• Journal of Korea Game Society
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• v.18 no.5
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• pp.123-132
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• 2018

Various methods have been proposed to efficiently animate the motion of soft objects in realtime. In order to maintain the topology between the elements of the objects, it is required to employ constraint forces, which limit the size of the time steps for the numerical integration and reduce the efficiency. To tackle this, an implicit method with larger steps was proposed. However, the method is, in essence, a linear system with a large matrix, of which solution requires heavy computations. Several approximate methods have been proposed, but the approximation is obtained with an increased damping and the loss of accuracy. In this paper, new integration method based on harmonic oscillation with better stability was proposed, and it was further stabilized with the hybridization with approximate implicit method. GPU parallelism can be easily implemented for the method, and large-scale soft objects can be simulated in realtime.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.1
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• pp.88-93
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• 2015

To estimate RCS(Radar Cross Section) at arbitrary incident angles for large objects, an interpolation method is required based on the pre-calculated RCS database at finite discrete sampling points. It is numerically difficult to compute the RCS by a large object at all required sampling points, since the computation time may be very long for one sampling point and many sampling points are required to satisfy the exact sampling condition. Therefore, it may be required to accurately estimate the RCS at any incident angles based on a database whose size is as small as possible. In this paper, the accuracy of two interpolation methods base on the sinc-and VSH(Vector Spherical Harmonics) functions are numerically compared.

• The Journal of Korean Physical Therapy
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• v.6 no.1
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• pp.121-132
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• 1994

This study was carried out to know the change of age-related hand function. 210 adults without neurosurgical and orthopedic disability from 15 to 90 years of age participation this study voluntarily. The results are as followings. 1. The hand function decreased according to age increasing. 2. The dominant and non-dominant hand function was decreased in ever-sixty age groups in the subtests of writing, card turning small common objects, simulated feeding, large light objects and large heavy objects greatly, but decreased between forty and fifty age groups in checkers greatly. 3. The dominant hand function was more excellent than non-dominant hand. 4. The dominant and non-dominant hand function was statistically significant between age groups(p<0.01). 5. The one-way ANOVA of subtests according to age increasing revealed significant statistically(p<0.01). 6. The correlation coefficients between subtests and age increasing revealed significant statistically in the dominant and non-dominant hand(p<0.01).

• Current Optics and Photonics
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• v.6 no.6
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• pp.619-626
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• 2022

In this study, we develop a three-dimensional (3D) terahertz time-of-flight (THz-TOF) imaging technique with a large depth range, based on asynchronous optical sampling (ASOPS) methods. THz-TOF imaging with the ASOPS technique enables rapid scanning with a time-delay span of 10 ns. This means that a depth range of 1.5 m is possible in principle, whereas in practice it is limited by the focus depth determined by the optical geometry, such as the focal length of the scan lens. We characterize the spatial resolution of objects at different vertical positions with a focal length of 5 cm. The lateral resolution varies from 0.8-1.8 mm within the vertical range of 50 mm. We obtain THz-TOF images for samples with multiple reflection layers; the horizontal and vertical locations of the objects are successfully determined from the 2D cross-sectional images, or from reconstructed 3D images. For instance, we can identify metallic objects embedded in insulating enclosures having a vertical depth range greater than 30 mm. For feasible practical use, we employ the proposed technique to locate a metallic object within a thick chocolate bar, which is not accessible via conventional transmission geometry.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.73-81
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• 2024

Recently, mobile manipulators have been utilized in agriculture industry for weed removal and harvest automation. This paper proposes a domain adaptive fruit detection method for harvest automation, by utilizing OWL-ViT model which is an open-vocabulary object detection model. The vision-language model can detect objects based on text prompt, and therefore, it can be extended to detect objects of undefined categories. In the development of deep learning models for real-world problems, constructing a large-scale labeled dataset is a time-consuming task and heavily relies on human effort. To reduce the labor-intensive workload, we utilized a large-scale public dataset as a source domain data and employed a domain adaptation method. Adversarial learning was conducted between a domain discriminator and feature extractor to reduce the gap between the distribution of feature vectors from the source domain and our target domain data. We collected a target domain dataset in a real-like environment and conducted experiments to demonstrate the effectiveness of the proposed method. In experiments, the domain adaptation method improved the AP50 metric from 38.88% to 78.59% for detecting objects within the range of 2m, and we achieved 81.7% of manipulation success rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.401-410
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• 2007

In this paper, we propose water quality monitoring system using vision camera and multiple objects tracking method. The proposed system analyzes object individually using vision camera unlike monitoring system using sensor method. The system using vision camera consists of individual object segmentation part and objects tracking part based on interrelation between successive frames. For real-time processing, we make background image using non-parametric estimation and extract objects using background image. If we use non-parametric estimation, objects extraction method can reduce large amount of computation complexity, as well as extract objects more effectively. Multiple objects tracking method predicts next motion using moving direction, velocity and acceleration of individual object then carries out tracking based on the predicted motion. And we apply exception handling algorithms to improve tracking performance. From experiment results under various conditions, it shows that the proposed system can be available for real-time water quality monitoring system since it has very short processing time and correct multiple objects tracking.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.500-503
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• 1989

Our work is an attempt to recognize objects without a rigid ordering of steps and with fuller use of previous results as analysis proceeds. We assume that the difference in brightness between the objects and the background is large enough to detect the background boundaries easily. Lines are mostly proposed insted of found by exhaustive search in the scne, the program is relatively efficient.

• Proceedings of the ESK Conference
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• 1996.10a
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• pp.197-205
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• 1996

Unification of neural network with a hierarchical pattern recognition is presented for recognizing large set of objects. A two-step identification procedure is developed for pattern recognition: coarse and fine identification. The coarse identification is designed for finding a class of object while the fine identification procedure is to identify a specific object. During the training phase a course neural network is trained for clustering larger set of reference objects into a number of groups. For training a fine neural network, expert neural network is also trained to identify a specific object within a group. The presented idea can be interpreted as two step identification. Experimental results are given to verify the proposed methodology.

• Journal of The Korean Astronomical Society
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• v.38 no.2
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• pp.173-174
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• 2005

On behalf of the IRSF/SIRIUS group, I introduce some recent results from our deep near-infrared surveys (J, Hand Ks bands, limiting magnitude of Ks=17) toward star forming regions in the Milky Way Galaxy (MWG) and Large Magellanic Cloud (LMC) with the near-infrared camera SIRIUS. We discovered a rich population of low-mass young stellar objects associated with the W3 and NGC 7538 regions in the MWG based on the near-infrared colors arid magnitudes. The high sensitivity of our survey enables us to detect intermediate-mass pre-main sequence stars, i.e. HAEBE stars, even in the LMC. We detected many HAEBE candidate stars in the N159/N160 complex star forming region in the LMC with the IRSF 1.4-m telescope. Spatial distributions of the young stellar objects indicate the sequential cluster formation in each star forming region in the complex and large scale (a few ${\times}$ 100 pc) sequential cluster formation over the entire complex.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.2 s.95
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• pp.68-73
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• 1999

Generally, most of machining processes are done according to the dimention of the draft made by CAD. However, there are many cases that a sample is given without the draft because of the simplicity of the shape in the machining of 2D objects. To cut the same shape as the given sample, this paper proposes the method to extract the geometric information about a large sample using the robot vision and to draw the demensional draft for the machining. Because the resolution of one frame in the vision system is too low, it is necessary to set up a camera according to the desired resolution and to capture the image moving along the contour. And the overall outline can be compounded of the sequentially captured images. In the experiment, we compared the product after the cutting with the original sample and found that the size of two objects was coincided within the allowed error bound.