• Title/Summary/Keyword: 뎁스 시뮬레이션

Search Result 4, Processing Time 0.02 seconds

Performance Analysis of Landing Point Designation Technique Based on Relative Distance to Hazard for Lunar Lander (달 착륙선의 위험 상대거리 기반 착륙지 선정기법 성능 분석)

  • Lee, Choong-Min;Park, Young-Bum;Park, Chan-Gook
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.44 no.1
    • /
    • pp.12-22
    • /
    • 2016
  • Lidar-based hazard avoidance landing system for lunar lander calculates hazard cost with respect to the desired local landing area in order to identify hazard and designate safe landing point where the cost is minimum basically using slope and roughness of the landing area. In this case, if the parameters are only considered, chosen landing target can be designated near hazard threatening the lander. In order to solve this problem and select optimal safe landing point, hazard cost based on relative distance to hazard should not be considered as well as cost based on terrain parameters. In this paper, the effect of hazard cost based on relative distance to hazard on safe landing performance was analyzed and it was confirmed that landing site designation with two relative distances to hazard results in the best safe landing performance by an experiment using three-dimensional depth camera.

Comparison and Analysis of Quantum Software Simulators (양자 소프트웨어 시뮬레이터 비교 및 분석)

  • Kim, Jane;Cho, Seong-Min;Seo, Seung-Hyun
    • Proceedings of the Korea Information Processing Society Conference
    • /
    • 2021.05a
    • /
    • pp.188-191
    • /
    • 2021
  • 최근 IBM, Intel 과 같은 글로벌 ICT 기업들과 여러 스타트업들이 양자 컴퓨터 개발에 성공하였으며 그에 따라 양자 시뮬레이터와 컴파일러에 대한 관심이 높아졌다. 여러 개의 시뮬레이터가 존재하는 만큼 시뮬레이터마다 제공하는 기능과 성능 역시 제각각 다르다. 본 논문에서는 비교적 접근이 쉬운 파이썬과 Q# 기반의 대표적인 양자 시뮬레이터 3 가지(Qiskit, Project Q, Quantum Development Kit)에서 제공하는 기능들을 소개하고 시뮬레이션 실행시간을 비교한다. 10 뎁스의 20 큐비트 회로에서는 QDK 시뮬레이터가 0.227 초로 실행 시간이 가장 짧았고, 10 큐비트의 10 뎁스 회로의 경우 Project Q 가, 1000 뎁스의 경우 Qiskit 이 가장 짧은 실행시간으로 측정됐다.

A Study on Modeling Automation of Human Engineering Simulation Using Multi Kinect Depth Cameras (여러 대의 키넥트 뎁스 카메라를 이용한 인간공학 시뮬레이션 모델링 자동화에 관한 연구)

  • Jun, Chanmo;Lee, Ju Yeon;Noh, Sang Do
    • Korean Journal of Computational Design and Engineering
    • /
    • v.21 no.1
    • /
    • pp.9-19
    • /
    • 2016
  • Applying human engineering simulation to analyzing work capability and movements of operators during manufacturing is highly demanded. However, difficulty in modeling digital human required for simulation makes engineers to be reluctant to utilize human simulation for their tasks. This paper addresses such problem on human engineering simulation by developing the technology to automatize human modeling with multiple Kinects at different depths. The Kinects enable us to acquire the movements of digital human which are essential data for implementing human engineering simulation. In this paper, we present a system for modeling automation of digital human. Especially, the system provides a way of generating the digital model of workers' movement and position using multiple Kinects which cannot be generated by single Kinect. Lastly, we verify the effects of the developed system in terms of modeling time and accuracy by applying the system to four different scenarios. In conclusion, the proposed system makes it possible to generate the digital human model easily and reduce costs and time for human engineering simulation.

Fuzzy-based Threshold Controlling Method for ART1 Clustering in GPCR Classification (GPCR 분류에서 ART1 군집화를 위한 퍼지기반 임계값 제어 기법)

  • Cho, Kyu-Cheol;Ma, Yong-Beom;Lee, Jong-Sik
    • Journal of the Korea Society of Computer and Information
    • /
    • v.12 no.6
    • /
    • pp.167-175
    • /
    • 2007
  • Fuzzy logic is used to represent qualitative knowledge and provides interpretability to a controlling system model in bioinformatics. This paper focuses on a bioinformatics data classification which is an important bioinformatics application. This paper reviews the two traditional controlling system models The sequence-based threshold controller have problems of optimal range decision for threshold readjustment and long processing time for optimal threshold induction. And the binary-based threshold controller does not guarantee for early system stability in the GPCR data classification for optimal threshold induction. To solve these problems, we proposes a fuzzy-based threshold controller for ART1 clustering in GPCR classification. We implement the proposed method and measure processing time by changing an induction recognition success rate and a classification threshold value. And, we compares the proposed method with the sequence-based threshold controller and the binary-based threshold controller The fuzzy-based threshold controller continuously readjusts threshold values with membership function of the previous recognition success rate. The fuzzy-based threshold controller keeps system stability and improves classification system efficiency in GPCR classification.

  • PDF