• 한국정보디스플레이학회:학술대회논문집
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• 2009.10a
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• pp.1386-1388
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• 2009

We report on a new method of fabricating color filters based on selective wetting of color inks. The reversible formation of a hydrophobic layer provides sequential generation and protection of successive color filter patterns through a simple coating process. The transmittance and geometrical properties of the fabricated color filter were described.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1985.10a
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• pp.109-112
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• 1985

This paper proposes a algorithm of phonemes extraction in korean character pattern recognition. The phonemes are classified into the patterns which are separable and connected with each other. The former is extracted by means of pattern matching in consideration of topological structure of ponemes and direction of stroke sequentially. The latter is extracted by means of index and window algorithm which are performed by a 3$\times$3 sequential local operation in the thinned character pattern.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.70-72
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• 2003

대용량 데이터베이스로부터 순차 패턴을 발견하는 문제는 지식 발견 또는 데이터 마이닝(Data Mining) 분야에서 주요한 패턴 추출 문제이다. 순차 패턴은 추출 기법에 있어 연관 규칙의 Apriori 알고리즘과 비슷한 방식을 사용하며 그 과정에서 시퀀스는 해쉬 트리 구조를 통해 다루어 진다. 이러한 해쉬 트리 구조는 항목들의 정렬과 데이터 시퀀스의 지역성을 무시한 저장 구조로 단순 검색을 통한 다수의 복잡한 포인터 연산수행을 기반으로 한다. 본 논문에서는 이러한 해쉬 트리 구조의 단정을 보완한 다단게 선형 배치 트리(MLLT, Multi-level Linear Location Tree)를 제안하고, 다단계 선형 배치 트리를 이용한 효율적인 마이닝 메소드(MLLT-Join)를 소개한다.

• The Korean Journal of Physiology and Pharmacology
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• v.15 no.6
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• pp.371-382
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• 2011

We performed experiments using Aplysia neurons to identify the mechanism underlying the changes in the firing patterns in response to temperature changes. When the temperature was gradually increased from $11^{\circ}C$ to $31^{\circ}C$ the firing patterns changed sequentially from the silent state to beating, doublets, beating-chaos, bursting-chaos, square-wave bursting, and bursting-oscillation patterns. When the temperature was decreased over the same temperature range, these sequential changes in the firing patterns reappeared in reverse order. To simulate this entire range of spiking patterns we modified nonlinear differential equations that Chay and Lee made using temperature-dependent scaling factors. To refine the equations, we also analyzed the spike pattern changes in the presence of potassium channel blockers. Based on the solutions of these equations and potassium channel blocker experiments, we found that, as temperature increases, the maximum value of the potassium channel relaxation time constant, ${\tau}_n(t)$ increases, but the maximum value of the probabilities of openings for activation of the potassium channels, n(t) decreases. Accordingly, the voltage-dependent potassium current is likely to play a leading role in the temperature-dependent changes in the firing patterns in Aplysia neurons.

• The Research Journal of the Costume Culture
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• v.32 no.2
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• pp.199-214
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• 2024

Until now, research on consumers' purchasing behavior has primarily focused on psychological aspects or depended on consumer surveys. However, there may be a gap between consumers' self-reported perceptions and their observable actions. In response, this study aimed to investigate consumer purchasing behavior utilizing a big data approach. To this end, this study investigated the purchasing patterns of fashion items, both online and in retail stores, from a data-driven perspective. We also investigated whether individual consumers switched between online websites and retail establishments for making purchases. Data on 516,474 purchases were obtained from fashion companies. We used association rule analysis and K-means clustering to identify purchase patterns that were influenced by customer loyalty. Furthermore, sequential pattern analysis was applied to investigate the usage patterns of online and offline channels by consumers. The results showed that high-loyalty consumers mainly purchased infrequently bought items in the brand line, as well as high-priced items, and that these purchase patterns were similar both online and in stores. In contrast, the low-loyalty group showed different purchasing behaviors for online versus in-store purchases. In physical environments, the low-loyalty consumers tended to purchase less popular or more expensive items from the brand line, whereas in online environments, their purchases centered around items with relatively high sales volumes. Finally, we found that both high and low loyalty groups exclusively used a single preferred channel, either online or in-store. The findings help companies better understand consumer purchase patterns and build future marketing strategies around items with high brand centrality.

• Journal of KIBIM
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• v.6 no.1
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• pp.1-8
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• 2016

This paper provides a method for generating flight path of Unmanned Aerial Vehicle (UAV) that is intended to be used in visual inspection of dome-type nuclear containment building. The method basically employs 3-D model to extract accurate location coordinates. Two basic route patterns that provide guide lines in defining moving locations were defined for each side wall and dome section of the containment. The route patterns support sequential capturing of images as well. In addition, several simple equations and an algorithm for calculation of the moving location on the route were developed on the basis of 3-D geometric characteristics of the containment building. A prototype computer program has been implemented to validate the proposed method, and a case study shows the method can visualize covering area in 3-D model as well.

• Journal of Computing Science and Engineering
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• v.7 no.4
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• pp.272-284
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• 2013

In this paper, we propose a new framework for anomaly detection in medical wireless sensor networks, which are used for remote monitoring of patient vital signs. The proposed framework performs sequential data analysis on a mini gateway used as a base station to detect abnormal changes and to cope with unreliable measurements in collected data without prior knowledge of anomalous events or normal data patterns. The proposed approach is based on the Mahalanobis distance for spatial analysis, and a kernel density estimator for the identification of abnormal temporal patterns. Our main objective is to distinguish between faulty measurements and clinical emergencies in order to reduce false alarms triggered by faulty measurements or ill-behaved sensors. Our experimental results on both real and synthetic medical datasets show that the proposed approach can achieve good detection accuracy with a low false alarm rate (less than 5.5%).

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.272-281
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• 2009

In this paper, three-dimensional optimal evasive maneuver patterns for air-to-surface attack missiles against proportionally navigated anti-air defense missiles were investigated. An interception error of the defense missile is produced by an evasive maneuver of the attack missile. It is assumed that the defense missiles are continuously launched during the flight of attack missile. The performance index to be minimized is then defined as the negative square integral of the interception errors. The direct parameter optimization technique based on SQP and a co-evolution method based on the augmented Lagrangian formulation are adopted to get the attack missile's optimal evasive maneuver patterns. The overall shape of the resultant optimal evasive maneuver is represented as a deformed barrel-roll.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.884-888
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• 2003

In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

• Journal of Applied Biological Chemistry
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• v.42 no.2
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• pp.92-96
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• 1999

To study the regulatory mechanism of isoprenoid (carotenoid) biosynthesis, we have compared the expression patterns of nine isoprenoid biosynthetic genes in Korean red pepper (Capsicum. annuum cv. NocKaung). The expression of geranylgeranyl pyrophosphate synthase gene was initially induced at early ripening stage (I1) and was rather slightly decreased during pepper fruit ripening. The ex-pression of phytoene synthase gene was strongly induced at semi-ripening stage (I2) and the phytoene desaturase transcript was maximally induced at the fully ripened stage (R). Our results suggest that genes encoding two 3-hydroxy-3-methylglutaryl-CoA reductase isozymes (HMGR1 and HMGR2) and farnesyl pyrophosphate synthase might be not so critical in pepper carotenoid biosynthesis but three genes encoding geranylgeranyl pyrophosphate synthase, phytoene synthase and phytoene desaturase were induced in a sequential manner and coordinately regulated during the ripening of pepper fruit.