• Journal of Engineering Education Research
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• v.23 no.3
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• pp.59-65
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• 2020

This paper introduces the association method for the program outcomes of engineering education accreditation and the competency units of National Competency Standards(NCS). This association method can be used to efficiently develop an engineering curriculum that is based on both of the NCS and the engineering education accreditation. The association method consists of an analysis phase, an association phase and a checking phase. We also deals with the curriculum development procedure that uses the proposed association of program outcomes and competency units. Also, we provide the application of this method to the computer engineering program for NCS-based engineering education accreditation. Thus we can systematically and efficiently develop curriculums for the NCS-based engineering education accreditation by using the proposed method.

• The Journal of the Acoustical Society of Korea
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• v.40 no.2
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• pp.109-120
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• 2021

This paper proposes the H∞ norm based data association gate method to apply robustly the data association gate of passive sonar automatic target tracking which is on non-linear targets in dense cluttered environment. For target tracking, data association method selects the measurements within validated gate, which means validated measuring extent, as candidates for the data association. If the extent of the validated gate in the data association is not proper or the data association executes under dense cluttered environment, it is difficult to maintain the robustness of target tracking due to interference of clutter measurements. To resolve this problem, this paper proposes a novel gating method which applies H∞ norm based bisection algorithm combined with 3-σ gate method under Gaussian distribution assumption and tracking error covariance. The proposed method leads to alleviate the interference of clutters and to track the non-linear maneuvering target robustly. Through analytic method and simulation to utilize simulated data of horizontal and vertical bearing measurements, improvement of data association robustness is confirmed contrary to the conventional method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.240-259
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• 2020

Analyzing network traffic is the basis of dealing with network security issues. Most of the network security systems depend on the feature selection of network traffic data and the detection ability of malicious traffic in network can be improved by the correct method of feature selection. An FAFS method, which is short for Fuzzy Association Feature Selection method, is proposed in this paper for network malicious traffic detection. Association rules, which can reflect the relationship among different characteristic attributes of network traffic data, are mined by association analysis. The membership value of association rules are obtained by the calculation of fuzzy reasoning. The data features with the highest correlation intensity in network data sets are calculated by comparing the membership values in association rules. The dimension of data features are reduced and the detection ability of malicious traffic detection algorithm in network is improved by FAFS method. To verify the effect of malicious traffic feature selection by FAFS method, FAFS method is used to select data features of different dataset in this paper. Then, K-Nearest Neighbor algorithm, C4.5 Decision Tree algorithm and Naïve Bayes algorithm are used to test on the dataset above. Moreover, FAFS method is also compared with classical feature selection methods. The analysis of experimental results show that the precision and recall rate of malicious traffic detection in the network can be significantly improved by FAFS method, which provides a valuable reference for the establishment of network security system.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.5
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• pp.812-817
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• 2011

In this paper, we propose new data association method called the Highest Probability Data Association with Limited Measurement Numbers(HPDA-LIMN) using a Signal Itensity Ordering method applied to tracking in clutter environment. The performance of HPDA-LIMN algorithm is tested in a series of Monte Carlo simulations runs and is compared with the exiting data association method in cluttered environment.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.351-361
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• 2003

The previous studies to extract features for document through word association have the problems of updating profiles periodically, dealing with noun phrases, and calculating the probability for indices. We propose more effective feature extraction method which is using association word mining. The association word mining method, by using Apriori algorithm, represents a feature for document as not single words but association-word-vectors. Association words extracted from document by Apriori algorithm depend on confidence, support, and the number of composed words. This paper proposes an effective method to determine confidence, support, and the number of words composing association words. Since the feature extraction method using association word mining does not use the profile, it need not update the profile, and automatically generates noun phrase by using confidence and support at Apriori algorithm without calculating the probability for index. We apply the proposed method to document classification using Naive Bayes classifier, and compare it with methods of information gain and TFㆍIDF. Besides, we compare the method proposed in this paper with document classification methods using index association and word association based on the model of probability, respectively.

• International Journal of Contents
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• v.7 no.4
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• pp.19-23
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• 2011

This paper proposes a segmentation method for overlapped vehicles based on analysis of the vehicle location and the spatiotemporal association information. This method can be used in an intelligent transport system. In the proposed method, occlusion is detected by analyzing the association information based on a vehicle's location in continuous images, and occlusion segmentation is carried out by using the vehicle information prior to occlusion. In addition, the size variations of the vehicle to which association tracking is applied can be anticipated by learning the variations according to the overlapped vehicles' movements. To assess the performance of the suggested method, image data collected from CCTVs recording traffic information is used, and average success rate of occlusion segmentation is 96.9%.

• Journal of the Korean Professional Engineers Association
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• v.34 no.1
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• pp.35-43
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• 2001

This paper Is described for the maintenance and repair method for the pier structure currently under repair works in the Han river bridges. During the economic growth period from the year 1960 to 1980, our engineer was concentrated only for study of the construction method of bridge. We have neglected the importance for the maintenance & repair method of construction structure. Therefore this paper will give you some ideas of repair and maintenance method.

• Journal of the Korean Professional Engineers Association
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• v.33 no.1
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• pp.83-88
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• 2000

Taguchi developed and provided various independent methods for actual application in design of experiments. Taguchi method is described in philosophy, method and others related to quality management. This thesis is one of case studies for improving the bond strength of epoxy resin by Taguchi method which is applied as a optimum developing tool in six sigma management revolution in many companies.

• Journal of Korea Multimedia Society
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• v.4 no.2
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• pp.171-181
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• 2001

The previous Bayesian document categorization method has problems that it requires a lot of time and effort in word clustering and it hardly reflects the semantic information between words. In this paper, we propose a weighted Bayesian document categorizing method based on association word knowledge base acquired by mining technique. The proposed method constructs weighted association word knowledge base using documents in training set. Then, classifier using Bayesian probability categorizes documents based on the constructed association word knowledge base. In order to evaluate performance of the proposed method, we compare our experimental results with those of weighted Bayesian document categorizing method using vocabulary dictionary by mutual information, weighted Bayesian document categorizing method, and simple Bayesian document categorizing method. The experimental result shows that weighted Bayesian categorizing method using association word knowledge base has improved performance 0.87% and 2.77% and 5.09% over weighted Bayesian categorizing method using vocabulary dictionary by mutual information and weighted Bayesian method and simple Bayesian method, respectively.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.55-62
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• 2015

This study suggested Nationwide Inundation Analysis method for Storm and Flood Damage Insurance Rate. Suggested modified Level-Pool method considers Zoning of urban plan to reflect real inundated area and limit inundation-boundary. Inundated area, as results of modified Level-Pool method, compared with inundation risk area on "storm and flood damage mitigation total plan". Simulated inundated area by modified Level-Pool method was more matched than results of traditional method. Therefore, modified Level-Pool method could be useful to analyze nationwide inundated area.