• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.203-210
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• 2000

In this paper, we propose a new unsupervised learning network and competitive learning algorithm for pattern classification. The proposed network is based on relative similarity, which is similarity measure between input data and cluster group. So, the proposed network and algorithm is called relative similarity network(RSN) and learning algorithm. According to definition of similarity and learning rule, structure of RSN is designed and pseudo code of the algorithm is described. In general pattern classification, RSN, in spite of deletion of learning rate, resulted in the identical performance with those of WTA, and SOM. While, in the patterns with cluster groups of unclear boundary, or patterns with different density and various size of cluster groups, RSN produced more effective classification than those of other networks.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1240-1242
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• 1996

In a still mill, the effective surface defect inspection algorithm is necessary. For this purpose, this paper proposed the preprocessing algorithm for surface defect inspection of cold mill strip. This consists of live steps. They are edge detection, binarizing, noise deletion, combining of fragmented defect and selecting the largest defect. Especially, binarizing is a critical problem. Bemuse the performance of the preprocessing is largely depend on the binarized image. So, we develope the adaptive thresholding method, which is multilevel thresholding. The thresholding value is varied according to the mean graylevel value of each test image. To investigate the performance of the proposed algorithm, we classified the detected defect using neural network. The test image is 20 defect images captured at German Sick Co. This algorithm is proved to have good property in cold mill strip surface inspection.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.35-42
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• 2014

This paper suggests a method that obtains the minimum spanning tree (MST) far more easily and rapidly than the present ones. The suggested algorithm, firstly, simplifies a graph by means of reducing the number of edges of the graph. To achieve this, it applies a method of eliminating the maximum weight edge if the valency of vertices of the graph is equal to or more than 3. As a result of this step, we can obtain the reduced edge population. Next, it applies a method in which the maximum weight edge is eliminated within the cycle. On applying the suggested population minimizing and maximum weight edge deletion algorithms to 9 various graphs, as many as the number of cycles of the graph is executed and MST is easily obtained. It turns out to lessen 66% of the number of cycles and obtain the MST in at least 2 and at most 8 cycles by only deleting the maximum weight edges.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.11
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• pp.613-619
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• 2001

The IP address lookup problem is to find the longest matching IP prefix for a given IP address from the routing table and has been a central bottleneck in speeding up the Internet. In this paper, we propose a new algorithm for this problem based on the segment tree data structure. Given n IP prefixes, our algorithm can do IP address in Ο(log n) time. It also handles the insertion and deletion of IP prefixes efficiently without rebuilding the total data structure.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.763-769
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• 2022

Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.605-629
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• 2023

This paper proposes some diagnostics procedures for the skew-t linear regression model with censored response. The skew-t distribution is an attractive family of asymmetrical heavy-tailed densities that includes the normal, skew-normal and student's-t distributions as special cases. Inspired by the power and wide applicability of the EM-type algorithm, local and global influence analysis, based on the conditional expectation of the complete-data log-likelihood function are developed, following Zhu and Lee's approach. For the local influence analysis, four specific perturbation schemes are discussed. Two real data sets, from education and economics, which are right and left censoring, respectively, are analyzed in order to illustrate the usefulness of the proposed methodology.

• Journal of Korean Society of Transportation
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• v.24 no.3 s.89
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• pp.167-176
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• 2006

An minimum path algorithm for integrated networks with departure time constraints require considering arrival time of arriving mode, transfer time. waiting time, and departure time of next mode. Integrated network with diverse modes commonly include departure time constraints. Because public mode suck as train and airplane have fixed service schedule which provide passengers. This study developed the k-path algorithm in integrated network with time varying conditions and departure time constraints. We proposed the extended method based on entire path deletion method, and examined the application of the proposed algorithm through case study.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.3
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• pp.237-250
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• 2003

Since an orthotropic steel deck bridge has large number of design variables and shows complex structural behavior, it would be very difficult and impractical to directly use a Conventional Single Level (CSL) optimization algorithm for its optimum design. Thus, in this paper, an Improved Multi Level Design Synthesis (IMLDS) optimization algorithm is proposed to improve the computational efficiency. In the proposed IMLDS algorithm, a coordination method is introduced to divide the bridge into main girders and orthotropic steel deck with preserving the characteristics of the structural behavior. For an efficient optimization of the bridge, the IMLDS algorithm incorporates the various crucial approximation techniques such as constraints deletion, Automatic Differentiation (AD), stress reanalysis, and etc. In the case of orthotropic steel deck system, optimum design problems are characterized by mixed continuous discrete variables and discontinuous design space. Thus, a modified Genetic Algorithm (GA) is also applied to optimize discrete member design for orthotropic steel deck. From the numerical example, the efficiency and convergency of the IMLDS algorithm proposed in this paper is investigated. It may be positively stated that the IMLDS algorithm will lead to more effective and practical design compared with previous algorithms.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.317-323
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• 2008

Mass transit information can contribute many benefits to users. Especially, transportation information technology is developing highly with information technology in Korea recently. Hereafter, it is expected to give customized transportation information to users individually with the advent of ubiquitous age in earnest. This public transportation information service can be realized by path finding algorithm in public transportation networks including travel and transfer attributes. In this research, constraints are constructed with the primary facts influencing users. Moreover, the method reducing user's path finding condition arbitrarily is proposed by making the maximum value as variables. In this study, transfer frequency, total travel time, seat confirmation, transfer time and travel time become constraint condition based on k path finding algorithm considering service time constraint condition. Moreover, case study about user customized transfer information is performed in Seoul and metropolitan subway networks.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.184-193
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• 1994

This paper considers the Updating Minimum-weight Spanning Tree Problem(UMP), that is, the problem to update the Minimum-weight Spanning Tree(MST) in response to topology change of the network. This paper proposes the algorithm which reconstructs the MST after several links deleted and added. Its message complexity and its ideal-time complexity are Ο(m＋n log(t＋f)) and Ο(n＋n log(t＋f)) respectively, where n is the number of processors in the network, t(resp.f) is the number of added links (resp. the number of deleted links of the old MST), And m=t＋n if f=Ο, m=e (i.e. the number of links in the network after the topology change) otherwise. Moreover the last part of this paper touches in the algorithm which deals with deletion and addition of processors as well as links.