• Spatial Information Research
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• v.19 no.2
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• pp.71-76
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• 2011

In this paper, for using emerging patterns to define and analyze the significant difference of safe and non-safe power load lines, and identify which line is potentially non-safe, we proposed an incremental TFP-tree algorithm for mining emerging patterns that can search efficiently within limitation of memory. Especially, the concept of pre-infrequent patterns pruning and use of two different minimum supports, made the algorithm possible to mine most emerging patterns and handle the problem of mining from incrementally increased, large size of data sets such as power consumption data.

• Journal of Technology Innovation
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• v.14 no.2
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• pp.143-165
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• 2006

By analyzing five in-depth case studies of suppliers in newly emerging Vietnam's motorcycle industry, this paper explores the differences in patterns and processes of capability improvement of suppliers who participate in different kinds of supplier-assembler network with different structures. The paper finds the correlation between the kinds of suppliers' capabilities improved and the structure of networks they participate in. While suppliers in arm-length networks can improve more upstream capabilities (structure design, process desist), suppliers in embedded networks can improve more downstream capabilities (process design, process setup, process maintenance and delivery control). Two capability improvement patterns of firms in newly emerging economy are indicated. The first pattern is asymmetrical improvement, either upstream or downstream capabilities, by participating in either arm-length or embedded networks. This pattern obstructs the suppliers to meet the requirements of new buyers rho come from different kinds of network. The second pattern is symmetrical improvement by joining both arm-length and embedded networks.

• ETRI Journal
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• v.43 no.2
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• pp.246-259
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• 2021

Traditional wisdom on how late industrialized countries follow the technology trajectories of preceding economies is in need of reformation as these countries have attained industrial leadership in a growing number of fields. However, current understandings about these countries' development of their emerging technologies have yet to investigate the divergence of idiosyncratic technology trajectories. The aim of this paper was to explore how their knowledge production strategies in emerging technology sectors are diverging. Specifically, this research examines the changing patterns of knowledge production in quantum technology in South Korea and China by developing a knowledge portfolio and knowledge strategic diagram. According to the knowledge portfolio, the relative literature position differs. In the knowledge strategic diagram, there are diverging patterns in the emerging keywords sector. This paper contributes to the literature by demonstrating the diverging strategies of late industrialized countries in their transition from catch-up to post-catch-up paradigms and provides policy implications for countries developing an idiosyncratic trajectory in emerging technology sectors.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.59-72
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• 2012

Since a protein displays its specific functions when disorder region of protein sequence transits to order region with provoking a biological reaction, the separation of disorder region and order region from the sequence data is urgently necessary for predicting three dimensional structure and characteristics of the protein. To classify the disorder and order region efficiently, this paper proposes a classification/prediction method using sequence data while acquiring a non-biased result on a specific characteristics of protein and improving the classification speed. The emerging patterns based EPs-TFP methods utilizes only the essential emerging pattern in which the redundant emerging patterns are removed. This classification method finds the sequence patterns of disorder region, such sequence patterns are frequently shown in disorder region but relatively not frequently in the order region. We expand P-tree and T-tree conceptualized TFP method into a classification/prediction method in order to improve the performance of the proposed algorithm. We used Disprot 4.9 and CASP 7 data to evaluate EPs-TFP technique, the results of order/disorder classification show sensitivity 73.6, specificity 69.51 and accuracy 74.2.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.325-327
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• 2008

In electrical industry, classification methodology has been an important issue for analyzing power consumption patterns. It has many applications including decisions on energy purchasing, load switching as well as helping in infrastructure development. Our aim in this work is to classify the electrical section and find potentially non-safe electrical sections. For this purpose, we use Emerging Patterns based classification. The classification method uses the aggregate score of emerging patterns to build classifier. The proposed methodology was applied to a set of electrical section data of the Korea power. The test data and relational electricity information and knowledge are supported by Korea Electric Power Research Institute (KEPRI).

• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.11-26
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• 2009

In order to diagnose cardiovascular disease, we proposed EP-based(emerging pattern- based) classification technique using multi-parametric diagnosis indexes. We analyzed linear/nonlinear features of HRV for three recumbent postures and extracted four diagnosis indexes from ST-segments to apply the multi-parametric diagnosis indexes. In this paper, classification model using essential emerging patterns for diagnosing disease was applied. This classification technique discovers disease patterns of patient group and these emerging patterns are frequent in patients with cardiovascular disease but are not frequent in the normal group. To evaluate proposed classification algorithm, 120 patients with AP (angina pectrois), 13 patients with ACS(acute coronary syndrome) and 128 normal people data were used. As a result of classification, when multi-parametric indexes were used, the percent accuracy in classifying three groups was turned out to be about 88.3%.

• ETRI Journal
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• v.40 no.1
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• pp.111-121
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• 2018

To find the emerging patterns (EPs) in streaming transaction data, the streaming is first divided into some time windows containing a number of transactions. Itemsets are generated from transactions in each window, and then the emergence of itemsets is evaluated between two windows. In the tilted-time windows model (TTWM), it is assumed that people need support data with finer accuracy from the most recent windows, while accepting coarser accuracy from older windows. Therefore, a limited array's elements are used to maintain all support data in a way that condenses old windows by merging them inside one element. The capacity of elements that accommodates the windows inside is modeled using a particular number sequence. However, in a stream, as new data arrives, the current array updating mechanisms lead to many null elements in the array and cause data incompleteness and inaccuracy problems. Two models derived from TTWM, logarithmic TTWM and Fibonacci windows model, also inherit the same problems. This article proposes a novel push-front Fibonacci windows model as a solution, and experiments are conducted to demonstrate its superiority in finding more EPs compared to other models.

• Journal of Korean Society of Rural Planning
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• v.26 no.4
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• pp.53-65
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• 2020

This study aimed to provide a basic information for managing the water quality of national and regional 1st rivers in Gyeongnam by analyzing the emerging hot spot patterns in BOD, T-P, and TOC, and by grouping the changing trends into clusters. The emerging hot spot analysis for each water quality item was implemented in ArcGIS Desktop with monthly water quality data from 96 water environmental monitoring stations in Gyeongnam, and then four patterns of water quality change were classified by the K-mean cluster analysis. As for BOD, persistent cold spot pattern covered about 42.9% of target rivers, and T-P concentration tended to be low or be getting lower at over 70% of target rivers. While, for TOC, about 70% of target rivers resulted in oscillating hot spots. In addition, the cluster analysis showed that the downstream of Nakdong river had the top priority in terms of water quality management because of the increasing concentration for all the three water quality.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.251-258
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• 2023

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

• Journal of Fashion Business
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• v.15 no.2
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• pp.160-173
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• 2011

Stripe has been one of the all-time favorite fabric patterns so far and the usages have been widely applied of nearly everything ranging from everyday dress to interior fabrics. As the times change, patterns of this simple geometrical design have gradually become varied. Many effects of stripe patterns have allowed the patterns to be used in fabrics for fashion design and the patterns are considered fit for expressing individual characteristics. By studying theoretical background on categories of stripe patterns and the characteristics as a design and by researching the trends and properties exhibited in the modern fabric design, this paper will seek the potential of stripe patterns for design of a modern sense and the directions to express the patterns as a value-added design. This research was conducted through literature, books published at home and abroad, research papers and photographs on stripe patterns. Domestic magazines, web research, and photographs published since 2000 were studied for an analysis of the trends and characteristics of stripe patterns displayed in the modern fabric design. As the results, this research will explain the tendencies of stripe patterns on the modern fabric designs divided into several ways: simple and restrained modernity, active and sporty property, mannishness putting practicality forward-emerging as the status of women rises, and femininity emphasizing elegant women. The characteristics of the Plastic are categorized simplicity, rhythmicality, and Mixing of patterns.