, applies weight to the normal vectors, and applies interpolation to enhance discrimination so that the information on the surface with less area may be less reflected on composing a feature descriptor. This research measures similarity between models with a L1-norm in the probability density histogram where the distances of feature descriptors are normalized. Experimental results have shown that the proposed method has improved the retrieval performance described in an average normalized modified retrieval rank(ANMRR) by about 17.2% and the retrieval performance described in a quantitative discrimination scale by 9.6%~17.5% as compared to the existing method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.5
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• pp.2381-2387
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• 2013

This paper deals with an optimal angle error reduction method of magnetic hall sensor using hall effect elements with yoke. The magnetic position sensor is required to generate ideal sine and cosine waveforms from its hall effect elements according to rotation angle for precise angle information. However, the output signals are easy to include harmonics due to uneven magnetic field distribution from disturbance in the vicinity of hall effect elements. Thus, The paper studies a way which makes sine and cosine waveforms robust in disturbance and reduces harmonics by installing a yoke around Hall effect elements. The angle detection simulation for the magnetic hall sensor is performed by 3 dimensional finite element method and Taguchi method, one of the design of experiments. For the Taguchi method, three design parameters related to position of hall effect elements and shape of hall effect element yoke are selected.

• Journal of KIISE:Software and Applications
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• v.37 no.8
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• pp.629-640
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• 2010

The exemplar-based inpainting model is widely used to remove objects from natural images and to restore a damaged region. This paper presents a method which improves the performance of the conventional exemplar-based inpainting model by modifying three major parts in the model: data term, confidence term and patch selection. While the conventional data term is calculated using the local gradient, the proposed method uses 16 compass masks to get the global gradient to make the method robust to noise. To overcome the problem that the confidence term gets negligible in the inside of the eliminated region, a method is proposed which makes the confidence term decrease slowly in the eliminated region. The patch selection procedure is modified so that the closer patch has higher weight. Experiments showed that the proposed method produced more natural images and lower reconstruction error than the conventional exemplar-based inpainting.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.45-51
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• 2016

In this paper, we develop an iterative maximum likelihood (ML) receiver for generalized spatial modulation systems. In the proposed ML receiver, to mitigate the deleterious effect of channel information errors on symbol detection, the instantaneous covariance matrix of effective noise is estimated, which is then used to obtain improved ML solutions. The estimated covariance matrix is updated through multiple iterations to enhance the estimation accuracy. The simulation results show that the proposed ML receiver outperforms the conventional ML detection scheme, which does not take the effect of channel information errors into account.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1401-1410
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• 2017

Cryptographic synchronization which synchronizes internal state of cryptographic algorithm and ciphertext stream between an encryptor and a decryptor affects the quality of secure communication. If there happens a synchronization loss between a transmitter and a receiver in a secure communication, the output of the receiver is unintelligible until resynchronization is made. Especially, in the secure communication on a wireless channel with high BER, synchronization performance can dominate its quality. In this paper, we proposed a novel and noise robust synchronization signal generation method as well as its detection algorithm. We generated a synchronization signal in the form of a masking structure based on the maximal length sequence, and developed a detection algorithm using a correlation property of the maximal length sequence. Experimental results have demonstrated that the proposed synchronization signal outperforms the conventional concatenated type synchronization signal in a noisy environment.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.33-41
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• 2011

Although conventional text-based passwords are used as the most common authentication method, they have significant drawbacks such as guess attacks, dictionary attacks, key loggers, and shoulder-surfing. To address the vulnerabilities of traditional text-based passwords, graphical password schemes have been developed as possible alternative solutions, but they have a potential drawback that they are more vulnerable to shoulder-surfing than conventional text-based passwords. In this paper, we present a new Hangul password input method to prevent shoulder-surfing attacks. Our approach uses Hangul as a password, and it requires the users to locate their password in the given wheeling password grid instead of entering the password. Our approach makes it difficult for attackers to observe a user's password since the system shows the users' passwords with decoy characters as the noise on the screen. Also, we provide security analysis for random attacks, dictionary attacks, and shoulder-surfing attacks, and it shows that our password system is robust against these attacks.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.2
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• pp.1-13
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• 2017

In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.