• Title/Summary/Keyword: 맵 생성 알고리즘

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Integrated Control Algorithm of Hydraulic Pump with Electric Motor to Improve Energy Efficiency of Electric Excavator (전기굴삭기 에너지 효율 향상을 위한 유압펌프-전동기 통합 제어 알고리즘)

  • Lee, Jeeho;Lee, Jihye;Lee, Hyeongcheol;Oh, Chang Eun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.39 no.2
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    • pp.195-201
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    • 2015
  • An electric excavator consumes battery energy to drive an electric motor attached to a hydraulic pump to generate hydraulic power. In a conventional hydraulic excavator, the hydraulic pump is controlled by regulators, which are used to optimize the diesel engine efficiency. Because of a lack of battery energy capacity, an electric excavator controller should consider not only the electric motor efficiency but also the hydraulic pump efficiency. Thus, electric motor and hydraulic pump efficiency maps were constructed. An optimal operating map (OOM) was created based on the most efficient operating points under each input condition. An integrated control algorithm controlled the speed of the electric motor and displacement of the hydraulic pump according to the OOM. To confirm the utility of this algorithm, a model-in-the-loop simulator for the algorithm with an electric excavator was established. The simulation results showed that the integrated control algorithm improved the energy efficiency of an electric excavator.

A study on integrating and discovery of semantic based knowledge model (의미 기반의 지식모델 통합과 탐색에 관한 연구)

  • Chun, Seung-Su
    • Journal of Internet Computing and Services
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    • v.15 no.6
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    • pp.99-106
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    • 2014
  • Generation and analysis methods have been proposed in recent years, such as using a natural language and formal language processing, artificial intelligence algorithms based knowledge model is effective meaning. its semantic based knowledge model has been used effective decision making tree and problem solving about specific context. and it was based on static generation and regression analysis, trend analysis with behavioral model, simulation support for macroeconomic forecasting mode on especially in a variety of complex systems and social network analysis. In this study, in this sense, integrating knowledge-based models, This paper propose a text mining derived from the inter-Topic model Integrated formal methods and Algorithms. First, a method for converting automatically knowledge map is derived from text mining keyword map and integrate it into the semantic knowledge model for this purpose. This paper propose an algorithm to derive a method of projecting a significant topic map from the map and the keyword semantically equivalent model. Integrated semantic-based knowledge model is available.

Generation and Continual Improvement of Cutting Conditions for an Enhancement of Product Quality (제품품질 개선을 위한 가공조건의 생성과 지속적 향상 방법론)

  • Park, Byoung-Tae
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.30 no.1
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    • pp.74-81
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    • 2007
  • 절삭가공에서 가공조건은 가공비용의 감소와 제품 품질의 향상에 영향을 주는 주요 요인 중의 하나이다. 본 논문에서는 밀링작업을 대상으로 가공조건을 보다 효율적으로 수정하고 이를 지속적으로 향상시킬 수 있는 방법론과 이를 기반으로 개발된 작업설계시스템을 소개한다. 개발된 시스템은 (1) 표준 가공조건을 세부 공정별 요구 사항이 만족되도록 수정하고, (2) 퍼지아트맵 신경회로망 모델을 이용하여, 생성된 가공조건을 온라인(incremental) 학습한 후, (3) 보다 효율적인 새로운 가공조건이 생성되었을 때 이를 교체알고리즘이라 불리는 제안된 알고리즘을 이용하여 기존의 가공조건을 대체하는 3가지 핵심 기능으로 구성된다. 우선 새로운 방법론이 적용된 작업설계시스템의 전반적인 내용을 소개한 후, 다음으로 다양한 시뮬레이션을 통하여 제안된 방법론의 성능을 예시한다. 마지막으로 실제부품에 적용한 실행 결과를 기술하고 토의한다.

A Fast Algorithm of the Belief Propagation Stereo Method (신뢰전파 스테레오 기법의 고속 알고리즘)

  • Choi, Young-Seok;Kang, Hyun-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.5
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    • pp.1-8
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    • 2008
  • The belief propagation method that has been studied recently yields good performance in disparity extraction. The method in which a target function is modeled as an energy function based on Markov random field(MRF), solves the stereo matching problem by finding the disparity to minimize the energy function. MRF models provide robust and unified framework for vision problem such as stereo and image restoration. the belief propagation method produces quite correct results, but it has difficulty in real time implementation because of higher computational complexity than other stereo methods. To relieve this problem, in this paper, we propose a fast algorithm of the belief propagation method. Energy function consists of a data term and a smoothness tern. The data term usually corresponds to the difference in brightness between correspondences, and smoothness term indicates the continuity of adjacent pixels. Smoothness information is created from messages, which are assigned using four different message arrays for the pixel positions adjacent in four directions. The processing time for four message arrays dominates 80 percent of the whole program execution time. In the proposed method, we propose an algorithm that dramatically reduces the processing time require in message calculation, since the message.; are not produced in four arrays but in a single array. Tn the last step of disparity extraction process, the messages are called in the single integrated array and this algorithm requires 1/4 computational complexity of the conventional method. Our method is evaluated by comparing the disparity error rates of our method and the conventional method. Experimental results show that the proposed method remarkably reduces the execution time while it rarely increases disparity error.

Automatic Source Classification Algorithm using Mean-Shift Clustering and stepwise merging in Color Image (컬러영상에서 Mean-Shift 군집화와 단계별 병합 방법을 이용한 자동 원료 선별 알고리즘)

  • Kim, Sang-Jun;Jang, JiHyeon;Ko, ByoungChul
    • Proceedings of the Korea Information Processing Society Conference
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    • 2015.10a
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    • pp.1597-1599
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    • 2015
  • 본 논문에서는 곡물이나 광석 등의 원료들 중에서 양품 및 불량품을 검출하기 위해, Color CCD 카메라로 촬영한 원료영상에서 Mean-Shift 클러스터링 알고리즘과 단계별 병합 방법을 제안하고 있다. 먼저 원료 학습 영상에서 배경을 제거하고 영상 색 분포정도를 기준으로 모폴로지를 이용하여 영상의 전경맵을 얻는다. 전경맵 영상에 대해서 Mean-Shift 군집화 알고리즘을 적용하여 영상을 N개의 군집으로 나누고, 단계별로 위치 근접성, 색상대푯값 유사성을 비교하여 비슷한 군집끼리 통합한다. 이렇게 통합된 원료 객체는 영상채널마다의 연관관계를 반영할 수 있도록 RG/GB/BR의 2차원 컬러분포도로 표현한다. 원료 객체별로 변환된 2차원 컬러 분포도에서 분포의 주성분의 기울기와 타원들을 생성한다. 객체별 분포 타원은 테스트 원료 영상데이터에서 양품과 불량품을 검출하는 임계값이 된다. 본 논문에서 제안한 방법으로 다양한 원료영상에 실험한 결과, 기존 선별방식에 비해 사용자의 인위적 조작이 적고 정확한 원료 선별 결과를 얻을 수 있었다.

Search Space Reduction by Vertical-Decomposition of a Grid Map (그리드 맵의 수직 분할에 의한 탐색 공간 축소)

  • Jung, Yewon;Lee, Juyoung;Yu, Kyeonah
    • Journal of KIISE
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    • v.43 no.9
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    • pp.1026-1033
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    • 2016
  • Path-finding on a grid map is a problem generally addressed in the fields of robotics, intelligent agents, and computer games. As technology advances, virtual game worlds tend to be represented more accurately and more realistically, resulting in an excessive increase in the number of grid tiles and in path-search time. In this study, we propose a path-finding algorithm that allows a prompt response to real-time queries by constructing a reduced state space and by precomputing all possible paths in an offline preprocessing stage. In the preprocessing stage, we vertically decompose free space on the grid map, construct a connectivity graph where nodes are the decomposed regions, and store paths between all pairs of nodes in matrix form. In the real-time query stage, we first find the nodes containing the query points and then retrieve the corresponding stored path. The proposed method is simulated for a set of maps that has been used as a benchmark for grid-based path finding. The simulation results show that the state space and the search time decrease significantly.

A study on the face detection of moving object using BMA and dynamic GTM (BMA와 동적 GTM을 이용한 움직이는 객체의 얼굴 영역 검출에 관한 연구)

  • 장혜경;김영호;김대일;홍종선;강대성
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.114-117
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    • 2003
  • 본 논문에서는 video stream내의 움직이는 객체 정보를 추정하고 동적 GTM(genetic tree-map) 알고리즘을 사용하여 얼굴 영역 검출 기법을 제안한다. 기존의 일반적인 객체 추정 기법은 클러스터(cluster)과정을 통하여 영상 정보를 분할하고 그 중 움직이는 객체 부분을 복원함으로서 추정하였다. 제안하는 기법은 BMA(block matching algorithm)[1] 알고리즘을 사용하여 video stream 에서 움직이는 객체 정보를 얻고 클러스터 알고리즘으로 PCA(principal component analysis)를 사용한다. PCA 기법은 입력 데이터에 관해 통계적 특성을 이용하여 주성분을 찾는다. 주축과 영역분할 알고리즘을 사용하여 데이터를 분할하고, 분할된 객체 정보를 사용하여 특정 객체만을 추정하는 것이 가능하다. 이렇게 추정된 객체를 얼굴영역의 feature에 대하여 신경망 학습인 동적 GTM 알고리즘을 사용하여 생성된 동적 GTM 맵의 정보에 따라 객체의 얼굴영역만을 추출해 낼 수 있다[2-6].

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Analysis of Certificate Compression Algorithms for Efficient PQC TLS Communication (효율적인 PQC TLS 통신을 위한 인증서 압축 알고리즘 분석)

  • Jung Hun Kang;Jane Kim;Seung-Hyun Seo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.1193-1195
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    • 2023
  • 전 세계적으로 PQC migration 을 위한 암호 표준화, 로드맵 발표 등 많은 관심이 집중되고 있다. 그 중, 인터넷 환경에 필수적으로 사용되는 TLS 는 PQC 전환이 필수적이다. 하지만 NIST 표준으로 선정된 PQC 서명 알고리즘들은 기존 서명 알고리즘에 비해 공개키와 서명의 크기가 크다. 따라서 TLS 통신에 필요한 인증서를 PQC 서명알고리즘을 통해 생성하게 되면 통신 오버헤드가 급증하는 문제가 있다. 이에, 본 논문에서는 TLS 에 사용되는 인증서에 RFP8879 에 정의된 3 가지 압축알고리즘(Zlib, Z-standard, Brotli)과, CBOR 인코딩 기법을 사용하여 인증서 압축성능을 비교해본다.

Soft Shadow with integral Filtering (적분기반 필터링을 이용한 소프트 섀도우)

  • Zhang, Bo;Oh, KyoungSu
    • Journal of Korea Game Society
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    • v.20 no.3
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    • pp.65-74
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    • 2020
  • In the shadow map method, if the shadow map is magnified, the shadow has a jagged silhouette. Herein, we propose a soft shadow method that filters reshaped silhouettes analytically. First, the shadow silhouette is reshaped through sub-texel edge detection, which is based on linear or quadratic curve models. Second, an integral shadow filtering algorithm is used to accurately obtain the average shadow intensity from a definite integral estimation. The implementation demonstrates that our solution can effectively eliminate jagged aliasing and efficiently generate soft shadows.

Analysis of Relationship between Objective Performance Measurement and 3D Visual Discomfort in Depth Map Upsampling (깊이맵 업샘플링 방법의 객관적 성능 측정과 3D 시각적 피로도의 관계 분석)

  • Gil, Jong In;Mahmoudpour, Saeed;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.19 no.1
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    • pp.31-43
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    • 2014
  • A depth map is an important component for stereoscopic image generation. Since the depth map acquired from a depth camera has a low resolution, upsamling a low-resolution depth map to a high-resolution one has been studied past decades. Upsampling methods are evaluated by objective evaluation tools such as PSNR, Sharpness Degree, Blur Metric. As well, the subjective quality is compared using virtual views generated by DIBR (depth image based rendering). However, works on the analysis of the relation between depth map upsampling and stereoscopic images are relatively few. In this paper, we investigate the relationship between subjective evaluation of stereoscopic images and objective performance of upsampling methods using cross correlation and linear regression. Experimental results demonstrate that the correlation of edge PSNR and visual fatigue is the highest and the blur metric has lowest correlation. Further, from the linear regression, we found relative weights of objective measurements. Further we introduce a formulae that can estimate 3D performance of conventional or new upsampling methods.