• 제목/요약/키워드: beam training

검색결과 115건 처리시간 0.028초

세 가지 주요 검도 공격 동작에서의 근-골격계 응력과 번형률 해석에 관한 연구 (A Study on the Stress and Strain Analysis of Human Muscle Skeletal Model in Kendo Three Typical Attack Motions)

  • 이중현;이영신
    • 한국정밀공학회지
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    • 제25권9호
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    • pp.126-134
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    • 2008
  • Kendo is one of the popular sports in modem life. Head, wrist and thrust attack are the fast skill to get a score on a match. Human muscle skeletal model was developed for biomechanical study. The human model was consists with 19 bone-skeleton and 122 muscles. Muscle number of upper limb, trunk and lower limb part are 28, 60, 34 respectively. Bone was modeled with 3D beam element and muscle was modeled with spar element. For upper limb muscle modelling, rectus abdominis, trapezius, deltoideus, biceps brachii, triceps brachii muscle and other main muscles were considered. Lower limb muscle was modeled with gastrocenemius, gluteus maximus, gluteus medius and related muscles. The biomechanical stress and strain analysis of human muscle was conducted by proposed human bone-muscle finite element analysis model under head, wrist and thrust attack for kendo training.

3D Dynamic Simulation for the Dismantling Process of the KRR-2

  • Kim, Sung-Kyun;Jeong, Kawn-Seong;Lee, Kune-Woo;Park, Jin-Ho
    • 한국방사성폐기물학회:학술대회논문집
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    • 한국방사성폐기물학회 2004년도 Proceedings of the 4th Korea-China Joint Workshop on Nuclear Waste Management
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    • pp.114-129
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    • 2004
  • The 3D simulations for the Rotary Specimen Rack (RSR), the shielding concret, and the reactor core dismantling processes in the Korea Research Reactor-1&2(KRR-1&2) were carried out in the present work. The four main dismantling items, which are the RSR, reactor core, beam tube, and the thermal column and the shield concrete, were selected among the many components in the KRR-2 by consideration of the activation, worker training, difficulty of the work and so on. On the basis of these, we built 3D CAD models, selected the proper dismantling technologies, and reviewed their dismantling processes. In this study, the 3D simulation results of the shielding concrete, and the reactor core dismantling processes are also presented and discussed.

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레이저 표면경화공정에서 신경회로망을 이용한 경화층깊이 추정 (Estimation of Hardened Depth in Laser Surface Hardening Processes Using Neural Networks)

  • 박영준;조형석;한유희
    • 대한기계학회논문집
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    • 제19권8호
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    • pp.1907-1914
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    • 1995
  • An on-line measurement of the workpiece hardened depth in laser surface hardening processes is very much difficult to achieve, since the hardening process occurs in depth wise direction. In this paper, the hardened depth is estimated using a multilayered neural network. Input data of the neural network are the surface temperatures at arbitrary chosen five surface points, laser power and traveling speed of laser beam torch. To simulate the actual hardening process, a finite difference method(FDM) is used to model the process. Since this model yields the calculation results of the temperature distribution around the workpiece volume in the vicinity of the laser torch, this model is used to obtain the network's training data and laser to evaluate the performance of the neural network estimator. The simulation results show that the proposed scheme can be used to estimate the hardened depth with reasonable accuracy.

Crack identification in short shafts using wavelet-based element and neural networks

  • Xiang, Jiawei;Chen, Xuefeng;Yang, Lianfa
    • Structural Engineering and Mechanics
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    • 제33권5호
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    • pp.543-560
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    • 2009
  • The rotating Rayleigh-Timoshenko beam element based on B-spline wavelet on the interval (BSWI) is constructed to discrete short shaft and stiffness disc. The crack is represented by non-dimensional linear spring using linear fracture mechanics theory. The wavelet-based finite element model of rotor system is constructed to solve the first three natural frequencies functions of normalized crack location and depth. The normalized crack location, normalized crack depth and the first three natural frequencies are then employed as the training samples to achieve the neural networks for crack diagnosis. Measured natural frequencies are served as inputs of the trained neural networks and the normalized crack location and depth can be identified. The experimental results of fatigue crack in short shaft is also given.

RLS 알고리즘을 변형한 새로운 블라인드 적응형 알고리즘 (New blind adaptive algorithm using RLS algorithm)

  • 권태송;황현철;김백현;곽경섭
    • 한국통신학회논문지
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    • 제27권6B호
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    • pp.629-637
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    • 2002
  • RLS 알고리즘은 스마트 안테나에서 가중치 벡터를 갱신하기 위한 적응형 배열 안테나 알고리즘으로서 배열안테나 출력신호와 송신기에서 보내주는 학습 신호열의 차를 이용한다. 본 논문에서 제안된 알고리즘은 RLS 알고리즘을 기반으로 하고 블라인드 적응형 알고리즘 방법을 응용하여 구한 참조신호를 사용하여 오류신호를 구하였다. 그리고 모의실험을 통해 제안된 알고리즘이 기존의 블라인드 적응형 알고리즘(LS-DRMTA, LS-DRMTCMA)보다 BER 기준에서 사용자 수용비율이 67∼74%정도 향상 되었음을 확인하였고 빔패턴을 도시하여, 빔이 원하는 신호와 간섭신호에 올바르게 형성하는지 알아보았다

A new blind adaptive method using RLS algorithm with Decision direction method

  • Kwon, Tae-song;Yoo, Sung-kyun;Kwak, Kyung-sup
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1586-1589
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    • 2002
  • RLS algorithm is a kind of the adaptive algorithms in smart antennas and adapts the weight vector using the difference between the output signal of array antennas and the known training sequence. In this paper, we propose a new algorithm based on the RLS algorithm. It calculates the error signal with reference signal derived from blind scheme. Simulation results show that the proposed algorithm yields more user capacity by 67∼74% than other blind adaptive algorithms(LS-DRMTA, LS-DRMTCMA) at the same BER and the beamformer forms null beams toward interference signals and the main beam toward desired signal.

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Application of artificial neural networks (ANNs) and linear regressions (LR) to predict the deflection of concrete deep beams

  • Mohammadhassani, Mohammad;Nezamabadi-pour, Hossein;Jumaat, Mohd Zamin;Jameel, Mohammed;Arumugam, Arul M.S.
    • Computers and Concrete
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    • 제11권3호
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    • pp.237-252
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    • 2013
  • This paper presents the application of artificial neural network (ANN) to predict deep beam deflection using experimental data from eight high-strength-self-compacting-concrete (HSSCC) deep beams. The optimized network architecture was ten input parameters, two hidden layers, and one output. The feed forward back propagation neural network of ten and four neurons in first and second hidden layers using TRAINLM training function predicted highly accurate and more precise load-deflection diagrams compared to classical linear regression (LR). The ANN's MSE values are 40 times smaller than the LR's. The test data R value from ANN is 0.9931; thus indicating a high confidence level.

실선 시험에 의한 소성어업의 동요특성 (Experimental analysis on the motion response of the small fishing boat toward wave direction)

  • 강일권;윤점동
    • 한국항해학회지
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    • 제19권1호
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    • pp.1-8
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    • 1995
  • The motion of a small boat in seas is affected in relatively higher degrees than the case of a larger ship by the specific characteristics of sea waves, i.e., the wave length and height. Ship's motion caused by sea waves is a matter of special importance to small fishing boats, because they carry out fishing job in rough seas frequently. This is an experimental study on the rolling and pitching motions of full scale ship. In the experiment, the ship's motions were measured for head, how, beam, quarter and following seas. The experiment were carried out on board the training ship Pusan 404(160 GT) in the adjacent waters off NAM HYENG JAE DO on Dec. 13th 1994. The sea condition during the measurements was that wave height 2.5m, no swell and the wind velocity of 12 m/sec. Some statistic considerations were given to the observed data by the series analysis methods and discussed in this paper.

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Dental radiology reporting status and recording frequency of reporting items in Korea

  • Jinwoo Choi
    • Imaging Science in Dentistry
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    • 제53권1호
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    • pp.35-42
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    • 2023
  • Purpose: This study investigated the current dental radiology reporting methods and the recording rate of 10 mandatory reporting items in Korea. Materials and Methods: An original online survey created using Google Forms was distributed to dental practitioners. The survey asked about the participants' age, experience, workplace, use of radiologic equipment, radiology reporting methods, and recording reporting items. Results: In total, 354 responses were analyzed. Radiologic reporting in dental charts was the most commonly used method for each modality. Four out of 10 mandatory items were recorded at a high rate, but the remaining 6 items had substantially lower recording rates, often below 50%. The participants who reported radiographic findings through other separate methods had higher item scores than those who wrote findings in dental charts(P<0.05). Conclusion: Radiologic societies and dental associations should encourage the use of separate reports for radiographic examinations. Education regarding radiology reports and the justification for reporting items should be reinforced in dental schools, training courses on radiology, and the continuing education curriculum.

평균대 옆공중돌기 동작의 운동역학적 분석 (Kinetic Analysis of the Salto Side-Ward Tucked on the Balance Beam)

  • 여홍철;장재관
    • 한국운동역학회지
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    • 제18권3호
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    • pp.61-69
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    • 2008
  • 본 연구는 평균대에서 필수요구조건(EGR)에 해당되는 동작인 옆공중돌기 동작의 성공과 실패를 운동역학적으로 비교 분석하였다. 연구대상은 국가대표 선수들로 하였으며, 연구의 목적은 기술의 실수 요인을 규명하여 지도자 및 선수들에게 과학적으로 유용한 정보를 제공하는데 있다. 성공시 옆공중돌기 동작의 신체중심은 평균대 중앙 중심으로 좌-우축으로 벗어나는 결과가 나타나고 동작의 특성상 회전하는 방향으로 신체중심이 이동한다는 것을 나타내고 있다. 도약구간인 event2와 3에서 성공시 상 하 변화가 크게 나타나 체공시간을 높이는 것으로 투사변인이 실패시 보다 높게 나타나는 결과를 뒷받침 해 주고 있다. 또한 공중 비약을 위해 다리를 차는 동작을 하는 오른쪽 고관절 각도와 속도, 각속도가 실패시 보다 성공시 동작에서 모두 크게 나타나 도약의 최적조건을 수행하고 있다. 어깨를 중심으로 상지분절의 속도와 견관절 각속도를 크게 함으로써 운동량을 증가시켰으며 그중 오른쪽 견관절 각속도가 크게 나타난 이유는 오른쪽 다리를 잡기 위한 결과이다. 옆 공중돌기 동작에서 실패시 보다 성공시 동작에서 x축을 중심으로 각운동량이 크게 나타나 공중 비행 동작은 x축을 중심으로 각운동량을 크게 하는 것이 중요한 요인으로 나타났으며 옆공중돌기 특성상 y축과 z축으로 각운동량도 적정한 비율로 동작이 이루어져야 성공적인 동작을 만들수 있다.