• Title/Summary/Keyword: 5-이웃

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A Multiple-Symbol Interval Estimation Algorithm for Precision Improvement of Initial Carrier-Frequency Synchronization in Multiband-OFDM UWB System (MB-OFDM UWB 시스템에서 초기 반송파 주파수 동기의 정확도 향상을 위한 다중 심볼 간격 추정 알고리즘)

  • Jin, Yong-Sun;Park, Kye-Wan
    • 전자공학회논문지 IE
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    • v.47 no.3
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    • pp.35-40
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    • 2010
  • In this paper, we propose an algorithm to improve the precision of initial carrier-frequency offset estimation for multiband-OFDM (MB-OFDM) UWB system which is considering the quantization-noise effect. In the general OFDM system, the two adjacent and repeated preamble symbols are used for the initial carrier-frequency synchronization while the performance of the frequency-offset estimation is bounded by quantization effect generated from analog-to-digital conversion at the receiver. This paper proposes a method in which one-symbol interval between two adjacent preamble symbols for the initial frequency synchronization is extended to multiple-symbol interval between non-adjacent symbols in an extent that phase ambiguity does not occur. In this paper, we also present '6' as optimal multiple symbol interval for the MB-OFDM system with 30 preamble symbols on 3-band hopping and with 4-bit A/D conversion at the receiver. Under the channel environments for the MB-OFDM UWB system, the simulation results show that the proposed estimation algorithm can achieve the initial estimation in offset precision less than 5 ppm.

A Comparative Study using Bibliometric Analysis Method on the Reformed Theology and Evangelicalism (개혁신학과 복음주의에 관한 계량서지학적 비교 연구)

  • Yoo, Yeong Jun;Lee, Jae Yun
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.29 no.3
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    • pp.41-63
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    • 2018
  • This study aimed at analyzing journals and index terms, authors of the reformed theology and evangelicalism, neutral theological position by using bibliometrical analyzing methods. The analyzing methods are average linkage and neighbor centralities, profile cosine similarities. Especially, when analyzing the relationship between authors, we interpreted the research topic by finding the key shared index terms between the authors. In the journal analysis results, 9 journals were largely clustered together in the two clusters of the reformed theology and evangelicalism, but Presbyterian Theological Quarterly that is thought to be a reformed journal was clustered in evangelical cluster. In the index terms analysis results of the clusters, the reformed theology and evangelicalism were key words representing the two clusters. In the authors' analysis results, we had 9 clusters and the Presbyterian theologian studying the reformed theology had the four clusters and the non-Presbyterian theologian had the 5 clusters. Therefore, we consistently had the two clusters of the reformed theology and evangelicalism in all the analysis of the journals and the index terms, the authors.

A Study on the Generation of Crew Scheduling Diagram Using Neighborhood Search Method for Improving Railway Operation Management (철도 운영관리 효율화를 위한 이웃해 탐색기법을 사용한 승무다이아 생성방안)

  • Lee, Jaehee;Park, Sangmi;Kang, Leenseok
    • Korean Journal of Construction Engineering and Management
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    • v.20 no.5
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    • pp.42-51
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    • 2019
  • The train operation institution establishes a transportation plan based on the forecast of transport demand and the ability of train vehicles to transport, and establishes a train operation plan accordingly. The train operation plan adjusts the intervals between trains, creates a timetable (train diagram) for trains, and establishes a plan for the operation of train vehicles used for train operation. The train operation institution shall establish a crew schedule to determine and place the crew members of the trains arranged in the diagram in order to enhance the efficiency of the operation management of the trains. In this study, the authors apply the neighborhood search method that satisfies the constraints at the phase of generating the crew diagram. This suggests a methodology for efficient management of crew schedule plan. The crew diagram generated in this study compared with the existing crew diagram in accordance with the actual operating train timetable, and verified the effectiveness of the suggested method.

A Parallel Processing of Finding Neighbor Agents in Flocking Behaviors Using GPU (GPU를 이용한 무리 짓기에서 이웃 에이전트 찾기의 병렬 처리)

  • Lee, Jae-Moon
    • Journal of Korea Game Society
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    • v.10 no.5
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    • pp.95-102
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    • 2010
  • This paper proposes a parallel algorithm of the flocking behaviors using GPU. To do this, we used CUDA as the parallel processing architecture of GPU and then analyzed its characteristics and constraints. Based on them, the paper improved the performance by parallelizing to find the neighbors for an agent which requires the largest cost in the flocking behaviors. We implemented the proposed algorithm on GTX 285 GPU and compared experimentally its performance with the original spatial partitioning method. The results of the comparison showed that the proposed algorithm outperformed the original method up to 9 times with respect to the execution time.

A Parallel Thinning Algorithm by the 8-Neighbors Connectivity Value (8-이웃 연결값에 의한 병렬세선화 알고리즘)

  • Won, Nam-Sik;Son, Yoon-Koo
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.5
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    • pp.701-710
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    • 1995
  • A thinning algorithm is a very important procedure in order to increase recognition rate in the character recognition. This paper is the study of a parallel thinning algorithm available for the recognition of various characters, and it proposes the parallel thinning algorithm using the 8-neighbors connectivity value. Characteristics of the proposed algorithm are easiness of implementation of parallelism, the result of thinning is perfectly-8 connectivity and represented by numeric information. The proposed algorithm is very suitable for characters having many curve segments such as English, Japanese etc. Performance evaluation was performed by the measure of similarity to reference skeleton.

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명사취재-정순택 부산광역시 교육감

  • KOREA ASSOCIATION OF HEALTH PROMOTION
    • 건강소식
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    • v.24 no.9 s.262
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    • pp.2-5
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    • 2000
  • 65년 독일의 원조를 받아 해운대에 한독 여자기술학교를 세우면서 교육계와 인연을 맺은 정순택 교육감은 교육의 목표를 함께 사는 삶울 위하여 정해진 규칙을 충실히 지키고 이웃을 사랑하고 남의 불행에 가슴 아파할 줄 아는 사람다운 사람을 길러주는 것이라고 강조한다. 살아 온 날의 대부분을 학생을 가르치고 또 한편으로는 스스로도 무언가를 끊임없이 배우고 연마하기를 게을리하지 않았던 정교육감이 만들어 온 부산 교육의 이야기를 들어본다.

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더불어 사는 삶의 지혜 나눔과 베품의 미학

  • 김학순
    • 가정의 벗
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    • v.37 no.1 s.425
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    • pp.8-9
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    • 2004
  • 한 통계에 따르면 우리 나라 사람 10명 중 4$\~$5명은 평생 단 한번도 기부금을 내 본 적이 없다고 한다. 탈무드 우화처럼 남을 먼저 배려하는 마음은 바로 나를 돕는 길이자 더불어 잘 사는 아름다운 세상 만들기의 지름길이다. 돈만이 이웃돕기의 수단은 아니다. 시간과 사랑을 쏟는 봉사활동도 중요하다. 더불어 사는 삶의 지혜가 오롯이 녹아있는 나눔과 베품의 미학을 깨달아야 할 것이다.

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행복한 나눔 2 - 온기 담은 김장 봉사활동

  • Go, Yeong-Jae
    • 보건세계
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    • v.62 no.5
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    • pp.10-13
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    • 2013
  • 서울 토박이로서, 부산 해운대는 이따금 TV에서나 보았던 한여름의 뜨거운 햇살과 수많은 인파로 북적이는 백사장으로 기억된다. 그러나 부산 해운대의 촬영장을 찾은 날은 내 기억과는 정반대였다. 초겨울임을 알리는 차가운 바닷바람을 맞으며 '부산은 따뜻하겠지'라는 안일한 생각으로 얇은 재킷만 챙겨 부산 출장을 떠난 내 자신이 야속할 따름이었다. 본격적인 겨울의 시작을 알리는 12월. 우리 주변의 불우이웃을 돌아보고 함께 더불어 잘사는 세상을 만들기 위한 작은 첫걸음을 내딛는 12월 2일은 그렇게 시작하였다.

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Directional conditionally autoregressive models (방향성을 고려한 공간적 조건부 자기회귀 모형)

  • Kyung, Minjung
    • The Korean Journal of Applied Statistics
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    • v.29 no.5
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    • pp.835-847
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    • 2016
  • To analyze lattice or areal data, a conditionally autoregressive (CAR) model has been widely used in the eld of spatial analysis. The spatial neighborhoods within CAR model are generally formed using only inter-distance or boundaries between regions. Kyung and Ghosh (2010) proposed a new class of models to accommodate spatial variations that may depend on directions. The proposed model, a directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Properties of maximum likelihood estimators of a Gaussian DCAR are discussed. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.

Bayesian analysis of directional conditionally autoregressive models (방향성 공간적 조건부 자기회귀 모형의 베이즈 분석 방법)

  • Kyung, Minjung
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.5
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    • pp.1133-1146
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    • 2016
  • Counts or averages over arbitrary regions are often analyzed using conditionally autoregressive (CAR) models. The spatial neighborhoods within CAR model are generally formed using only the inter-distance or boundaries between the sub-regions. Kyung and Ghosh (2009) proposed a new class of models to accommodate spatial variations that may depend on directions, using different weights given to neighbors in different directions. The proposed model, directional conditionally autoregressive (DCAR) model, generalized the usual CAR model by accounting for spatial anisotropy. Bayesian inference method is discussed based on efficient Markov chain Monte Carlo (MCMC) sampling of the posterior distributions of the parameters. The method is illustrated using a data set of median property prices across Greater Glasgow, Scotland, in 2008.