• 제목/요약/키워드: map-reduce

검색결과 853건 처리시간 0.03초

소음지도를 이용한 도로교통소음에 관한 연구 - 시화멀티테크노밸리 개발사업을 중심으로 - (A Study on the Road Traffic Noise Effect Using a Noise Map - Development of Sihwa Multi Techno Valley -)

  • 정재훈;김흥만;권우택;김형철
    • 환경영향평가
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    • 제18권2호
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    • pp.89-97
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    • 2009
  • Korean society is faced with various new problems arising from the development projects of new towns, industrial cities, large-scale residential complexes, etc. started from the 1970s. Particularly with the construction of residential and industrial complexes by the roadsides, they are openly exposed to road traffic noise and vibration. Thus, the objective of this study is to examine using noise maps how increasing traffic volume affects road traffic noise and what problems it causes in areas where new towns or complexes are constructed by development projects. According to the results of this study, in areas around the sites of development projects, the noise level increased by road traffic noise compared to that before development and was 1.16~6.92 times higher than the environmental noise standard, but measures to reduce road traffic noise was lukewarm. In addition, areas with soundproof facilities showed a noise level 1~3 step lower than other areas, and in individual buildings, the noise level on the side facing the road was 1~2 step higher than that on the rear side.

적외선 조명 및 단일카메라를 이용한 입체거리 센서의 개발 (3D Range Measurement using Infrared Light and a Camera)

  • 김인철;이수용
    • 제어로봇시스템학회논문지
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    • 제14권10호
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    • pp.1005-1013
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    • 2008
  • This paper describes a new sensor system for 3D range measurement using the structured infrared light. Environment and obstacle sensing is the key issue for mobile robot localization and navigation. Laser scanners and infrared scanners cover $180^{\circ}$ and are accurate but too expensive. Those sensors use rotating light beams so that the range measurements are constrained on a plane. 3D measurements are much more useful in many ways for obstacle detection, map building and localization. Stereo vision is very common way of getting the depth information of 3D environment. However, it requires that the correspondence should be clearly identified and it also heavily depends on the light condition of the environment. Instead of using stereo camera, monocular camera and the projected infrared light are used in order to reduce the effects of the ambient light while getting 3D depth map. Modeling of the projected light pattern enabled precise estimation of the range. Identification of the cells from the pattern is the key issue in the proposed method. Several methods of correctly identifying the cells are discussed and verified with experiments.

NC파트프로그램의 검증 및 오류 수정에 관한 연구 (A Study on Verification and Editing of NC Part-program)

  • 김찬봉;박세형;양민양
    • 대한기계학회논문집
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    • 제17권5호
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    • pp.1074-1083
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    • 1993
  • 본 연구에서 제시된 방법은 Fig.2(c)에 나타낸 방법으로 공구궤적의 검증과 더불어 NC공구궤적의 잘못된 부분과 정도를 찾아내 수정할 수 있도록하여 기존의 NC검증시스템의 비효율성을 해결하고자 했다.

에지 정보를 이용한 유전 알고리즘 기반의 다해상도 스테레오 정합 (A Multiresolution Stereo Matching Based on Genetic Algorithm using Edge Information)

  • 홍석근;조석제
    • 정보처리학회논문지B
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    • 제17B권1호
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    • pp.63-68
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    • 2010
  • 본 논문은 스테레오 시각에서 에지 정보를 이용한 유전 알고리즘 기반의 다해상도 스테레오 영상 정합 방법을 제안하고자 한다. 정합 환경을 최적화 문제로 간주하여 유전 알고리즘을 이용하여 해를 찾는다. 비용함수는 스테레오 정합에서 주로 고려할 수 있는 제약 조건으로 구성하였다. 처리의 효율성을 높이기 위해, 영상 피라미드 방벙을 적용하여 최저해상도에서 최초 변위도를 계산한다. 그리고 최초 변위도는 다음 해상도로 전파되고, 보간된 후 변위 정제를 수행한다. 실험을 통해 제안한 방법이 변위 탐색 시간을 감소시킬 뿐만 아니라 정합의 타당성을 보증함을 확인하고자 한다.

RDP: A storage-tier-aware Robust Data Placement strategy for Hadoop in a Cloud-based Heterogeneous Environment

  • Muhammad Faseeh Qureshi, Nawab;Shin, Dong Ryeol
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권9호
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    • pp.4063-4086
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    • 2016
  • Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

Sparse Feature Convolutional Neural Network with Cluster Max Extraction for Fast Object Classification

  • Kim, Sung Hee;Pae, Dong Sung;Kang, Tae-Koo;Kim, Dong W.;Lim, Myo Taeg
    • Journal of Electrical Engineering and Technology
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    • 제13권6호
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    • pp.2468-2478
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    • 2018
  • We propose the Sparse Feature Convolutional Neural Network (SFCNN) to reduce the volume of convolutional neural networks (CNNs). Despite the superior classification performance of CNNs, their enormous network volume requires high computational cost and long processing time, making real-time applications such as online-training difficult. We propose an advanced network that reduces the volume of conventional CNNs by producing a region-based sparse feature map. To produce the sparse feature map, two complementary region-based value extraction methods, cluster max extraction and local value extraction, are proposed. Cluster max is selected as the main function based on experimental results. To evaluate SFCNN, we conduct an experiment with two conventional CNNs. The network trains 59 times faster and tests 81 times faster than the VGG network, with a 1.2% loss of accuracy in multi-class classification using the Caltech101 dataset. In vehicle classification using the GTI Vehicle Image Database, the network trains 88 times faster and tests 94 times faster than the conventional CNNs, with a 0.1% loss of accuracy.

산업용 로봇의 기어소음 특성 고찰 (Identification of Gear Noise for Industrial Robots)

  • 김동해;이종문
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2002년도 추계학술대회논문집
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    • pp.152-155
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    • 2002
  • An industrial robot noise has various noise sources such as gears, motors, bearings, and controller fans. Among these, gears are the most dominant source for noise. The gear noise, caused by tooth profile, elastic deformation, machining error and wear, is directly correlated with the transmission error of mating gear. Due to the fact that has several axis and many gears, it is difficult to understand the characteristics of the vibration and noise of robots. In this study, some advanced analysis techniques based on digital signal processing such as power spectrum, time spectral map, RPM map, and etc., were applied for locating the dominant frequency components of the robot noises and identifying their sources. In addition, sound quality analysis was performed in order to evaluate the operator's annoyance. The noise and vibration measurements were carried out at several points during the operation of each axis considering the effect of load and posture of the robot. Eased on the results, proper countermeasures to reduce excessive noise level have been suggested considering the characteristics of sources.

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초음파의 멀티 에코 기능을 이용한 주차 공간의 코너 감지법 (Comer Detection of Parking Lot Using Multiple Echo Ultrasonic)

  • 김병성;박완주;서동은;이쾌희;김동석
    • 한국자동차공학회논문집
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    • 제16권2호
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    • pp.66-73
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    • 2008
  • In this paper, ultrasonic range system which detects parking lot in parking area is studied. The important part for detecting parking lot accurately is to detect the first and second corners of possible parking lot, and for that, new method using multiple echo function is introduced in this paper. Many probabilistic methods have been used to reduce uncertainties of ultrasonic sensor for distance and location of objects. Method using multiple echo, however, gives accurates results as well as simple algorithm. For experiments in parking space, ultrasonic range system was attached to a Pioneer AT-2 and final parking space map was created in a fusion with position information from wheels of a Pioneer AT-2. We will show the results are compared with error of another methods.

지적재조사에서 UAS 영상 기반 지적 경계확정 시범 연구 (Demonstration of UAS Image-Based Intellectual Demarcation in Cadastral Reexaminationy)

  • 김달주;강준오;한웅지;이용창
    • 도시과학
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    • 제7권1호
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    • pp.29-38
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    • 2018
  • The cadastral rehabilitation project, which has been implemented since 2012, is a project to re-examine the national land that is not in conformity with the cadastral map, There is a lot of trouble in securing financial resources for business execution. This study examines the utility of UAS(Unmanned Aerial System) image - based cadastral demarcation as an alternative to budget reduction in the current state of cadastral rehabilitation, reasonable boundary adjustment, UAV(Unmanned Aerial Vehicles) is used to create 3D models and orthoimages of business districts, and to check accuracy by superimposing and comparing with digital maps of NGII(National Geographic Information Institute). As a result of the study, the accuracy of the 3D model and the orthoimage through the SfM(Structure-from-Motion) - based image interpretation of the digital map of the NGII were derived. In particular, we confirmed the similarity of UAS-based orthoimage with the cadastral boundaries affirmation, It is anticipated that the cost saving effect of current survey and boundary survey can be expected. In addition, it is easy to prepare a report to reduce civil complaints, which is a problematic element of the adjustment.

신뢰확산 알고리듬을 이용한 선 그룹화 기반 스테레오 정합 (Stereo Matching using Belief Propagation with Line Grouping)

  • 김봉겸;임재권
    • 대한전자공학회논문지SP
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    • 제42권3호
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    • pp.1-6
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    • 2005
  • 변이 영상을 마코브 랜덤필드(MRF)로 모델링한 마코브 네트워크에서 신뢰확산 알고리듬은 각 화소에 대응되는 노드들 사이에 메시지를 전달하는 방식으로 이루어진다. 최초 메시지는 알고리듬의 반복을 통해 특정한 값으로 수렴하게 되며, 수렴된 값을 얻기 위해서는 많은 알고리듬의 반복이 필요하다. 본 논문에서는 알고리듬의 반복을 줄이기 위해 영상내 물체들을 선들의 조합 구성으로 보고 각각의 선들은 같은 메시지를 갖는 노드들의 집합으로 간주하여 기존의 신뢰확산 알고리듬을 단순화하였다.