• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.999-1009
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• 2019

The importance of high-resolution sea ice maps of the Arctic Ocean is increasing due to the possibility of pioneering North Pole Routes and the necessity of precise climate prediction models. In this study,sea ice classification algorithms for two deep learning models were examined using Sentinel-1 A/B SAR data to generate high-resolution sea ice classification maps. Based on current ice charts, three classes (Open Water, First Year Ice, Multi Year Ice) of training data sets were generated by Arctic sea ice and remote sensing experts. Ten sea ice classification algorithms were generated by combing two deep learning models (i.e. Simple CNN and Resnet50) and five cases of input bands including incident angles and thermal noise corrected HV bands. For the ten algorithms, analyses were performed by comparing classification results with ground truth points. A confusion matrix and Cohen's kappa coefficient were produced for the case that showed best result. Furthermore, the classification result with the Maximum Likelihood Classifier that has been traditionally employed to classify sea ice. In conclusion, the Convolutional Neural Network case, which has two convolution layers and two max pooling layers, with HV and incident angle input bands shows classification accuracy of 96.66%, and Cohen's kappa coefficient of 0.9499. All deep learning cases shows better classification accuracy than the classification result of the Maximum Likelihood Classifier.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.81-88
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• 2014

The researcher of this study applied PCA on aerial hyper-spectral sensor and selectively combined bands which contain high amount of information, creating five types of PCA images. By applying Spectral Angle Mapping-supervised classification technique on each type of image, classification process was carried out and accuracy was evaluated. The test result showed that the amount of information contained in the first band of PCA-transformation image was 76.74% and the second accumulated band contained 98.40%, suggesting that most of information were contained in the first and the second PCA components. Quantitative classification accuracy evaluation of each type of image showed that total accuracy, producer's accuracy and user's accuracy had similar patterns. What drew the researcher's attention was the fact that the first and the second bands of the PCA-transformation image had the highest accuracy according to the classification accuracy although it was believed that more than four bands of PCA-transformation image should be contained in order to secure accuracy when doing the qualitative classification accuracy.

• Journal of Korean Society of Forest Science
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• v.76 no.1
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• pp.41-50
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• 1987

The various conditions of photographs, especially kinds of films, combinated filters and seasons are important factors for forestry purpose aerial photography. In this paper the variations of tones were compared between color and color infrared, panchromatic black and white and infrared black and white, and among false color photographic images created by using 3 kinds of filters when prints are made. Color infrared film was good for identifying tree species, for its spectral signatures had a greater range of tones and hues than color signatures. In that case taken in May were more effective than taken April. False color photographs were not so good as color photographs because they were mostly dark and indistinct. Infrared black and white film with medium red filter showed potential for separating broad-leaved forests from conifers. MSS composed photographs, when composed with proper bands and densities, were proved useful for distinguishing land use types but not applicable to more detailed practices such as forest type separation and tree species identification.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.16-28
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• 2013

Recently the various applications and spectral indices development of airborne hyperspectral imagery(A-HSI) has been increased. Especially the vegetation indices (VIs) were used to verify stress and vigor of vegetation. The VIs needs two or more spectral bands selectively to calculate as NIR(near infrared) and red wavelength. The A-HIS has specific band characteristics as narrow, continues and many. The A-HIS has narrow, continues and many specific band characteristics. That could be make it confuse which of bands could be explained for appropriate vegetation characteristics. If the A-HIS bands is not the same the wavelength with VIs' development band setting, then it need a selection adequate for spectral characteristics of target vegetation. Therefore we set 4 substitute bands for NIR and red wavelength respectively and calculated two VIs combined with substitute bands such as NDVI(normalized difference vegetation index) and MSRI(modified simple ratio index). To consider the variation of each VIs, we adapted the image differencing method of change detection technique. Also, we used spectral derivative to identify appropriate bands for spectral characteristics of digital forest cover type map. The result of adequate bands for two VIs selected red #3 as 680.2nm and NIR #2 as 801.7nm. This wavelength was good for any forest type in low variations.

• Geotechnical Engineering
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• v.11 no.4
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• pp.37-48
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• 1995

The dynamic behavior of dry sand under different vibration conditions is studied through laboratory experiments. Sinusoidal and random vibration experiments of sand are carried out in vertical direction under various surcharge loads. Five different sand samples are selected for the azperiment. They are composed of four different -size samples of particles and one sample which is simulated the field condition. In case of sinusoidal vibration, the change in relative density is measured with acceleration levels. To produce an acceleration, the vibration amplitude is maintained within the range of 0.4mm~0.6mm and the vibration frequency is changed within the range of 3Hz~40Hz. In case of random vibration, the combined sinusoidal acceleration is produced by a random vibration generator and the change in relative density is measured by an accelerometer. Based on the experimental results, it is found that the sandy soil is compacted to 94%~99% of relative density by vertical acceleration and the peak acceleration producing the maximum relative density is proportional to the difference between maximum and minimum void ratios. It is also found that the effect of surcharge loading : the greater the surcharge loading, the larger the change in relative density and the greater the acceleration required to change the relative density.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.537-542
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• 2022

There is a limit to the current indoor air quality (IAQ) monitoring method using fixed sensors and devices. A mobile robot for IAQ monitoring was developed by mounting IAQ monitoring sensors on a small multi-legged robot to minimize vibration and protect the sensors from vibration while robot moves. The developed mobile robot used a simple gait mechanism to enable the robot to move forward, backward, and turns only with the combination of forward and reverse rotation of the two DC motors. Due to the simple gait mechanism, not only IAQ data measurements but also gait motion control were processed using a single Arduino board. Because the mobile robot has small number of electronic components and low power consumption, a relatively low-capacity battery was mounted on the robot to reduce the weight of the battery. The weight of mobile robot is 1.4kg including links, various IAQ sensors, motors, and battery. The gait and turning speed of the mobile robot was measured at 3.75 cm/sec and 14.13 rad/sec. The maximum height where the robot leg could reach was 33 mm, but the mobile robot was able to overcome the bumps up to 24 mm.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1489-1503
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• 2022

Drone and sensor technologies are enabling digitalization of agricultural crop's growth information and accelerating the development of the precision agriculture. These technologies could be able to assess damage of crops when natural disaster occurs, and contribute to the scientification of the crop insurance assessment method, which is being conducted through field survey. This study was aimed to calculate lodged damage rate from the vegetation indices extracted by drone based RGB images for soybean. Support Vector Classifier (SVC) models were considered by adding vegetation indices to the Crop Surface Model (CSM) based lodged damage rate. Visible Atmospherically Resistant Index (VARI) and Green Red Vegetation Index (GRVI) based lodged damage rate classification were shown the highest accuracy score as 0.709 and 0.705 each. As a result of this study, it was confirmed that drone based RGB images can be used as a useful tool for estimating the rate of lodged damage. The result acquired from this study can be used to the satellite imagery like Sentinel-2 and RapidEye when the damages from the natural disasters occurred.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.365-371
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• 2022

In order to obtain excellent spatial resolution in the PET detector, when the detector module is designed using very small scintillation pixels, overlap occurs at the edges and corners of the scintillation pixel array in the flood image. By using a light guide, the occurrence of overlap can be reduced. In this study, after using a scintillator of 0.8 mm × 0.8 mm × 20 mm to form a 14 × 14 array, 3 mm × 3 mm SiPM pixels are combined with 4 × 4 photosensor to reduce the occurrence of overlap. The optimal thickness of the light guide used for this purpose was derived. Quantitative evaluation was performed based on scintillation pixel images of edges and corners where overlap occurs mainly in the acquired flood image. Quantitative evaluation was calculated through the interval and full width at half maximum between scintillation pixel images, and when a light guide with a thickness of 2 mm was used, the best image was obtained with a k value of 2.60. In addition, as a result of measuring the energy resolution through the energy spectrum, the light guide with a thickness of 2 mm showed the best result at 28.5%. If a 2 mm light guide is used, it is considered that the best flood image and energy resolution with minimal overlap can be obtained.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.109-116
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• 2022

In this paper, we propose a band rejection filter (BRF) with a state variable filter (SVF) structure to effectively remove the influence of 60 Hz line frequency noise introduced into the sensor system. The conventional BRF of the SVF structure uses an additional operational amplifier (OPAMP) to add a low pass filter (LPF) output and a high pass filter (HPF) output or an input signal and a band pass filter. Therefore, the notch frequency and the notch depth that determine the signal attenuation of the BRF greatly depend on the tolerance of the resistors used to obtain the sum or difference of the signals. On the other hand, in the proposed BRF, since the BRF output is formed naturally within the SVF structure, there is no need for a combination between each port. The notch frequency of the proposed BRF is 59.99 Hz, and it can be confirmed that it is not affected at all by the tolerance of the resistor through the Monte Carlo simulation results. The notch depth also has an average of -42.54dB and a standard deviation of 0.63dB, confirming that normal operation as a BRF is possible. Also, with the proposed BRF, noise filtering was applied to the electrocardiogram (ECG) signal that interfered with 60 Hz noise, and it was confirmed that the 60 Hz noise was appropriately suppressed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.6
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• pp.82-92
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• 2022

This study aims to investigate the effect of total electrochemical cell resistance (TECR) on electrochemical impedance (EI) measurements of reinforced concrete (RC) by electrochemical impedance spectroscopy (EIS) using a three-electrode system. A series of experimental study is performed to measure electrochemical behavior of a steel bar embedded in a concrete cube specimen, with a side length of 200 mm, in various experimental conditions. Main variables include concrete dry conditions, coupling resistance between sensing electrodes and concrete surface, and area of the counter electrode. It is demonstrated that EI values remains stable when the compliant voltage of a measuring device is sufficiently great compared to the potential drop caused by TECR of concrete specimens. It is confirmed that the effect of the coupling resistance of TECR is far more influential than other two factors (concrete dry conditions and area of the counter electrode). The results in this study can be used as a fundamental basis for development of a surface-mount sensor for corrosion monitoring of reinforced concrete structures exposed to wet-and-dry cycles under marine environment.