• Journal of Digital Contents Society
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• v.15 no.6
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• pp.711-719
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• 2014

Along with the advent of ubiquitous computing environment, it is becoming a part of our common life style that the demands for enjoying the wireless internet using intelligent portable device such as smart phone and iPad, are increasing anytime or anyplace without any restriction of time and place. The recommending service becomes a very important technology which can find exact information to present users, then is easy for customers to reduce their searching effort to find out the items with high purchasability in e-commerce. Traditional mining association rule ignores the difference among the transactions. In order to do that, it is considered the importance of type of merchandise or service and then, we suggest a new recommending service using mining sequential pattern based on weight to reflect frequently changing trends of purchase pattern as time goes by and as often as customers need different merchandises on e-commerce being extremely diverse. To verify improved better performance of proposing system than the previous systems, we carry out the experiments in the same dataset collected in a cosmetic internet shopping mall.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.06a
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• pp.502-502
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• 2007

Current thin film process using memory device fabrication process use expensive processes such as manufacturing of photo mask, coating of photo resist, exposure, development, and etching. However, direct printing technology has the merits about simple and cost effective processes because inks are directly injective without mask. And also, this technology has the advantage about fabrication of fine pattern line on various substrates such as PCB, FCPB, glass, polymer and so on. In this work, we have fabricated the fine and thick metal pattern line for the electronic circuit board using metal ink contains Ag nano-particles. Metal lines are fabricated by two types of printing methods. One is a conventional printing method which is able to quick fabrication of fine pattern line, but has various difficulties about thick and high resolution DPI(Dot per Inch) pattern lines because of bulge and piling up phenomenon. Another(Second) methods is sequential printing method which has a various merits of fabrication for fine, thick and high resolution pattern lines without bulge. In this work, conductivities of metal pattern line are investigated with respect to printing methods and pattern thickness. As a result, conductivity of thick pattern is about several un.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.63-72
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• 2019

The purpose of this study is to apply the types of urban street pattern and the shape of streets to the master plan of a religious community complexes. The street pattern is a framework of urban structure and to understand the urban structure is helpful to understand the nature of urban streets. By analysing the precedent researches, the types of street patterns are classified as a serial pattern, a branching pattern, a grid pattern and a web pattern. The street patterns are hierarchically composed and classified as a differential development and sequential development. There are boundaries and gates where the street space is differentiated to the more private level. The urban streets continue to the architectural streets such as arcades, deck streets, corridors, lobbies and halls. The purposes and results of the master plan of this religious community complexes are as follows. 1) The school area, housing area and service area are properly separated and connected. They are separated by the building masses and connected by the street space in between. 2) The street pattern of this complexes is a serial pattern where the streets are the center of each functional building groups. The entry square is divided by the symbolic building. The one branch is school street and the other is living street. These streets are combined again to the festival street. 3) The architectural streets are organically related to the urban streets. 4) Each street spaces are of adequate form according to its properties as a place. 5) There are boundaries or gates such as a gab between buildings, posts, arches and deck streets according to the relationship between streets.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.19-29
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• 2011

Due to the development of web technologies and the increasing use of smart devices such as smart phone, in recent various web services are widely used in many application fields. In this environment, the topic of supporting personalized and intelligent web services have been actively researched, and an analysis technique on a web-click stream generated from web usage logs is one of the essential techniques related to the topic. In this paper, for efficient analyzing a web-click stream of sequences, a sequential pattern mining technique is proposed, which satisfies the basic requirements for data stream processing and finds a refined mining result. For this purpose, a concept of interesting sequential patterns with a time-interval constraint is defined, which uses not on1y the order of items in a sequential pattern but also their generation times. In addition, A mining method to find the interesting sequential patterns efficiently over a data stream such as a web-click stream is proposed. The proposed method can be effectively used to various computing application fields such as E-commerce, bio-informatics, and USN environments, which generate data as a form of data streams.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1009-1014
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• 2009

The Internet has changed the daily lives of human being in Korea and elsewhere in the world. It has changed the paradigms of traditional commercial activities and created immense opportunities for new business models. Recently, there has been much attention to the internet shopping mall as a means of commercial transaction. To make internet shopping mall competitive, effective customer satisfaction service should be provided and it is necessary to dynamic analysis method for customers' purchasing pattern. In this paper we apply the sequential analysis to comparison of two kinds of sales through the analysis of customers' purchasing pattern.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.365-370
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• 2014

The existing system consumes a considerable amount time and cost for extracting the patterns from whole sequences or misaligned sequences. In this paper, We propose the classification system, which creates the partition sequence sections using multiple sequence alignment method and extracts the sequential patterns from these section. These extracted patterns are accumulated motif candidate sets and then used the training sets of SVM classifier. This proposed system predicts a HPV-type(high/low) using the learned knowledges from known/unknown protein sequences and shows more improved precision, recall than previous system in 30% minimum support.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.698-701
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• 2002

Subspace analysis (which includes PCA) seeks for feature subspace (which corresponds to the eigenspace), given multivariate input data and has been widely used in computer vision and pattern recognition. Typically data space belongs to very high dimension, but only a few principal components need to be extracted. In this paper I present a fast sequential algorithm for subspace analysis or tracking. Useful behavior of the algorithm is confirmed by numerical experiments.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.155-166
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• 2002

Neural networks have been studied as a popular tool for classification and they are very flexible. Also, they are used for many applications of pattern classification and pattern recognition. This paper focuses on Bayesian approach to feed-forward neural networks with single hidden layer of units with logistic activation. In this model, we are interested in deciding the number of nodes of neural network model with p input units, one hidden layer with m hidden nodes and one output unit in Bayesian setup for fixed m. Here, we use the latent variable into the prior of the coefficient regression, and we introduce the 'sequential step' which is based on the idea of the data augmentation by Tanner and Wong(1787). The MCMC method(Gibbs sampler and Metropolish algorithm) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.9
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• pp.38-48
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• 1998

Generating test patterns for asynchronous sequential circuits remains to be a very difficult problem. There are few algorithms for this problem, and previous works cut feedback loops, and insert synchronous flip-flops in the feedback loops during ATPG. The conventional algorithms are similar to the algorithms for synchronous sequential circuits. This means that the conventional algorithms generate test patterns by modeling asynchronous sequential circuits as synchronous sequential circuits. So, test patterns generated by those algorithms nay not detect target faults when the test patterns are applied to the asynchronous sequential circuit under test. In this paper an algorithm is presented to generate test patterns for asynchronous sequential circuits. Test patterns generated by the algorithm can detect target faults for asynchronous sequential circuits with the minimal possibility of critical race problem and oscillation. And it is guaranteed that the test patterns generated by the algorithm will detect target faults.