• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2006년도 추계 학술발표회 논문집
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• pp.353-356
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• 2006

In this paper, the prediction method of internal temperature for reinforced concrete columns under high temperature is presented. Finite element method is employed to facilitate thermal analysis for any position of column. And the effect of the heat of vaporization is applied. To demonstrate the validity of this numerical procedure, the prediction by the proposed algorithm is compared with the test results from this study. The proposed algorithm is in good agreement with experimental results.

• 한국정밀공학회지
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• 제15권7호
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• pp.175-181
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• 1998

This paper describes realtime visual tracking system of moving object for three dimensional target using EKF(Extended Kalman Filter). We present a new realtime visual tracking using EKF algorithm and image prediction algorithm. We demonstrate the performance of these tracking algorithm through real experiment. The experimental results show the effectiveness of the EKF algorithm and image prediction algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.39-42
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• 2005

H.264, a recently proposed international video coding standard, has adopted context-based adaptive variable length coding (CAVLC) as the entropy coding tool in the baseline profile. By combining an adaptive variable length coding technique with context modeling, we can achieve a high degree of redundancy reduction. However, CAVLC in H.264 has weakness that the correct prediction rate of the variable length coding (VLC) table is low in a complex area, such as the boundary of an object. In this paper, we propose a VLC table prediction scheme considering multiple reference blocks; the same position block of the previous frame and the neighboring blocks of the current frame. The proposed algorithm obtains the new weighting values considering correctness of the VLC table for each reference block. Using this method, we can enhance the prediction rate of the VLC table and reduce the bit-rate.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권3호
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• pp.98-109
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• 2006

Fire control system(FCS) errors can be classified as hardware errors, filter prediction errors, effective ballistic function errors, and aiming errors. Among these errors, the filter prediction errors are the most significant error sources. To reduce them, a target future position calculation method using the acceleration estimate is suggested and it is compared with the constant velocity target prediction method. Simulation results show that the suggested method has better performance than the constant velocity prediction method. Target tracking algorithm is established with multiple target tracking filters based on IMM structure.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.191-196
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• 2006

In GPS Positioning, the error of satellite orbit will affect user's position accuracy directly, it is important to determine the satellite orbit precise. The real-time orbit is needed in kinematic GPS positioning, the precise GPS orbit from IGS would be delayed long time, so orbit prediction is key to real-time kinematic positioning. We analyze the GPS predicted ephemeris, on the base of comparison of EKF and UKF, a new orbit prediction method is put forward based on UKF in this paper, the result shows that UKF improves the orbit predicted precision and stability. It offers a new method for others satellites orbit determination as Galileo, and so on.

• International journal of advanced smart convergence
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• 제7권4호
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• pp.27-39
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• 2018

Since the global positioning system (GPS) has been included in mobile devices (e.g., for car navigation, in smartphones, and in smart watches), the impact of personal GPS log data on daily life has been unprecedented. For example, such log data have been used to solve public problems, such as mass transit traffic patterns, finding optimum travelers' routes, and determining prospective business zones. However, a real-time analysis technique for GPS log data has been unattainable due to theoretical limitations. We introduced a machine learning model in order to resolve the limitation. In this paper presents a new, three-stage real-time prediction model for a person's daily route activity. In the first stage, a machine learning-based clustering algorithm is adopted for place detection. The training data set was a personal GPS tracking history. In the second stage, prediction of a new person's transient mode is studied. In the third stage, to represent the person's activity on those daily routes, inference rules are applied.

• 한국연초학회지
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• 제11권2호
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• pp.115-126
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• 1989

This study was conducted to determine the time and methods of predicting tobacco yield, by studying the relationship of yield components to yield. 1. The relationship between each position in leaf dry weight and approached gradually each other and also correlation coefficient of top leaf was higher than that of lower leaf. The leaf dry weight per plant was highly correlated with leaf area from 16th leaf position on stalk. Leaf dry weight of each leaf position on stalk was highly correlated with leaf dry weight per plant at 14 to 16th leaf position. 2. The correlation coefficient between leaf dry weight and leaf area per plant was higher at the late growth stage than at the early growth stage, and higher between the near stages. Correlation coefficient between leaf dry weights was higher than that of leaf areas. 3. Flue-cured tobacco yield be estimated from leaf dry weight per plant at 50 to 55 days after transplanting. 4. Air-cured tobacco yield could be predicted from leaf dry weight per plant at 60 days after transplanting.

• 한국항행학회논문지
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• 제5권1호
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• pp.26-36
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• 2001

시 변환 영상에서 가장 중요한 문제 중의 하나는 자동 목표 추적이다. 본 논문에서는 퍼지 예측을 이용한 이동물체의 위치예측 및 추적 기법을 제안한다. 먼저, 누적 차영상을 이용하여 물체와 배경을 분리한 다음 이동물체를 추출한다. 그리고 추출된 물체에 무게 중심법을 이용하여 물체의 중심점을 추출하고 추출된 물체에 가변 크기 탐색창을 사용하여 추적 성능을 높일 수 있는 기법을 제안한다. 또한 효율적인 물체 추적을 위한 조건으로 비선형적인 예측이 필요한데 본 논문에서는 다음 프레임에서의 물체의 위치를 예측하기 위해 퍼지 예측 방법을 제안한다. 실험을 통해 제안된 퍼지 예측 시스템이 여러 상황하에서 이동물체를 안정적으로 추적함을 보인다.

• 로봇학회논문지
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• 제11권4호
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• pp.277-284
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• 2016

A new prediction scheme has been proposed for the robust teleoperation in a non-visible environment. The positioning error caused by the time delay in the non-visible environment has been compensated for by the Smith predictor and the sensory data have been estimated by the Grey model. The Smith predictor is effective for the compensation of the positioning error caused by the time delay with a precise system model. Therefore the dynamic model of a mobile robot has been used in this research. To minimize the unstable and erroneous states caused by the time delay, the estimated sensor data have been sent to the operator. Through simulations, the possibility of compensating the errors caused by the time delay has been verified using the Smith predictor. Also the estimation reliability of the measurement data has been demonstrated. Robust teleoperations in a non-visible environment have been performed with a mobile robot to avoid the obstacles effective to go to the target position by the proposed prediction scheme which combines the Smith predictor and the Grey model. Even though the human operator is involved in the teleoperation loop, the compensation effects have been clearly demonstrated.

• 한국가시화정보학회지
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• 제21권1호
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• pp.18-25
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• 2023

In these days, high dimensional data prediction technology based on neural network shows compelling results in many different kind of field including engineering. Especially, a lot of variants of convolution neural network are widely utilized to develop pixel level prediction model for high dimensional data such as picture, or physical field value from the sensors. In this study, velocity vector field of ideal flow on ship surface is estimated on pixel level by Unet. First, potential flow analysis was conducted for the set of hull form data which are generated by hull form transformation method. Thereafter, four different neural network with a U-shape structure were conFig.d to train velocity vectors at the node position of pre-processed hull form data. As a result, for the test hull forms, it was confirmed that the network with short skip-connection gives the most accurate prediction results of streamlines and velocity magnitude. And the results also have a good agreement with potential flow analysis results. However, in some cases which don't have nothing in common with training data in terms of speed or shape, the network has relatively high error at the region of large curvature.