• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.5
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• pp.280-288
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• 2003

In this paper, we propose a design method of the LVQ network using the SOM. The proposed method determines subclasses and initial reference vectors of the LVQ network using the SOM. The efficacy of the proposed method is verified by means of simulations on iris data of Fisher and character recognition. The results show that the proposed method improves considerably on the performance of the conventional LVQ network.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1987.04a
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• pp.9-13
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• 1987

K-emans alsor/thm was used to classify cloud-type that is low, mix and cumuionimbus Tnitiat ciustercenters and K parameter is given in this paper by coatse computins and Fisher’s alsorithm. Results indicate that performance index is minimized and mix cloud is well clallified.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.205-209
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• 1999

일반화된 지수생존모형(generalized exponential survival model)을 고려하여 이 모형의 모수를 추정하는 수정된 FS(modified Fisher scoring)방법을 제안한다. 이를 위해 우도방정식(likelihood equation)을 유도하고 초기추정치 (initial estimate)를 포함한 추정알고리즘(estimating algorithm)을 개발한다.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.67-77
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• 1999

For a orientation-shift model supported on the unit sphere, Euler angles are the conventional measure to parametrize orientation-shifts. The essential role which is played by rotationally symmetry of an underlying distribution is reviewed. In this paper we propose the inference procedure based on Euler angles for the rotationally symmetric spherical distribution. The likelihood ratio test(LRT) based on the Euler angles is worked out. The asymptotic distribution of the test under the null hypotheses and certain contiguous alternatives is obtained.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1101-1110
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• 2008

The present paper investigates about the formation of the logical thinking and the intuitive thinking in mathematical concepts with reference to secondary talented students (students aged 16$\sim$17 years). As a main result, we conclude that their preference between the logical and the intuitive thinking does not related to the distinction of the school level and sex, while their consistence between them relates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1424-1440
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• 2015

It is a challenging problem to search the intended images from a large number of candidates. Content based image retrieval (CBIR) is the most promising way to tackle this problem, where the most important topic is to measure the similarity of images so as to cover the variance of shape, color, pose, illumination etc. While previous works made significant progresses, their adaption ability to dataset is not fully explored. In this paper, we propose a similarity learning method on the basis of probabilistic generative model, i.e., probabilistic latent semantic analysis (PLSA). It first derives Fisher kernel, a function over the parameters and variables, based on PLSA. Then, the parameters are determined through simultaneously maximizing the log likelihood function of PLSA and the retrieval performance over the training dataset. The main advantages of this work are twofold: (1) deriving similarity measure based on PLSA which fully exploits the data distribution and Bayes inference; (2) learning model parameters by maximizing the fitting of model to data and the retrieval performance simultaneously. The proposed method (PLSA-FK) is empirically evaluated over three datasets, and the results exhibit promising performance.

• The Journal of Engineering Geology
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• v.6 no.2
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• pp.83-93
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• 1996

A method is proposed to estimate aquifer parameters in a heterogeneous and anisotropic aquifer under steady-state groundwater flow conditions on the basis of maximum likelihood concept. Zonation method is adopted for parameterization, and estimation errors are analyzed by examining the estimation error covariance matrix in the eigenspace. This study demonstrates the ability of the proposed model to estimate parameters and helps to understand the characteristics of the inverse problem. This study also explores various features of the inverse methodology by applying it to a set of field data of the Taegu area. In the field example, transmissivities were estimated under three different zonation patterns. Recharge rates in the Taegu area were also estimated using MODINV which is an inverse model compatible with MODFLOW.The estimation results indicate that anisotropy of aquifer parameters should be considered for the crystalline rock aquifer which is the dominant aquifer system in Korea.

• Agribusiness and Information Management
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• v.2 no.1
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• pp.15-29
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• 2010

Recently, IPTV population is growing by leaps and bounds. and We performed FGI(Focus Group Interview) with various experts related to agriculture field to establish Agriculture and Fisheries special channel. this growth has social background that is change of paradigm caused by the convergence of broadcasting, demand for Agriculture and Fisheries special channel using new media thanks to interests in Wellbeing, Green food. so we think that we need to consider the way to establish Agriculture and Fisheries special channel and its validity from all angles. that is why we are having a heated discussion with Agriculture and Fisheries marketing experts, farmer, fisher(Korean Cyber Farmer Association), broadcasting experts. Concretely, government budget is needed to establish Agriculture and Fisheries special channel, so we are just about to examine its validity and find business model. to make this discussion detailed, we made 4 subjects. First, Do we need agro-fishery products distribution channel using media? Second, After establishing of Agriculture and Fisheries special channel, how many demands will occur? Third, Should we make Agriculture and Fisheries special channel public channel? Fourth, What would be profit model of Agriculture and Fisheries special channel?

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1291-1300
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• 2008

In this paper, we propose a intelligent system to improve the accuracy of pattern recognition. The proposed intelligent system consist in SOFM, LVQ and FCM algorithm. We are confirmed the effectiveness of the proposed intelligent system through the several experiments that classify Fisher's Iris data and face image data that offered by ORL of Cambridge Univ. and EMG data. As the results of experiments, the proposed intelligent system has better accuracy of pattern recognition than general LVQ.