• Title/Summary/Keyword: Convergence pattern

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Sensitivity Analysis of the Speed Reducer using Magnetic Force (마그네트 기반 감속기의 민감도 해석)

  • Jung, Kwang Suk
    • Journal of Institute of Convergence Technology
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    • v.4 no.2
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    • pp.11-15
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    • 2014
  • Magnet gear transfers a high speed torque of the driving side to a low speed following side. Of course, the torque is amplified as much as a ratio between pole number of magnet gears constituting both sides through ferromagnet modulator. However, the parameters of the overall magnetic system influence the transmitting torque strongly. They include a pole number of permanent magnet, magnet thickness, reducing ratio, harmonic modulator thickness, and open ratio etc. In this paper, the influences of the parameters are analyzed using finite element method tool. By comparison, a desirable design specification is proposed, including a recommended modulator pattern.

A License Plate Recognition Using Intensity Variation and Hybrid Pattern Vector (명암도 변화값과 하이브리드 패턴 벡터를 이용한 번호판 인식)

  • 석영수;김정훈;이응주
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2001.06a
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    • pp.153-156
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    • 2001
  • 본 논문에서는 하이브리드 패턴 벡터를 이용하여 차량 번호를 실시간으로 인식하는 알고리즘을 제안하였다. 차량 입력 영상에서 전처리 과정을 거쳐 번호판의 수평 및 수직 명암값 빈도수 변화를 이용해 번호판 영역을 추출하고 하이브리드 패턴을 적용해 더 정확한 번호판 문자 및 숫자를 인식하는 알고리즘을 제안하였다. 제안한 알고리즘의 번호판 추출 과정에서는 번호판 영역의 문자와 배경이 뚜렷하게 구별되는 특성 및 번호 판 영역의 상대적인 크기의 특성과 수평 및 수직 빈도 수를 추하여 입력된 차량영상에서 번호판 영역을 추출한다. 또한 번호판 영역에서 잡음 제거와 세선화(Thinning)를 적용해 문자 및 숫자를 하이브리드 패턴 벡터를 적용하여 문자의 크기, 문자와 문자 사이의 밀집도의 특성, 이동에 무관한 특성을 이용해 차량 번호를 인식하는 알고리즘을 제안하였다. 제안한 방법들을 적용한 결과 기존의 원형 패턴 벡터 보다 훨씬 계산 속도가 빠르며, 차량 번호판의 크기에 관계없이 잡음에 영향을 받지 않고 차량 번호를 실시간으로 처리할 수 있는 가능성을 제시하였고, 번호판 영역이 불규칙한 조명 상태에서도 더 정확한 차량 번호를 인식 할 수 있는 알고리즘을 본 논문에서 제안하였다.

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Moving Obstacles Collision Avoidance of a Mobile Robot using an Intelligent Network (지능형 네트워크를 이용한 이동 로봇의 이동장애물 회피 응용)

  • 박윤명;하달영;최부귀
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.2
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    • pp.64-70
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    • 2002
  • This paper proposes a new construction method of neural networks. The construction method consists of two fundmental ideas, which are a parallel selection-style evaluation and rules evolution. A new collision avoidance algorithm using genetic and neural network is proposed to avoid moving obstacles such as mobile robots. The input parameters of this algorithm is position of moving obstacles and target. Output is a regenerated direction of mobile robot. This algorithm is very simple and so, it is available to application of real time process. The pattern of collision avoidance is learned through test execution.

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Fast Optimization by Queen-bee Evolution and Derivative Evaluation in Genetic Algorithms

  • Jung, Sung-Hoon
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.4
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    • pp.310-315
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    • 2005
  • This paper proposes a fast optimization method by combining queen-bee evolution and derivative evaluation in genetic algorithms. These two operations make it possible for genetic algorithms to focus on highly fitted individuals and rapidly evolved individuals, respectively. Even though the two operations can also increase the probability that genetic algorithms fall into premature convergence phenomenon, that can be controlled by strong mutation rates. That is, the two operations and the strong mutation strengthen exploitation and exploration of the genetic algorithms, respectively. As a result, the genetic algorithm employing queen-bee evolution and derivative evaluation finds optimum solutions more quickly than those employing one of them. This was proved by experiments with one pattern matching problem and two function optimization problems.

An Effective Data Model for Forecasting and Analyzing Securities Data

  • Lee, Seung Ho;Shin, Seung Jung
    • International journal of advanced smart convergence
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    • v.5 no.4
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    • pp.32-39
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    • 2016
  • Machine learning is a field of artificial intelligence (AI), and a technology that collects, forecasts, and analyzes securities data is developed upon machine learning. The difference between using machine learning and not using machine learning is that machine learning-seems similar to big data-studies and collects data by itself which big data cannot do. Machine learning can be utilized, for example, to recognize a certain pattern of an object and find a criminal or a vehicle used in a crime. To achieve similar intelligent tasks, data must be more effectively collected than before. In this paper, we propose a method of effectively collecting data.

The Study of Software Optimal Release Using Sensitivity Analysis (민감도 분석을 이용한 소프트웨어 최적방출시기에 관한 연구)

  • Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.8 no.4
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    • pp.121-126
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    • 2008
  • It is of great practical interest to decide when to stop testing a software system in development phase and transfer it to the user. This decision problem called an optimal release policies. In this paper discussed to specify an optimal release policies. In this paper, propose an optimal release policies of the life distribution applied Erlang distribution of special pattern of Gamma distribution. In this paper, discuss optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement. From Sensitivity Analysis, make out estimating software optimal release time.

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A New digital Echo Canceler for Baseband Data Transmission in Two-Wire Subscriber Lines (이선 가입자에서의 기본대역 전송을 위한 새로운 디지탈 반향제법방식)

  • 황찬식;심영석
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.21 no.2
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    • pp.24-28
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    • 1984
  • A new type of digital echo canceler for two-wire digital transmission is presented. The new principle estimates an echo signal by use of the arithmetic means estimate for each transmitted data pattern, which leads to relatively simple hardware. The principle is compared with adaptive digital filter methods through theoretical analysis and computer simulation. The results show that the proposed method has fast convergence property with respect to its hardware simplicity and that the convergence time is independent of echo level. Quantization effects are also analyzed.

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An Estimate for Convergence and Efficiency of Nonlinear Shape Analysis According to the Control Techniques (제어기법에 따른 비선형 형상해석의 수렴성 및 효율성 펑가)

  • Jeong, Eul-Seok;Jeon, Jin-Hyung;Shon, Su-Deog;Kim, Seung-Deog
    • Proceeding of KASS Symposium
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    • 2006.05a
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    • pp.214-223
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    • 2006
  • Membrane structures, a kind of lightweight soft structural system, are used for spatial structures. The material property of the membrane has strong axial stiffness, but little bending stiffness. The design procedure of membrane structures are needed to do shape finding, stress-deformation analysis and cutting pattern generation. In shape finding, membrane structures are unstable structures initially. These soft structures need to be introduced initial stresses because of its initial unstable state, and happen large deformation phenomenon. Therefore, in this study, to find the structural shape after large deformation caused by initial stress, we need the shape analysis considering geometric nonlinear term. And we investigate the evaluation of shape analysis technique's convergence and efficiency according to the control method

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A License Plate Extraction and Recognition Using Intensity Variation and Circular Pattern Vector (명암도 변화값과 원형 패턴 벡터를 이용한 차량번호판 추출 및 인식)

  • 김규영;김종민;이응주
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2000.08a
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    • pp.241-244
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    • 2000
  • 본 논문에서는 차량 영상의 수평 및 수직 명암 값 변화 정보를 이용하여 번호판 영역을 추출하고 원형 패턴 벡터를 이용하여 번호판 내용을 인식하는 알고리즘에 관해 기술하였다. 제안된 알고리즘에서는 번호판 영역에서 문자와 배경이 뚜렷하게 구별되고, 일정한 명암도 변화를 가지면서 다른 영역보다 밀집도가 높다는 특성을 이용하여 수평 및 수직 명암도 변화값을 구하여 차량영상에서 번호판 영역을 추출하며 상당히 어둡거나 밝게 입력된 영상에도 동일한 인식 성능을 얻기 위하여 밝기 보정을 수행한다. 또한, 입력 문자의 크기, 이동 및 회전에 무관한 특성을 추출을 위해 원형 패턴 벡터를 이용하여 차량 번호를 인식하는 알고리즘을 제안하였다. 제안한 방법들을 적용한 결과 계산 속도가 훨씬 빠르며, 차량 번호판의 크기에 관계없이, 또한 잡음에 크게 영향을 받지 않으면서 번호판 추출이 정확하여 실시간 처리의 가능성을 제시하였을 뿐만 아니라 번호판 영역이 불투명하거나 불규칙한 조명 상태에서도 검출이 가능하였다.

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Study on Frame Stiffness based on Lamination Pattern of Carbon Bicycle Frame Materials (카본 자전거 프레임 소재의 적층 패턴에 따른 프레임 강성 연구)

  • Choi, Ung-Jae;Kim, Hong-Gun;Kwac, Lee-Ku
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.6
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    • pp.51-58
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    • 2021
  • The notion of leisure has changed with industrial development and improvement in life quality. Bicycling is a healthy sport; it is an exercise performed while enjoying nature. There have been many changes in the materials that are used to manufacture the bicycle frame. Iron and aluminum have been mainly used in bicycle frames. However, carbon-based materials are lighter and stronger than metal frames. The bicycles made of carbon composite changes frame rigidity depending on the direction of the carbon sheet sacking angle. We study the direction of composite material and how they affect the stiffness of frames based on the stacking angle.