• 한국생물공학회:학술대회논문집
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• 2003.04a
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• pp.497-497
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• 2003

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.527-535
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• 2000

Accurate determination of the relative restraint of beam-to-column connections is important for both the strength and the serviceability of structural frames. But steel frame analysis is carried out under the assumption that the connections are either fixed or pinned. Overestimating the connection restraint can result in underestimating lateral sway and underestimating the connection restraint can lead to underestimating forces developed in the beams and columns. This implies that the exact stiffness of connections as well as the geometric effects should be considered in the frame analysis and the overall behavior of connections could be described adequately. Therefore, the stiffness matrix which is able to consider the moment-rotation of connection was derived previously and the modified exponential model, power model and the proposed log model are adopted for modeling the semi-rigid connections. The main purpose of this study is to examine the feasibility of the derived stiffness matrix and to show the validity of log model proposed.

• Imaging Science in Dentistry
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• v.47 no.4
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• pp.227-231
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• 2017

Purpose: Sialolithiasis is one of the most prevalent large obstructive disorders of the submandibular glands. The aim of this study was to investigate submandibular sialolithiasis with computed tomography (CT) and scintigraphy, with a particular focus on the relationship between CT values of the submandibular glands and their excretion rate. Materials and Methods: Fifteen patients with submandibular sialolithiasis who underwent CT and salivary gland scintigraphy were included in this study. The relationship between the CT values of submandibular glands with and without sialoliths and salivary gland excretion measured using salivary gland scintigraphy was statistically analyzed. Dynamic images were recorded on the computer at 1 frame per 20 seconds. The salivary gland excretion fraction was defined as A (before stimulation test [counts/frame]) / B (after stimulation test [counts/frame]) using time-activity curves. Results: The CT values in the submandibular glands with and without sialoliths was $9.9{\pm}44.9$ Hounsfield units(HU) and $34.2{\pm}21.8HU$, respectively (P=.233). Regarding the salivary gland excretion fraction using scintigraphy, the A/B value in the submandibular glands with sialoliths ($1.09{\pm}0.23$) was significantly lower than in the submandibular glands without sialoliths($1.99{\pm}0.57$, P=.000). Conclusion: Assessments of the CT values and the salivary gland excretion fraction using scintigraphy in the submandibular glands seem to be useful tools evaluating submandibular sialolithiasis.

• Journal of Broadcast Engineering
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• v.23 no.6
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• pp.886-895
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• 2018

In this paper, we introduce a technique to detect the video forgery by using the regularity that occurs in the video compression process. The proposed method uses the hierarchical regularity lost by the video double compression and the frame deletion. In order to extract such irregularities, the depth information of CU and TU, which are basic units of HEVC, is used. For improving performance, we make a depth map of CU and TU using local information, and then create input data by grouping them in GoP units. We made a decision whether or not the video is double-compressed and forged by using a general three-dimensional convolutional neural network. Experimental results show that it is more effective to detect whether or not the video is forged compared with the results using the existing machine learning algorithm.

• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.1-9
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• 2019

With the development of imaging information communication technology in modern society, imaging acquisition and mass production technology have developed rapidly. However, crime rates using these technology are increased and forensic studies are conducted to prevent it. Identification techniques for image acquisition devices are studied a lot, but the field is limited to images. In this paper, camera model identification technique for video, not image is proposed. We analyzed video frames using the trained model with images. Through training and analysis by considering the frame characteristics of video, we showed the superiority of the model using the P frame. Then, we presented a video camera model identification system by applying a majority-based decision algorithm. In the experiment using 5 video camera models, we obtained maximum 96.18% accuracy for each frame identification and the proposed video camera model identification system achieved 100% identification rate for each camera model.

• Structural Engineering and Mechanics
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• v.22 no.3
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• pp.371-399
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• 2006

The theoretical background and capabilities of the developed program, SAR-CWF, for stochastic analysis of 3D reinforced-concrete shear wall-frame structures subject to seismic excitations is presented. Incremental stiffness and strength properties of system members are modeled by extended Roufaiel-Meyer hysteretic relation for bending while shear deformations for walls by Origin-Oriented hysteretic model. For the critical height of shear-walls, division to sub-elements is performed. Different yield capacities with respect to positive and negative bending, finite extensions of plastic hinges and P-${\delta}$ effects are considered while strength deterioration is controlled by accumulated hysteretic energy. Simulated strong motions are obtained from a Gaussian white-noise filtered through Kanai-Tajimi filter. Dynamic equations of motion for the system are formed according to constitutive and compatibility relations and then inserted into equivalent It$\hat{o}$-Stratonovich stochastic differential equations. A system reduction scheme based on the series expansion of eigen-modes of the undamaged structure is implemented. Time histories of seismic response statistics are obtained by utilizing the computer programs developed for different types of structures.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1177-1188
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• 2002

To classify real time Lead pin images in this paper, The image acquisition system was composed to C.C.D, image frame grabber(DT3153), P.C(PentiumIII). I proposed image processing algorithms. This algorithms were composed to real time monitoring, Lead Pin image acquisition, image noise deletion, object area detection, point detection and pattern classification algorithm. The raw images were acquired from Lead pin images using the system. The result images were obtained from raw images by image processing algorithms. In implemental result, The right recognition was 97 of 100 acceptable products, 95 of 100 defective products. The recognition rate was 96% for total 200 Lead Pins.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1641-1644
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• 2005

Magnetic actuation utilizes the mechanic torque that is the result of interaction of the current in a coil with an external magnetic field. A main obstacle is, however, that torques can only be produced perpendicular to the magnetic field. In addition, there is uncertainty in the Earth magnetic field models due to the complicated dynamic nature of the field. Also, the magnetic hardware and the spacecraft can interact, causing both to behave in undesirable ways. This actuation principle has been a topic of research since earliest satellites were launched. Earlier magnetic control has been applied for nutation damping for gravity gradient stabilized satellites, and for velocity decrease for satellites without appendages. The three axes of a micro-satellite can be stabilized by using an electromagnetic actuator which is rigidly mounted on the structure of the satellite. The actuator consists of three mutually-orthogonal air-cored coils on the skin of the satellite. The coils are excited so that the orbital frame magnetic field and body frame magnetic field coincides i.e. to make the Euler angles to zero. This can be done using a Neural Network controller trained by PD controller data and driven by the difference between the orbital and body frame magnetic fields.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.292-304
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• 2005

In this paper we present the linearized equations of motion for a bicycle as a benchmark. The results obtained by pencil-and-paper and two programs are compared. The bicycle model we consider here consists of four rigid bodies, viz. a rear frame, a front frame being the front fork and handlebar assembly, a rear wheel and a front wheel, which are connected by revolute joints. The contact between the knife-edge wheels and the flat level surface is modelled by holonomic constraints in the normal direction and by non-holonomic constraints in the longitudinal and lateral direction. The rider is rigidly attached to the rear frame with hands free from the handlebar. This system has three degrees of freedom, the roll, the steer, and the forward speed. For the benchmark we consider the linearized equations for small perturbations of the upright steady forward motion. The entries of the matrices of these equations form the basis for comparison. Three diffrent kinds of methods to obtain the results are compared : pencil-and-paper, the numeric multibody dynamics program SPACAR, and the symbolic software system Auto Sim. Because the results of the three methods are the same within the machine round-off error, we assume that the results are correct and can be used as a bicycle dynamics benchmark.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.9A
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• pp.2289-2304
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• 1998

For the performance analysis and traffic control of ATM networks carrying video sequences, need an appropriate video traffic model. In this paper, we propose a new traffic model for MPEG compressed videos which are widely used for any type of video applications at th emoment. The proposed modeling scheme uses scene-based traffic characteristics and considers the correlation between frames of consecutiv GOPs. Using a simple scene detection algorithm, scene changes are modeled by state transitions and the number of GOPs of a scene state is modeled by a geometric distirbution. Frames of a scene stte are modeled by mean I, P, and B frame size. For more accurate traffic modeling, quantization errors (residual bits) that the state transition model using mean values has are compensated by autoregressive processes. We show that our model very well captures the traffic chracteristics of the original videos by performance analysis in terms of autocorrelation, histogram of frame bits genrated by the model, and cell loss rate in the ATM multiplexer with limited buffers. Our model is able to perrorm translations between levels (i.e., GOP, frame, and cell levels) and to estimate very accurately the stochastic characteristics of the original videos by each level.