• Structural Monitoring and Maintenance
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• v.7 no.1
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• pp.59-67
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• 2020

This study aims to develop the fuzzy risk assessment model of the debris flow to verify the accuracy of risk assessment in order to help related organizations reduce losses caused by landslides. In this study, actual cases of landslides that occurred are utilized as the database. The established models help us assess the occurrence of debris flows using computed indicators, and to verify the model errors. In addition, comparisons are made between the models to determine the best one to use in practical applications. The results prove that the risk assessment model systems are quite suitable for debris flow risk assessment. The reproduction consequences of highlight point discovery are shown in highlight guide coordinating toward discover steady and coordinating component focuses and effectively identified utilizing these two systems, by examining the variety in the distinguished highlights and the element coordinating.

• Korean Journal of Optics and Photonics
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• v.5 no.2
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• pp.311-318
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• 1994

We fabricated fiber-optic polarizers utilizing polarization selective mode coupling between the guided mode of a fiber and the surface plasmon mode supported by a thin aluminium film deposited on the polished side of a fiber. AI thin films with various thicknesses were coated onto the 633 nm, 830 nm, 1.3 fJITI single mode fibers. The maximum extinction ratio was higher than 30 dB for most of the samples and the best result was 42 dB at 90 A film thickness, with 1.3 fJITI single mode fiber. The insertion loss ranged from 0.2 dB to 1.5 dB.1.5 dB.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1382-1383
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• 2008

In this paper, we have studied for analysis of the partial discharge(PD) signal based on fuzzy algorism. Partial discharge signal detector is difficult because of partial discharge signal is very non-linear. Also, it is very difficult work that separate partial discharge signal from noise. We constructed partial discharge accumulation detection system that use Labview for detection of non-linear partial discharge signal. And analyzed Partial discharge signal that is detected by Labview system utilizing Fuzzy model.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.4
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• pp.791-796
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• 2001

Friction stir welding is a solid phase welding process that does not melt the metal when welding. The FSW is the most remarkable and potentially useful new welding technique that is still in development. Friction stir butt welding process on 2 mm thick Al 1050 plates by utilizing a milling machine was experimentally studied. With the optimized heat generating tool welds could be achieved that are void and crack free. It was found that the friction stir welded tensile test specimens failed in the HAZ outside of the weld metal, and that the tensile strength was above 90% of that of the base metal.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.85-90
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• 2012

In Korea, livestock has grown into the most value-added business in the agricultural and forest industry. But due to the recent outbreak of deadly infectious diseases such as foot-and-mount disease and avian influenza (AI), the demand for IT-enabled cutting-edge management system is getting stronger. As for humans, pilot projects and researches concerning U-healthcare have been carried out since early 2000. So this study explored the current progress of U-healthcare introduction, and suggested the strategies to develop technologies of collecting, processing, and utilizing information; to apply elements for a service model development and prioritization; to provide policy and institutional support. Therefore it is expected to vitalize the livestock U-healthcare in the future through continuous study based on these results.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.263-272
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• 2021

At a time when securing driving safety is the most important in the development and commercialization of autonomous vehicles, AI and big data-based algorithms are being studied to enhance and optimize the recognition and detection performance of various static and dynamic vehicles. However, there are many research cases to recognize it as the same vehicle by utilizing the unique advantages of radar and cameras, but they do not use deep learning image processing technology or detect only short distances as the same target due to radar performance problems. Radars can recognize vehicles without errors in situations such as night and fog, but it is not accurate even if the type of object is determined through RCS values, so accurate classification of the object through images such as cameras is required. Therefore, we propose a fusion-based vehicle recognition method that configures data sets that can be collected by radar device and camera device, calculates errors in the data sets, and recognizes them as the same target.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.195-200
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• 2019

Media art, which is a combination of media technology and art, is making a lot of progress in combination with AI, IoT and VR. This paper aims to meet people's needs by creating a video that simulates the dance moves of an object that users admire by using media art that features interactive interactions between users and works. The project proposed a universal image synthesis system that minimizes equipment constraints by utilizing a deep running-based Skeleton estimation system and one of the deep-running neural network structures, rather than a Kinect-based Skeleton image. The results of the experiment showed that the images implemented through the deep learning system were successful in generating the same results as the user did when they actually danced through inference and synthesis of motion that they did not actually behave.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.228-233
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• 2021

In this study, we analyze the credit information (loan, delinquency information, etc.) of individual business owners to generate voluminous training data to establish a bankruptcy prediction model through a partial synthetic training technique. Furthermore, we evaluate the prediction performance of the newly generated data compared to the actual data. When using conditional tabular generative adversarial networks (CTGAN)-based training data generated by the experimental results (a logistic regression task), the recall is improved by 1.75 times compared to that obtained using the actual data. The probability that both the actual and generated data are sampled over an identical distribution is verified to be much higher than 80%. Providing artificial intelligence training data through data synthesis in the fields of credit rating and default risk prediction of individual businesses, which have not been relatively active in research, promotes further in-depth research efforts focused on utilizing such methods.

• International journal of advanced smart convergence
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• v.11 no.3
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• pp.79-84
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• 2022

Due to a series of online sex crimes cases and online class conversions caused by the spread of the coronavirus, alternatives to sex education in schools are urgently required. As a result of this study, the metaverse sex education platform was designed. Using this platform, learners are expected to cultivate correct adult awareness and digital citizenship. Within the metaverse platform, learners can participate more actively in learning. Instead of exposing one's name and face in a place dealing with sensitive gender issues, one can participate in education through his or her decorated avatar and participate in education much more actively than face-to-face education and express one's opinion through chat. In addition, education by level can be received regardless of time and place, which can have the effect of bridging the educational gap between urban and rural areas. In this paper, we propose a new sex education platform without time and space constraints by utilizing metaverse.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.251-252
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• 2009

본 논문에서는 AIS의 표준 메시지 포맷과 사양을 확장하여 선박의 항해안전을 향상시키고 AIS시스템의 활용을 극대화할 수 있는 AIS 데이타 응용 포맷과 사양을 개발하여 제안하였다. 그리고 국내에서 적극적으로 활용되기 위해서 필요한 6비트 체계를 사용하는 AIS통신에서의 한글메시지의 구현방안을 제시하여 메시지의 한글화 및 단말기의 한글화 방안도 마련하였다. 테스트 결과 개발된 포맷들은 여객선의 운항관리나 교통방송, 어선의 입출항 및 어획량 보고, NAVTEX정보, 구난정보, 기상정보등을 전송할 수 있게 되어 그 활용범위는 광범위하고 특히 GPS플로터나 ECDIS같은 전자해도 기반의 항해시스템과 연동되면 선박의 해양사고 발생을 미연에 방지함은 물론 해상교통안전 향상 및 사고취약선박에 대한 안전향상에 큰 도움이 될 것으로 기대된다.