• Journal of Science and Technology Studies
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• v.11 no.1
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• pp.89-121
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• 2011

The majority of previous researchers on body management practices including plastic surgery has agreed that there is a strong connection between social demands of plastic surgery and public exposures of beautiful body-images, which this research intends to analyze further. This study, on the one hand, discovers how body-images are produced and consumed through clinical practices of plastic surgery, particularly, surgeon-patient consultation processes based on the researcher's participant observation on a plastic surgery clinic in Korea, and shows how visualization technologies are mobilized to reconstruct not only boundaries of patients' bodies but also those of medical disciplines by viewing plastic surgery practices as knowledge production activities, on the other hand. While revealing that surgeon-patient consultation is the process to transform patient's bodies to "scientific" objects and visualization technologies have been made to help plastic surgeons to make their disciplines "scientific" ones, this article also pays attention to complicated effects of new imaging technology beyond a mere means of "scientification" of plastic surgery.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.938-942
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• 2007

The importance of process improvement under construction has arisen from recent issue, lower productivity in the construction site. The various 3D modeling program is utilized in the procedure of construction as an alternative solution. However, it's still shortage of the consideration about a specific technical application. The purpose of the study in this paper is helpful to improve the productivity of construction site using 3D realization of constructing place as one of extensive modeling technologies, which leads to not only efficient management of construction site allowing people to check the real time situation in the place but also the revitalization of information flow about building process control and prgress, Therefore, I research into modeling algorithm and extensive construction site realization technology. 3D realization of building place would reduce the safety concerns by providing the real time information about construction site, and it could help to access easily to similar project through collecting and appling the database of sites. Furthermore it can be an opportunity to develop the procedure of production in construction industry and to upgrade the image of this field.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.684-692
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• 2016

In the manufacturing process of the LQFP/TQFP (Low-profile Quad Flat Package/Thin Quad Flat Package), the requirement of a 3 dimensional inspection is increasing rapidly and a 3D inspection of the shape of a chip has become an important report of quality control. This study developed a 3 dimensional measurement system based on PMP (Phase Measuring Profilometry) for an inspection of the LQFP/TQFP chip and image processing algorithms. The defects of the LQFP/TQFP chip were classified according to the dimensions. The 2 dimensional optical system was designed by the dorm illumination to achieve constant light distribution, In the 3 dimensional optical system, PZT was used for moving 90 degree in phase. The problem of 2 ambiguity was solved from the measured moir? pattern using the ambiguity elimination algorithm that finds the point of ambiguity and refines the phase value. The proposed 3D measurement system was evaluated experimentally.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.463-466
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• 2010

In this paper, CCTV based fire surveillance system should aim to development. Advantages and Disadvantages analyzed of Existing sensor-based fire surveillance system and video-based fire surveillance system. To national support U-City, U-Home, U-Campus, etc, spread the ubiquitous environment appropriate to fire surveillance system model and a fire judgement technology. For this study, Microsoft LifeCam VX-1000 using through the capturing images and analyzed for apple and tomato, Finally we used H.264. The client uses the Linux OS with ARM9 S3C2440 board was manufactured, the client's role is passed to the server to processed capturing image. Client and the server is basically a 1:1 video communications. So to multiple receive to video multicast support will be a specification. Is fire surveillance system designed for multiple video communication. Video data from the RGB format to YUV format and transfer and fire detection for Y value. Y value is know movement data. The red color of the fire is determined to detect and calculate the value of Y at the fire continues to detect the movement of flame.

• Journal of the Korean Wood Science and Technology
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• v.47 no.2
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• pp.229-238
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• 2019

Various wood defects occur during tree growing or wood processing. Thus, to use wood practically, it is necessary to objectively assess their quality based on the usage requirement by accurately classifying their defects. However, manual visual grading and species classification may result in differences due to subjective decisions; therefore, computer-vision-based image analysis is required for the objective evaluation of wood quality and the speeding up of wood production. In this study, the SIFT+k-NN and CNN models were used to implement a model that automatically classifies knots and analyze its accuracy. Toward this end, a total of 1,172 knot images in various shapes from five domestic conifers were used for learning and validation. For the SIFT+k-NN model, SIFT technology was used to extract properties from the knot images and k-NN was used for the classification, resulting in the classification with an accuracy of up to 60.53% when k-index was 17. The CNN model comprised 8 convolution layers and 3 hidden layers, and its maximum accuracy was 88.09% after 1205 epoch, which was higher than that of the SIFT+k-NN model. Moreover, if there is a large difference in the number of images by knot types, the SIFT+k-NN tended to show a learning biased toward the knot type with a higher number of images, whereas the CNN model did not show a drastic bias regardless of the difference in the number of images. Therefore, the CNN model showed better performance in knot classification. It is determined that the wood knot classification by the CNN model will show a sufficient accuracy in its practical applicability.

• Korean Journal of Heritage: History & Science
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• v.52 no.1
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• pp.170-189
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• 2019

Sochi Heo Ryun (小癡 許鍊, 1808-1893) was a literary artist of Chinese paintings of the Southern School during the late Joseon dynasty and the founder of paintings in the literary artist's style of Jindo County in South Jeolla Province. He was also a professional literary artist who acquired both learning and painting techniques under Choui (a Zen priest) and Kim Jeong-hee's teachings. Heo Ryun's landscape paintings were influenced by Kim Jung -hee. However, his ink orchid paintings, which he began producing in his later years, were not related to the 'Ink Orchid Paintings of Chusa (秋史蘭)'. His ink orchid paintings as a whole drew attention as he followed the old methods but still used rough brush strokes . Ordinary orchids were drawn based on Confucian content. However, his Jebal (題跋) and seal (印章) contain not only Confucian characters but also Taoist and Buddhist meanings. Therefore, it is possible to guess his direction of life and his private world of suffering. Ryun's ink orchid paintings reflected a variety of philosophies and aesthetic sensibilities. He went through a process of stylistic change over time and formed an 'Ink Orchid Painted Thought' in later life. The main characteristic of Sochi's ink orchid paintings is that he formed his own special methods for orchid paintings by mimicking the Manuals of Paintings. He drew orchids with his fingers in the beginning. Then, Jeongseop, Lee Ha-eung, Cho Hee-ryong, and others developed an organic relationship with the painting style of ink orchid paintings. Then in later years, orchid paintings reached the point of 'Picture Painted Thought (寫意畵)'. The above consideration shows that ink orchid paintings, which he produced until the end of his life, were the beginning of his mental vision and will to realize the image of a literal artist.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.10-15
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• 2020

Ultraviolet rays, which have wavelengths smaller than 400 nm, are very harmful to the eyes. Recently, high-energy visible light was also revealed to be harmful to retinal cells. Therefore, polymer eyeglass lenses that can block UV and high-energy visible light are needed for eye health. In this study, high-refractive-index polymer eyeglass lens, n=1.67, were manufactured using the injection-mold method with the m-xylene diisocyanate monomer, 2,3-bis((2-mercaptoethyl)thio)-1-propanethiol monomer, benzotriazole UV absorber, release of alkyl phosphoric ester, dye mixture of CI solvent violet 13, and catalyst of dibutyltin dichloride mixture. A multi-layer anti-reflection coating was applied to manufactured polymer eyeglass lenses for both sides using an E-beam evaporation system. The optical properties of the manufactured lenses with the UV and high-energy visible light-blocking function were analyzed by UV-visible spectrophotometry. As a result, the polymer eyeglass lens with a UV absorber of 0.5 wt. % blocked 99% of UV and high-energy visible light shorter than 411 nm. The average transmittance of the polymer eyeglass lens with a UV absorber of 0.5wt.% was 97.9% in the range of 460 ~ 660 nm for photopic eye sensitivity higher than 10%. Therefore, clear image acquisition in photopic vision is possible.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.263-278
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• 2022

With the recent advent of IoT technology, automatic pet feeders are being distributed so that owners can feed their companion animals while they are out. However, due to behaviors of pets, the method of measuring weight, which is important in automatic feeding, can be easily damaged and broken when using the scale. The 3D camera method has disadvantages due to its cost, and the 2D camera method has relatively poor accuracy when compared to 3D camera method. Hence, the purpose of this study is to propose a deep learning approach that can accurately estimate weight while simply using a 2D camera. For this, various convolutional neural networks were used, and among them, the ResNet101-based model showed the best performance: an average absolute error of 3.06 grams and an average absolute ratio error of 3.40%, which could be used commercially in terms of technical and financial viability. The result of this study can be useful for the practitioners to predict the weight of a standardized object such as feed only through an easy 2D image.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.51-58
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• 2022

Drivable area detection, one of the main functions of advanced driver assistance systems, means detecting an area where a vehicle can safely drive. The drivable area detection is closely related to the safety of the driver and it requires high accuracy with real-time operation. To satisfy these conditions, V-disparity-based method is widely used to detect a drivable area by calculating the road disparity value in each row of an image. However, the V-disparity-based method can falsely detect a non-road area as a road when the disparity value is not accurate or the disparity value of the object is equal to the disparity value of the road. In a road environment including vegetation, such as a highway and a country road, the vegetation area may be falsely detected as the drivable area because the disparity characteristics of the vegetation are similar to those of the road. Therefore, this paper proposes a drivable area detection method and hardware architecture with a high accuracy in road environments including vegetation areas by reducing the number of false detections caused by V-disparity characteristic. When 289 images provided by KITTI road dataset are used to evaluate the road detection performance of the proposed method, it shows an accuracy of 90.12% and a recall of 97.96%. In addition, when the proposed hardware architecture is implemented on the FPGA platform, it uses 8925 slice registers and 7066 slice LUTs.