• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.513-516
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• 2002

In electrical impedance tomography(EIT), various image reconstruction algorithms have been used in order to compute the internal resistivity distribution of the unknown object with its electric potential data at the boundary. Mathematically the EIT image reconstruction algorithm is a nonlinear ill-posed inverse problem. This paper presents two intelligent optimization algorithm techniques such as genetic algorithm and simulated annealing for the solution of the static EIT inverse problem. We summarize the simulation results for the three algorithm forms: modified Newton-Raphson, genetic algorithm, and simulated annealing.

• Bulletin of the Korean Chemical Society
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• v.28 no.1
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• pp.85-88
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• 2007

Ab initio periodic Hartree-Fock calculations with the full potential and minimum basis set are applied to interpretation of scanning tunneling microscope (STM) and atomic force microscope (AFM) images on 1TVTe2. Our results show that the simulated STM image shows asymmetry while the simulated AFM image shows the circular electron densities at the bright spots without asymmetry of electron density to agree with the experimental AFM image. The bright spots of both the STM and AFM images of VTe2 are associated with the surface Te atoms, while the patterns of bright spots of STM and AFM images are different.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.479-490
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• 2003

This study proposed a modified anisotropic diffusion restoration for image classification. The anisotropic diffusion restoration uses a probabilistic model based on Markov random field, which represents geographical connectedness existing in many remotely sensed images, and restores them through an iterative diffusion processing. In every iteration, the bonding-strength coefficient associated with the spatial connectedness is adaptively estimated as a function of brightness gradient. The gradient function involves a constant called "temperature", which determines the amount of discontinuity and is continuously decreased in the iterations. In this study, the proposed method has been extensively evaluated using simulated images that were generated from various patterns. These patterns represent the types of natural and artificial land-use. The simulated images were restored by the modified anisotropic diffusion technique, and then classified by a multistage hierarchical clustering classification. The classification results were compared to them of the non-restored simulation images. The restoration with an appropriate temperature considerably reduces error in classification, especially for noisy images. This study made experiments on the satellite images remotely sensed on the Korean peninsula. The experimental results show that the proposed approach is also very effective on image classification in remote sensing.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.125-132
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• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.285-293
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• 2021

The construction of underground structures such as power supply lines, communication lines, utility tunnels has significantly increased worldwide for improving urban aesthetics ensuring citizen safety, and efficient use of underground space. Those underground structures are usually constructed along with vertical cylindrical shafts to facilitate their construction and maintenance. When constructing a vertical shaft through the open-cut method, the walls are mostly designed to be flexible, allowing a certain level of displacement. The earth pressure applied to the flexible walls acts as an external force and its accurate estimation is essential for reasonable and economical structure design. The earth pressure applied to the flexible wall is closely interrelated to the displacement of the surrounding ground. This study simulated stepwise excavation for constructing a cylindrical vertical shaft through a centrifugal model experiment. One quadrant of the axisymmetric vertical shaft and the ground were modeled, and ground excavation was simulated by shrinking the vertical shaft. The deformation occurring on the entire ground during the excavation was continuously evaluated through digital image analysis. The digital image analysis evaluated complex ground deformation which varied with wall displacement, distance from the wall, and ground depth. When the ground deformation data accumulate through the method used in this study, they can be used for developing shaft wall models in future for analyzing the earth pressure acting on them.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.2
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• pp.87-95
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• 2008

Ladar (Laser Detection And Ranging, Lidar) is a sensor to acquire precise distances to the surfaces of target region using laser signals, which can be suitably applied to ATD (Automatic Target Detection) for guided missiles or aerial vehicles recently. It provides a range image in which each measured distance is expressed as the brightness of the corresponding pixel. Since the precise 3D models can be generated from the Ladar range image, more robust identification and recognition of the targets can be possible. If we simulate the data of Ladar sensor, we can efficiently use this simulator to design and develop Ladar sensors and systems and to develop the data processing algorithm. The purposes of this study are thus to simulate the signals of a Ladar sensor based on linear frequency modulation and to create range images from the simulated Ladar signals. We first simulated the laser signals of a Ladar using FM chirp modulator and then computed the distances from the sensor to a target using the FFT process of the simulated signals. Finally, we created the range image using the distances set.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.359-364
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• 2022

The change detection in remote sensing results in errors due to the camera's optical factors, seasonal factors, and land cover characteristics. The inclination of the building in the image was simulated according to the camera angle using the Cycle Generative Adversarial Network method, and the simulated image was used to contribute to the improvement of change detection accuracy. Based on CycleGAN, the inclination of the building was similarly simulated to the building in the other image based on the image of one of the two periods, and the error of the original image and the inclination of the building was compared and analyzed. The experimental data were taken at different times at different angles, and Kompsat-3A high-resolution satellite images including urban areas with dense buildings were used. As a result of the experiment, the number of incorrect detection pixels per building in the two images for the building area in the image was shown to be reduced by approximately 7 times from 12,632 in the original image and 1,730 in the CycleGAN-based simulation image. Therefore, it was confirmed that the proposed method can reduce detection errors due to the inclination of the building.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.93-96
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• 2001

In this paper, the performance of DS/CDMA-BPSK system for image transmission is simulated by computer, and received image is compared with the origin image. In order to transmit standard image 'Lena', the image is discrete-cosine- transformed and quantized. Then image transmission data is made through assigning 8 bits to the image and high frequency data part of the image is compressed for reducing the size of data. The source-coded image is transmitted and received by the DS/CDMA-BPSK system. The BER, PSNR, and source Quality are changed according to the number of multiple access users, processing gain of the system, and SMR.

• Restorative Dentistry and Endodontics
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• v.32 no.2
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• pp.87-94
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• 2007

This study was done to evaluate transportation of the apical foramen after 0.5 mm overinstrumentation by ProFile, ProTaper and $K^3$ in simulated resin root canal. Sixty simulated resin root canal with a curvature of J and S-shape were divided into two groups. Each group consisted of three subgroups with 10 blocks according to the instruments used: $ProFile^{(R)},\;ProTaper^{TM},\;and\;K^{3TM}$. Simulated resin root canal was prepared by ProFile, ProTaper and $K^3$ with 300 rpm by the crown-down preparation technique. Pre- and post-instrumentation apical foramen images were overlapped and recorded with Image-analyzing microscope 100X (Camcope, Sometech Inc, Korea). The amounts of difference in width and dimension on overlapped images were measured after reference points were determined by Image Analysis program ($Image-Pro^{(R)}$ Express, Media Cybernetic, USA). Data were analyzed using Kruskal-Wallis and Mann-Whitney U-test. The results suggest that ProFile showed significantly less canal transportation and maintained original apical foramen shape better than $K^3$ and ProTaper.

• Journal of Biosystems Engineering
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• v.21 no.2
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• pp.167-174
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• 1996

A Fuzzy Logic Controller(FLC) was developed for the autonomous operation of speedsprayer in an orchard. The autonomous operation with the FLC was graphically simulated under the real condition of the orchard. Image processing was used to find out the direction of running and four ultrasonic sensors were used to detect obstacles for the running. The simulation results showed that the speedsprayer could be operated autonomously with the FLC combined with the image processing and the ultrasonic sensors.