• Korean Journal of Remote Sensing
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• v.13 no.2
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• pp.133-150
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• 1997

The purpose of this paper is to develop an algorithm of classification and interpretation of seafloor based on side scan sonar data. The algorithm consists of mosaicking of sonar data using navigation data, correction and compensation of the acouctic amplitude data considering the charateristics of the side scan sonar system, and segmentation of the seafloor using digital image processing techniques. The correction and compensation process is essential because there is usually difference in acoustic amplitudes from the same distance of the port-side and the starboard-side and the amplitudes become attenuated as the distance is increasing. In this paper, proposed is an algorithm of compensating the side scan sonar data, and its result is compared with the mosaicking result without any compensation. The algorithm considers the amplitude characteristics according to the tow-fish's depth as well as the attenuation trend of the side scan sonar along the beam positions. This paper also proposes an image segmentation algorithm based on the texture, where the criterion is the maximum occurence related with gray level. The preliminary experiment has been carried out with the side scan sonar data and its result is demonstrated.

• Korean Journal of Remote Sensing
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• v.26 no.3
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• pp.317-324
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• 2010

In recent years, many automatic classification approaches have been employed. An automatic classification method can be effective, time-saving and can produce objective results due to the exclusion of operator intervention. This paper proposes a classification method based on automated training for high resolution multispectral images using ancillary data. Generally, it is problematic to automatically classify high resolution images using ancillary data, because of the scale difference between the high resolution image and the ancillary data. In order to overcome this problem, the proposed method utilizes the classification results of a Landsat image as a medium for automatic classification. For the classification of a Landsat image, a maximum likelihood classification is applied to the image, and the attributes of ancillary data are entered as the training data. In the case of a high resolution image, a K-means clustering algorithm, an unsupervised classification, was conducted and the result was compared to the classification results of the Landsat image. Subsequently, the training data of the high resolution image was automatically extracted using regular rules based on a RELATIONAL matrix that shows the relation between the two results. Finally, a high resolution image was classified and updated using the extracted training data. The proposed method was applied to QuickBird and SPOT-5 images of non-accessible areas. The result showed good performance in accuracy assessments. Therefore, we expect that the method can be effectively used to automatically construct thematic maps for non-accessible areas and update areas that do not have any attributes in geographic information system.

• Bulletin of the Korean Chemical Society
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• v.14 no.6
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• pp.713-717
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• 1993

The crystal structure of the potassium salt of penicillin V has been studied by the X-ray crystallographic methods. Crystal data are as follows; potassium 3,3-dimethyl-7-oxo-6-phenoxyacetoamido-4-thia-1- azabicyclo[3.2.0]-heptane-2${\alpha}$-carboxylate, $K^+{\cdot}C_{16}H_{18}N_2O_5S^-$, $M_r$= 388.5, triclinic, Pl, a= 9.371 (1), b= 12.497 (2), c= 15.313 (2) ${\AA},\;{\alpha}= 93.74\;(2),\;{\beta}=99.32\;(1),\;{\gamma}=90.17\;(1)^{\circ},\;V=1765.7\;(2)\;{\AA}^3$, Z=4, $D_m=1.461\;gcm^{-1},\;{\lambda}(Cu\;K{\alpha})=1.5418\;{\AA},\;{\mu}=40.1\;cm^{-1}$, F(000)=808, T=296 K. The structure was solved by the heavy atom and difference Fourier methods with intensity data measured on an automated four-circle diffractometer. The structure was refined by the full-matrix least-squares method to a final R= 0.081 for 3563 observed $[I_0{\geq}2{\sigam}(I_0)]$ reflections. The four independent molecules assume different overall conformations with systematically different orientations of the phenyl groups although the penam moieties have the same closed conformations. There are intramolecular hydrogen bonds between the exocyclic amide nitrogen and phenoxy oxygen atoms. The penam moiety is conformationally very restricted although the carboxyl and exocyclic amide groups apparently have certain rotational degrees of freedom but the phenyl group is flexible about the ether bond despite the presence of the intramolecular N-H${\cdots}$O hydrogen bond. There are complicated pseudo symmetric relationships in the crystal lattice. The penam moieties are related by pseudo 20.5 screw axes and the phenyl groups by pseudo centers of symmetry. The potassium ions, related by both pseudo symmetries, form an infinite zigzag planar chain parallel to the b axis. Each potassium ion is coordinated to seven oxygen atoms in a severely distorted pentagonal bipyramid configuration, forming the infinite hydrophilic channels which in turn form the molecular stacks. Between these stacks, there are only lipophilic interactions involving the phenyl groups.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.445-452
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• 2018

The field of agriculture, forestry, and other land-use (AFOLU) is concerned with greenhouse emissions of agriculture (crop and livestock), as is the field of land-use, land-use change, and forestry (LULUCF). The 1996 IPCC guideline and the 2006 IPCC guideline are used in combination for calculation of greenhouse gas emission from the agricultural sector, and the 2003 IPCC guideline is used for that from the land-use sector. In this research, we analyzed GHG emissions of the cropland sector in AFOLU based on the 2006 IPCC guideline. The results showed that GHG emissions of 1990 was $-504Gg{\cdot}CO_2-eq$, while that of the last year was $2,871Gg{\cdot}CO_2-eq$. Compared with the 2003 methodology, total emissions according to the 2006 IPCC was lower except in 1997 and 2003. This trend is due to difference of analyzed emission sources, lower default values, and global warming potential by the 2006 IPCC. The results are estimated using limited data at the Tier 1 level and the first issue to be solved is the activity data from the land-use change matrix. Although this result should be improved, it can be used as the basis for calculating GHG emissions of the AFOLU sector.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.29 no.3
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• pp.404-413
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• 2019

Objectives: Chronic obstructive pulmonary disease(COPD) is an important cause of mortality in workers exposed to hazardous dust, such as crystalline silica or coal, and COPD is related to inflammation and oxidative stress in the lung. The aim of this study was to evaluate the association of oxidative stress and inflammation to COPD in retired workers exposed to mineral dust. Methods: The levels of malondialdehyde(MDA) in EBC as biomarkers for oxidative stress and C-reactive protein(CRP) and lactate dehydrogenase(LD) as biomarkers for inflammation were measured in 107 male subjects(63 pneumoconiosis and 42 COPD subjects). Results: Mean levels of EBC MDA(2.03 nmol/L vs. 4.65 nmol/L, p=0.010) and serum LD(170.3 U/L vs. 185.9 U/L, p=0.022) were significantly higher in subjects with COPD, but mean levels of serum CRP(p=0.469) did not show a statistical difference between the study groups. Level of EBC MDA was negatively correlated with ${%}FEV_1$ predicted(r=-0.279, p=0.004) and ${%}FEV_1/FVC$ ratio(r=-0.397, p<0.001). Conclusions: These results suggest that EBC is a useful biological matrix for investigation of respiratory oxidative stress. High levels of EBC MDA and serum LD are related to COPD in retired workers exposed to mineral dust.

• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.200-211
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• 2016

To support cross potential array and direct potential array, the array for leakage detection of all kinds of water facilities is proposed and it is named as the D-Lux array. The D-Lux array data are arranged to a coloured matrix and it is called the D-Lux view. Low potential difference of anomalous zone shown in D-Lux view implies the indication of leakage zone. Furthermore, for an intuitive interpretation of D-Lux array, equipotential distribution map is made by using D-Lux and direct potential array data. Equipotential distribution map makes us possible to predict import point, export point and the path of water leakage that we could have not anticipated in D-Lux view and the graphs. The water tank experiment and numerical analysis were carried out as preparatory experiment and the field explorations were conducted at a concrete weir and a fill dam. As a result, effective and specific detection of leakage path was possible for the concrete weir and the fill dam.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.4
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• pp.602-608
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• 2021

Recently, research and development has been conducted to impart high performance and functionality to concrete materials by mixing various reinforcing materials into the matrix. Ductile fiber reinforced concrete using a large amount of fibers shows a distributed multiple cracking behavior, and various studies are being conducted on this material. However, research is focused on static behavioral analysis but studies on cyclic behaviors are not sufficient. In this study, beams were made of ductile fiber reinforced concrete with various fiber contents, and static and fatigue flexural tests were performed. As a result, the effect of fiber content on the flexural behavior was analyzed. Also, the applied load level and fatigue life relationship of ductile fiber reinforced concrete was proposed. Concrete with high ductile property could be achieved with a fiber content of 2%. When 0.5% fiber was more added, the maximum flexural strength was similar, but the flexural toughness is nearly doubled. On the other hand, there was no significant difference in the fatigue life of these two mixtures.

• Journal of radiological science and technology
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• v.45 no.1
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• pp.41-47
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• 2022

The purpose of this study is to apply a deep learning model that can distinguish lung perfusion and lung ventilation images in nuclear medicine, and to evaluate the image classification ability. Image data pre-processing was performed in the following order: image matrix size adjustment, min-max normalization, image center position adjustment, train/validation/test data set classification, and data augmentation. The convolutional neural network(CNN) structures of VGG-16, ResNet-18, Inception-ResNet-v2, and SE-ResNeXt-101 were used. For classification model evaluation, performance evaluation index of classification model, class activation map(CAM), and statistical image evaluation method were applied. As for the performance evaluation index of the classification model, SE-ResNeXt-101 and Inception-ResNet-v2 showed the highest performance with the same results. As a result of CAM, cardiac and right lung regions were highly activated in lung perfusion, and upper lung and neck regions were highly activated in lung ventilation. Statistical image evaluation showed a meaningful difference between SE-ResNeXt-101 and Inception-ResNet-v2. As a result of the study, the applicability of the CNN model for lung scintigraphy classification was confirmed. In the future, it is expected that it will be used as basic data for research on new artificial intelligence models and will help stable image management in clinical practice.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.259-268
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• 2022

Unlike the general buyer-supplier relationship, there are cases wherein the bargaining power of suppliers is greater than that of buyers. This relationship can be found especially in the shipbuilding industry. Thus, this paper focused on strategic items presented in Kraljic's study. The purpose of this study was to examine factors influencing buyers' purchase of strategic items in a market wherein the bargaining power of suppliers is superior. Results show that the path coefficient between environment factor and satisfaction factor was the highest. Additionally, the path coefficient between environment factor and reliability factor was the next highest. Also, as a result of analyzing if there is a difference in perception according to the superiority and inferiority of bargaining power perceived by buyers, significant results were found in some path coefficients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1462-1468
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• 2022

Among the data used for the diagnosis of calf disease, feces play an important role in disease diagnosis. In the image of calf feces, the health status can be known by the shape, color, and texture. For the fecal image that can identify the health status, data of 207 normal calves and 158 calves with diarrhea were pre-processed according to fecal status and used. In this paper, images of fecal variables are detected among the collected calf data and images are trained by applying GLCM-CNN, which combines the properties of CNN and GLCM, on a dataset containing disease symptoms using convolutional network technology. There was a significant difference between CNN's 89.9% accuracy and GLCM-CNN, which showed 91.7% accuracy, and GLCM-CNN showed a high accuracy of 1.8%.