• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.421-428
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• 2006

Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.494-497
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• 1994

We propose a novel velocity detection method of moving object based on a speckle pattern on the target surface using a self-mixing laser diode (SMLD). By this measurement, it was confirmed that the speckle signal has its waveform independent of the target velocity, and has its averaged frequency directly proportional to the target velocity. So it will be possible to detect the velocity of the target transversely translating against the laser light beam using a compact measuring system.

• Industry Promotion Research
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• v.5 no.3
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• pp.53-60
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• 2020

This paper describes the role of counselors' transitional object for the therapeutic activation of clients who have lost the function of selfobject based on Heinz Kohut's Self theory. In this study, it was an opportunity to confirm that human beings need self-target throughout their lives. Next, referring to the process of metamorphic internalization, infants return to reality from a fantasy world, experiencing parental limitations due to optimal frustration through self-targeting. The role of a counselor as a transfer target shall ensure that the counsellor establishes an cohesive self-identity and uses the appropriate self-target. And they should empathize with the over-the-topism and flauntism of the physician, and the counselor should be the object of idealization, giving the interviewer the opportunity to be recognized and identified. The counselor may provide the best frustration for the counsellor during the consultation process. When the counselor acknowledges his mistake, the counselor looks at the counselor realistically and builds a healthy self to achieve transformative internalization. If you form an cohesive self to a physician through counseling, you can empathize with others and form a healthy human relationship. Then you can control your emotions and have a vision. And the patient realizes that he or she has no choice but to live by having a relationship with the right person throughout his or her life.

• Industry Promotion Research
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• v.6 no.4
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• pp.39-45
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• 2021

This study presented the role of the counselor's transitional object through literature research, focusing on Winnicott's theory. In the process of development, infants experience anxiety when they move from absolute dependence to relative dependence with their mother. In this way, the counselor's role as an transitional object buffers separation anxiety and depressive anxiety about the loss experience, and mediates from the omnipotent fantasy to the real world. transitional objects are new objects and have a function of contributing to adaptation in reality. And it leads to the stage of separation and individualization through transitional object and transitional phenomena. It can be said that he acquires a sense of the real other that exists in order to create and destroy omnipotent, and to adapt to reality. A good enough mother makes the child's omnipotence meaningful. In this case, the true self helps the infant's weak self to grow and lead him to live his own life. When the mother fails to satisfy the infant's needs, her fantasies and spontaneous impulses are lacking. In other words, when the mother fails to reflect the infant's needs, the infant looks at her mother's mood, giving up her true self and creating a false self. The pathology of the absolute dependence phase is caused by the failure of a good enough mother's empathy and nurturing environment. At this time, the child experiences the collapse of the omnipotence illusion and experiences annihilation anxiety. Therefore, effective counseling can be carried out when providing a comfortable and stable environment by reducing separation anxiety and depressive anxiety of clients through the role of the counselor's transitional object in the counseling field.

• Journal of KIISE:Software and Applications
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• v.33 no.9
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• pp.741-750
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• 2006

In this paper, we propose a method for reconstructing a 3D object (or a set of objects) from a 2D drawing provided by a designer. The input 2D drawing consists of a set of contours that may partially overlap each other or be self-overlapping. Accordingly, the resulting 3D object(s) may occlude each other or be self-occluding. The proposed method is composed of three major steps: 2D contour analysis, 3D skeleton computation, and 3D object construction. Our main contribution is to compute the 3D skeleton from the self-intersecting 2D counterpart. We formulate the 3D skeleton construction problem as a sequence of optimization problems, to shape the skeleton and place it in the 3D space while satisfying C1-continuity and intersection-free conditions. Our method is mainly for a silhouette-based sketching interface for the design of 3D objects including self-intersecting objects.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.19-28
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• 2022

In this paper, we propose the Detector Scheduler which determines the best tracking-by-detection (TBD) mechanism to perform real-time high-accurate multi-object tracking (MOT). The Detector Scheduler determines whether to run a detector by measuring the dissimilarity of features between different frames. Furthermore, we propose a self-supervision method to learn the Detector Scheduler with tracking results since it is difficult to generate ground truth (GT) for learning the Detector Scheduler. Our proposed self-supervision method generates pseudo labels on whether to run a detector when the dissimilarity of the object cardinality or appearance between frames increases. To this end, we propose the Detector Scheduling Loss to learn the Detector Scheduler. As a result, our proposed method achieves real-time high-accurate multi-object tracking by boosting the overall tracking speed while keeping the tracking accuracy at most.

• Journal of IKEEE
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• v.18 no.4
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• pp.636-644
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• 2014

This paper is to technically implement the sensing platform for Home-Wellness Robot. First, self-localization technique is based on a smart home and object in a home environment, and IOT(Internet of Thing) between Home Wellness Robots. RF tag is set in a smart home and the absolute coordinate information is acquired by a object included RF reader. Then bluetooth communication between object and home wellness robot provides the absolute coordinate information to home wellness robot. After that, the relative coordinate of home wellness robot is found and self-localization through a stereo camera in a home wellness robot. Second, this paper proposed fuzzy control methode based on a vision sensor for approach object of home wellness robot. Based on a stereo camera equipped with face of home wellness robot, depth information to the object is extracted. Then figure out the angle difference between the object and home wellness robot by calculating a warped angle based on the center of the image. The obtained information is written Look-Up table and makes the attitude control for approaching object. Through the experimental with home wellness robot and the smart home environment, confirm performance about the proposed self-localization and posture control method respectively.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.425-430
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• 2022

As robots are considered one of the mainstream digital transformations, robots with machine vision becomes a main area of study providing the ability to check what robots watch and make decisions based on it. However, it is difficult to find a small object in the image mainly due to the flaw of the most of visual recognition networks. Because visual recognition networks are mostly convolution neural network which usually consider local features. So, we make a model considering not only local feature, but also global feature. In this paper, we propose a detection method of a small marker on the object using deep learning and an algorithm that considers global features by combining Transformer's self-attention technique with a convolutional neural network. We suggest a self-attention model with new definition of Query, Key and Value for model to learn global feature and simplified equation by getting rid of position vector and classification token which cause the model to be heavy and slow. Finally, we show that our model achieves higher mAP than state of the art model YOLOr.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.281-288
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• 2006

Recent increase in the number of pixels of a non-metric digital camera encourages to use it for close-range photogrammetry such as modeling cultural asset and buildings. However, these cameras have to be calibrated far close-range photogrammetry application. For self-calibration, an appropriate pbotograrnmetric network and object field should be designed. In this paper, we studied the effect on self-calibration accuracy changes according to the change of the number of ground control points, dimensions of the ground control points, and the combination of images. We concluded that self-calibration with three photos including a vertical photo can give the stable accuracy of interior orientation parameters and 10 ground control points on a plane can give high accuracy for object reconstruction.

• Journal of Sensor Science and Technology
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• v.3 no.2
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• pp.57-64
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• 1994

This paper describes the measurement of tissue blood flow by the the self-mixing effect of laser diode. A Laser doppler signals due to the moving object and the tissue blood flow were detected by the self-mixing effect of laser diode. The Doppler shifted frequency was changed linearly with the driving frequency of moving object and was increase after the exercise. The results of in-vivo experiment were consistent with the result of exercise physiology.