• 정보과학회 컴퓨팅의 실제 논문지
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• 제24권3호
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• pp.105-112
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• 2018

데이터의 양이 증가하면서 단일 노드 데이터베이스로는 저장과 처리를 동시에 수행하기에는 부족하다. 따라서, 데이터를 분산시켜 복수 노드로 구성된 분산 데이터베이스에 저장되고 있으며 분석 역시 효율성을 위해 병렬 기능을 제공해야한다. 전통적인 분석 방식은 데이터베이스에서 분석 노드로 데이터를 이동시킨 후 분석을 수행하기 때문에 네트워크의 비용이 발생하며 사용자가 분석을 위해 분석 프레임 워크도 다를 수 있어야한다. 본 연구는 군집화 분석 기법인 K-Means 군집화 알고리즘을 관계형 데이터 베이스와 칼럼 기반 데이터베이스를 이용한 분산 데이터베이스 환경에서 SQL로 구현하는 In-database 분석 함수로의 설계와 구현 그리고 관계형 데이터베이스에서의 성능 최적화 방법을 제안한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2004년도 봄 학술발표논문집 Vol.31 No.1 (B)
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• pp.115-117
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• 2004

Recently, mining far association rules in distributed database environments is a central problem in knowledge discovery area. While the data are located in different share-nothing machines, and each data site grows by time. Mining global frequent itemsets is hard and not efficient in large number of distributed sewen. In many distributed databases. time component(which is usually attached to transactions in database), contains meaningful time-related rules. In this paper, we design a new DTA(distributed temporal association) algorithm that combines temporal concepts inside distributed association rules. The algorithm confirms the time interval for applying association rules in distributed databases. The experiment results show that DTA can generate interesting correlation frequent itemsets related with time periods.

• 제어로봇시스템학회논문지
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• 제14권10호
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• pp.1038-1046
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• 2008

This paper presents a framework to generate human-like movements of a humanoid in real time using the movement primitive database of a human. The framework consists of two processes: 1) the offline motion imitation learning based on an Evolutionary Algorithm and 2) the online motion generation of a humanoid using the database updated bγ the motion imitation teaming. For the offline process, the initial database contains the kinetic characteristics of a human, since it is full of human's captured motions. The database then develops through the proposed framework of motion teaming based on an Evolutionary Algorithm, having the kinetic characteristics of a humanoid in aspect of minimal torque or joint jerk. The humanoid generates human-like movements far a given purpose in real time by linearly interpolating the primitive motions in the developed database. The movement of catching a ball was examined in simulation.

• 전자공학회논문지A
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• 제32A권12호
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• pp.184-197
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• 1995

In this paper, high speed IC package-to-package interconnections are modeled as lossless multiconductor transmission lines operating in the TEM mode. And, three mathematical algorithms for computing electrical parameters of the lossless multiconductor transmission lines are described. A semi-analytic Green's function method is used in computing per unit length capacitance and inductance matrices, a matrix square root algorithm based on the QR algorithm is used in computing a characteristic impedance matrix, and a matrix algorithm based on the theory of M-matrix is used in computing a diagonally matched load impedance matrix. These algorithms are implemented in a computer program DIME (DIagonally Matched Load Impedance Extractor) which computes electrical parameters of the lossless multiconductor transmission lines. Also, to illustrate the concept of design database for high speed IC package-to-package interconnection, a database for the multi conductor strip transmission lines system is constructed. This database is constructed with a sufficiently small number of nodes using the multi-dimensional cubic spline interpolation algorithm. The maximum interpolation error for diagonally matched load impedance matrix extraction from the database is 1.3 %.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권11호
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• pp.780-785
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• 2004

In this paper, we proposed a ventricular fibrillation detection algorithm based on wavelet transform and artificial neural network. we selected RR intervals, the 6th and 7th wavelet coefficients(D6, D7) as features for classifying ventricular fibrillation. To evaluate the performance of the proposed algorithm, we compared the result of the proposed algorithm with that of fuzzy inference and fuzzy-neural network. MIT-BIH Arrhythmia database, Creighton University Ventricular Tachyarrhythmia database and MIH-BIH Malignant Ventricular Arrhythmia database were used as test and learning data. Among the algorithms, the proposed algorithm showed that the classification rate of normal and abnormal beat was sensitivity(%) of 96.10 and predictive positive value(%) of 99.07, and that of ventricular fibrillation was sensitivity(%) of 99.45. Finally. the proposed algorithm showed good performance compared to two other methods.

• 한국정보처리학회논문지
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• 제6권11호
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• pp.2863-2874
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• 1999

Apartment auction is a system that is used for the citizens to get a house. This paper deals with the implementation of a web-based intelligent decision support system using OLAP technique and data mining technique for auction decision support. The implemented decision support system is working on a real auction database and is mainly composed of OLAP Knowledge Extractor based on data warehouse and Auction Data Miner based on data mining methodology. OLAP Knowledge Extractor extracts required knowledge and visualizes it from auction database. The OLAP technique uses fact, dimension, and hierarchies to provide the result of data analysis by menas of roll-up, drill-down, slicing, dicing, and pivoting. Auction Data Miner predicts a successful bid price by means of applying classification to auction database. The Miner is based on the lazy model-based classification algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm and applies the concepts such as decision fields, dynamic domain information, and field weighted function to this algorithm to reflect the characteristics of auction database.

• 반도체디스플레이기술학회지
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• 제18권4호
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• pp.57-61
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• 2019

Nowadays, portable digital cameras such as smart phone cameras are being popularly used for entertainment and visual information recording. Given a database of geo-tagged images, a visual location recognition system can determine the place depicted in a query photo. One of the most common visual location recognition approaches is the bag-of-words method where local image features are clustered into visual words. In this paper, we propose a new bag-of-words-based visual location recognition algorithm using time-series streetview database. The proposed algorithm selects only a small subset of image features which will be used in image retrieval process. By reducing the number of features to be used, the proposed algorithm can reduce the memory requirement of the image database and accelerate the retrieval process.

• 한국정보과학회논문지:데이타베이스
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• 제31권4호
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• pp.409-421
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• 2004

데이타베이스 공유 시스템(DSS)은 고성능 트랜잭션 처리를 위하여 여러 개의 처리 노드를 연결한 구조로서, 각 노드는 데이타베이스를 저장한 디스크를 공유한다. DSS를 구성하는 노드들이 고장날 경우 데이타베이스를 정확한 상태로 복구하기 위한 회복 과정이 필요한데 DSS에서 회복 작업은 하나의 노드로 구성된 일반적인 데이타베이스 시스템보다 많은 시간이 소요된다. 그 이유는 데이타베이스를 회복하기 위해 여러 노드에 나누어 저장된 로그들을 병합하여야 하며, 병합된 로그들을 이용하여 REDO 작업을 수행하여야 하기 때문이다. 본 논문에서는 Oracle 9i Real Application Cluster (ORAC)에서 제안된 캐쉬 연합 알고리즘의 성능을 개선한 2VC(Two Version Caching) 알고리즘을 제안한다. 2VC는 단일 노드 고장에 대한 회복 작업에서 로그 병합 과정을 생략할 수 있으므로 빠른 데이타베이스 회복을 지원할 수 있다는 장점을 갖는다. 뿐만 아니라, ORAC에서 발생하는 불필요한 디스크 기록 오버헤드를 줄임으로써 정상적인 트랜잭션 처리의 성능을 향상시킬 수 있다.

• 한국공간정보시스템학회:학술대회논문집
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• 한국공간정보시스템학회 2005년도 추계학술대회
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제10권1호
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• pp.107-119
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• 2006

인터넷과 웹 기술 발전에 따라 데이터베이스에 축적되는 자료의 양이 급속히 늘어나고 있다. 데이터베이스의 응용 범위가 확대되고 대용량 데이터베이스로부터 유용한 지식을 발견하고자 하는 데이터 마이닝(Data Mining) 기술에 대한 연구가 활발하게 진행되고 있다. 기존의 알고리즘들은 대부분 후보 항목 집합들을 줄임과 동시에 데이터베이스의 크기를 줄이는 방법으로 발전해 오고 있다. 그러나 후보 항목집합들을 줄이는 노력이나 데이터베이스의 크기를 줄이는 방법들이 빈발 항목집합들을 생성하는 전 과정에서 필요로 하지는 않는다. 그러한 방법들이 어느 과정에서는 시간을 줄이는데 효과가 있지만 다른 과정에서는 오히려 그러한 방법들을 적용하는데 더 많은 시간이 소요되기 때문이다. 본 논문에서는 트랜잭션들의 길이가 짧거나 데이터베이스를 이루는 항목들의 수가 비교적 적은 트랜잭션 데이터베이스에서 해슁 기법을 사용하여 데이터베이스를 한 번 스캔하고 동시에 각 트랜잭션에서 발생 가능한 모든 부분집합들을 해쉬 테이블에 저장함으로써 최소 지지도에 영향을 받지 않고 기존의 알고리즘보다 더 짧은 시간에 빈발항목집합을 발견할 수 있는 효과적인 연관 규칙 탐사 알고리즘을 제안하고 실험하였다.