• Journal of Korean Society of Archives and Records Management
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• v.7 no.1
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• pp.83-109
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• 2007

This paper focuses on the Bijombon Haerampeon written by Lee Eonjin The analysis of the paper is associated with the following: i) the career of Lee Eonjin ; ii) the manuscripts and collected works of Lee Eonjin ; iii) Haerampeon ; iv) Lee Yeonghyu and Nam Ok ; v) and the comparison of the Bijombon Haerampeon and Haerampeon carried in Songmokkwanjip and Songmokkwansinyeogo. Lee Eonjin(1740-1766) was a great poet and better known as one of the four great interpreters in Chosun dynasty. Woosangingbok was the only manuscripts handed down up to now among the works of Lee Eonjin. Woosangingbok ran the Bijombon Haerampeon, 6 pieces of itinery, 3 pieces of poem, 5 pieces of letter. Lee Eonjin visited Japan from the 6th of October, 1763 to the 20th of June in 1764 as a member of Tongsinsa in attendance upon Cho Om. He wrote Haerampeon vividly with five characters what he observed during his stay in Japan. It was composed on board of Ilkido from the 28th of May to the 8th of June in 1746. After Lee Yeonghyu and Nam Ok reviewed Haerampeon, Lee Yeonghyu placed a blue point and circle and Nam Ok placed a red point and circle. Ultimately the result raised the value of Haerampeon. Haerampeon is to be divide into four parts. Four parts are described below: the first part, the geographic features and products of Japan; the second part, the grow of Osaka city and the cityward tendency of world products; the third part, the racial prejudice, religion, and life; and the fourth part, the good neighborly relations with Japan. Finally, as compared with the proofing and difference of three kinds of text, namely, the Bijombon Haerampeon and Haerampeon carried in Songmokkwanjip and Songmokkwansinyeogo, it is approved that the Bijombon Haerampeon is the most correct text and has the value of cultural properties as a national treasure. The Result of this research will be contributed for research Lee Eonjin and utilized as information resources in the field of bibliographic science, Korean language and literature, and historical studies, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.542-544
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• 2022

In this study, a basic study was conducted to confirm the wound recovering ability using LEDs. After cultured fibroblast on 6-wells we formed a wound. Here, LEDs of a specific wavelength are irradiated and check the wound healing through Matlab image processing. As a result, it was confirmed that fibroblast recovered faster when LED was irradiated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.397-399
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• 2021

In this study, a basic study on the development of a multi-stimulation system was conducted to suppress lung cancer cell proliferation. Stimulation was applied to lung cancer cells using a photo-stimulating system and ultrasonic waves that generate a specific frequency, and the effect of inhibiting proliferation of cells was imaged and quantitatively evaluated. As a result of the experiment, when a single LED, single ultrasound stimulus were applied and ultrasound and LED stimuli were applied at the same time, meaningful results were shown in the proliferation rate of lung cancer cells.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.539-541
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• 2022

Photodynamic therapy is one of the ways to treat cancer using light and during laser irradiation, photosensitizers react and combine with oxygen to destroy cancer cells. This treatment is in the spotlight as a treatment that minimizes side effects in cancer patients. Among them, photosensitizers differ in the treatment area, treatment effect, and degree of absorption depending on the type. Therefore, in this study, a quantitative evaluation study was conducted on the effect of inhibiting cancer cell proliferation by irradiating blue LEDs on HELA cell lines injected with 5-ALA among photosensitizers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.323-325
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• 2022

In this paper, after administration of Chlorin e6 to kill cervical cancer cells, PDT (photodynamic therapy) using laser or LED was studied for Ce6 concentration and apoptosis by administration time. After photostimulation was applied to cervical cancer cells, qualitative and quantitative evaluation through imaging and quantitative evaluation using CCK-8 were performed. As a result of the experiment, as the concentration of Ce6 increased, a large amount of cells were killed, and it was confirmed that the Ce6+PDT test group killed more. When comparing the LED and the laser, the laser was able to kill cells only at a local location, and the LED showed the result that it was possible to kill the cells in a wide range. In addition, when irradiating a local location, such as a laser, when measuring the cell viability, it is judged to be accurate to image processing the location.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.399-401
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• 2022

A definitive diagnosis to classify the breast malignancy status may be achieved by microscopic analysis using surgical open biopsy. However, this procedure requires experts in the specializing of histopathological image analysis directing to time-consuming and high cost. To overcome these issues, deep learning is considered practically efficient to categorize breast cancer into benign and malignant from histopathological images in order to assist pathologists. This study presents a pre-trained convolutional neural network model architecture with a 100% fine-tuning scheme and Adagrad optimizer to classify the breast cancer histopathological images into benign and malignant using a 40× magnification BreaKHis dataset. The pre-trained architecture was constructed using the InceptionResNetV2 model to generate a modified InceptionResNetV2 by substituting the last layer with dense and dropout layers. The results by demonstrating training loss of 0.25%, training accuracy of 99.96%, validation loss of 3.10%, validation accuracy of 99.41%, test loss of 8.46%, and test accuracy of 98.75% indicated that the modified InceptionResNetV2 model is reliable to predict the breast malignancy type from histopathological images. Future works are necessary to focus on k-fold cross-validation, optimizer, model, hyperparameter optimization, and classification on 100×, 200×, and 400× magnification.