• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.707-716
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• 2017

The advances in image display devices necessitate display images suitable for the user's purpose. The display devices should be able to provide object-based image information when a depthmap is required. In this paper, we represent the algorithm using a histogram-based image segmentation method for depthmap generation. In the conventional K-means clustering algorithm, the number of centroids is parameterized, so existing K-means algorithms cannot adaptively determine the number of clusters. Further, the problem of K-means algorithm tends to sink into the local minima, which causes over-segmentation. On the other hand, the proposed algorithm is adaptively able to select centroids and can stand on the basis of the histogram-based algorithm considering the amount of computational complexity. It is designed to show object-based results by preventing the existing algorithm from falling into the local minimum point. Finally, we remove the over-segmentation components through connected-component labeling algorithm. The results of proposed algorithm show object-based results and better segmentation results of 0.017 and 0.051, compared to the benchmark method in terms of Probabilistic Rand Index(PRI) and Segmentation Covering(SC), respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.3
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• pp.600-611
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• 1996

Recently, neural network-based speech recognition has been studied to utilize the adaptivity and learnability of neural network models. However, conventional neural network models have difficulty in the co-articulation processing and the boundary detection of similar phonmes of the Korean speech. Also, in case of using one phonotopic map, learning speed may dramatically increase and inaccuracies may be caused because homogeneous learning and recognition method should be applied for heterogenous data. Hence, in this paper, a neural net typewriter has been designed using a hierarchical self-organizing classifier(HSOC), and related algorithms are presented. This HSOC, during its learing stage, distributed phoneme data on hierarchically structured multiple phonotopic maps, using Kohonen's self-organizing feature maps(SOFM). Presented and experimented in this paper were the algorithms for deciding the number of maps, map sizes, the selection of phonemes and their placement per map, an approapriate learning and preprocessing method per map. If maps are divided according to a priorlinguistic knowledge, we would have difficulty in acquiring linguistic knowledge and how to alpply it(e.g., processing extended phonemes). Contrarily, our HSOC has an advantage that multiple phonotopic maps suitable for given input data are self-organizable. The resulting three korean phonotopic maps are optimally labelled and have their own optimal preprocessing schemes, and also confirm to the conventional linguistic knowledge.

• Restorative Dentistry and Endodontics
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• v.32 no.6
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• pp.514-521
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• 2007

The purinoreceptor, $P2X_3$ is a ligand-gated cation channel activated by extracellular ATP. It has been reported that ATP can be released during inflammation and tissue damage, which in turn may activate $P2X_3$ receptors to initiate nociceptive signals. However, little is known about the contribution of $P2X_3$ to the dental pain during pulpal inflammation. Therefore, the purpose of this study was to investigate the expression of $P2X_3$ and its colocalization with TRPV1 to understand the mechanism of pain transmission through $P2X_3$ in the human dental pulp with double labeling immunofluorescence method. In the human dental pulp, intense $P2X_3$ immunoreactiyity was observed throughout the coronal and radicular pulp. Of all $P2X_3$-positive fibers examined, 79.4% coexpressed TRPV1. This result suggests that $P2X_3$ along with TRPV1 may be involved in the transmission of pain and potentiation of noxious stimuli during pulpal inflammation.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.44 no.2
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• pp.183-189
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• 2018

Blue light is the highest energy wavelengths in the visible light region and induces skin aging and active oxygen. Studies on harmful mechanism of skin are under way. Research on blue light blocking materials in cosmetics and formulation studies are in the early stage, and the test methods related to blue light blocking measurement are not established. The blue light blocking efficacy was established by referring to the test method of the sunscreen in vitro test(COLIPA guideline, ISO 24443, FDA Final Rule on Sunscreen Testing and Labeling). The blue light blocking effect was evaluated for 17 kinds out of 27 kinds of sunscreen raw materials suggested in KFDA guideline. The Effect was 14.97% for zinc oxide and 16.32% for bishexyloxyphenol methoxyphenyl triazine, 35.47% for methylene bis-benzotriazolyltetramethylbutylphenol, and 65.96% for titanium dioxide. In addition, the effect of micro-titanium dioxide was twice as high as that of the nano-titanium dioxide. The results suggested that the light blocking effect test method can be used to search for blue light blocking materials and study cosmetic formulations.

• Journal of Broadcast Engineering
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• v.24 no.3
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• pp.472-484
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• 2019

This paper proposes a time-domain sound event detection algorithm using DNN (Deep Neural Network). In this system, time domain sound waveform data which is not converted into the frequency domain is used as input to the DNN. The overall structure uses CRNN structure, and GLU, ResNet, and Squeeze-and-excitation blocks are applied. And proposed structure uses structure that considers features extracted from several layers together. In addition, under the assumption that it is practically difficult to obtain training data with strong labels, this study conducted training using a small number of weakly labeled training data and a large number of unlabeled training data. To efficiently use a small number of training data, the training data applied data augmentation methods such as time stretching, pitch change, DRC (dynamic range compression), and block mixing. Unlabeled data was supplemented with insufficient training data by attaching a pseudo-label. In the case of using the neural network and the data augmentation method proposed in this paper, the sound event detection performance is improved by about 6 %(based on the f-score), compared with the case where the neural network of the CRNN structure is used by training in the conventional method.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.

• Ecology and Resilient Infrastructure
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• v.9 no.4
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• pp.218-227
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• 2022

This study attempted classification through deep learning-based image training for land cover classification in river spaces which is one of the important data for efficient river management. For this purpose, land cover classification analysis with the RGB image of the target section based on the category classification index of major land cover map was conducted by using the learning outcomes from the result of labeling. In addition, land cover classification of the river spaces was performed by unsupervised and supervised classification from Sentinel-2 satellite images provided in an open format, and this was compared with the results of deep learning-based image classification. As a result of the analysis, it showed more accurate prediction results compared to unsupervised classification results, and it presented significantly improved classification results in the case of high-resolution images. The result of this study showed the possibility of classifying water areas and wetlands in the river spaces, and if additional research is performed in the future, the deep learning based image train method for the land cover classification could be used for river management.

• The Korean Journal of Nuclear Medicine Technology
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• v.26 no.1
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• pp.15-26
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• 2022

Purpose Recently, in the process of examining the self-disposal of radioactive waste by the Korea Institute of Nuclear Safety, it is difficult to reach the final approval process for self-disposal. In connection with this, we intend to increase the processing efficiency of self-disposal and strengthen safety by analyzing cases of recent supplementary matters. Materials and Methods From 2018 to 2021, we compare and review a supplementary requests that preparing the procedures and plans for the self-disposal of radioactive waste by 20 institutions. In this regard, based on the provisions of the Atomic Energy Safety Act, we derive a detailed proposals for the self-disposal of radioactive waste by arranging the review processing period calculation and supplementary requests that occurred during the review process. Results The representative supplementary requests of the Korea Institute of Nuclear Safety are the calculation of the storage period by type and nuclide of radioactive waste, the contents of the packaging container, the RASIS reporting method, the planned storage method for self-disposal, confirmation of the final disposal company, and the storage period of the waste filter Calculation, radioactive labeling, etc. And it is emphasized as important. Conclusion The expected effects of the guidelines reflecting the latest supplements include reduction of the time required for document preparation and increase of work processing efficiency, improvement of storage efficiency in the radioactive waste storage room, and economic cost reduction. If the radioactive waste self-disposal guideline presented in this study is applied to the field, it is thought that it will be helpful in improving the work efficiency of those who are experiencing difficulties.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.261-268
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• 2023

[¹⁸F]Fluorocholine is a radiopharmaceutical used non-invasively in positron emission tomography to diagnose parathyroid adenoma, prostate cancer, and hepatocellular carcinoma by evaluating the choline metabolism. In this study, a radiolabeling method for [¹⁸F]fluorocholine was optimized using a solid phase extraction (SPE) cartridge. [¹⁸F]Fluorocholine was labeled in two steps using an automated synthesizer. In the first step, dibromomethane was reacted with [¹⁸F]KF/K2.2.2/K₂CO₃ to obtain the intermediate [¹⁸F]fluorobromomethane. In the second step, [¹⁸F]fluorobromomethane was passed through a Sep-Pak^Ⓡ Silica SPE cartridge to remove the impurities and then reacted with N,N-dimethylaminoethanol (DMAE) in a Sep-Pak^Ⓡ C18 SPE cartridge to label [¹⁸F]fluorocholine. The reaction conditions of [¹⁸F]fluorocholine were optimized. The synthesis yield was confirmed according to the number of silica cartridges and DMAE concentration. No statistically significant difference in the synthesis yield of [¹⁸F]fluorocholine was observed when using four or three silica cartridges (P>0.05). The labeling yield was 11.5±0.5% (N=4) when DMAE was used as its original solution. On the other hand, when diluted to 10% with dimethyl sulfoxide, the radiochemical yield increased significantly to 30.1±5.2% (N=20). In conclusion, [¹⁸F]Fluorocholine for clinical use can be synthesized stably in high yield by applying an optimized synthesis method.

• The Korean Journal of Nuclear Medicine
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• v.33 no.6
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• pp.527-536
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• 1999

Purpose: Radiotracers that bind to the central benzodiazepine receptor are useful for the investigation of various neurological and psychiatric diseases. [C-11]Flumazenil, a benzodiazepine antagonist, is the most widely used radioligand for central benzodiazepine receptor imaging by PET. We synthesized 3-(2-[F-18]fluoro)flumazenil, a new fluorine-18 ($t_{1/2}$= 110 min) labeled analogue of benzodiazepine receptor imaging agent, and evaluated in vivo for biodistribution in mice. Materials and Methods: Flumazenil (Ro 15-1788) was synthesized by a modification of the reported method. Precursor of 3-(2-[F-18]fluoro)flumazenil, the tosylated flumazenil derivative was prepared by the tosylation of the ethyl ester by ditosylethane. [F-18] labeling of tosyl substitued flumazenil precursor was performed by adding F-18 ion at $85^{\circ}C$ in the hot ceil for 20 min. The reaction mixture was trapped by C18 cartridge, washed with 10% ethanol, and eluted by 40% ethanol. Bidistribution in mice was determined after intravenous injection. Results: The total chemical yield of tosylated flumazenil derivative was ${\sim}40%$. The efficiency of labeling 3-(2-[F-18]fluoro)flumazenil was 66% with a total synthesis time of 50 min. Brain uptakes of 3-(2-[F-18]fluoro)flumazenil at 10, 30, 60 min after injection, were $2.5{\pm}0.37,\;2.2{\pm}0.26,\;2.1{\pm}0.11$ and blood activities were $3.7{\pm}0.43,\;3.3{\pm}0.07,\;3.3{\pm}0.09%ID/g$, respectively. Conclusion: We synthesized a tosylated flumazenil derivative which was successfully labeled with no-carrier-added F-18 by nucleophilic substitution.