• Journal of Korea Multimedia Society
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• v.5 no.2
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• pp.198-205
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• 2002

Most studies of the ARQ schemes are conducted under the limited error rate of a fairly stationary channel. In nonstationary channel, error rates vary considerably and variety of error rate is wide. This paper proposes an effective Stop-and-Wait ARQ scheme which estimates the channel state in a simple manner based on the received acknowledgement messages, and can adaptively switch its operation mode in a channel where error rates vary slowly. It provides higher throughput than other comparable Stop-and-Wait ARQ schemes under a wide variety of error rate conditions.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.591-598
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• 2021

One of the requirements of metro trains is to stop with precision to ensure that the train can stop precisely at the designated location on the platform. If this is not satisfied, interference with the screen door occurs, causing inconvenience to passengers and delays in operation. In the case of an automatic operated train, the current position is determined by the current speed information of the train, and control is performed by issuing an acceleration/deceleration command. Therefore, accurate control becomes impossible if the error of the speed information is large. In metro railroads, a Precision Stop Marker (PSM) is used to correct the position error, so that the error of stop control can be reduced by correcting the position error at a specific point. On the other hand, because the PSM itself has only position information, it does not compensate for the speed error. This paper proposes a method for performing in-place stop control by estimating the speed with the PSM progress information. The speed can be estimated when the train is operated at a constant deceleration speed, and the target deceleration can be obtained to perform stop control. The feasibility and excellence of the proposed method are shown through a numerical simulation.

• The Journal of Information Technology
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• v.8 no.3
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• pp.105-115
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• 2005

The CMA and MMA blind equalization algorithm has the inevitable large residual error caused by mismatching between the symbol constellation at a steady state after convergence. Stop-and-Go algorithm has a very superior residual error characteristics at a steady state but a relatively slow convergence characteristics. In this paper, we propose a SAG-Flagged MMA as a new adaptive blind equalization algorithm with a Stop-and-Go flag which follows a flagged MMA in update scheme of tap weights as appling the flag obtaining from Stop-and-Go algorithm to MMA. Using computer simulation, it is confirmed that the proposed algorithm has an enhancing performance from the viewpoint of residual ISI, residual error and convergence speed in comparison with MMA and Stop-and-Go algorithm. Algorithm has a new error function using the decided original constellation instead of the reduced constellation. By computer simulation, it is confirmed that the proposed algorithm has the performance superiority in terms of residual ISI and convergence speed compared with the adaptive blind equalization algorithm of CMA family, Constant Modulus Algorithm with Carrier Phase Recovery and Modified CMA(MCMA).

• Korean Journal of Construction Engineering and Management
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• v.13 no.2
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• pp.110-119
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• 2012

The Plan and equipment of vertical lifting are very important in high-rise building construction site, and unmanned lifts usage is increasing for financial and efficient reason. However if lift stop position error occur, It can be accumulated. And the lift can not be available during an engineer fix the problem. So loss of time and cost will occur when lifts have problems. This paper reports an improved lift stop position sensing device for preventing loss of time and cost from lift stop position error. The result of tests showed that the system has a correction function of lift stop position error, and the accuracy of device which was developed in this paper was about 9.75mm better than existing equipment.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.205-215
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• 2012

A GPS sensor is widely used in many areas such as navigation, or air traffic control. Particularly, the car navigation system is equipped with GPS sensor for locational information. However, when a car goes through a tunnel, forest, or built-up area, GPS receiver cannot get the enough number of satellite signals. In these situations, a GPS receiver does not reliably work. A GPS error can be formulated by sum of bias error and sensor noise. The bias error is generated by the geometric arrangement of satellites and sensor noise error is generated by the corrupted signal noise of receiver. To enhance GPS sensor accuracy, these two kinds of errors have to be removed. In this research, we make the road database which includes Road Database File (RDF). RDF includes road information such as road connection, road condition, coordinates of roads, lanes, and stop lines. Among the information, we use the stop line coordinates as a feature point to correct the GPS bias error. If the relative distance and angle of a stop line from a car are detected and the detected stop line can be associated with one of the stop lines in the database, we can measure the bias error and correct the car's location. To remove the other GPS error, sensor noise, the Kalman filter algorithm is used. Additionally, using the RDF, we can get the information of the road where the car belongs. It can be used to help the GPS correction algorithm or to give useful information to users.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.5
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• pp.143-152
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• 1994

The velocity trajectory profile of trolley is designed to minimize both swinging while transportation of load and the stop position error at the final stop position. This profile is designed to be automatically programmed by the digital control algorithm when the length of chain and the desired travel distance are given as a priori. Also, to minimize both swinging and the stop position error the anti-swing controller which improves poor damping characteristics of the crane and the stop position controller are employed. The experimentalresults of sequential adaptation of the velocity trajectory profile and these two controllers show that this control scheme has excellent control performance as compared with that of the uncontrolled crane system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1074-1081
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• 2000

In this paper, in order to speed up the convergence process and improve the steady mean square error simultaneously, we propose the Stop-and-Go Dual Mode Modified Constant Modulus Algorithm(SAG DM MCMA) for adaptive blind channel equalization of high order QAM. The proposed algorithm is a hybrid scheme of the Modified CMA that treat error signals with real and imaginary components of the equalizer output, the concept of dual mode CMA, and Stop-and-Go algorithm. As a result it can prevent blind equalization from converging to incorrect direction and simultaneously operates reliably for tap weight adaptation. We demonstrate via simulation that the proposed algorithm achieves lower steady state mean square error and residual ISI than the conventional algorithms under high order QAM signals and severe channel environment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.1
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• pp.30-37
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• 2001

The purpose of this study is to present the method to determine the optimal stop time of HVAC using Artificial Neural Network model, one of the learning methods. For this, the performance of determining the stop time of HVAC for unexperienced learning data was evaluated, and time interval for measurement of input data and permissible error needed for practical application of ANN model were presented using the results of daily simulation.

• International Journal of Air-Conditioning and Refrigeration
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• v.13 no.1
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• pp.22-30
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• 2005

The purpose of this study is to present a method to determine the optimal stop time of HVAC using the Artificial Neural Network model, which is one of the learning methods. For this, the performance of determining the stop time of HVAC for unexperienced learning data was evaluated, and time interval for measurement of input data and permissible error needed for practical application of ANN model were presented using the results from daily simulation.

• The Journal of the Acoustical Society of Korea
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• v.15 no.6
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• pp.33-40
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• 1996

In this paper, we resolved a trade-off problem of the blind equalizer based on the stop-and-go algorithm that is commonly used for QAM demodulation in CATV receiver. The stop-and-go algorithm has used the LMS(least mean square) algorithm in the updating operation of tap weights so that the structure of equalizer is simple, but there is a trade-off between convergence speed and steady state error as in the typical LMS algorithm. We used the variable step size algrithm to improve the convergence speed with the steady state error in the constant level. With respect to the same level of the steady state error, the variable step size stop-and-go algortihm improved convergence speed by about $36%{\sim}56%$ as compared with that of the constant step size algortihm.