• Title/Summary/Keyword: Digital filtering

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Case-based Filtering by Using Degree of Membership for Digital Contents (디지털 콘텐츠를 위한 소속도를 이용한 사례기반 필터링)

  • Kim, Hyung-Il
    • The Journal of the Korea Contents Association
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    • v.10 no.10
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    • pp.9-18
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    • 2010
  • As digital contents become vast in quantity, it takes long time for users to search the digital contents they want, which is a problem that has arisen. Therefore, it is required to have the technology that analyzes vast digital contents and extracts the appropriate contents for users in order to provide them with contents they want. For a fast searching of digital contents suitable for users, it is necessary to have the technology of filtering for digital contents. In this paper, we propose a method of filtering digital contents suitable for individual users. The method suggested in this paper is to analyze case-based information in digital contents and provide the digital contents suitable for individual users. The case for using digital contents is used for analysis of users' preference. Various simulations were conducted to confirm the effectiveness of the proposed method.

A Study on the Digital Distance Relaying Techniques Using Kalman Filtering (칼만필터링에 의한 디지털 거리계전 기법에 관한 연구)

  • 김철환;박남옥;신명철
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.3
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    • pp.219-226
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    • 1992
  • In this study, Kalman filtering theory is applied to the estimation of symmetrical components from fault voltage and current signal when it comes to faults with the power system. An algorithm for estimating fault location accurately and quickly by calculating the symmetrical components from the extracted fundamental voltage phasor and current phasor is presented. Also, to confirm the validity of digital distance relaying techniques using Kalman filtering, the experimental results obtained by using the digital simulation of power system is shown.

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Image Restoration Simulation of Digital X-ray Images Based upon Filtering Techniques and the Quality Evaluation of the Restored Images (다양한 필터링 기법을 이용한 디지털 X-선 영상복원 시뮬레이션 및 정량적 화질평가)

  • Lee, So-Young;Choi, Sung-Il;Oh, Ji-Eun;Cho, Hee-Moon;Lee, Sung-Ju;Park, Yeon-Ok;Cho, Hyo-Sung
    • Journal of the Korean Society of Radiology
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    • v.2 no.4
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    • pp.33-40
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    • 2008
  • Images acquired by a digital X-ray imaging system are inherently degraded due to system degradation process and additive noise sources. The system degradation in image quality is typically described as the system response function characterized by the modulation transfer function (MTF) and the noise term described as the noise power spectrum (NPS). In this case, we can restore the blur image as close as possible to the original image by using modified filtering designed for digital imaging system, as we know more precisely about the MTF and the NPS. In this paper, by performing simulation, we tried to restore blurred images taken from a digital X-ray imaging system based upon conventional filtering techniques such as a direct-inverse filtering, limited-inverse filtering, or a Wiener filtering, and evaluated the characteristics of the image restoration.

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Misclassified Area Detection Algorithm for Aerial LiDAR Digital Terrain Data (항공 라이다 수치지면자료의 오분류 영역 탐지 알고리즘)

  • Kim, Min-Chul;Noh, Myoung-Jong;Cho, Woo-Sug;Bang, Ki-In;Park, Jun-Ku
    • Journal of Korean Society for Geospatial Information Science
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    • v.19 no.1
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    • pp.79-86
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    • 2011
  • Recently, aerial laser scanning technology has received full attention in constructing DEM(Digital Elevation Model). It is well known that the quality of DEM is mostly influenced by the accuracy of DTD(Digital Terrain Data) extracted from LiDAR(Light Detection And Ranging) raw data. However, there are always misclassified data in the DTD generated by automatic filtering process due to the limitation of automatic filtering algorithm and intrinsic property of LiDAR raw data. In order to eliminate the misclassified data, a manual filtering process is performed right after automatic filtering process. In this study, an algorithm that detects automatically possible misclassified data included in the DTD from automatic filtering process is proposed, which will reduce the load of manual filtering process. The algorithm runs on 2D grid data structure and makes use of several parameters such as 'Slope Angle', 'Slope DeltaH' and 'NNMaxDH(Nearest Neighbor Max Delta Height)'. The experimental results show that the proposed algorithm quite well detected the misclassified data regardless of the terrain type and LiDAR point density.

A Study on Contents Preference Prediction Method using Tags based on Content-based Filtering (Tag를 이용한 CBF방식의 컨텐츠 선호도 예측 방법)

  • Um, Tae-Kwang;Choi, Sung-Hwan;Lee, Jae-Hwang
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.613-614
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    • 2008
  • A content recommendation according to users preferences comes up in the Internet application due to contents overwhelming. This paper newly proposes a method to predict contents preference using tags in conjunction with Content-Based Filtering. By implementing this method, this paper cleans up the contents sparsity problem in Content-Based Filtering, and shows the outstanding improvements.

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A Hybrid Collaborative Filtering Method using Context-aware Information Retrieval (상황인식 정보 검색 기법을 이용한 하이브리드 협업 필터링 기법)

  • Kim, Sung Rim;Kwon, Joon Hee
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.6 no.1
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    • pp.143-149
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    • 2010
  • In ubiquitous environment, information retrieval using collaborative filtering is a popular technique for reducing information overload. Collaborative filtering systems can produce personal recommendations by computing the similarity between your preference and the one of other people. We integrate the collaboration filtering method and context-aware information retrieval method. The proposed method enables to find some relevant information to specific user's contexts. It aims to makes more effective information retrieval to the users. The proposed method is conceptually comprised of two main tasks. The first task is to tag context tags by automatic tagging technique. The second task is to recommend items for each user's contexts integrating collaborative filtering and information retrieval. We describe a new integration method algorithm and then present a u-commerce application prototype.

The Calculation of the Amount of Wear using Digital Filtering (디지털 필터링을 이용한 마멸량 계산)

  • 전종하;구영필;조용주
    • Tribology and Lubricants
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    • v.16 no.2
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    • pp.133-137
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    • 2000
  • A new method to calculate the wear amount using surface profile signal was suggested. It takes advantage of filtering technic to estimate the original surface profile of wear track precisely. The original profile of wear track was estimated by comparing with outside of wear track. The estimated surface profile was well fitted to the original profile assumed unknown.

Image Sequence Stabilization Scheme Using FIR Filtering

  • Kim, Pyung-Soo
    • International Journal of Control, Automation, and Systems
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    • v.1 no.4
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    • pp.515-519
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    • 2003
  • This paper proposes a new image sequence stabilization (ISS) scheme based on filtering of absolute frame positions. The proposed ISS scheme removes undesired motion effects in real-time, while preserving desired gross camera displacements. The well-known finite impulse response (FIR) filter is adopted for filtering. The proposed ISS scheme provides a filtered position and velocity with fine inherent properties. It is demonstrated that the filtered position is not affected by the constant velocity. It is also shown that the filtered velocity is separated from the position. Via numerical simulations, the performance of the proposed scheme is shown to be superior to the existing Kalman filtering scheme.

A Study on Recommendation System Using Collaborative Filtering (Collaborative Filtering기반 추천 시스템에 관한 연구)

  • Lee, Jae-Hwang;Kim, Yong-Ku;Jang, Jeong-Rok;Um, Tae-Kwang
    • Proceedings of the KIEE Conference
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    • 2008.10b
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    • pp.231-232
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    • 2008
  • 본 논문은 협업 필터링(Collaborative Filtering)기반의 추천시스템에 필요한 알고리즘을 제안한다. 제안한 알고리즘은 사용자의 선호도를 Implicit Feedback을 통해 예측하는 Implicit Rating과 사용자 선호도와 컨텐츠의 정보를 바탕으로 사용자의 프로파일을 형성하는 Tag 기반의 사용자 프로파일과 P2P망 내에서 자신과 유사한 사용자 그룹을 형성하는 알고리즘으로 구성되어 있다. 제안한 알고리즘을 적용하여 Web Text 기반의 CF기반의 개인화 추천시스템을 구현하였으며 구현된 프로그램을 실제 사용자에게 배포하여 Feasibility를 검증하였다.

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