• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.1
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• pp.83-90
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• 2002

This paper proposed the strategy learning method by means of the fusion of Back-Propagation neural network and Q learning algorithm for two-person, deterministic janggi board game. The learning process is accomplished simply through the playing each other. The system consists of two parts of move generator and search kernel. The one consists of move generator generating the moves on the board, the other consists of back-propagation and Q learning plus $\alpha$$\beta$ search algorithm in an attempt to learn the evaluation function. while temporal difference learns the discrepancy between the adjacent rewards, Q learning acquires the optimal policies even when there is no prior knowledge of effects of its moves on the environment through the learning of the evaluation function for the augmented rewards. Depended on the evaluation function through lots of games through the learning procedure it proved that the percentage won is linearly proportional to the portion of learning in general.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.2
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• pp.86-99
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• 2007

Packet filtering is to filter out potentially malicious network packets. In order to test a packet filtering function we should verify whether security policies are performed correctly as intended. However there are few existing tools to test the function. Besides, they need user participation when generating test cases or deciding test results. Many security administrators have a burden to test systematically new security policies when they establish new policies or modify the existing ones. To mitigate the burdens we suggest a new test method with minimal user articipation. Our tool automates generation steps of the test cases and the test oracles, respectively. By using the test oracles generated automatically, deciding test results is possible without user intervention. Our method realizes an automatic testing in three phases; test preparation phase, test execution, and test evaluation. As a result it may enhance confidence of test activities more highly. This paper describes the design and implementation of our test method and tool.

• Plant Breeding and Biotechnology
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• v.6 no.4
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• pp.313-320
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• 2018

Rice is the staple food of more than 50% of the world population. Cultivated rice has the AA genome (diploid, 2n = 24) and small genome size of only 430 megabase (haploid genome). As the sequencing of rice genome was completed by the International Rice Genome Sequencing Project (IRGSP), many researchers in the world have been working to explore the gene function on rice genome. Insertional mutagenesis has been a powerful strategy for assessing gene function. In maize, well characterized transposable elements have traditionally been used to clone genes for which only phenotypic information is available. In rice endogenous mobile elements such as MITE and Tos have been used to generate gene-tagged populations. To date T-DNA and maize transposable element systems have been utilized as main insertional mutagens in rice. The Ac/Ds system offers the advantage of generating new mutants by secondary transposition from a single tagged gene. To enhance the efficiency of gene detection, advanced gene-tagging systems (i.e. activation, gene or enhancer trap) have been employed for functional genomic studies in rice. Internationally, there have been many projects to develop large scales of insertional mutagenized populations and databases of insertion sites has been established. Ultimate goals of these projects are to supply genetic materials and informations essential for functional analysis of rice genes and for breeding using agronomically important genes. In this report, we summarize the current status of Ac/Ds-mediated gene tagging systems that has been conducted by collaborative works in Korea.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.3
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• pp.97-104
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• 2002

In this paper we describe the method which optimizes the partition of the input space by means of measure of fuzziness for fuzzy neural network. It covers its generation of fuzzy rules for input sub space. It verifies the performance of the system depended on the various time interval of the input. This method divides the input space into several fuzzy regions and assigns a degree of each of the generated rules for the partitioned subspaces from the given data using the Shannon function and fuzzy entropy function generating the optimal knowledge base without the irrelevant rules. In this scheme the basic idea of the fuzzy neural network is to realize the fuzzy rule base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by the steepest descent algorithm. According to the input interval the proposed inference procedure proves that the fast convergence of root mean square error (RMSE) owes to the optimal partition of the input space

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.3-8
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• 2016

We propose a modified form of the decision-directed least mean square (DD LMS) algorithm that is widely used in the optimization of self-adaptive equalizers, and show the modified version greatly improves the initial convergence properties of the conventional algorithm. Existing DD LMS regards the difference between a equalizer output and a quantization value for it as an error, and achieves an optimization of the equalizer based on minimizing the mean squared error cost function for the equalizer coefficients. This error generating method is useful for binary signal or a single-level signals, however, in the case of multi-level signals, it is not effective in the initialization of the equalizer. The modified DD LMS solves this problem by modifying the error generation. We verified the usefulness and performance of the modified DD LMS through experiments with multi-level signals under distortions due to intersymbol interference and additive noise.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.2
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• pp.321-330
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• 2015

There have been found many modified malwares which could avoid detection simply by replacing a sequence of characters or a part of code. Since the existing anti-virus program performs signature-based analysis, it is difficult to detect a malware which is slightly different from the well-known malware. This paper suggests a method of detecting modified malwares by extending a hash-value based code comparison. We generated hash values for individual functions and individual code blocks as well as the whole code, and thus use those values to find whether a pair of codes are similar in a certain degree. We also eliminated some numeric data such as constant and address before generating hash values to avoid incorrectness incurred from them. We found that the suggested method could effectively find inherent similarity between original malware and its derived ones.

• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.227-243
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• 2008

This study investigates an event detection method with the aim of generating an event-focused news summary from a set of news articles on a certain event using a multi-document summarization technique. The event detection method first classifies news articles into the event related topic categories by employing a SVM classifier and then creates event clusters containing news articles on an event by a modified single pass clustering algorithm. The clustering algorithm applies a time penalty function as well as cluster partitioning to enhance the clustering performance. It was found that the event detection method proposed in this study showed a satisfactory performance in terms of both the F-measure and the detection cost.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.7-13
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• 2021

In this paper, the function of starting the negative voltage used in the IT equipment when it is generated and the method of controlling it using a microcontroller for the function to detect the overload and respond to it are presented. To do this, the limitations of the existing negative voltage generation circuit and the problems that occur during overload were analyzed, and a circuit that detects and controls the overload condition without a separate current sensing circuit was presented. In order to confirm the effect of the proposed method, an experiment was conducted by configuring an experimental circuit. As a result of the experiment, compared to the existing negative voltage generation circuit, which falls into a latch-up state when overloaded and enters a dangerous state, the proposed circuit detects this, stop the operation of the circuit, and informs the user of such an abnormal state to take action. have. In addition, since the starting point of the circuit is determined according to the system state, the experimental result was confirmed that the starting time was significantly shortened by about 23% compared to the time switch method.

• The Journal of the Korea Contents Association
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• v.3 no.3
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• pp.11-18
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• 2003

Error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information. To solve this problem, we propose the improved method appling edge enhanced weights based on local characteristic of the original images. We consider edge information as local characteristic. First, we produce edges by appling 3$\times$3 sobel operator to the original image. The edge is normalized from 0 to 1. Edge information weights are computed by using sinusoidal function and the normalized edge information. The edge enhanced weights are computed by using edge information weights multiplied input pixels. The proposed method is compared with conventional methods by measuring the edge correlation and quality of the recovered images from the halftoned images. The proposed method provides better quality than the conventional method due to the enhanced edge and represents efficiently the detail edge. Also, the proposed method is improved in edge representation than the conventional method.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.3
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• pp.501-507
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• 2015

The online banking service handles a banking business over the internet, it is necessary to ensure that all financial transactions are processed securely. So, there are various authentication technique for e-banking service : a certificate, a personal identification number(PIN), a security card and a one-time password(OTP). Especially, the security card is most important means including secret information. If the secret information of card is leaked, it means not only loss of security but also easy to attack because security card is a difficult method to get. In this paper, we propose that a multi-channel security card saves an secret information in distributed channel. Proposed multi-channel security card reduces vulnerability of the exposed and has a function to prevent phishing attacks through decreasing the amount of information displayed and generating secret number randomly.