• Physical Therapy Korea
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• v.13 no.4
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• pp.23-29
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• 2006

The purpose of the present study was to examine gaze effects on spatial and kinematic characteristics during a pointing task. Subjects were asked to watch and point to an aimed target (2 mm in diameter) displayed on a vertically mounted board. Four gaze conditions were developed as combinations of "seeing-aiming" in terms of the eye movements: Focal-Focal (F-F), Focal-Fixing (F-X), Fixing-Focal (X-F), and Fixing-Fixing (X-X). Both the home target and an aimed target were presented for 1 second and then were disappeared in F-F and X-F. In X-F and X-X, only an aimed target disappeared after 1 second. Subjects were asked to point (with index finger tip) to an aimed target accurately as soon as the aimed target was removed. A significant main effect of gaze was found (p<.01) for normalized movement time. Peripheral retina targets had significantly larger absolute error compared to central retina targets on the x (medio-lateral) and z (superior-inferior) axes (p<.01). A significant undershooting to peripheral retina targets on the x axis was found (p<.01). F-F and X-F had larger peak velocities compared to F-X and X-X (p<.01). F-F and X-F were characterized by more time spent in the deceleration phase compared to F-X and X-X (p<.01). The present study demonstrates that central vision utilizes a form of on-line visual processing to reach to an object, and thus increases spatial accuracy. However, peripheral vision utilizes a relatively off-line visual processing with a dependency on proprioceptive information.

• The Journal of Korean Society for Radiation Therapy
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• v.21 no.1
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• pp.1-7
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• 2009

Purpose: The purpose is to evaluate the accuracy of correcting the targeting error through the Target Location System (TLS) for the location change error of the reference point which arises from the movement or motion of patient during the treatment using the CyberKnife. Materials and Methods: In this test, Gafchromic MD-55 film was inserted into the head and neck phantom to analyze the accuracy of the targeting, and then the 6 MV X-ray of CyberKnife (CyberKnife Robotic Radiosurgery System G4, Accuray, US) was irradiated. End to End (E2E) program was used to analyze the accuracy of targeting, which is provided by Accuray Corporation. To compute the error of the targeting, the test was carried out with the films that were irradiated 12 times by maintaining the distance within the rage of $0{\pm}0.2\;mm$ toward x, y, z from the reference point and maintaining the angle within the rage of $0{\pm}0.2^{\circ}$ toward roll, pitch, yaw, and then with the films which were irradiated 6 times by applying intentional movement. And the correlation in the average value of the reference film and the test film were analyzed through independent samples t-test. In addition, the consistency of dose distribution through gamma-index method (dose difference: 3%) was quantified, compared, and analyzed by varying the distance to agreement (DTA) to 1 mm, 1.5 mm, 2 mm, respectively. Results: E2E test result indicated that the average error of the reference film was 0.405 mm and the standard deviation was 0.069 mm. The average error of the test film was 0.413 mm with the standard deviation of 0.121 mm. The result of independent sampling t-test for both averages showed that the significant probability was P=0.836 (confidence level: 95%). Besides, by comparing the consistency of dose distribution of DTA through 1 mm, 1.5 mm, 2 mm, it was found that the average dose distribution of axial film was 95.04%, 97.56%, 98.13%, respectively in 3,314 locations of the reference film, consistent with the average dose distribution of sagittal film that was 95.47%, 97.68%, 98.47%, respectively. By comparing with the test film, it was found that the average dose distribution of axial film was 96.38%, 97.57%, 98.04%, respectively, at 3,323 locations, consistent with the average dose distribution of sagittal film which was 95.50%, 97.87%, 98.36%, respectively. Conclusion: Robotic CyberKnife traces and complements in real time the error in the location change of the reference point caused by the motion or movement of patient during the treatment and provides the accuracy with the consistency of over 95% dose distribution and the targeting error below 1 mm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.839-847
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• 2011

This paper proposes a new guidance law for increasing the lethality of munitions. The well known PNG (Proportional Navigation Guidance) is inadequate for the munitions because of some weaknesses. Even if the munition does not have the impact point error, the acceleration command is non zero because the line-of-sight changes at all times in flight. Therefore, we use a difference between a target and an impact point. This proposed guidance law is similar to PNG in the form, but this guidance law concentrates a correction rate of flight path angle instead of the LOS (Line of Sight) rate. The correction of flight path angle is defined as the amount of impact point error. This impact point error can be calculated by neural networks rapidly. Finally, we show that the simulation results prove the suitability of this law.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.11-18
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• 2021

This paper shows the applicability of deep learning algorithm in predicting target position and getting correction value of impact point in order to improve the accuracy of naval gun firing. Predicting target position, the proposed model using LSTM model and RN structure is expected to be more accurate than existing method using kalman filter. Getting correction value of impact point, the another proposed model suggests a reinforcement model that manages factors which is related in ballistic calculation as data set, and learns using the data set. The model is expected to reduce error of naval gun firing. Combining two models, a ballistic calculation model for improving accuracy of naval gun firing based on deep learning algorithm was designed.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.136-142
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• 2007

This paper proposes a new approach on nonlinear maneuvering target tracking. In this paper, proposed algorithm is the Kalman filter based on the adaptive interactive multiple model using the concept of predicted impact point and utilize modified Kalman filter regarding the error between measurement position and predicted impact point. The unknown target acceleration is regarded as an additional process noise to the target model, and each sub-model is characterized in accordance with the valiance of the overall process noise which is obtained on the basis of each acceleration interval. To compensate the decreasing performance of Kalman filter in nonlinear maneuver, we construct optional algorithm to utilize proposed method or Kalman filter selectively. To effectively estimate the acceleration during the target maneuvering, the rapid increase of the noise scale is recognized as the acceleration to be used in maneuvering target's movement equation. And a few examples are presented to show suggested algorithm's executional potential.

• Journal of the Korea Computer Graphics Society
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• v.29 no.1
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• pp.1-11
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• 2023

Deep-learning-based image segmentation is one of the most widely employed lane detection approaches, and it requires a post-process for extracting the key points on the lanes. A general approach for key-point extraction is using a fixed threshold defined by a user. However, finding the best threshold is a manual process requiring much effort, and the best one can differ depending on the target data set (or an image). We propose a novel key-point extraction algorithm that automatically adapts to the target image without any manual threshold setting. In our adaptive key-point extraction algorithm, we propose a line-level normalization method to distinguish the lane region from the background clearly. Then, we extract a representative key point for each lane at a line (row of an image) using a kernel density estimation. To check the benefits of our approach, we applied our method to two lane-detection data sets, including TuSimple and CULane. As a result, our method achieved up to 1.80%p and 17.27% better results than using a fixed threshold in the perspectives of accuracy and distance error between the ground truth key-point and the predicted point.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.819-824
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• 2017

This paper presents a target localization scheme for distributed Multi-input Multi-output(MIMO) radar system using ToA measurements obtained from multiple transmitter and receiver pairs. The proposed method can locate the target from an arbitrary initial point by iteratively finding the Taylor linear approximation equation. The simulation results show that proposed method achieves the better mean square error(MSE) performance than the existing target localization methods, and furthermore, attains Cramer-Rao Lower Bound(CRLB).

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.861-868
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• 2010

This study explored an extended three-dimensional Fitts' law that is more suited for the pointing task than the conventional Fitts' law. The experiments were conducted under the manipulation of the distance to the target, size of the target, and direction of the target's location that can be described by two angles, $\theta1$ and $\theta2$. Considering the starting point as the center of coordinates, $\theta1$ is the angle between the positive z-axis and the target location and $\theta2$ is the angle between the positive y-axis and the projected target location on the x-y plane. From the experimental results, we confirmed that all four variables significantly affect the movement time. As we extended the index of difficulty of the conventional Fitts' model by incorporating $\theta1$ and $\theta2$, we established an extended Fitts' model that showed better accordance with the empirical data than the conventional Fitts' model and 3D Fitts' law of Murata and Iwase, in terms of the $r^2$ and the standard error of the residual between the measured movement time and the predicted value.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.1
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• pp.108-114
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• 2014

This paper describes a method to set an intensity-based initial validation gate for tracking filter while preserves the ability of tracking a target with maximum speed. First, we collected real data set of signal versus distance of an airplane target. And at each data point, we computed maximum distance the target can move. And a function is modeled to expect the maximum moving pixels on the lateral direction based on the intensity of the detected target in IR image sequence. The initial prediction error covariance can be computed using this function to decide the size of the initial validation gate. The simulation results show the proposed method can set the appropriate initial validation gates to track the targets with the maximum speed.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.513-521
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• 2014

If the target error of an estimator at the present time is greater than the coefficient of variation(CV) of the estimator at the previous time, sample size at this point should be decreased. Various papers have researched sample size determination methods using the CV of an estimator at the previous time, variation of population size and target error of the estimator at this time in sampling on successive occasions. We research a new sample size determination method additionally using change of population CV. We compare the proposed method with existing ones in various simulation settings.