• 제목/요약/키워드: motion classification

검색결과 363건 처리시간 0.026초

A Fast Block Mode Decision Scheme for P- Slices of High profile in H.264/AVC

  • Kim, Jong-Ho;Pahk, Un-Kyung;Kim, Mun-Churl;Choi, Jin-Soo
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.142-147
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    • 2009
  • The recent H.264/AVC video coding standard provides a higher coding efficiency than previous standards. H.264/AVC achieves a bit rate saving of more than 50 % with many new technologies, but it is computationally complex. Most of fast mode decision algorithms have focused on Baseline profile of H.264/AVC. In this paper, a fast block mode decision scheme for P- slices in High profile is proposed to reduce the computational complexity for H.264/AVC because the High profile is useful for broadcasting and storage applications. To reduce the block mode decision complexity in P- pictures of High profile, we use the SAD value after $16{\times}16$ block motion estimation. This SAD value is used for the classification feature to divide all block modes into some proper candidate block modes. The proposed algorithm shows average speed-up factors of 47.42 ${\sim}$ 67.04% for IPPP sequences.

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시공간적 계층 메모리 학습 알고리즘을 이용한 근전도 패턴인식 (Electromyogram Pattern Recognition by Hierarchical Temporal Memory Learning Algorithm)

  • 성무중;추준욱;이승하;이연정
    • 한국지능시스템학회논문지
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    • 제19권1호
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    • pp.54-61
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    • 2009
  • 본 논문에서는 비전 패턴인식 알고리즘인 시공간적 계층 메모리 학습 알고리즘을 이용한 새로운 근전도 패턴인식 방법을 제시한다. 효율적인 근전도 신호의 학습과 분류를 위하여 단순화된 2 레벨의 공간적 집합, 시간적 집합, 그리고 관리 맵퍼를 이용한 수정된 시공간적 계층 메모리 학습 알고리즘을 제안한다. 인식 성능을 향상시키기 위해서 관리 맵퍼 학습뿐만 아니라 시간적 집합 학습에도 카테고리 정보를 사용한다. 실험을 통하여 열 가지 손동작이 성공적으로 인식됨을 검증한다.

상지형태와 의복소매에 관한 인간공학적 연구 (제1보) (Ergonomic studies of arm shapes and sleeve: Classification of arm shapes)

  • 함옥상;조경애
    • 대한인간공학회지
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    • 제16권1호
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    • pp.29-45
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    • 1997
  • This study aims at designing sleeves which are suitable for arm shapes and arm movements. With the samples of of ordinary 24 women aged from 20 to 22, the arm shapes and movements were measured 3-dimensionally using a motion analyzer and a sonic digitizer, and then clasified into three characteristic types (A, B, and C). Our analysis leads to the following conclusion. The factors classifying arm shapes are the length from acromion to posterior armpit point, arm hole length, the cap height, difference in height between anterior and posterior armpit points, armhole circumference, upper arm circumferemce, armhole depth, and underarm circumference. The characteristics of arm type A is that the armhole depth and the length from acromion to posterior armpit point are the largest, while the circumference inbe- tween upper arm and elbow is the smallest among the three arm types. Thus, the large circumference difference between upper and lower arms is the most notable in arm type A. The factors classifying arm shapes for arm type B are the smallest except for the circumference inbetween upper arm and elbow which is larger than that for arm type A. The circumference difference betweemn upper and lower arms is small for arm type B. Arm type C has the smallest armhole depth, while other factors are similar to those for arm type B. In type C, the size of upper arm is comparatively small on the frontal plane, while it is the largest on the sagital plane.

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Real-time structural damage detection using wireless sensing and monitoring system

  • Lu, Kung-Chun;Loh, Chin-Hsiung;Yang, Yuan-Sen;Lynch, Jerome P.;Law, K.H.
    • Smart Structures and Systems
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    • 제4권6호
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    • pp.759-777
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    • 2008
  • A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

BWIM방법을 이용한 차량 정보 추정시 정밀도 향상 방안에 관한 연구 (A Study on Accuracy Improvement for Estimation of Vehicle Information Using BWIM Methodology)

  • 황효상;경갑수;이희현;전준창
    • 한국안전학회지
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    • 제28권1호
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    • pp.63-73
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    • 2013
  • Dynamic strain history curve measured in the field is influenced by various factors such as vehicle type, speed, noise, temperature and running location etc.. Because such curve is used for vehicle weight estimation methodology suggested by Moses, exact strain history curve is the most important thing for exact estimation of vehicle weight. In this paper, effect of such factors mentioned above is investigated on the measured strain history curves, and results of weight estimation of vehicles are discussed quantitatively. From this study, it was known that temperature effect contained in the strain history curve measured for long time in-site gives the biggest effect on result of weight estimation and it can be removed by using the mode value. Furthermore, gross vehicle weight can be estimated within 5% error corresponding to A class of the European classification if effects of temperature and noise are removed and vehicle properties such as speed, axle arrangement and running location are considered properly.

V-형 선형 초음파 모터의 구동 특성 (Driving Characteristic of Ultrasonic Linear Motor with V-type)

  • 정성수;서산동;박태곤
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
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    • pp.274-275
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    • 2006
  • A linear ultrasonic motor was designed by a combination of the longitudinal and bending mode. Linear ultrasonic motors are based on an elliptical motion on the surface of elastic body, such as bar or plates. The corresponding eigen-mode of one resonance frequency can be excited twice at the same time with a phase shift of 90 degrees in space and time. That is excite symmetric and anti-symmetric modes. Then it determines the thrust and speed of the motor. Linear ultrasonic motors are investigated experimentally in according to be fabricated a general classification to motor structure and material characteristic. There was the first to simulate as use of finite element analysis ANSYS 9.0. The AL-T2W8-ARM14-LEG18-ANGLE80 motor has a maxim efficiency 17 [%] under the speed 0.14 [m/s], thrust 345 [gf] and preload 280 [gf], operating frequency is 57.6 [kHz].

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의수 제어용 동작 인식을 위한 웨어러블 밴드 센서 (Wearable Band Sensor for Posture Recognition towards Prosthetic Control)

  • 이슬아;최영진
    • 로봇학회논문지
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    • 제13권4호
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    • pp.265-271
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    • 2018
  • The recent prosthetic technologies pursue to control multi-DOFs (degrees-of-freedom) hand and wrist. However, challenges such as high cost, wear-ability, and motion intent recognition for feedback control still remain for the use in daily living activities. The paper proposes a multi-channel knit band sensor to worn easily for surface EMG-based prosthetic control. The knitted electrodes were fabricated with conductive yarn, and the band except the electrodes are knitted using non-conductive yarn which has moisture wicking property. Two types of the knit bands are fabricated such as sixteen-electrodes for eight-channels and thirty-two electrodes for sixteen-channels. In order to substantiate the performance of the biopotential signal acquisition, several experiments are conducted. Signal to noise ratio (SNR) value of the knit band sensor was 18.48 dB. According to various forearm motions including hand and wrist, sixteen-channels EMG signals could be clearly distinguishable. In addition, the pattern recognition performance to control myoelectric prosthesis was verified in that overall classification accuracy of the RMS (root mean squares) filtered EMG signals (97.84%) was higher than that of the raw EMG signals (87.06%).

Floating Gas Power Plants

  • Kim, Hyun-Soo
    • 한국산업융합학회 논문집
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    • 제23권6_1호
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    • pp.907-915
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    • 2020
  • Specification selection, Layout, specifications and combinations of Power Drives, and Ship motions were studied for FGPP(Floating Gas-fired Power Plants), which are still needed in areas such as the Caribbean, Latin America, and Southeast Asia where electricity is not sufficiently supplied. From this study, the optimal equipment layout in ships was derived. In addition, the difference between engine and turbine was verified through LCOE(Levelized Cost of Energy) comparison according to the type and combination of Power Drives. Analysis of Hs(Significant Height of wave) and Tp(spectrum Peak Period of wave) for places where this FGPP will be tested or applied enables design according to wave characteristics in Brazil and Indonesia. Normalized Sloshing Pressures of FGPP and LNG Carrier are verified using a sloshing analysis program, which is CFD(Computational Fluid Dynamics) software developed by ABS(American Bureau of Shipping). Power Transmission System is studied with Double bus with one Circuit Breaker Topology. A nd the CFD analysis allowed us to calculate linear roll damping coefficients for more accurate full load conditions and ballast conditions. Through RAO(Response Amplitude Operator) analysis, we secured data that could minimize the movement of ships according to the direction of waves and ship placement by identifying the characteristics of large movements in the beam sea conditions. The FGPP has been granted an AIP(Approval in Principle) from a classification society, the ABS.

Significant radiologic factors related to clinical outcomes after arthroscopic rotator cuff retear repair

  • Joo, Min-Su;Kim, Jeong-Woo
    • Clinics in Shoulder and Elbow
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    • 제25권3호
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    • pp.173-181
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    • 2022
  • Background: Healing of the tendon itself is not always related to successful clinical outcomes after rotator cuff repair. It was hypothesized that certain radiologic factors affecting clinical outcomes could exist in case of the retear after arthroscopic rotator cuff repair (ARCR) and the radiologic factors could help predict clinical process. The purpose of this study was to identify the radiologic factors associated with clinical outcomes of the retear after ARCR. Methods: Between January 2012 and December 2019, among patients with sufficient footprint coverage for ARCR, 96 patients with Sugaya classification 4 or higher retear on follow-up magnetic resonance imaging were included. The association between clinical outcomes such as American Shoulder and Elbow Surgeons (ASES) score, Constant score and range of motion and radiologic variables such as initial tear dimension, retear dimension, variance of tear dimension, critical shoulder angle, acromial index, and acromiohumeral distance was analyzed. Results: Preoperatively, the ASES and Constant scores were 59.81±17.02 and 64.30±15.27, respectively. And at the last follow-up, they improved to 81.56±16.29 and 78.62±14.16, respectively (p<0.01 and p<0.01). In multiple linear regression analysis, the variance of the mediolateral dimension of tear had statistically significant association with the ASES and Constant scores (p<0.01 and p=0.01). Conclusions: In patients with the retear after ARCR, the variance in the mediolateral dimension of tear had significantly negative association with the clinical outcomes. This could be considered to be reference as relative criteria and needed more sample and mechanical study.

인공지능 기반의 스마트 센서 기술 개발 동향 (Recent Progress of Smart Sensor Technology Relying on Artificial Intelligence)

  • 신현식;김종웅
    • 마이크로전자및패키징학회지
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    • 제29권3호
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    • pp.1-12
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    • 2022
  • 인공지능 기술의 급속한 발전으로 기존 센서에 인간의 지능과 유사한 기능을 부여하기 위한 연구가 큰 주목을 받고 있다. 기존에는 주로 센서로써의 기초 성능지표, 예를 들어 감도 및 속도 등을 향상시키기 위한 연구가 주로 진행되었지만, 최근에는 분류나 예측 등의 인공지능을 센서에 결합하기 위한 시도가 확대되고 있다. 이를 바탕으로 최근 질병 감지 센서, 모션 감지 센서 및 가스 센서 등 거의 센서 전 분야에서 지능형 센서에 대한 연구 결과가 활발히 보고되고 있다. 본 논문에서는 인공지능의 기본적인 개념, 종류 및 메커니즘과 더불어, 최근 보고된 지능형 센서에의 적용 사례에 대해 알아보고자 한다.