• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.836-844
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• 2020

A very large number of pixels is required to generate a computer generated hologram (CGH) with a large-size and wide viewing angle equivalent to that of an analog hologram, which incurs a very large amount of computation. For this reason, a high-performance computing device and long computation time were required to generate high-definition CGH. To solve these problems, in this paper, we propose a technique for generating high-definition CGH by arraying the pre-calculated low-definition CGH and multiplying the appropriately-shifted concave lens function. Using the proposed technique, 0.1 Gigapixel CGH recorded by the point cloud method can be used to calculate 2.5 Gigapixels CGH at a very high speed, and the recorded hologram image was successfully reconstructed through the experiment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.534-541
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• 2021

This study aims to establish an efficient future technology development strategy in the information and telecommunications industry by grasping related technology trends and fusion complexity through an analysis based on standard patents. Analyzing 1,983 patents related to the information and telecommunications industry identified the trends in major patent applicants and detailed technologies in the world. In addition, technology trends were investigated through keyword analysis to examine the degree of complexity in information and communications technology, confirming the direction of research in information technology. Electronic component and wireless communications fields have relatively few standard patents, but they are highly convergent with other industrial technologies. Computer information processes and communication and broadcasting technologies are highly related to each other, so they can be used as standard fusion technologies in standard patents. In addition, standardization activities in optical and image/sound devices are found to be high.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.70-76
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• 2021

A cylindrical microlens (CML) has been widely used as an optical element for organic light-emitting diodes (OLEDs), light diffusers, image sensors, 3D imaging, etc. To fabricate high-performance optoelectronic devices, the CML with high aspect ratio is demanded. In this work, we report on facile solution-based processes (i.e., slot-die and needle coatings) to fabricate the CML using poly(methyl methacrylate) (PMMA). It is found that compared with needle coating, slot-die coating provides the CML with lower aspect ratio due to the wide spread of solution along the hydrophilic head lip. Although needle coating provides the CML with high aspect ratio, it requires a high precision needle array module. To demonstrate that the aspect ratio of CML can be enhanced using slot-die coating, we have varied the molecular weight of PMMA. We can achieve the CML with higher aspect ratio using PMMA with lower molecular weight at a fixed viscosity because of the higher concentration of PMMA solute in the solution. We have also shown that the aspect ratio of CML can be further boosted by coating it repeatedly. With this scheme, we have fabricated the CML with the width of 252 ㎛ and the thickness of 5.95 ㎛ (aspect ratio=0.024). To visualize its light diffusion property, we have irradiated a laser beam to the CML and observed that the laser beam spreads widely in the vertical direction of the CML.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.967-973
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• 2020

As the implementation of export controls is spreading, the importance of classifying strategic items is increasing, but Korean export companies that are new to export controls are not able to understand the concept of strategic items, and it is difficult to classifying strategic items due to various criteria for controlling strategic items. In this paper, we propose a method that can easily approach the process of classification by lowering the barrier to entry for users who are new to export controls or users who are using classification of strategic items. If the user can confirm the decision result by providing a manual or a catalog for the procedure of classifying strategic items, it will be more convenient and easy to approach the method and procedure for classfying strategic items. In order to achieve the purpose of this study, it utilizes deep learning, which are being studied in image recognition and classification, and OCR(optical character reader) technology. And through the research and development of the support tool, we provide information that is helpful for the classification of strategic items to our companies.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_2
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• pp.699-706
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• 2021

Existing license plate recognition system is used as an optical character recognition method, but a method of using deep learning has been proposed in recent studies because it has problems with image quality and Korean misrecognition. This requires a lot of data collection, but the collection of license plates is not easy to collect due to the problem of the Personal Information Protection Act, and labeling work to designate the location of individual license plates is required, but it also requires a lot of time. Therefore, in this paper, to solve this problem, five types of license plates were created using a virtual Korean license plate generation program according to the notice of the Ministry of Land, Infrastructure and Transport. And the generated license plate is synthesized in the license plate part of collectable vehicle images to construct 10,147 learning data to be used in deep learning. The learning data classifies license plates, Korean, and numbers into individual classes and learn using YOLOv5. Since the proposed method recognizes letters and numbers individually, if the font does not change, it can be recognized even if the license plate standard changes or the number of characters increases. As a result of the experiment, an accuracy of 96.82% was obtained, and it can be applied not only to the learned license plate but also to new types of license plates such as new license plates and eco-friendly license plates.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.79-84
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• 2022

This paper presents an enhancement method of document restoration capability which is robust for security, loss, and contamination, It is based on two methods, that is, encryption and DnCNN(DeNoise Convolution Neural Network). In order to implement this encryption method, a mathematical model is applied as a spatial frequency transfer function used in optics of 2D image information. Then a method is proposed with optical interference patterns as encryption using spatial frequency transfer functions and using mathematical variables of spatial frequency transfer functions as ciphers. In addition, by applying the DnCNN method which is bsed on deep learning technique, the restoration capability is enhanced by removing noise. With an experimental evaluation, with 65% information loss, by applying Pre-Training DnCNN Deep Learning, the peak signal-to-noise ratio (PSNR) shows 11% or more superior in compared to that of the spatial frequency transfer function only. In addition, it is confirmed that the characteristic of CC(Correlation Coefficient) is enhanced by 16% or more.

• Journal of the Korean Wood Science and Technology
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• v.30 no.2
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• pp.79-86
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• 2002

Anatomical characteristics of Mulpurenamu (Korean ash, Praxmus rhynchopbylla), Deulmaenamu (Manshurican ash, Fraxinus mandsburica) and Sheamulpure (Sieboldiana ash, Fraxinus sieboldiana) grown in Korea were examined by an optical microscopy and an image analysis. Some characteristics such as boundary of annual rings, shape and size of vessel elements, arrangement of axial parenchyma cells in cross section, and cell volumetric composition showed significant differences between the sample species. In radial variation of elements, fiber length and vessel size increased from the pith for about 10 to 15 years and then reached a more or less constant. The results of this study can be used for identification of wood and indices of wood quality in Fraxinus spp.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.5
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• pp.29-41
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• 2022

Alien species cause problems in various ecosystems, reduce biodiversity, and destroy ecosystems. Due to these problems, the problem of a management plan is increasing, and it is difficult to accurately identify each individual and calculate the number of individuals, especially when researching alien turtle species such as GPS and PIT based on capture. this study intends to conduct an individual recognition study using a UAV. Recently, UAVs can take various sensor-based photos and easily obtain high-definition image data at low altitudes. Therefore, based on previous studies, this study investigated five variables to be considered in UAV flights and produced a test paper using them. OCR was used to monitor the displayed turtles using the manufactured test paper, and this confirmed the recognition rate. As a result, the use of yellow numbers showed the highest recognition rate. In addition, the minimum threat distance was confirmed to be 3 to 6m, and turtles with a shell size of 6 to 8cm were also identified during the flight. Therefore, we tried to propose an object recognition methodology for turtle display text using OCR, and it is expected to be used as a new turtle monitoring technique.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.129-149
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• 2022

Records have temporal characteristics, including the past and present; linguistic characteristics not limited to a specific language; and various types categorized in a complex way. Processing records such as text, video, and audio in the life cycle of records' creation, preservation, and utilization entails exhaustive effort and cost. Primary natural language processing (NLP) technologies, such as machine translation, document summarization, named-entity recognition, and image recognition, can be widely applied to electronic records and analog digitization. In particular, Korean deep learning-based NLP technologies effectively recognize various record types and generate record management metadata. This paper provides an overview of Korean NLP technologies and discusses considerations for applying NLP technology in records management. The process of using NLP technologies, such as machine translation and optical character recognition for digital conversion of records, is introduced as an example implemented in the Python environment. In contrast, a plan to improve environmental factors and record digitization guidelines for applying NLP technology in the records management field is proposed for utilizing NLP technology.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.715-722
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• 2022

If you don't regularly go to the dentist to check your teeth, it is difficult to notice cavities or various diseases of your teeth until you have pain or discomfort. Dental plaque is produced by the combination of food or foreign substances and bacteria in the mouth. Starch breaks down from the bacteria that form tartar. The acid that occurs at this time melts the enamel of the teeth and becomes a cavity. So tartar management is important. Poppyrin, the metabolism of bacteria in the mouth, reacts at 405 nm wavelengths and becomes red fluorescent, which can be seen by imaging through certain wavelength filters. By the above method, Frag and tartar are fluorescently detected and photographed with a yellow series of filters that pass wavelengths of 500 nm or more. It uses MATLAB to detect and display red fluorescence through image processing. Using the difference in voltage between normal teeth and tartar through an optical measuring circuit, it was connected to an Arduino and displayed on the LCD. This allows the user to know the presence and location of dental plaque more accurately.