• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.700-705
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• 2020

Generative adversarial networks are methods of generating images by opposing two neural networks. When generating the image, randomly generated noise is rearranged to generate the image. The image generated by this method is not generated well depending on the noise, and it is difficult to generate a proper image when the number of pixels of the image is small In addition, the speed and size of data accumulation in data classification increases, and there are many difficulties in labeling them. In this paper, to solve this problem, we propose a technique to generate noise based on random noise using real data. Since the proposed system generates an image based on the existing image, it is confirmed that it is possible to generate a more natural image, and if it is used for learning, it shows a higher hit rate than the existing method using the hostile neural network respectively.

• Advances in nano research
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• v.10 no.5
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• pp.461-470
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• 2021

Infection is one of the major mortality causes throughout the globe. Nuclear medicine plays an important role in diagnosis of deep infections such as osteomyelitis, arthritis infection, heart valve and heart prosthesis infections. Techniques such as labeled leukocytes are sensitive and selective for tracking the inflammations but they are not suitable for differentiating infection from inflammation. Anionic linear-globular dendrimer-G₂ was synthesized then conjugation to gemifloxacin antibiotic. The structures were identified by FT-IR, ¹H-NMR, C-NMR, LC-MS and DLS. The toxicity of gemifloxacin and dendrimer-gemifloxacin complex was compared by MTT test. Dendrimer-G₂-gemifloxacin was labeled by Technetium-99m and its in-vitro stability and radiochemical purity were investigated. In-vivo biodistribution and SPECT imaging were studied in a rabbit model. Identify and verify the structure of the each object was confirmed by FT-IR, ¹H-NMR, C-NMR and LC-MS, also, the size and charge of this compound were 128 nm and -3/68 mv respectively. MTT test showed less toxicity of the dendrimer-G₂-gemifloxacin than free gemifluxacin (P < 0.001). Radiochemical yield was > %98. Human serum stability was 84% up to 24 h. Biodistribution study at 50 min, 24 and 48 h showed that the complex is significantly absorbed by the intestine and accumulation in the lungs and affects them, finally excreted through the kidneys, biodistribution results are consistent with results from full image means of SPECT/CT technique.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.4
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• pp.69-78
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• 2023

With the rapid growth of artificial intelligence, the demand for semiconductors is enormously increasing everywhere. To ensure the manufacturing quality and quantity simultaneously, the importance of automatic defect detection during the packaging process has been re-visited by adapting various deep learning-based methodologies into automatic packaging defect inspection. Deep learning (DL) models require a large amount of data for training, but due to the nature of the semiconductor industry where security is important, sharing and labeling of relevant data is challenging, making it difficult for model training. In this study, we propose a new framework for securing sufficient data for DL models with fewer computing resources through a divide-and-conquer approach. The proposed method divides high-resolution images into pre-defined sub-regions and assigns conditional labels to each region, then trains individual sub-regions and boundaries with boundary loss inducing the globally coherent and seamless images. Afterwards, full-size image is reconstructed by combining divided sub-regions. The experimental results show that the images obtained through this research have high efficiency, consistency, quality, and generality.

• Journal of dental hygiene science
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• v.16 no.6
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• pp.464-471
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• 2016

The purpose of this study was to provide information on the labeling of nutritional components on beverages to aid in nutrition education and oral health promotion. The study was conducted to evaluate nutritional effects and risk factors associated with the consumption of different beverages with respect to oral health. A total of 52 products from seven different types of beverages were analyzed for their nutrient content, sugar content, and pH. The sugar content per serving size, based on the nutrition labeling of beverages, was highest for the milk beverages, at 26.6 g, and lowest for the teas, at 13.0 g. According to the recommendation of the World Health Organization (WHO), beverages should contain less than 10% (50 g) total sugars. Our assessment revealed that total sugars in and carbonated beverages were 53.2% and 50.0% of daily value, respectively. Therefore, the milk and carbonated beverages contained more than 50% sugars per serving size, exceeding the recommendation of WHO. The pH of the beverages, from the most acidic to the least acidic were: carbonated beverages, pH 3.0; fruit and vegetable beverages, pH 3.1; mixed beverages, pH 3.6; fruit and vegetable juices, pH 3.7; teas, pH 4.7; coffees, pH 6.6; and milk beverages, pH 6.8. The intake of acidic and sweetened beverages could potentially cause dental caries and erosion. Therefore, the results of this study could be used by oral health care professionals to counsel their patients by providing relevant information on the possibility of oral disease caused by consumption of commercial beverages.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.1
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• pp.40-47
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• 2009

Purpose: Differentiated thyroid cancer (DTC) has variable degree of F-18 FDG avidity. The purpose of this study was to evaluate the relationship between F-18 FDG uptake and pathological or immunohistochemical features of DTC. Materials and Methods: DTC patients who underwent both pre-operative F-18 FDG PET/CT scan and surgery were included in the study. Maximum standardized uptake values (SUVmax) of primary tumor were calculated. If the primary tumor showed no perceptibly increased F-18 FDG uptake, region of interest was drawn based on finding of a portion of the PET/CT images. Pathological and immunohistochemical markers such as presence of lymph node (LN) metastasis and underlying thyroiditis, tumor size, Ki-67 labeling index, expressions of EGFR, COX-2, and Galectin-3 were evaluated. Results: Total of 106 patients was included (102 papillary carcinomas, 4 follicular carcinomas). The mean SUVmax of the large tumors (above 1 cm) was significantly higher than the mean SUVmax of small (equal to or less than 1 cm) ones ($7.8{\pm}8.5$ vs. $3.6{\pm}3.1$, p=0.004). No significant difference in F-18 FDG uptake was found according to the presence or absence of LN metastasis and underlying thyroiditis, or the degree of Ki-67 labeling index, expression of EGFR, COX- 2 and Galectin-3. Conclusion: In conclusion, the degree of F-18 FDG uptake in DTC was associated with the size of primary tumor. But there seem to be no relationship between F-18 FDG uptake of DTC and expression of Ki-67, EGFR, COX-2 and Galectin-3.

• Journal of Korean Neurosurgical Society
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• v.30 no.4
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• pp.443-450
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• 2001

Objective : The cyclin-dependent kinase inhibitor $p27^{kip1}$ protein is a negative regulator of the cell cycle, and its degradation is required for entry into the S phase. Loss of $p27^{kip1}$ expression has been reported to be associated with aggressive behavior in a variety of tumors of epithelial and lymphoid origin. However, its association with various astrocytic tumors has not been clearly demonstrated. We studied to investigate the relationship of $p27^{kip1}$ expression with the biological behavior of astrocytic tumors in addition to study on the role of $p27^{kip1}$ in the tumorigenesis of these tumors. Patients and Methods : From 1990 to 1998, a total of 29 astrocytic tumor of all grades obtained by operative resection were included for evaluation. We studied the expression of $p27^{kip1}$ protein immunohistochemical assay in astrocytic tumors and compared the findings with the clinicopathologic parameters. Immunohistochemical staining was performed on formalin-fixed paraffin-embedded sections by the avidin-biotin-peroxidase complex method. According to WHO classification, all cases were divided into astrocytomas(4 cases), anaplastic astrocytomas(9 cases), and glioblastomas(16 cases) by 3 pathologists. Clinical information was obtained from medical records, and others such as location and size of tumors from imaging studies. Results : Mean $p27^{kip1}$ protein labeling indexes(LI, mean${\pm}$standard deviation) of astrocytomas, anaplastic astrocytomas, and glioblastomas were $80.6{\pm}9.1$, $63.6{\pm}21.0$, and $28.9{\pm}18.7$, respectively, and were inversely correlated with grade of glial tumors(p<0.0001). Mean $p27^{kip1}$ protein LI in the recurrent group was lower than that in the nonrecurrent group, but there was no significant difference statistically(p=0.464). Additionally, $p27^{kip1}$ protein expression did not show any significant relationship to other prognostic factors such as age(p=0.1643), tumor size(p=0.8), or location(p=0.8). Conclusion : These results suggested that reduced expression of $p27^{kip1}$ protein may play a important role in the malignant transformation process of astrocytic tumor cells.

• Journal of Korea Multimedia Society
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• v.8 no.11
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• pp.1496-1509
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• 2005

In this paper, an adaptive license plate recognition system which detects and recognizes license plate at real-time by using projected plane convolution and Decision Tree Classifier is proposed. And it was tested in circumstances which presence of complex background. Generally, in expressway tollgate or gateway of parking lots, it is very difficult to detect and segment license plate because of size, entry angle and noisy problem of vehicles due to CCD camera and road environment. In the proposed algorithm, we suggested to extract license plate candidate region after going through image acquisition process with inputted real-time image, and then to compensate license size as well as gradient of vehicle with change of vehicle entry position. The proposed algorithm can exactly detect license plate using accumulated edge, projected convolution and chain code labeling method. And it also segments letter of license plate using adaptive binary method. And then, it recognizes license plate letter by applying hybrid pattern vector method. Experimental results show that the proposed algorithm can recognize the front and rear direction license plate at real-time in the presence of complex background environments. Accordingly license plate detection rate displayed $98.8\%$ and $96.5\%$ successive rate respectively. And also, from the segmented letters, it shows $97.3\%$ and $96\%$ successive recognition rate respectively.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.2
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• pp.1-9
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• 2003

We develop an experimental system to inspect a metal mask and, in this paper, introduce its inspection algorithm. This system is composed of an ASC(Area Scan Camera) and a belt type xy-table. The whole area of the metal mask is divided into several inspection blocks. The area of each block is equal to FOV(Field of View). For each block, the camera image is compared to the reference image. The reference image is made by gerber file. The rotation angle of the metal mask is calculated through the linear equation that is substituted two end points of horizontal boundary of a specific hole in a camera image. To calculate the position error caused by the belt type xy-table, HT(Hough-Transform) using distances among the holes in two images is used. The center of the reference image is moved as much as the calculated Position error to be coincided with the camera image. The information of holes in each image, such as centroid, size, width and height, are calculated through labeling. Whether a holes is mado correctly by laser machine or not, is judged by comparing the centroid and the size of hole in each image. Finally, we build the experimental system and apply this algorithm.

• Journal of Gastric Cancer
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• v.21 no.1
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• pp.103-109
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• 2021

Gastric adenocarcinoma of the fundic gland mucosa type (GA-FGM) was proposed as a new variant of gastric adenocarcinoma of the fundic gland type (GA-FG). However, at present, the influence of Helicobacter pylori and the speed of progression and degree of malignancy in GA-FGM remain unclear. Herein, we report the first case of intramucosal GA-FGM that was endoscopically observed before and after H. pylori eradication over 15 years. The lesion showed the same tumor size with no submucosal invasion and a low MIB-1 labeling index 15 years after its detection using endoscopy. The endoscopic morphology changed from 0-IIa before H. pylori eradication to 0-IIa+IIc and then 0-I after H. pylori eradication. These findings suggest that the unaltered tumor size reflects low-grade malignancy and slow growth, and that the endoscopic morphology is influenced by H. pylori eradication.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1407-1422
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• 2022

This study was conducted to classify tree species and assess the classification accuracy, using SE-Inception, a classification-based deep learning model. The input images of the dataset used Worldview-3 and GeoEye-1 images, and the size of the input images was divided into 10 × 10 m, 30 × 30 m, and 50 × 50 m to compare and evaluate the accuracy of classification of tree species. The label data was divided into five tree species (Pinus densiflora, Pinus koraiensis, Larix kaempferi, Abies holophylla Maxim. and Quercus) by visually interpreting the divided image, and then labeling was performed manually. The dataset constructed a total of 2,429 images, of which about 85% was used as learning data and about 15% as verification data. As a result of classification using the deep learning model, the overall accuracy of up to 78% was achieved when using the Worldview-3 image, the accuracy of up to 84% when using the GeoEye-1 image, and the classification accuracy was high performance. In particular, Quercus showed high accuracy of more than 85% in F₁ regardless of the input image size, but trees with similar spectral characteristics such as Pinus densiflora and Pinus koraiensis had many errors. Therefore, there may be limitations in extracting feature amount only with spectral information of satellite images, and classification accuracy may be improved by using images containing various pattern information such as vegetation index and Gray-Level Co-occurrence Matrix (GLCM).