• 제목/요약/키워드: Retrieving

검색결과 546건 처리시간 0.025초

구조물 전달함수 매개변수의 구성조건 관계 (Compatibility Relationship of Transfer Function Parameters of Structures)

  • 채장범
    • 한국정밀공학회지
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    • 제13권2호
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    • pp.168-175
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    • 1996
  • The measured vibration on a machine or a structure is shaped by the excitation waveform and the path transfer function. Mechanism diagnostics tends to focus on retrieving source features by minimizing the effects of the structiral path, while in structural diagnostics we are more interested in minimizing source effects and retrieving path parameters. In structural diagnostics, therefore, there are experimental issues of gathering date that are independent source effects and finding a transfer function signature that reveals structural defects. This paper describes how the transfer function can be obtained more accurately by experiment using the compatibility relationship which is newly discovered.

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Retrieving the Time History of Displacement from Measured Acceleration Signal

  • Han, Sangbo
    • Journal of Mechanical Science and Technology
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    • 제17권2호
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    • pp.197-206
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    • 2003
  • It is intended to retrieve the time history of displacement from measured acceleration signal. In this study, the word retrieving means reconstructing the time history of original displacement signal from already measured acceleration signal not just extracting various information using relevant signal processing techniques. Unlike extracting required information from the signal, there are not many options to apply to retrieve the time history of displacement signal, once the acceleration signal is measured and recorded with given sampling rate. There are two methods, in general, to convert measured acceleration signal into displacement signal. One is directly integrating the acceleration signal in time domain. The other is dividing the Fourier transformed acceleration signal by the scale factor of - $\omega$$^2$and taking the inverse Fourier transform of it. It turned out both the methods produced a significant amount of errors depending on the sampling resolution in time and frequency domain when digitizing the acceleration signals. A simple and effective way to convert the time history of acceleration signal into the time history of displacement signal without significant errors is studied here with the analysis on the errors involved in the conversion process.

Q-방법론을 이용한 재미관련 영상 검색 시스템의 설계 (Design of Amusement-related Film Retrieving System using the Q-Methodology)

  • 나성준;최이권;신동렬
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2011년도 제43차 동계학술발표논문집 19권1호
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    • pp.245-248
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    • 2011
  • 현재의 영상 검색 시스템은 일반적으로 카테고리 검색 및 분류 검색으로 구성되어 있다. 일반적인 영상 데이터베이스 구축 및 현재의 검색 방법으로는 영상에 대한 재미요인을 분석하여 사용자에게 제공되지 않는다. 하지만 본 논문에서 제시하는 Q-방법론을 사용하여 영상을 분석하였다. Q-방법론에 의하여 분석된 영상은 영상 서버에 저장되며 영상 위치와 분석된 영상 디스크립션 및 재미요인은 데이터베이스에 구축하였다. 또한, 카테고리 검색 및 분류 검색에 대한 단점을 보강하기 위하여 키워드 검색시 색인 사전을 참조하여 온톨로지 검색에 대한 기능을 강화하였다.

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PDA상에서 음성인식을 이용한 차량번호 조회시스템 (A car number retrieving system using speech recognition for PDA)

  • 김우성;김동환;윤재선;홍광석
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
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    • pp.281-284
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    • 2001
  • 본 논문에서는 PDA상에서 음성인식과 합성을 통하여 차량 번호를 조회할 수 있는 시스템을 구현하였다. 차량번호 인식을 위한 4연속 숫자음과 명령어 인식부분, 그리고 각 단계별로 합성된 음성을 들려주도록 구성하였다. 본 연구의 인식시스템은 화자독립으로 실험을 하였으며, 여러화자에 대한 4연속 차량번호 인식률과 명령어에 대한 인식률은 각각 97%, 99%가 나왔다.

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홀로그래픽 정보 저장 장치에서 클러스터링을 이용한 에러 감소 기법 제안 및 비교 (Design and Comparison of Error Reduction Methods Using Clustering in Holographic Data Storage System)

  • 김상훈;김장현;양현석;박영필
    • 정보저장시스템학회:학술대회논문집
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    • 정보저장시스템학회 2005년도 추계학술대회 논문집
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    • pp.83-87
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    • 2005
  • Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time in. Today any data storage system can not satisfy these conditions, but holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System architecture without mechanical actuating pare is possible, so fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this paper, to correct errors of binary data stored in holographic digital data storage system, find cluster centers using clustering algorithm and reduce intensities of pixels around centers. We archive the procedure by two algorithms of C-mean and subtractive clustering, and compare the results of the two algorithms. By using proper clustering algorithm, the intensity profile of data page will be uniform and the better data storage system can be realized.

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서브클러스터링을 이용한 홀로그래픽 정보저장 시스템의 비트 에러 보정 기법 (Bit Error Reduction for Holographic Data Storage System Using Subclustering)

  • 김상훈;양현석;박영필
    • 정보저장시스템학회논문집
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    • 제6권1호
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    • pp.31-36
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    • 2010
  • Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part so fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to correct errors of binary data stored in holographic data storage system, a new method for reduction errors is suggested. First, find cluster centers using subtractive clustering algorithm then reduce intensities of pixels around cluster centers. By using this error reduction method following results are obtained ; the effect of Inter Pixel Interference noise in the holographic data storage system is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

An Architecture for Efficient RDF Data Management Using Structure Index with Relation-Based Data Partitioning Approach

  • Nguyen, Duc;Oh, Sang-yoon
    • International Journal of Internet, Broadcasting and Communication
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    • 제5권1호
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    • pp.14-17
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    • 2013
  • RDF data is widely used for exchanging data nowadays to enable semantic web era. This leads to the need for storing and retrieving these data efficiently and effectively. Recently, the structure index in graph-based perspective is considered as a promising approach to deal with issues of complex query graphs. However, even though there are many researches based on structure indexing, there can be a better architectural approach instead of addressing the issue as a part. In this research, we propose architecture for storing, query processing and retrieving RDF data in efficient manner using structure indexing. Our research utilizes research results from iStore and 2 relation-based approaches and we focus on improving query processing to reduce the time of loading data and I/O cost.

새로운 이미지 거리를 통한 이미지 검색 방안 연구 (Study of the New Distance for Image Retrieval)

  • 이성임;임요한;조영민
    • 대한산업공학회지
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    • 제40권4호
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    • pp.382-387
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    • 2014
  • Image retrieval is a procedure to find images based on the resemblance between query image and all images. In retrieving images, the crucial step that arises is how to define the similarity between images. In this paper, we propose a new similarity measure which is based on distribution of color. We apply the new measure to retrieving two different types of images, wallpaper images and the logo of automobiles, and compare its performance to other existing similarity measures.

Design an Indexing Structure System Based on Apache Hadoop in Wireless Sensor Network

  • Keo, Kongkea;Chung, Yeongjee
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2013년도 춘계학술발표대회
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    • pp.45-48
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    • 2013
  • In this paper, we proposed an Indexing Structure System (ISS) based on Apache Hadoop in Wireless Sensor Network (WSN). Nowadays sensors data continuously keep growing that need to control. Data constantly update in order to provide the newest information to users. While data keep growing, data retrieving and storing are face some challenges. So by using the ISS, we can maximize processing quality and minimize data retrieving time. In order to design ISS, Indexing Types have to be defined depend on each sensor type. After identifying, each sensor goes through the Indexing Structure Processing (ISP) in order to be indexed. After ISP, indexed data are streaming and storing in Hadoop Distributed File System (HDFS) across a number of separate machines. Indexed data are split and run by MapReduce tasks. Data are sorted and grouped depend on sensor data object categories. Thus, while users send the requests, all the queries will be filter from sensor data object and managing the task by MapReduce processing framework.