• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2666-2671
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• 2011

In this paper, a theoretical approach was studied to make a baseline box type model satisfying the stiffness condition of a cut-out model. First, we compared the sum of the sectional theoretical deflections and the FEM result of the cut-out model under the static load test conditions, and we obtained good correlations from both the results. Second, To obtain the thickness of the baseline model, we used the mean value of geometric moment of intertia of the side wall and roof structure. Also, we compared the theoretical results and the FEM result of a baseline model, and we obtained good correlations. It is considered that the developed theoretical approach can be used for the weight reduction of train carbodies.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.1
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• pp.63.1-63.1
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• 2012

한국천문연구원은 GMT (Giant Magellan Telescope)의 부경 중의 하나인 FSM (Fast Steering Mirror)의 시험모델을 개발 중이다. 구경 1.06m의 반사경을 가공하는 중인데, 뒷면 경량화 가공을 마쳤다. 다음 작업으로 비축 비구면의 앞면을 가공하기 위해 반사경의 지지셀을 제작 중이다. 또한 tip-tilt 제어를 위한 test-bed를 제작하여 스프링과 진공을 이용한 무게 상쇄실험을 마쳤다. 미러 셀을 제작하여 실제 상황과 비슷한 환경에서 시험하고자 한다. 또한 tip-tilt의 최종 성능시험을 위한 장치를 개발하고 있다. 이 발표에서는 FSM 시험모델의 개발 현황에 대해 논한다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.136-139
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• 2007

무선 네트워크를 사용하는 RFID 시스템은 정보 유출에 취약하다. 하지만 하드웨어적인 제약으로 인해 물리적인 방법을 통한 보안 안전성 확보가 용이하지 않으므로, 경량화된 보안 프로토콜을 필요로 한다. 이에 본 논문에서는 리더간 네트워크 기술을 이용한 RFID 시스템을 위해 제안된 보안 프로토콜을 정형기법을 기반으로 하는 모델 체킹 방법을 통해 검증하였으며, 신뢰성 있는 보안 프로토콜을 적용한 RFID 시스템을 구축할 수 있도록 하였다.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.885-887
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• 2003

부양용해 기술은 티타늄등 용해 및 주조에 어려움이 있는 기능성 금속의 용해 시 소재의 오염이나 고가의 도가니 없이 용해할 수 있는 기술로써 기계 부품 경량화 및 고강도를 위한 기술 및 신수요 창출을 위한 기반을 제공할 수 있다. 본 논문은 실기용 부양용해 cold crucible의 설계 및 제작에 앞서 모사 cold crucible에 대한 기초 자료를 바탕으로 컴퓨터 시뮬레이션을 위한 3차원 전자기장 해석 model을 구축하여, 모사 모델과의 측정값과 전자장 해석결과를 비교하여, 실제 cold crucible 설계 제작시 다양한 형태로 활용될 수 있는 기본자료를 확보하는데 그 목적이 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.719-720
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• 2024

센서 기반의 자동화재탐지설비의 역할을 지원할 목적으로, 합성곱 신경망 기반의 AI 화재 감시장비등이 연구되어왔다. ai 기반 화재 감지에 사용되는 알고리즘은 전이학습을 주로 이용하고 있고, 이는 화재 감지에 기여도가 낮은 프로세스가 내장되어 있을 가능성이 존재하여, 딥러닝 모델의 복잡성을 가중시키는 원인이 될 수 있다. 본 연구에서는 이러한 모델의 복잡성을 개선하고자 다양한 딥러닝 및 해석 기술들을 분석하였고, 분석 결과를 토대로 화재 감지에 최적화된 아키텍처인 "IF2bNet" 을 제안한다. 구현한 아키텍처의 성능을 비교한 결과 동일한 성능을 내면서, 파라미터를 약 0.1 배로 경량화 하여, 복잡성을 완화하였다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.8
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• pp.1015-1019
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• 2013

To improve the energy efficiency and ride quality of an electric vehicle, it is highly desirable to develop a lightweight suspension system with high travel ratio. Air suspension systems with a rubber tube are often considered optimal for such requirements. In this study, a new lightweight air suspension system with high travel ratio was developed for use in electric vehicles. Furthermore, an FE-based multi-flexible-body dynamics (MFBD) model of the suspension system was developed as a tool for improving the design of an actual suspension system. The MFBD model includes the FE modeling of the rubber tube module as well as other essential parts of the air suspension system. The system parameters for the model were obtained from various experiments. The validity of the developed MFBD model was shown through a comparison between the experimental results and the simulation results.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.5
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• pp.477-483
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• 2013

The widlass base frame which is currently used is designed by lots of volume and costs so as to obtain high rigidity in spite of the greatly external load. The purpose of this research is to draw conceptual design of optimal design which can satisfy high rigidity existing windlass base frame has and lessening the body at the same time. Therefore, it progressed conceptual design by applying Topology optimization and Size optimization based on the finite-element analysis for the early model and indicated the result by comparing the early model with optimized model. As the result of Topology optimization, its stress was increased by about 6MPa and weight was decreased by about 560kg in comparison with the early model. In addition, in case of Size optimization, its stress was increased by about 7MPa and weight was decreased by about 1,560kg in comparison with the early model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of Convergence Society for SMB
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• v.5 no.2
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• pp.15-20
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• 2015

Recently, as smart phone technology is developing, wearable devices is also accelerating. But, the wearable device is necessary to operated for a long time with a small electric power because werable device is made compact. In this paper, we design and implement efficient lithium polymer battery model suitable to miniaturized wearable device in oder to maximize ease of use. The proposed model is characterized by a compact size of the battery by applying a thermal element and a light-weight battery. Also, proposed model gives greatly improve the life of wearable devices because it uses a method using the characteristics of the Peltier device using the temperature difference between the room temperature and body temperature of a person to generate power for charging. In particular, the proposed model can be used for the wearable device, as well as auxiliary charging of the smart phone.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1431-1439
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• 2017

In the security field, log analysis is important to detect malware or abnormal behavior. Recently, image visualization techniques for malware dectection becomes to a major part of security. These techniques can also be used in online games. Users can leave a game when they felt bad experience from game bot, automatic hunting programs, malicious code, etc. This churning can damage online game's profit and longevity of service if game operators cannot detect this kind of events in time. In this paper, we propose a new technique of PNG image conversion based churn prediction to improve the efficiency of data analysis for the first. By using this log compression technique, we can reduce the size of log files by 52,849 times smaller and increase the analysis speed without features analysis. Second, we apply data mining technique to predict user's churn with a real dataset from Blade & Soul developed by NCSoft. As a result, we can identify potential churners with a high accuracy of 97%.