• Composites Research
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• v.13 no.6
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• pp.47-54
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• 2000

One promising method for impact detection of composite structures is based on the use of piezopolymer thin fim (PVDf) sensor. In this paper, the relationship between the contact force and the signals of the attached strain gage and PVDF sensor to the composite plate subjected to low-velocity impact were derived. The relation for the open circuit and short circuit voltage of PVDF sensor was derived based on the equivalent circuit model of the piezoelectric sensor. The work was then extended to include experimental investigation into the use of short circuit voltage of PVDF sensor without using charge amplifier to detect low-velocity impact. The natural frequencies and damping ratio of the composite plate obtained from the vibration test were used to modify the analytical model and therefore the differences between measured and simulated signal of the modified analytical model in both forward and backward problem were considerably reduced. The reconstructed contact force and simulated sensor signals agreed well with the measured contact force, strain gage signal, and PVDF sensor singanl.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1184-1191
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• 2016

This paper introduces the development of a transient monitoring system to detect the early stage of a transient, to identify the type of the transient scenario, and to inform an operator with the remaining time to turbine trip when there is no operator's relevant control. This study focused on the transients originating from a secondary system in nuclear power plants (NPPs), because the secondary system was recognized to be a more dominant factor to make unplanned turbine-generator trips which can ultimately result in reactor trips. In order to make the proposed methodology practical forward, all the transient scenarios registered in a simulator of a 1,000 MWe pressurized water reactor were archived in the transient pattern database. The transient patterns show plant behavior until turbine-generator trip when there is no operator's intervention. Meanwhile, the operating data periodically captured from a plant computer is compared with an individual transient pattern in the database and a highly matched section among the transient patterns enables isolation of the type of transient and prediction of the expected remaining time to trip. The transient pattern database consists of hundreds of variables, so it is difficult to speedily compare patterns and to draw a conclusion in a timely manner. The transient pattern database and the operating data are, therefore, converted into a smaller dimension using the principal component analysis (PCA). This paper describes the process of constructing the transient pattern database, dealing with principal components, and optimizing similarity measures.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.12
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• pp.1124-1131
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• 2011

In this paper, image reconstruction algorithm for breast cancer detection using MT(Microwave Tomography) was investigated. The breast cancer detection system under development uses 16 transmit/receive antennas. The signal waveform was a sinusoidal wave at 900 MHz. To solve the 2D inverse scattering problem, we used the 2D FDTD (Finite Difference Time Domain) method for forward calculation and LMA(Levenberg-Marquardt Algorithm) for optimization. The result of the image reconstruction using the numerical phantom by MRI(Magnetic Resonance Imaging) obtained from real patient of breast cancer showed that we can detect the position of the tumor accurately.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.5
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• pp.330-338
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• 2024

With the growing interest in rehabilitation therapy and exercise programs, there is an increasing need for smart content that simultaneously addresses both health and engagement. Particularly, exercises performed in a state of physical imbalance carry a high risk of injury, making it essential to detect and integrate balance into the training process. This paper proposes Rehabilitation Training program that combines a pressure platform with virtual reality (VR) technology to address this issue. The program enables users to perform exercises such as squats, stationary walking, and forward-backward walking in a VR environment, utilizing real-time foot pressure data captured through a pressure mat. Additionally, an algorithm based on YOLOv8-pose extracted skeletal coordinates is proposed to assess body balance and automatically count squat repetitions. The experimental results showed an average accuracy of 87.9% for each posture, confirming that users can be provided with a safer, more efficient, and immersive training experience through this approach.

• The Journal of the Korea Contents Association
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• v.20 no.7
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• pp.47-55
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• 2020

Along with the increased use of smart devices, the incidence of turtle neck syndrome among modern people has increased. Turtle neck syndrome is a posture in which the head is forward compared to the torso due to longer front muscles in the neck and shorter upper muscles, and it is more effective to fix the usual posture habits than surgery or medication. Thus, in this paper, a system is proposed to detect and warn posture that can cause turtle neck syndrome in real time. Image data of correct posture and turtle neck posture are collected to create a CNN-based learning model. Using only the webcam(Built-in camera), the sitting position that enters the camera is verified in real time through the learning model, and if it is a turtle neck position, it generates a warning sound and induces the correct posture. The system can induce people to correct their usual posture habits to treat turtle neck syndrome and prevent more serious diseases such as neck discs.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3710-3717
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• 1999

For the development of unmanned autonomous vehicle, it is essential to detect obstacles, especially vehicles, in the forward direction of navigation. In order to reliably exclude regions that do not contain obstacles and save a considerable amount of computational effort, it is often necessary to confine computation only to ROI(region of interest)s. A ROI is usually chosen as the interior region of the lane. We propose a computationally simple and efficient method for the detection of lanes based on Hough transform and quadratic curve fitting. The proposed method first employs Hough transform to get approximate locations of lanes, and then applies quadratic curve fitting to the locations computed by Hough transform. We have experimented the proposed method on real outdoor road scene. Experimental results show that our method gives accurate detection of straight and curve lanes, and is computationally very efficient.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1053-1065
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• 2020

With the recent development of hardware performance and artificial intelligence technology, sophisticated fake videos that are difficult to distinguish with the human's eye are increasing. Face synthesis technology using artificial intelligence is called Deepfake, and anyone with a little programming skill and deep learning knowledge can produce sophisticated fake videos using Deepfake. A number of indiscriminate fake videos has been increased significantly, which may lead to problems such as privacy violations, fake news and fraud. Therefore, it is necessary to detect fake video clips that cannot be discriminated by a human eyes. Thus, in this paper, we propose a deep-fake detection model applied with Bidirectional Convolution LSTM and Attention Module. Unlike LSTM, which considers only the forward sequential procedure, the model proposed in this paper uses the reverse order procedure. The Attention Module is used with a Convolutional neural network model to use the characteristics of each frame for extraction. Experiments have shown that the model proposed has 93.5% accuracy and AUC is up to 50% higher than the results of pre-existing studies.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.35-47
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• 2010

To complement inaccurate edge information and detect correctly the boundary of a vehicle in an image, an extended edge analysis technique is presented in this paper. The vehicle is detected using the bottom boundary generated by a vehicle and the road surface and the left and right side boundaries of the vehicle. The proposed extended edge analysis method extracts the horizontal edge by merging or dividing the nearby edges inside the region of interest set beforehand because various noises deteriorates the horizontal edge which can be a bottom boundary. The horizontal edge is considered as the bottom boundary and the vertical edges as the side boundaries of a vehicle if the extracted horizontal edge intersects with two vertical edges which satisfy the vehicle width condition at the height of the horizontal edge. This proposed algorithm is more efficient than the other existing methods when the road surface is complex. It is proved by the experiments executed on the roads having various backgrounds.

• Geophysics and Geophysical Exploration
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• v.18 no.4
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• pp.216-222
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• 2015

Airborne transient electromagnetic (ATEM) surveying was introduced several decades ago in the mining industry to detect shallow conductive targets. However, conventional ATEM systems have limited depth of investigation because of weak signal strength. Recently, the grounded electrical source airborne transient electromagnetic (GREATEM) system was proposed to increase the depth of investigation. The GREATEM is a semi-airborne transient electromagnetic system because a long grounded wire is used as the transmitter. Traditionally, ATEM sounding data have been interpreted with 1D earth models to save the computing time because modern ATEM systems generally collect large data sets. However, the GREATEM 1D modeling requires numerical integration along the wire, so it takes much more time than the 1D modeling of conventional ATEM. In this study, the adaptive Born forward mapping (ABFM) was applied to the ATEM 1D modeling because the ABFM is incommensurably faster than the ordinary GREATEM 1D modeling. Comparing the results from ordinary and ABFM 1D modeling, it was confirmed that the ABFM can be applied to the 1D modeling of GEATEM.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.2
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• pp.28-33
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• 2008

This paper presents a continuous-time equalizer adopting a clock loss tracking technique for digital display interface. This technique uses bottom hold circuit to detect the incoming clock loss. The generated loss signal is directly fed to equalizer filters, building adaptive feed-forward loops which contribute the stability of the system. The design was done in $0.18{\mu}m$ CMOS technology. Experimental results summarize that eye-width of minimum 0.7UI is achieved until -33dB channel loss at 1.65Gbps. The average power consumption of the equalizer is a maximum 10mW, a very low value in comparison to those of previous researches, and the effective area is $0.127mm^2$.