• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.765-771
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• 2019

Noise in skull X-ray imaging is inevitable, which reduces imaging quality and diagnostic accuracy and increases errors due to the nature of digital imaging devices. Increasing the dose can attenuate noise, but that could lead to big problems with higher exposure dose received by patients. Thus, noise reduction algorithms are actively being studied at low doses to solve dose problems and reduce noise at the same time. Wiener filter and median filter have been widely used, with the disadvantages of poor noise reduction efficiency and loss of much information about imaging boundary. The purpose of this study is to apply total variation (TV) algorithm to skull X-ray imaging that can compensate for the problems of previous noise reduction efficiency to assess quantitatively and compare them. For this study, skull X-ray imaging is obtained using various kVp and mAs using the skull phantom using the X-ray device of Siemens. In addition, contrast to noise ratio (CNR) and coefficient of variation (COV) are compared and measured when noisy image, median filter, Wiener filter and TV algorithm were applied to each phantom imaging. Experiments showed that when TV algorithms were applied, CNR and COV characteristics were excellent under all conditions. In conclusion, we've been able to see if we can use TV algorithm to improve image quality and CNR could be seen to increase due to the decrease in noise as the amount of increased mAs. On the other hand, COV decreased as the amount of increased mAs, and when kVp increased, noise was reduced and the transmittance was increased, so COV was reduced.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.48-48
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• 2019

Amorphophallus paeoniifolius (Dennst.) Nicolson는 영명으로 Elephant yam 또는 Whitespot giant arum 으로 불리는 천남성과(Araceae) 식물로 동아시아, 뉴기니, 오세아니아, 마다가스카르 등지에서 자생하고 있으며 숲의 가장자리 또는 2차림에서 발견 된다. 다년생 식물로 덩이줄기는 어두운 갈색의 둥근모양으로 직경 20~25 cm로 자라고 수염뿌리가 사방으로 달린다. IUCN 적색목록(Red List)에 관심대상 종(LC: Least Concern)에 속하는 식물이다. 현지인들은 마(Dioscorea Polystachya Turcz.)처럼 채소로 먹기도 하며 약용으로 쓰이기도 하는데 복부장애, 소화불량, 천식, 기관지염, 빈혈 등에 약효가 있다. Amorphophallus paeoniifolius은 $25^{\circ}C{\sim}35^{\circ}C$, 연강수량 1,000~1,500 mm에서 잘 자란다. 가운데 눈이 올라오면서 생장을 시작하고 며칠이 지나서야 잎 또는 꽃으로 자라는지 알 수 있다. 잎의 생육주기는 잎눈이 생장을 시작하면 잎자루 끝에 소엽과 소잎자루가 접힌 채로 올라온다. 소엽들이 펴지면서 완전한 모습을 갖추는데 30일 이상의 생장기간을 갖는다. 잎의 형태는 우상복엽(pinnate compound leaf)으로 우산처럼 보이는 잎 하나로 광합성을 한다. 잎은 최대 높이 2.5~3 m, 너비 3 m까지 자라며, 잎자루의 색은 녹색과 청색으로 얼룩덜룩한 무늬가 있다. 인공환경 조건에서 Amorphophallus paeoniifolius 생활사 중 잎의 주기를 연구하기 위해서 광, 온도 등의 지상부 환경은 열대 및 아열대 식물의 자생지와 유사하게 조성하였고, 지하부 환경은 인공 배합토를 사용하여 조성하였다. 평균온도는 $25{\sim}28^{\circ}C$, 겨울철 최저 $16^{\circ}C$, 여름철 최고 $33^{\circ}C$를 유지 관리 하였다. 자동 환경제어시스템으로 온도 및 환기를 유지 관리하고 필요에 따라 수동제어 관리를 병행하여 조절하였다. Amorphophallus paeoniifolius는 잎을 먼저 생성하고 광합성으로 생산된 영양물질을 덩이뿌리에 저장을 하고 그 영양물질을 이용하여 꽃을 피우는 생육 특성을 지닌다. 실험에 사용된 공시 식물은 2018년 12월 미얀마에서 생체(덩이줄기) 형태로 도입되었다. 화분에 식재 후 약 5개월이 지난 시점에서 잎의 생장이 시작되었다. 2019년 7월 29일 기준으로 높이 80 cm, 너비 60 cm의 크기로 성장하였으며, 생육환경에 따라 3~5개월 뒤 잎이 지고 나면 다시 덩이줄기로 되돌아갈 것으로 판단된다. 하지만 지금까지 이 식물에 알려진 정보는 인공환경에서의 연구가 아닌 자연환경에서의 연구결과이기 때문에 인공적인 온실 환경에서 자란 Amorphophallus paeoniifolius는 잎의 주기는 더 오래 갈 수도 있으며 꽃의 주기 또한 느리거나 빠를 수 있다. 잎의 생장주기(Leaf Cycle)시 잎자루가 낮과 밤의 방향을 달리 하여 자라는 것이 관찰되었다. 이는 광합성을 위해서 잎자루의 방향을 햇빛 방향으로 돌리는 것으로 판단된다. Amorphophallus paeoniifolius를 실내 조경 식물 또는 식 약용의 소재식물로 활용하기 위해서는 꽃의 생장주기 등 추가적인 모니터링과 연구가 필요하다.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.358-365
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• 2019

This study was conducted to estimate the dimensions of horticultural products and the mean plant height of plug seedlings using three-dimensional (3D) images. Two types of camera, a ToF camera and a stereo-vision camera, were used to acquire 3D images for horticultural products and plug seedlings. The errors calculated from the ToF images for dimensions of horticultural products and mean height of plug seedlings were lower than those predicted from stereo-vision images. A new indicator was defined for determining the mean plant height of plug seedlings. Except for watermelon with tap, the errors of circumference and height of horticultural products were 0.0-3.0% and 0.0-4.7%, respectively. Also, the error of mean plant height for plug seedlings was 0.0-5.5%. The results revealed that 3D images can be utilized to estimate accurately the dimensions of horticultural products and the plant height of plug seedlings. Moreover, our method is potentially applicable for segmenting objects and for removing outliers from the point cloud data based on the 3D images of horticultural crops.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.415-423
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• 2021

Citizen participation and Living Lab are attracting interest as one of the major strategies for the success of smart cities. In a Living Lab, citizens, who are the end-users of technology, participate in the search for alternatives to define and solve problems and repeat experiments to verify alternatives in a circular process. The purpose of this research was to present an operating model of a citizen-participating online community platform to improve urban problems, implement and test it, and show its applicability. To this end, an operation model of a citizen-participating online community platform was proposed to improve urban problems. An online platform was designed and implemented to reflect the functions pursued by the operation model. Finally, a pilot test for the function was performed using the Oma Elementary School case located in Ilsan, Goyang-si, Gyeonggi-do. The operating model was designed with the city's pedestrian environment and children. As a result, the sharing and communicating process of urban issues among community members worked appropriately according to the designed intention. The Living Lab coordinator could visualize and view urban issues posted by users on a map based on location information. Visualizing the urban problem as a heat map confirmed that urban problems were concentrated in a specific area.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.194-204
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• 2021

The reason why domestic fermented tea is less recognized than the world's top three black[Sri Lanka Uva black tea, India Darjeeling black tea, China Keemun(祁門) black tea] teas is that there is a very lack of scientific basis for clear quality standards and functionality. This researcher identified the major components of the world's top three black teas and fermented teas derived from domestic wild tea trees through analysis of various instruments such as HPLC, TOF-MS, and ELISA reader. In addition, in order to compare the physiological activity of the world's three major black teas and domestic fermented teas, the biological activity was compared and analyzed through DPPH·ABTS free radical scavenging activity and NO production inhibition. Furthermore, comparative analysis data on organic acid, free sugar, and tannic acid were obtained for quality comparison of palatable foods. When the above results are summarized, it is believed that it is possible to present the quality standards of Korean tea, and it is expected that the globalization of Korean tea will be possible.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.105-118
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• 2021

This study pays attention to the fact that the fake news is attracting attention because it causes various social problems. To find out these fake news' influence, the study conducted the experiment to examine that the fake news related to the electronic voting system affects on the news users' attitude of using the system, intention to participate in the election through the system and reliability of news services. The results have shown that the fake news framed with negative contents reduced users' attitude of using the system and intention of participation in the election. Especially, as a result of examining the difference in the fake news' influence according to each news services, in the case that users recognized that the news was fake after exposing to the general internet news, the attitude of using the system and the intention of participation in the election have reduced and recovered again. However, users who exposed to Naver, Facebook believed the negative content of the fake news more strongly. Through these results, this study empirically confirmed that the fake news has a tendency to exert influence on users' cognitive dimension and to reinforce awareness in a direction consistent with the initial exposure information.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.269-282
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• 2021

As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.116-126
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• 2021

Ground Component Command (GCC) has been developing operational planning and execution systems to implement "Decisive Integrated Operations", which is the concept of ground operations execution, and achieved remarkable results. In particular, "Simultaneous Offense-Defense Integrated Operations" is developed mainly to neutralize enemies in deep areas and develop favorable conditions for the allies early by simultaneously attacking and defending from the beginning of the war. On the other hand, it is limited to providing scientific and reasonable support for the commander's decision-making process because analyzing the effects of the deep operation with existing M&S systems is impossible. This study developed a model for analyzing the effects of deep operations that can be used in the KJCCS. Previous research was conducted on the effects of surveillance, physical strike, and non-physical strike, which are components of deep operations to find the characteristics and limitations and suggest a research direction. A methodology for analyzing the effects of deep operations reflecting the interactions of components using data was then developed by the GCC, and input data for each field was calculated through combat experiments and a literature review. Finally, the Deep operations Effect CAlculating Model(DECAM) was developed and distributed to the GCC and Corps battle staff during the ROK-US Combined Exercise. Through this study, the effectiveness of the methodology and the developed model were confirmed and contribute to the development of the GCC and Corps' abilities to perform deep operations.

• (The) Korean Journal of Advertising
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• v.28 no.2
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• pp.7-25
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• 2017

The previous studies regarding prosocial behavior have been researched based on donors' personal traits and the effects of donees emotions. However, studies in identifying the effects of regulatory focus as motivational traits and the emotions resulting from donees' expression on prosocial behaviors have not been researched as much thoroughly. Specifically, consumers with prevention-focus perceive fit as the goal attainability process by avoiding negative factors. Thus, it is expected that the intentions of doing a charitable deed greater will more increase when the donees look sad than when they look happy. On the other hand, consumers with promotion-focus perceive fit as the consequential benefits of goal attainability when they are in the condition of a positive emotion. As a result, the intention of doing a charitable deed is expected to be increased greater when the donees have happier faces than sad faces. According to the experimental results, consumers with prevention focus more intended to do a charitable deed when the donees' expression was presented with a sad expression by mediating sadness. On the contrary, consumers with promotion focus show higher intention of doing a charitable deed when the donees looked happier by mediating happy feelings. This study has a theoretical meaningfulness in respect to expanding previous research concerning regulatory focus into donation contexts. Furthermore, this study has practical implications by presenting the donation strategies on information presentations of donees.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.31-39
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• 2018

Recently, there has been active studies to provide a user-friendly interface in a virtual reality environment by recognizing user hand gestures based on deep learning. However, most studies use separate sensors to obtain hand information or go through pre-process for efficient learning. It also fails to take into account changes in the external environment, such as changes in lighting or some of its hands being obscured. This paper proposes a hand gesture recognition method based on deep learning that is strong in external environments without the need for pre-process of RGB images obtained from general webcam. In this paper we improve the VGGNet and the GoogLeNet structures and compared the performance of each structure. The VGGNet and the GoogLeNet structures presented in this paper showed a recognition rate of 93.88% and 93.75%, respectively, based on data containing dim, partially obscured, or partially out-of-sight hand images. In terms of memory and speed, the GoogLeNet used about 3 times less memory than the VGGNet, and its processing speed was 10 times better. The results of this paper can be processed in real-time and used as a hand gesture interface in various areas such as games, education, and medical services in a virtual reality environment.