• Journal of the Korean Society of Safety
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• v.18 no.4
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• pp.98-104
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• 2003

Various nondestructive evaluation (NDE) techniques have been studied to locate steel rebars of dowel, and to detect invisible damage such as voids and cracks inside concrete and debonding between rebars and concrete caused by corrosions and earthquakes. In this study, the aurhors developed 3-dimensional (3D) electromagnetic (EM) imaging technology to detect such damage and to identify exact location of steel rebars of dowel. The authors have developed sub-surface two-dimensional (2D) imaging technique using tomographic antenna array in previous works. In this study, extending the earlier analytical and experimental works on 2D image reconstruction, a 3D microwave imaging system using tomographic antenna array was developed, and multi-frequency technique was applied to improve quality of the reconstructed image and to reduce background noises. This paper presents the analytical expressions of numerical focusing procedures for 3D image reconstruction and numerical simulation to study the resolution of the system and the effectiveness of multi-frequency technique. Also, the design of 4?4 antenna array with switching devices is introduced as a preliminary study for the final design of whole array.

• Journal of Korean Society of Disaster and Security
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• v.10 no.2
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• pp.1-6
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• 2017

In the previous research, the research on the development of subway disaster detection system that discovers the disaster early warning of the subway station disaster and the evacuation to the passengers based on the Internet of things. This paper as a follow-up study analyzes the sensor data installed in the station in real time to quickly detect the disaster. In particular, we developed a statistical methodology based on the Mahalanobis distance in consideration of the environment that varies depending on the installation location of the sensor during initial system construction.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.550-557
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• 2008

Delamination damage at a bolt hole in a composite stiffened panel was detected using a built-in piezoelectric active sensor array. Various signal processing techniques were used to detect an invisible small scale delamination around a fastener hole due to localized transverse loading. A built-in piezoelectric sensor array was used to generate diagnostic signals and to measure response signals. Then, the response signals were processed to extract damage-sensitive features. Damage indexes were calculated to estimate the severity and location of the damage from the features.

• Smart Media Journal
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• v.6 no.3
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• pp.49-56
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• 2017

Images and Videos that include the human face contain a lot of information. Therefore, accurately extracting human face is a very important issue in the field of computer vision. However, in real life, human faces have various shapes and textures. To adapt to these variations, A model-based approach is one of the best ways in which unknown data can be represented by the model in which it is built. However, the model-based approach has its weaknesses when the motion between two frames is big, it can be either a sudden change of pose or moving with fast speed. In this paper, we propose an enhanced human face-tracking model. This approach included human face detection and motion estimation using Cascaded Convolutional Neural Networks, and continuous human face tracking and modeling correction steps using the Active Appearance Model. A proposed system detects human face in the first input frame and initializes the models. On later frames, Cascaded CNN face detection is used to estimate the target motion such as location or pose before applying the old model and fit new target.

• Nuclear Engineering and Technology
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• v.39 no.1
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• pp.43-50
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• 2007

A partial flow blockage in an assembly of a liquid metal reactor could result in a cooling deficiency of the core. To develop a partial blockage detection system, we have studied the changes of the temperature fluctuation characteristics in the upper plenum according to changes of the t10w blockage conditions in an assembly. We analyzed the temperature fluctuation in the upper plenum with the Large Eddy Simulation (LES) turbulence model in the CFX code and evaluated its statistical parameters. Based on the results of the statistical analyses, we developed a neural network model for detecting a partial flow blockage in an assembly. The neural network model can retrieve the size and the location of a flow blockage in an assembly from a change of the root mean square, the standard deviation, and the skewness in the temperature fluctuation data. The neural network model was found to be a possible alternative by which to identify a flow blockage in an assembly of a liquid metal reactor through learning and validating various flow blockage conditions.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.10a
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• pp.320-324
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• 2013

A crack identification method using an equivalent bending stiffness for cracked beam and committee of neural networks is presented. The equivalent bending stiffness is constructed based on an energy method for a straight thin-walled pipe, which has a through-the-thickness crack, subjected to bending. Several numerical analysis for a steel cantilever pipe using the equivalent bending stiffness are carried out to extract the natural frequencies and mode shapes of the cracked beam. The extracted modal properties are used in constructing a training patterns of a neural network. The input to the neural network consists of the modal properties and the output is composed of the crack location and size. Multiple neural networks are constructed and each individual network is trained independently with different initial synaptic weights. Then, the estimated crack locations and sizes from different neural networks are averaged. Experimental crack detection is carried out for 3 damage cases using the proposed method, and the identified crack locations and sizes agree reasonably well with the exact values.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.2
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• pp.45-53
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• 2019

RGB-D SLAM (Simultaneous Localization and Mapping) refers to the technology of using deep camera as a visual sensor for SLAM. In view of the disadvantages of high cost and indefinite scale in the construction of maps for laser sensors and traditional single and binocular cameras, a method for creating three-dimensional map of indoor environment with deep environment data combined with RGB-D SLAM scheme is studied. The method uses a mobile robot system equipped with a consumer-grade RGB-D sensor (Kinect) to acquire depth data, and then creates indoor three-dimensional point cloud maps in real time through key technologies such as positioning point generation, closed-loop detection, and map construction. The actual field experiment results show that the average error of the point cloud map created by the algorithm is 0.0045m, which ensures the stability of the construction using deep data and can accurately create real-time three-dimensional maps of indoor unknown environment.

• Structural Engineering and Mechanics
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• v.71 no.2
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• pp.175-183
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• 2019

This paper deals with damage detection in a girder bridge using transmissibility functions as input data to Artificial Neural Networks (ANNs). The original contribution in this work is that these two novel methods are combined to detect damage in a bridge. The damage was simulated in a real bridge in Vietnam, i.e. Ca-Non Bridge. Finite Element Method (FEM) of this bridge was used to show the reliability of the proposed technique. The vibration responses at some points of the bridge under a moving truck are simulated and used to calculate the transmissibility functions. These functions are then used as input data to train the ANNs, in which the target is the location and the severity of the damage in the bridge. After training successfully, the network can be used to assess the damage. Although simulated responses data are used in this paper, the practical application of the technique to real bridge data is potentially high.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1355-1363
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• 2018

Many radionuclides exist in normal environment and artificial radionuclides also can be detected. The radionuclides ($^{131}I$) are widely used for labeling compounds and radiation therapy. In Korea, the radionuclide ($^{131}I$) is produced at the Radioisotope Production Facility (RIPF) at the Korea Atomic Energy Research Institute in Daejeon. The residents around the RIPF assume that $^{131}I$ detected in environmental samples is produced from RIPF. To ensure the safety of the residents, the radioactive concentration of $^{131}I$ near the RIPF was investigated by monitoring environmental samples along the Gap River. The selected geographical places are near the nuclear installation, another possible location for $^{131}I$ detection, and downstream of the Gap River. The first selected places are the "front gate of KAERI", and the "Donghwa bridge". The second selected place is the sewage treatment plant. Therefore, the Wonchon bridge is selected for the upstream of the plant and the sewage treatment plant is selected for the downstream of the plant. The last selected places are the downstream where the two paths converged, which is Yongshin bridge (in front of the cogeneration plant). In these places, environmental samples, including sediment, fish, surface water, and aquatic plants, were collected. In this study, the radioactive iodine ($^{131}I$) detection along the Gap River will be investigated.

• Corrosion Science and Technology
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• v.17 no.6
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• pp.292-300
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• 2018

The modeling of 3D finite elements based on CAD data has been used to detect sites of corrosion defects in buried pipes. The results generated sophisticated profiles of electrolytic potential and vectors of current distributions on the earth surface. To identify the location of defects in buried pipes, the current distribution on the earth surface was projected to a plane of incidence that was identical to the pipe locations. The locations of minimum electrolytic potential value were found. The results show adequate match between the locations of real and expected defects based on modeling. In addition, the defect size can be calculated by integrating the current density curve. The results show that the defect sizes were $0.74m^2$ and $0.69m^2$, respectively. This technology may represent a breakthrough in the detection of indirect damage in various cases involving multiple defects in size and shape, complex/cross pipe systems, multiple anodes and stray current.