• 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.

• Advances in nano research
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• v.15 no.6
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• pp.579-585
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• 2023

This research delves into the intricate dynamics of the flight response exhibited by a golf ball that incorporates nanoparticles with the goal of enhancing its overall quality. The golf ball is meticulously modeled utilizing beam elements, and the impact of nanoparticles is intricately captured through the application of the Halpin-Tsai theory. Employing a numerical solution, the study thoroughly explores the flight response of the golf ball, taking into account the nuanced effects of the embedded nanoparticles. By scrutinizing the aerodynamic characteristics through advanced simulations, this investigation aims to provide valuable insights that could potentially revolutionize the design and performance of golf equipment, offering a pathway towards superior quality and enhanced functionality in the realm of golf ball technology. Results show that increase in the volume percent of nanoparticles, improves the flight response of the golf ball.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.spc1
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• pp.108-118
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• 2024

As shared electric kick scooters spread to cities worldwide as a result of the proliferation of personal mobility, they have emerged as a significant social issue, impacting pedestrian and user safety, as well as urban aesthetics. In this study, we propose solutions to the unique problems associated with shared electric kick scooters, such as illegal parking, charging, and redistribution. Furthermore, we present research on supplementary services utilizing electric kick scooters in urban areas to enhance citizen safety and user satisfaction through the development of an autonomous electric kick scooter system structure and operational strategies. We suggest a low-cost autonomous electric kick scooter structure and propose AI processing, sensor fusion, and system operation methods to add autonomous capabilities to affordable electric kick scooters. Additionally, we propose operational systems and related technologies for offering various supplementary services.

• Steel and Composite Structures
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• v.51 no.1
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• pp.43-51
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• 2024

In the current study, we aim to evaluate both microstructural characteristics and economic benefits of composite structures from supply chain utilizing AI-based method. In this regard, the various aspects of microstructure of composite materials along with the features of supply chain are discussed and quantified. In addition, the final economic aspects of the composite materials and are also presented. Based on available data, a designed artificial neural network is utilized for prediction of both microstructure and economical feature of the composite material. The results indicate that the supply chain could affect the microstructure of final composite materials which in turn make changes in the mechanical properties and durability of composite materials.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.401-402
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• 2024

인공지능 기술은 사회 전반에 걸쳐 다양한 분야에서 활용되고 있다. 그러나 인공지능 기술의 발전과 함께 인공지능 기술을 악용한 적대적 공격의 위험성도 높아지고 있다. 적대적 공격은 작은 왜곡으로도 의료, 교통, 커넥티드카 등 인간의 생명과 안전에 직결되는 인공지능 학습 모델의 성능에 악영향을 미치기 때문에 효과적인 탐지 기술이 요구되고 있다. 본 논문에서는 설명 가능한 AI 를 활용한 적대적 공격을 탐지하는 최신 연구 동향을 분석한다.