• 전자공학회논문지CI
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• 제43권5호
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• pp.17-28
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• 2006

본 논문에서는 데이터베이스에 새로운 트랜잭션이 추가되었을 때 순차 패턴을 갱신하는 문제를 연구하였다. 트랜잭션이 순차적으로 증가되는 환경에서 기존에 발견된 빈발 시퀸스를 재사용하여 순차패턴을 갱신하는 효율적인 알고리즘을 제안한다. 본 논문에서 제안한 방법은 후보 집합의 개수를 효율적으로 줄임으로써 AprioriAll이나 PrefixSpan 알고리즘보다 좋은 성능을 보임을 실험으로 확인하였다.

• 한국컴퓨터정보학회논문지
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• 제18권11호
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• pp.125-136
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• 2013

본 논문에서는 SSL VPN을 기반으로 사용자 인증과 사용자 단말의 무결성을 검증할 수 있는 네트워크 접근제어 기술을 제안한다. 사용자 단말이 VPN을 이용해 내부 네트워크에 접속할 때 사용자 인증과 사용자 단말의 보안패치, 바이러스 백신 등의 보안 서비스를 확인하는 안전성 검사를 수행한다. 그리고 변종의 악성코드를 탐지하기 위해 사용자 단말의 윈도우 API 정보를 통한 행위패턴을 바탕으로 악성코드를 탐지하고, 탐지의 신뢰도를 높이기 위해 순서패턴의 유사도를 비교하여 변종의 악성코드를 탐지하여 외부의 보안 위협으로부터 시스템을 보호한다.

• 대한전자공학회논문지
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• 제24권5호
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• pp.896-904
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• 1987

In this paper, a design method for sequential circuit which is easy to have Built-in Self Test is kproposed using the functional advantages of multifunctional BILBO and LSSD. To achieve the hardware reduction, it is designed that a multifunctional BILBO has double operational functions of NLFSR and LFSR, when neccessary, and that test signal could be used as an input-output signal in the same line. By applying the proposed multifunctional BILBO to the sequential PLA, the test patterns and the additional circuit could be reduced in test operation and the propagation delay is vanished in normal operation, as we expected. Above them, the partitioned method for large scale sequential circuit is also suggested and it is observed that test patterns and additional circuit in them reduced by this method.

• 복식문화연구
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• 제31권5호
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• pp.607-626
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• 2023

This study analyzes consumer fashion purchase patterns from a big data perspective. Transaction data from 1 million transactions at two Korean fashion brands were collected. To analyze the data, R, Python, the SPADE algorithm, and network analysis were used. Various consumer purchase patterns, including overall purchase patterns, seasonal purchase patterns, and age-specific purchase patterns, were analyzed. Overall pattern analysis found that a continuous purchase pattern was formed around the brands' popular items such as t-shirts and blouses. Network analysis also showed that t-shirts and blouses were highly centralized items. This suggests that there are items that make consumers loyal to a brand rather than the cachet of the brand name itself. These results help us better understand the process of brand equity construction. Additionally, buying patterns varied by season, and more items were purchased in a single shopping trip during the spring season compared to other seasons. Consumer age also affected purchase patterns; findings showed an increase in purchasing the same item repeatedly as age increased. This likely reflects the difference in purchasing power according to age, and it suggests that the decision-making process for pur- chasing products simplifies as age increases. These findings offer insight for fashion companies' establishment of item-specific marketing strategies.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권2호
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• pp.137-144
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• 2013

순차 패턴 탐사 기법은 순서를 갖는 패턴들의 집합 중에 빈발하게 발생하는 패턴을 탐사하는 기법이다. 순차 패턴 탐사 분야 중에 동적 가중치 순차 패턴 탐사는 가중치가 시간에 따라 변화하는 컴퓨팅 환경에 적용 가능한 탐사 기법으로 동적인 가중치 변화를 탐색 과정에 적용하여 다양한 환경에서 활용 가능하다. 이 논문에서는 다양한 순차 데이터가 들어오는 스트림 환경에서 동적 가중치를 적용하여 빈발한 이벤트들을 탐사하는 새로운 순차 패턴 탐사 기법을 제안한다. 제안하는 기법은 시간 순서에 의한 상대적인 동적 가중치를 사용하여 탐색해야 하는 후보 패턴을 줄여주고 해시 구조를 통한 데이터 입출력으로 빈발한 순차 패턴을 빠르게 탐사할 수 있다. 이 기법을 사용하면 기존 가중치를 적용하는 방식보다 메모리 사용과 처리 시간을 줄여줘 매우 효율적이다. 제안하는 기법은 다른 가중치 순차 패턴 탐사 기법과의 비교를 통해 동적 가중치 탐사 기법의 중요성을 보인다.

• 대한간호학회지
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• 제37권1호
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• pp.145-155
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• 2007

Purpose: The purpose of this study was to describe and to analyze real communication about a patient's discomfort between a patient with cancer and a nurse. Method: A dialogue analysis method was utilized. Fifteen patients and 4 nurses who participated in this research gave permission to be videotaped. The data was collected from January, 3 to February 28, 2006. Results: The communication process consisted of 4 functional stages: 'introduction stage', 'assessment stage', 'intervention stage' and 'final stage'. After trying to analyze pattern reconstruction in the 'assessment stage' and 'intervention stage', sequential patterns were identified. In the assessment stage, if the nurse lead the communication, the sequential pattern was 'assessment question-answer' and if the patient lead the communication, it was 'complaint-response'. In the intervention stage, the sequential pattern was 'nursing intervention-acceptance'. Conclusion: This research suggests conversation patterns between patients with cancer and nurses. Therefore, this study will provide insight for nurses in cancer units by better understanding communication behaviors.

• 산업경영시스템학회지
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• 제21권45호
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• pp.101-112
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• 1998

Data mining, which is also referred to as knowledge discovery in database, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information (such as knowledge rules, constraints, regularities) from data in databases. The discovered knowledge can be applied to information management, decision making, and many other applications. In this paper, a new data mining problem, discovering sequential patterns, is proposed which is to find all sequential patterns using sampling method. Recognizing that the quantity of database is growing exponentially and transaction database is frequently updated, sampling method is a fast algorithm reducing time and cost while extracting the trend of customer behavior. This method analyzes the fraction of database but can in general lead to results of a very high degree of accuracy. The relaxation factor, as well as the sample size, can be properly adjusted so as to improve the result accuracy while minimizing the corresponding execution time. The superiority of the proposed algorithm will be shown through analyzing accuracy and efficiency by comparing with Apriori All algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권1호
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• pp.169-189
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• 2015

Detection of anomalous events from video streams is a challenging problem in many video surveillance applications. One such application that has received significant attention from the computer vision community is traffic video surveillance. In this paper, a Lossy Count based Sequential Temporal Pattern mining approach (LC-STP) is proposed for detecting spatio-temporal abnormal events (such as a traffic violation at junction) from sequences of video streams. The proposed approach relies mainly on spatial abstractions of each object, mining frequent temporal patterns in a sequence of video frames to form a regular temporal pattern. In order to detect each object in every frame, the input video is first pre-processed by applying Gaussian Mixture Models. After the detection of foreground objects, the tracking is carried out using block motion estimation by the three-step search method. The primitive events of the object are represented by assigning spatial and temporal symbols corresponding to their location and time information. These primitive events are analyzed to form a temporal pattern in a sequence of video frames, representing temporal relation between various object's primitive events. This is repeated for each window of sequences, and the support for temporal sequence is obtained based on LC-STP to discover regular patterns of normal events. Events deviating from these patterns are identified as anomalies. Unlike the traditional frequent item set mining methods, the proposed method generates maximal frequent patterns without candidate generation. Furthermore, experimental results show that the proposed method performs well and can detect video anomalies in real traffic video data.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제2권8호
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• pp.565-570
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• 2013

기존의 순차 패턴 마이닝 기법은 주로 시점 기반 이벤트를 중심으로 연구되었다. 그러나 실생활에는 시작 시점과 종료 시점과 같은 시간 간격을 갖는 인터벌 이벤트가 많이 발생한다. Allen 연산자를 기반으로 두 인터벌 이벤트 사이의 인터벌 패턴을 탐사하는 기존의 기법은 세 개 이상의 인터벌 이벤트 사이에서 인터벌 패턴이 여러 의미로 해석될 수 있는 문제점을 가지고 있다. 이 논문은 인터벌 패턴 탐사에서 모호성 제거를 위한 효율적인 순차 탐색 마이닝 기법인 I_TPrefixSpan 알고리즘을 제안한다. 제안하는 기법은 인터벌 이벤트에 대한 이벤트 시퀀스를 생성함으로써 모호성을 제거하고 이벤트 시퀀스에 존재하는 항목만을 대상으로 순차 탐색함으로써 후보 집합 생성을 최소화 할 수 있다. 성능 평가를 통하여 제안하는 방법이 기존의 방법에 비하여 보다 효율적임을 보인다.

• 대한전자공학회논문지
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• 제13권3호
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• pp.1-6
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• 1976

이 논문에서는 Boolean difference를 이용하여 combinational 및 sequential 논리회로에서 발생하는 기능적인 고장에 대한 test pattern을 얻는 방법을 연구하였다. 이 방법은 test pattern을 얻고자 하는 회로의 Boolean 함수의 Boolean difference를 계산하므로써 체계적으로 test pattern을 얻는 절차를 보여주고 있다. 컴퓨터에 의한 실험결과에 의하며 이 방법은 combinational 회로 및 asynchronous sequential 회로에 적합하며, clock이 있는 flip flop을 적당히 모형화함으로서 이 방법을 synchronous sequential회로에도 적용할 수 있음이 입증되었다. In this paper, a method of test pattern generation for the functional failure in both combinational and sequentlal logic networks by using exterded Boole an difference is proposed. The proposed technique provides a systematic approach for the test pattern generation procedure by computing Boolean difference of the Boolean function that represents the Logic network for which the test patterns are to be generated. The computer experimental results show that the proposed method is suitable for both combinational and asynchronous sequential logic networks. Suitable models of clocked flip flops may make it possible for one to extend this method to synchronous sequential logic networks.