• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.221-232
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• 2021

This study analyzed co-registration results according to the geometric processing level of reference image, which are Level 1R and Level 1G provided from KOMPSAT-3 and KOMPSAT-3A images. We performed co-registration using each Level 1R and Level 1G image as a reference image, and Level 1R image as a sensed image. For constructing the experimental dataset, seven Level 1R and 1G images of KOMPSAT-3 and KOMPSAT-3A acquired from Daejeon, South Korea, were used. To coarsely align the geometric position of the two images, SURF (Speeded-Up Robust Feature) and PC (Phase Correlation) methods were combined and then repeatedly applied to the overlapping region of the images. Then, we extracted tie-points using the SURF method from coarsely aligned images and performed fine co-registration through affine transformation and piecewise Linear transformation, respectively, constructed with the tie-points. As a result of the experiment, when Level 1G image was used as a reference image, a relatively large number of tie-points were extracted than Level 1R image. Also, in the case where the reference image is Level 1G image, the root mean square error of co-registration was 5 pixels less than the case of Level 1R image on average. We have shown from the experimental results that the co-registration performance can be affected by the geometric processing level related to the initial geometric relationship between the two images. Moreover, we confirmed that the better geometric quality of the reference image achieved the more stable co-registration performance.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.175-197
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• 2021

Recently, with the development of deep learning technology, research on unstructured data analysis is being actively conducted, and it is showing remarkable results in various fields such as classification, summary, and generation. Among various text analysis fields, text classification is the most widely used technology in academia and industry. Text classification includes binary class classification with one label among two classes, multi-class classification with one label among several classes, and multi-label classification with multiple labels among several classes. In particular, multi-label classification requires a different training method from binary class classification and multi-class classification because of the characteristic of having multiple labels. In addition, since the number of labels to be predicted increases as the number of labels and classes increases, there is a limitation in that performance improvement is difficult due to an increase in prediction difficulty. To overcome these limitations, (i) compressing the initially given high-dimensional label space into a low-dimensional latent label space, (ii) after performing training to predict the compressed label, (iii) restoring the predicted label to the high-dimensional original label space, research on label embedding is being actively conducted. Typical label embedding techniques include Principal Label Space Transformation (PLST), Multi-Label Classification via Boolean Matrix Decomposition (MLC-BMaD), and Bayesian Multi-Label Compressed Sensing (BML-CS). However, since these techniques consider only the linear relationship between labels or compress the labels by random transformation, it is difficult to understand the non-linear relationship between labels, so there is a limitation in that it is not possible to create a latent label space sufficiently containing the information of the original label. Recently, there have been increasing attempts to improve performance by applying deep learning technology to label embedding. Label embedding using an autoencoder, a deep learning model that is effective for data compression and restoration, is representative. However, the traditional autoencoder-based label embedding has a limitation in that a large amount of information loss occurs when compressing a high-dimensional label space having a myriad of classes into a low-dimensional latent label space. This can be found in the gradient loss problem that occurs in the backpropagation process of learning. To solve this problem, skip connection was devised, and by adding the input of the layer to the output to prevent gradient loss during backpropagation, efficient learning is possible even when the layer is deep. Skip connection is mainly used for image feature extraction in convolutional neural networks, but studies using skip connection in autoencoder or label embedding process are still lacking. Therefore, in this study, we propose an autoencoder-based label embedding methodology in which skip connections are added to each of the encoder and decoder to form a low-dimensional latent label space that reflects the information of the high-dimensional label space well. In addition, the proposed methodology was applied to actual paper keywords to derive the high-dimensional keyword label space and the low-dimensional latent label space. Using this, we conducted an experiment to predict the compressed keyword vector existing in the latent label space from the paper abstract and to evaluate the multi-label classification by restoring the predicted keyword vector back to the original label space. As a result, the accuracy, precision, recall, and F1 score used as performance indicators showed far superior performance in multi-label classification based on the proposed methodology compared to traditional multi-label classification methods. This can be seen that the low-dimensional latent label space derived through the proposed methodology well reflected the information of the high-dimensional label space, which ultimately led to the improvement of the performance of the multi-label classification itself. In addition, the utility of the proposed methodology was identified by comparing the performance of the proposed methodology according to the domain characteristics and the number of dimensions of the latent label space.

• Korean Journal of Remote Sensing
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• v.30 no.2
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• pp.275-292
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• 2014

The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.

• Progress in Medical Physics
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• v.14 no.4
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• pp.211-217
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• 2003

The Principal component analysis (PCA) is a well-known data analysis method that is useful in linear feature extraction and data compression. The PCA is a linear transformation that applies an orthogonal rotation to the original data, so as to maximize the retained variance. PCA is a classical technique for obtaining an optimal overall mapping of linearly dependent patterns of correlation between variables (e.g. neurons). PCA provides, in the mean-squared error sense, an optimal linear mapping of the signals which are spread across a group of variables. These signals are concentrated into the first few components, while the noise, i.e. variance which is uncorrelated across variables, is sequestered in the remaining components. PCA has been used extensively to resolve temporal patterns in neurophysiological recordings. Because the retinal signal is stochastic process, PCA can be used to identify the retinal spikes. With excised rabbit eye, retina was isolated. A piece of retina was attached with the ganglion cell side to the surface of the microelectrode array (MEA). The MEA consisted of glass plate with 60 substrate integrated and insulated golden connection lanes terminating in an 8${\times}$8 array (spacing 200 $\mu$m, electrode diameter 30 $\mu$m) in the center of the plate. The MEA 60 system was used for the recording of retinal ganglion cell activity. The action potentials of each channel were sorted by off­line analysis tool. Spikes were detected with a threshold criterion and sorted according to their principal component composition. The first (PC1) and second principal component values (PC2) were calculated using all the waveforms of the each channel and all n time points in the waveform, where several clusters could be separated clearly in two dimension. We verified that PCA-based waveform detection was effective as an initial approach for spike sorting method.

• Korean Journal of Veterinary Research
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• v.9 no.1
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• pp.23-62
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• 1969

Throughout the studies the following experimental results were obtained and are summarized: 1. Multiplication of agents in primary cell cultures of both GF classical and CR-64 acute strain of Marek's disease infected chicken kidneys was accompanied by the formation of distinct transformed cell foci. This characteristic nature of cell transformation was passaged regularly by addition of dispersed cell from infected cultures to normal chicken kidney cell cultures, and also transferred was the nature of cell transformation to normal chick-embryo liver and neuroglial cell cultures. No cytopathic changes were noticed in inoculated chick-embryo fibroblast cultures. 2. The same cytopathic effects were noticed in normal kidney cell monolayers after the inoculation of whole blood and huffy coat cells derived from both forms of Marek's disease infected chickens. In these cases, however, the number of transformed cell foci appearing was far less than that of uninoculated monolayers prepared directly from the kidneys of Marek's disease infected chickens. 3. The change in cell culture IS regarded as a specific cell transformation focus induced by an oncogenic virus rather than it plaque in slowly progressing cytopathic effect by non-oncogenic viruses, and it is quite similar to RSV focus in chick-embryo fibroblasts in many respects. 4. The infective agent (cell transformable) were extremely cell-associated and could not be separated in an infective state from cells under the experimental conditions. 5. The focus assay of these agents was valid as shown by the high degree of linear correlation (r=0.97 and 0.99) between the relative infected cell concentration (in inoculum) and the transformed cell foci counted. 6. No differences were observed between the GF classical strain and the CR-64 acute strain of Marek's disease as far as cell culture behavior. 7. Characterization of the isolates by physical and chemical treatments, development of internuclear inclusions in Infected cells, and nucleic acid typing by differential stainings and cytochemical treatments indicated that the natures of these cell transformation agents closely resemble to those described fer the group B herpes viruses. 8. Susceptible chicks inoculated with infected kidney tissue culture cells developed specific lesions of Marek's disease, and in a case of prolonged observation after inoculation (5 weeks) the birds developed clinical symptoms and gross lesions of Marek's disease. Kidney cell cultures prepared from those inoculated birds and sacrificed showed a superior recovery of cell transformation property by formation of distinct foci. 9. Electron microscopic study of infected kidney culture cells (GF agent) by negative staining technique revealed virus particles furnishing the properties of herpes viruses. The particle was measured about $100m{\mu}$ and, so far, no herpes virus envelop has been seen from these preparations. 10. No relationship of both isolates to avian leukosis/sarcoma group viruses and PPLO was observed.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.12 no.1
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• pp.42-62
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• 2008

Objectives: It is well known that some parameters of the photoplethysmogram (PPG) acquired by time domain contour analysis can be used as markers of vascular aging. But the previous studies that have been performed for frequency domain analysis of the PPG to date have provided only restrictive and fragmentary information. The aim of the present investigation was to determine whether the harmonics extracted from the PPG using a fast Fourier transformation could be used as an index of vascular aging. Methods: The PPG was measured in 600 recruited subjects for 30 second durations, To grasp the gross age-related change of the PPG waveform, we grouped subjects according to gender and age and averaged the PPG signal of one pulse cycle. To calculate the conventional indices of vascular aging, we selected the 5-6 cycles of pulse that the baseline was relatively stable and then acquired the coordinates of the inflection points. For the frequency domain analysis we performed a power spectral analysis on the PPG signals for 30 seconds using a fast Fourier transformation and dissociated the harmonic components from the PPG signals. Results: A final number of 390 subjects (174 males and 216 females) were included in the statistical analysis. The normalized power of the harmonics decreased with age and on a logarithmic scale reduction of the normalized power in the third (r=-0.492, P<0.0001), fourth (r=-0.621, P<0.0001) and fifth harmonic (r=-0.487, P<0.0001) was prominent. From a multiple linear regression analysis, Stiffness index, reflection index and corrected up-stroke time influenced the normalized power of the harmonics on a logarithmic scale. Conclusions: The normalized harmonic power decreased with age in healthy subjects and may be less error prone due to the essential attributes of frequency domain analysis. Therefore, we expect that the normalized harmonic power density can be useful as a vascular aging marker.

• Journal of the Korean Chemical Society
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• v.63 no.6
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• pp.453-458
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• 2019

Synthesis of ZnCo₂O₃ oxide is performed by sol-gel method via nitrate-citrate route. Powder X-ray diffraction (XRD) study shows monoclinic unit cell having lattice parameters: a = 5.721(1) Å, b = 8.073(2) Å, c = 5.670(1) Å, β = 93.221(8)°, space group P_2/m and Z = 4. Average crystallite sizes determined by Scherrer equation are the range ~14-32 nm, whereas SEM micrographs show nano-micro meter size particles formed in ZnCo₂O₃. Endothermic peak at ~798 K in the Differential scanning calorimetric (DSC) trace without weight loss could be due to structural transformation and the endothermic peak ~1143 K with weight loss is due to reversible loss of O₂ in air atmosphere. Energy Dispersive X-ray (EDX) analysis profile shows the presence of elements Zn, Co and O which indicates the purity of the sample. Magnetic measurements in the range of +12 kOe to -12 kOe at 10 K, 77 K, 120 K and at 300 K by PPMS-II Physical Property Measurement System (PPMS) shows hysteresis loops having very low values of the coercivity and retentivity which indicates the weakly ferromagnetic nature of the oxide. Observed X-band EPR isotropic lineshapes at 300 K and 77 K show positive g-shift at g_iso ~2.230 and g_iso ~2.217, respectively which is in agreement with the presence of paramagnetic site Co²⁺(3d⁷) in the oxide. DC conductivity value of 2.875 ×10^-8 S/cm indicates very weakly semiconducting nature of ZnCo₂O₃ at 300 K. DRS absorption bands ~357 nm, ~572 nm, ~619 nm and ~654 nm are due to the d-d transitions ⁴T_1g(⁴F)→²E_g(²G), ⁴T_1g(⁴F)→⁴T_1g(⁴P), ⁴T_1g(⁴F)→⁴A_2g(⁴F), ⁴T_1g(⁴F)→⁴T_2g(⁴F), respectively in octahedral ligand field around Co²⁺ ions. Direct band gap energy, E_g~ 1.5 eV in the oxide is obtained by extrapolating the linear part of the Tauc plot to the energy axis indicates fairly strong semiconducting nature of ZnCo₂O₃.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.9
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• pp.1225-1233
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• 2017

Objective: Calving ease (CE) is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea. Methods: A total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo), gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE) and daughter calving ease (DCE) evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving). A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5) and 100% (CE1). A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package. Results: The estimated direct heritability ($h^2$) from SCE and DCE evaluations were $0.11{\pm}0.01$ and $0.08{\pm}0.01$, respectively. Maternal $h^2$ estimates were $0.05{\pm}0.02$ and $0.04{\pm}0.01$ from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were $-0.68{\pm}0.09$ (SCE) and $-0.71{\pm}0.09$ (DCE). The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA) was desirable and increasing over time, but the maternal PTA was undesirable and decreasing. Conclusion: The evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of calving difficulty in Korean Holsteins.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.31-43
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• 2015

This study had been aimed to conduct the camera calibration on VLBI antenna in the Space Geodetic Observation Center of Sejong City with a low-cost digital camera, which embedded in a mobile phone to determine the three-dimension position coordinates of the VLBI antenna, based on stereo images. The initial values for the camera calibration have been obtained by utilizing the Direct Linear Transformation algorithm and the commercial digital photogrammetry system, PhotoModeler $Scanner^{(R)}$ ver. 6.0, respectively. The accuracy of camera calibration results was compared with that the camera calibration results, acquired by a bundle adjustment with nonlinear collinearity condition equation. Although two methods showed significant differences in the initial value, the final calibration demonstrated the consistent results whichever methods had been performed for obtaining the initial value. Furthermore, those three-dimensional coordinates of feature points of the VLBI antenna were respectively calculated using the camera calibration by the two methods to be compared with the reference coordinates obtained from a total station. In fact, both methods have resulted out a same standard deviation of $X=0.004{\pm}0.010m$, $Y=0.001{\pm}0.015m$, $Z=0.009{\pm}0.017m$, that of showing a high degree of accuracy in centimeters. From the result, we can conclude that a mobile phone camera opens up the way for a variety of image processing studies, such as 3D reconstruction from images captured.

• Korean Journal of Materials Research
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• v.19 no.2
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• pp.61-67
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• 2009

Electrolessly deposited Co (Re,P) was investigated as a possible capping layer for Cu wires. 50 nm Co (Re,P) films were deposited on Cu/Ti-coated silicon wafers which acted as a catalytic seed and an adhesion layer, respectively. To obtain the optimized bath composition, electroless deposition was studied through an electrochemical approach via a linear sweep voltammetry analysis. The results of using this method showed that the best deposition conditions were a $CoSO_4$ concentration of 0.082 mol/l, a solution pH of 9, a $KReO_4$ concentration of 0.0003 mol/l and sodium hypophosphite concentration of 0.1 mol/L at $80^{\circ}C$. The thermal stability of the Co (Re,P) layer as a barrier preventing Cu was evaluated using Auger electron spectroscopy and a Scanning calorimeter. The measurement results showed that Re impurities stabilized the h.c.p. phase up to $550^{\circ}C$ and that the Co (Re,P) film efficiently blocked Cu diffusion under an annealing temperature of $400^{\circ}C$ for 1hr. The good barrier properties that were observed can be explained by the nano-sized grains along with the blocking effect of the impurities at the fast diffusion path of the grain boundaries. The transformation temperature from the amorphous to crystal structure is increased by doping the Re.