• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.173-180
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• 2004

In this paper we provide a new image restoration method based on the multiscale regularization in the redundant wavelet transform domain. The proposed method uses the redundant wavelet transform to decompose the single-scale image restoration problem to multiscale ones and applies scale dependent regularization to the decomposed restoration problems. The proposed method recovers sharp edges by applying rather less regularization to wavelet related restorations, while suppressing the resulting noise magnification by the wavelet shrinkage algorithm. The improved performance of the proposed method over more traditional Wiener filtering is shown through numerical experiments.

• Journal of Gifted/Talented Education
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• v.21 no.2
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• pp.449-463
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• 2011

The purpose of this study was to examine the validity of Multiple Intelligence Scales for Young Korean Children (MIS-YKC). Participants of this study were 357 children's parents and teachers from Seoul, Gyeongdo, Jeonlado & Choongchungdo. Data were analyzed by confirmatory factor analysis, Pearson's r and Cronbach's ${\alpha}$. Results are as follows. (1) Confirmatory factor analysis of MIS-YKC for parents MIS-YKC revealed that fit indices such as $X^2$=365.712 (df=168, p=.000), RMSEA=.057, SRMR=.047, NNFI=.935, CFI=.948. and MIS-KYC by teacher's evaluation $X^2$=436.765 (df=168, p=.000), RMSEA=.066, SRMR=.051, NNFI=.917, CFI=.934. (2) Correlations between multiple intelligence scales and IQ were significant. (3) Cronbach's ${\alpha}$ ranged from .80 and .86 for seven intelligence scales and .95 for the total scale by parents' evaluation. Cronbach's ${\alpha}$ is ranged from .76 and .91 for seven intelligence scales and .95 for the total scale by teacher's evaluation. All these results show that the multiple intelligence scales for young Korean children parents and teachers are quite reliable and valid.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.04b
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• pp.955-958
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• 2002

본 논문의 침입탐지시스템에서는 퍼지 추론을 통한 대표적인 세가지 다중 척도 결합을 제안하였다. 그 중 시스템 호출 척도에서는 권한이동 정보만을 이용한 감사자료 축약방법으로 기존 HMM 모델의 문제점인 모델링 시간 단축을 가능하게 하였고, 프로세스 척도에서는 권한이동 기반 모듈의 단점을 보완하기 위하여 모든 감사자료에 대하여 통계적 분석방법을 사용을 사용하였다. 파일 입출력 척도에서는 상태전이 모니터링을 통하여 파일에 대한 접속 상태 변이를 분석하는 방법을 제안하였다.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.397-406
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• 2003

As the information technology grows interests in the intrusion detection system (IDS), which detects unauthorized usage, misuse by a local user and modification of important data, has been raised. In the field of anomaly-based IDS several artificial intelligence techniques such as hidden Markov model (HMM), artificial neural network, statistical techniques and expert systems are used to model network rackets, system call audit data, etc. However, there are undetectable intrusion types for each measure and modeling method because each intrusion type makes anomalies at individual measure. To overcome this drawback of single-measure anomaly detector, this paper proposes a multiple-measure intrusion detection method. We measure normal behavior by systems calls, resource usage and file access events and build up profiles for normal behavior with hidden Markov model, statistical method and rule-base method, which are integrated with a rule-based approach. Experimental results with real data clearly demonstrate the effectiveness of the proposed method that has significantly low false-positive error rate against various types of intrusion.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.4
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• pp.1-12
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• 2018

Currently, a large amount of printed matter associated with code authentication method are diffused widely, however, they have been reproduced with great precision and distributed successively in illegal ways. In this paper, we propose an efficient code authentication method which classifies authentic or counterfeit with smart-phone, effectively. The proposed method stores original image code in the server side and then extracts multiple comparison measures describing the original image. Based on these multiple measures, a code authentication algorithm is designed in such a way that counterfeit printed images may be effectively classified and then the recognition rate may be highly improved. Through real experiments, it is shown that the proposed method can improve the recognition rate greatly and lower the mis-recognition rate, compared with single measure method.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.523-525
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• 2002

정보통신기술이 발전함에 따라 시스템 보안의 중요성이 점점 높아지고 있다. 이어 따라 내부자의 불법적인 시스템 사용이나 외부 침입자애 의한 중요 정보의 유출 및 조작을 알아내는 침입탐지시스템에 대한 연구가 활발히 이루어지고 있다. 침입탐지시스템에서는 사용자가 입력한 명령어, 네트워크 패킷, 시스템 호출 감사자료, 시스템 사용시간 등의 다양한 척도를 사용하여 침입여부를 결정하는데 사용하는 척도와 모델링 방법에 따라 취약점이 존재하여 탐지하지 못하는 침입이 있다. 본 논문에서는 단일척도 침입탐지 시스템의 취약점을 보안하기 위해 시스템 호출, 프로세스의 자원점유율, 파일접근이벤트의 세 가지 척도를 각각 최적의 방법으로 모델링 한 후 결합하는 침입탐지 방법을 제안하고 실험을 통해 그 가능성을 보인다.

• Clean Technology
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• v.17 no.2
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• pp.175-180
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• 2011

A novel multi-criteria decision making strategy is developed for the construction of industrial symbiosis network in eco-industrial park and the strategy is applied to the construction of acid/alkali wastewater neutralization network in Yeosu industrial complex. Acid (or alkali) wastewater is commonly generated in chemical industries, and it can be used as neutralizing agent for alkali (or acid) wastewater generated from another source. As a consequence, a large-scale industrial symbiosis network for wastewater neutralization can be constructed in petrochemical complexes where a large amount of acid/alkali wastewater is generated. In this study, substance flow model is constructed which describes the wastewater neutralization network and multi-criteria decision making strategy is applied to find a few candidate for industrial symbiosis network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.992-999
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• 2014

This paper presents an extensive experimental comparison of a variety of multi-label learning methods for the accurate prediction of subcellular localization of proteins which simultaneously exist at multiple subcellular locations. We compared several methods from three categories of multi-label classification algorithms: algorithm adaptation, problem transformation, and meta learning. Experimental results are analyzed using 12 multi-label evaluation measures to assess the behavior of the methods from a variety of view-points. We also use a new summarization measure to find the best performing method. Experimental results show that the best performing methods are power-set method pruning a infrequently occurring subsets of labels and classifier chains modeling relevant labels with an additional feature. futhermore, ensembles of many classifiers of these methods enhance the performance further. The recommendation from this study is that the correlation of subcellular locations is an effective clue for classification, this is because the subcellular locations of proteins performing certain biological function are not independent but correlated.

• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.13-22
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• 2013

Smartphone addiction has become more serious than internet addiction since people can download and run numerous applications with smartphones even without internet connection. However, smartphone addiction is not sufficiently dealt with in current studies. The S-scale method developed by Korea National Information Society Agency involves so many questions that respondents are likely to avoid the diagnosis itself. Moreover, since S-scale is determined by the total score of responded items without taking into account of demographic variables, it is difficult to get an accurate result. Therefore, in this paper, we have extracted important factors from all data, which affect smartphone addiction, including demographic variables. Then we classified the selected items with a neural network. The result of a comparative analysis with backpropagation learning algorithm and multiclass support vector machine shows that learning rate is slightly higher in multiclass SVM. Since multiclass SVM suggested in this paper is highly adaptable to rapid changes of data, we expect that it will lead to a more accurate self-diagnosis of smartphone addiction.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1983-1984
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• 2011

본 논문에서는 흉부 X선 영상으로부터 폐 종류 음영을 검출하기 위한 필터를 예측해서 바람직하게 평가하기 위한 방법을 제안한다. 더욱이 그 평가방법을 이용해서 이전부터 제안한 다중해상도 라플라시안-가우시안 필터의 평가를 행한다. 전문의의 진단보조 혹은 종합자동진단시스템의 구성요소로서 필터가 행하는 역할을 고려한 후에 필터가 만족해야할 조건 및 그 조건을 만족한 경우에 있어서 몇가지 성능평가 척도를 명확히 한다. 제안한 평가방법을 통해서 다중해상도 필터가 단일해상도 필터에 비해 높은 성능을 갖게됨을 명확히 한다.