• Journal of Korea Multimedia Society
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• v.15 no.3
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• pp.323-335
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• 2012

In this paper, we propose an AR(augmented reality) system using user's bare hand based on computer vision. It is important for registering a virtual object on the real input image to detect and track correct feature points. The AR systems with markers are stable but they can not register the virtual object on an acquired image when the marker goes out of a range of the camera. There is a tendency to give users inconvenient environment which is limited to control a virtual object. On the other hand, our system detects fingertips as fiducial features using adaptive ellipse fitting method considering the geometric characteristics of hand. It registers the virtual object stably by getting movement of fingertips with determining the shortest distance from a palm center. We verified that the accuracy of fingertip detection over 82.0% and fingertip ordering and tracking have just 1.8% and 2.0% errors for each step. We proved that this system can replace the marker system by tacking a camera projection matrix effectively in the view of stable augmentation of virtual object.

• Research in Community and Public Health Nursing
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• v.30 no.4
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• pp.449-459
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• 2019

Purpose: The aim of this study is to explore different types of self-rated health trajectories among one-person households in Korea. Methods: We used five time-point data derived from Korea Health Panel (2011~2015). A latent growth curve modeling was used to assess the overall feature of self-rated health trajectory in one-person households, and a latent class growth modeling was used to determine the number and shape of trajectories. We then applied multinomial logistic regression on each class to explore the predicting variables. Results: We found that the overall slope of self-rated health in one-person households decreases. In addition, latent class analysis demonstrated three classes: 1) High-Decreasing class (i.e., high intercept, significantly decreasing slope), 2) Moderate-Decreasing class (i.e., average intercept, significantly decreasing slope), and 3) Low-Stable class (i.e., low intercept, flat and nonsignificant slope). The multinomial logistic regression analysis showed that the predictors of each class were different. Especially, one-person households with poor health condition early were at greater risk of being Low-Stable class compared with High-Decreasing class group. Conclusion: The findings of this study demonstrate that more attentions to one-person households are needed to promote their health status. Policymakers may develop different health and welfare programs depending on different characteristics of one-person household trajectory groups in Korea.

• Journal of the Korea Computer Graphics Society
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• v.8 no.1
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• pp.37-45
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• 2002

We present a cloth simulation technique that is very stable yet also responsive. The stability of the technique allows the use of a large fixed time step when simulating various types of fabrics and character motions. The animations generated using this technique are strikingly realistic. Wrinkles form and disappear in a quite natural way, which is the feature that most distinguishes textile fabrics from other sheet materials. Significant improvements in both the stability and realism were made possible by overcoming the post-buckling instability as well as the numerical instability. The instability caused by buckling arises from a structural instability and therefore cannot be avoided by simply employing an implicit method. Addition of a damping force may help to avoid instabilities; however, it can significantly degrade the realism of the cloth motion. In this paper, a new buckling model based on immediate buckling assumption is proposed. A cloth element is assumed to reach a stable configuration immediately once it begins to buckle. This assumption makes it possible to simulate the fabric buckling stably without introducing any fictitious damping force. Consequently, it produces highly responsive cloth motion as well as improves the stability by modeling the fabric-specific buckling property adequately.

• Journal of IKEEE
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• v.22 no.2
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• pp.281-288
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• 2018

In this paper, we propose an intelligent face recognition and tracking system that distributes GPU resources using CUDA. The proposed system consists of five steps such as GPU allocation algorithm that distributes GPU resources in optimal state, face area detection and face recognition using deep learning, real time face tracking, and PTZ camera control. The GPU allocation algorithm that distributes multi-GPU resources optimally distributes the GPU resources flexibly according to the activation level of the GPU, unlike the method of allocating the GPU to the thread fixedly. Thus, there is a feature that enables stable and efficient use of multiple GPUs. In order to evaluate the performance of the proposed system, we compared the proposed system with the non - distributed system. As a result, the system which did not allocate the resource showed unstable operation, but the proposed system showed stable resource utilization because it was operated stably. Thus, the utility of the proposed system has been demonstrated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.131-142
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• 1994

This paper analyzes the properties of such algorithm that corresponds to the nonlinear adaptive algorithm with additional update terns, parameterized by the scalar factors ${\alpha}1,\;and\;{\alpha}2$. The analysis of concergence leads to eigenvalues of the transition matrix for the mean filter coefficient vector. Regions in which the algorithm becomes stable are demonstrated. The time constant is derived and the computational complexity of the QFG algorithm is compared with those of the conventional LMS. sign, and LFG algorithm. The properties of convergence in the mean square error is derived and the neccessary condition for the CFG algorithm to be stable is attaned. In the computer simulation a channel equalization is utilized to demonstrate the performance feature of the QFG algorithm. The QFG algorithm has the more computational complexities but the faster convergence speed than LMS and LFG algorithm. Since the QFG algorithm has smoother convergence, it may be useful in case where error bursting is a problem.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.10
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• pp.3-10
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• 2019

The high school credit system is a system in which students select complete various subjects, depending on their career, and graduate when their accumulated credit reaches the standard. It is expected that the high school credit system, which guarantees the individual's right of choice, will bring an educational effect that can respond to the student's career aptitude. However, it is expected that problems in the aspect of school life, such as the weakening of class belongingness or difficulty of securing a stable base venue within the school building would be accompanied. This research analyzed students' usage condition depending on the living base space environment feature in schools that are implementing moving-selective class in the aspect of activity domain formation and contemplated the venue evaluation. The purpose is to provide the basic data of an architectural plan of a stable living base space within the school building through this. 'Living base center type' and 'living base dispersion type' school buildings among Japanese integral department high schools were used as the target to analyze the usage condition in the aspect of domain formation. As a result, a conclusion was deducted that student's securement of territory consciousness about the base space and venue construction for the community of various studying groups affects life satisfaction.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.57-65
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• 2023

Various studies to enhance the accuracy of rice production forecasting are focused on improving the accuracy of the models. In contrast, there is a relative lack of research regarding the data itself, which the prediction models are applied to. When applying the same dependent variable and prediction model to two different sets of rice production data composed of distinct features, discrepancies in results can occur. It is challenging to determine which dataset yields superior results under such circumstances. To address this issue, by identifying potential influential features within the data before applying the prediction model and centering the modeling around these, it is possible to achieve stable prediction results regardless of the composition of the data. In this study, we propose a method to adjust the composition of the data's features in order to select optimal base variables, aiding in achieving stable and consistent predictions for rice production. This method makes use of the Korea Meteorological Administration's ASOS data. The findings of this study are expected to make a substantial contribution towards enhancing the utility of performance evaluations in future research endeavors.

• Journal of Convergence for Information Technology
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• v.12 no.2
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• pp.47-53
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• 2022

Recently, with the change of the intelligent security paradigm, study to apply various information generated from various information security systems to AI-based anomaly detection is increasing. Therefore, in this study, in order to convert log-like time series data into a vector, which is a numerical feature, the CBOW and Skip-gram inference methods of deep learning-based Word2Vec model and statistical method based on the coincidence frequency were used to transform the published ADFA system call data. In relation to this, an experiment was carried out through conversion into various embedding vectors considering the dimension of vector, the length of sequence, and the window size. In addition, the performance of the embedding methods used as well as the detection performance were compared and evaluated through GRU-based anomaly detection model using vectors generated by the embedding model as an input. Compared to the statistical model, it was confirmed that the Skip-gram maintains more stable performance without biasing a specific window size or sequence length, and is more effective in making each event of sequence data into an embedding vector.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.325-331
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• 2018

This paper deals with the dynamical analysis of a vessel that leads to capsize in regular beam seas. The complete investigation of nonlinear behaviors includes sub-harmonic motion, bifurcation, and chaos under variations of control parameters. The vessel rolling motions can exhibit various undesirable nonlinear phenomena. We have employed a linear-plus-cubic type damping term (LPCD) in a nonlinear rolling equation. Using the fourth order Runge-Kutta algorithm with the phase portraits, various dynamical behaviors (limit cycles, bifurcations, and chaos) are presented in beam seas. On increasing the value of control parameter ${\Omega}$, chaotic behavior interspersed with intermittent periodic windows are clearly observed in the numerical simulations. The chaotic region is widely spread according to system parameter ${\Omega}$ in the range of 0.1 to 0.9. When the value of the control parameter is increased beyond the chaotic region, periodic solutions are dominant in the range of frequency ratio ${\Omega}=1.01{\sim}1.6$. In addition, one more important feature is that different types of stable harmonic motions such as periodicity of 2T, 3T, 4T and 5T exist in the range of ${\Omega}=0.34{\sim}0.83$.