• Journal of Navigation and Port Research
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• v.36 no.10
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• pp.795-801
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• 2012

This paper describes theoretical approach methodology for the Probability based risk Evaluation Techniques (PET) to monitor the risk levels of small-sized sea floater as like a yacht pier. The risk decision-making process by risk criteria with five-step scales is the core concepts of PET. These five-step scales are calculated from cumulative probability distribution of response functions for the sea floater motions using closed-form expressions. In addition, The risk decision-making process of PET with the risk criteria is proposed in this work. To verify the usability of PET, simulation experiments are carried out using mimic signals with the electrical specifications of ADIS16405 sensor that is to be use as measurement tool for the floater motions. As results from experiments, the risk evaluation error by PET shows 0.38 levels in maximum 5.0 levels. These results clearly shown that the proposed PET can be use as the monitoring techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1394-1402
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• 2011

This paper describes solar light collecting system which employs parabolic reflector and Fresnel lens and its industrial application. We have introduced second-stage optical system so that it makes optical fiber overcome its numerical aperture limitation and also it makes focused light become collimated, which results in decreased light energy density. As result of these, light collecting efficiency become maximized and the system does not require separate cooling apparatus any more. The developed solar lighting system together with artificial light source like LED has been applied to plant factory as a hybrid lighting source. This makes us save electric energy for artificial lighting during day time. The intensity of LED light in the hybrid lighting system is controlled automatically according to ambient-light-sensor installed in the system so that the light intensity for a plant always keeps the same level no matter how the sun light changes. For a plant factory whose size is 330 square meters, when solar lighting system is applied, 28,080KWh electric energy can be saved per month.2 times.

• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.105-112
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• 2010

In this paper, the bio-signals, such as EEG, ECG were measured with a sensor and their characters were drawn out and analyzed. With results from the analysis, four emotion of rest, concentration, tension and depression were inferred. In order to assess one's emotion, the characteristic vectors were drawn out by applying various ways, including the frequency analysis of the bio-signals like the measured EEG and HRV. RBFN, a neural network of the complex structure of unsupervised and supervised learning, was applied to classify and infer the deducted information. Through experiments, the system suggested in this thesis showed better capability to classify and infer than other systems using a different neural network. As follow-up research tasks, the recognizance rate of the measured bio-signals should be improved. Also, the technology which can be applied to the wired or wireless sensor measuring the bio-signals more easily and to wearable computing should be developed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.15-16
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• 2012

General lighting will be replaced into LED due to the high efficiency, low power consumption, long life than conventional light, moreover, since it is a basically semiconductor device that can convert the electric energy to visible light at a very high speed, using these characteristics can be performed communication modulation via the high-speed ON-OFF switching. Recently, visible light communication (VLC: Visible Light Communication) technology is received attention and there have been many researches. This paper is implemented media signal transmission by combining LED with VLC, a transmitter used the LED light-emitting device and receiver used an infrared sensor. In order to increase the efficiency of the communication system to improve the existing LED visible light communication driver of power conversion efficiency and thermal issues that is applied to the visible light communication in order to improve the speed of transmission media to research a new way of LED driver.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.941-944
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• 2012

Microprocessor is widely used in various industries. So it is very important to learn about it. But it is very difficult because students must know about both hardware and software of it. Student usually learn about it with a complete educational product in many technical high school. It make them to have no chance to mixed various electronic parts such as sensors, motors and so on. It cause them to low the creative product making ability. So we adjust new course with the arduino instead of the complete educational product to microprocessor education. It help student to high the electronic part mixing ability and the creative electronic product making ability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1933-1941
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• 2016

This paper compares the performance of wireless communication technologies to replace the wired networks by wireless networks on avionics intra-communication. Due to the drawbacks of wired network, such as complexity, weight, maintenance cost and scalability, it leads to the high data rate and network traffic demands of avionics systems. Therefore, in WAIC(Wireless Avionics Intra-Communications) system suggested by ITU(International Telecommunication Union), based on environment of avionics system and requirements of a wired network, wireless network structures are defined to solve the problems of wired networks. In this paper, we consider features, advantages and disadvantages of wireless communication technologies which can be used for wireless avionics network, and we propose suitable wireless communication technology candidates for wireless avionics networks in WAIC environments.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2017.05a
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• pp.161.2-161.2
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• 2017

희토류계 영구자석은 대부분의 전기, 전자 제품의 핵심부품이며 높은 보자력, $BH_{max}$를 가지고 있어 자기기록저장매체, MEMS(엑츄에이터), 소형센서, 소형모터 등의 응용 분야에 적용시키기 위해 다양한 연구들이 진행되고 있다. 그러나 영구자석에 들어가는 희토류계 원소의 수급의 어려움 및 가격의 문제점으로 친환경 자석으로의 전환 및 희토류나 중희토류를 사용하지 않는 비희토류계 영구자석을 제조 및 개발하는데 많은 연구가 이루어지고 있다. 이 중 Fe-N 계 자성물질인 $Fe_{16}N_2$는 포화 자화 값이 현재까지의 비희토류계 자성물질 중 가장 높은 값(240emu/g)을 나타내며 상대적으로 높은 결정자기이방성 상수를 가지고 있어 비희토류계 영구자석 물질 중 하나로 주목받으며 연구되어지고 있다. 본 연구에서는 $Fe_{16}N_2$ 박막을 얻기 위해 DC Magnetron Sputtering 방법을 이용하여 Si wafer 위에 박막을 증착하고 증착시간에 따라 두께를 제어하여 제조한 후 박막의 미세구조, 상 분석, 자성 특성을 관찰을 통해 최적의 공정 조건을 찾고자 하였다. 증착 시간에 따른 박막의 성장 속도는 일정하게 증가하였으며, 증착 시간의 증가에 따라 박막 내 $Fe_{16}N_2$의 상대적인 분율은 감소하였다. 모든 공정 조건에서 $Fe_3N$, $Fe_4N$, $Fe_{16}N_2$ 상들이 섞여 성장하였으며 XRD를 통한 상분석과 더불어 VSM을 통한 자성 특성을 분석해본 결과 $Fe_{16}N_2$의 분율을 가장 높게 성장된 공정 조건은 증착 시간이 10분이며 박막의 두께가 ${\sim}1{\mu}m$ 일 때, 최적의 조건을 얻을 수 있었으며, 이 때의 자성 특성을 분석한 결과 ~2.45T의 포화 자화 값과 ~1.41T의 잔류 자화 값을 얻을 수 있었다.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.08a
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• pp.387-387
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• 2011

탄소 나노튜브(Carbon nanotubes, CNTs)는 육각형 모양의 구조로서 오직 탄소만으로 이루어진 소재이다. CNT는 열전도율이 다이아몬드보다 약 2배 우수하고, 전기 전도는 구리에 비해 1,000배 높으며, 강도는 강철보다 100배나 뛰어나다. CNT의 이러한 특성을 이용한 트랜지스터, 태양전지, 가스 검출을 위한 고감도 센서, 나노 섬유, 고분자-탄소나노튜브 고기능 복합체 등 많은 분야에서 연구가 활발히 진행되고 있다. 또한 수직으로 성장된 탄소 나노튜브는 일반적인 재료에서는 보기 드물게 힘들게 직경이 나노 크기인 반면 길이는 수 mm까지 합성 되기 때문에 앞서 언급한 분야로의 활용이 더욱 유리하며, 그 중에서도 나노 섬유, 나노 복합체로서의 활용에 극히 유용하다. 이러한 이유로 수직 배열된 CNT 합성에 많은 연구가 집중 되고 있다. 여러 합성 방법 중 성장 변수를 비교적 용이하게 조절 가능한 열 화학 기상 증착법(Thermal chemical vapor deposition, TCVD)을 이용하여 수직 배열된 수 mm의 CNT를 합성한 연구 결과들이 보고된 바 있다. 그러나 앞선 연구결과들은 CNT의 성장속도가 느릴 뿐만 아니라 합성 시간이 길어질수록 성장 속도가 감소하는 경향을 보였다. 반면, 마이크로웨이브 플라즈마 화학 기상 증착법(Microwave plasma CVD, MPCVD)은 기존의 다른 TCVD에 비해 낮은 온도에서 CNT를 합성할 수 있는 장점을 가지며, 고출력(~600 W 이상)의 플라즈마를 사용하기 때문에 성장률이 높고 고밀도의 CNT 합성이 가능하다. 본 연구에서는 철을 촉매금속으로 사용하고 MPCVD을 이용하여 얇은 다중벽 CNT를 합성하였다. 철은 직류 마그네트론 스퍼터(D.C magnetron sputter)를 사용하여 증착하였다. 합성시 가스는 탄소 공급원인 메탄($CH_4$)과 함께 플라즈마 공급원인 수소($H_2$)를 사용하였다. 또한 산소($O_2$)의 주입 여부에 따른 CNT의 성장 속도와 성장 길이를 비교하였다. 산소를 주입하였을 때, CNT의 성장 속도와 길이 모두 크게 향상됨을 확인 할 수 있었다. 이는 촉매금속 표면의 비정질 탄소의 흡착으로 인해 활성화된 촉매금속의 반응시간을 증가시키기 때문이다. 성장된 CNT는 주사전자 현미경(Scanning Electron Microscopy, SEM)과 라만 분광법(Raman spectroscopy)을 통해 표면형상과 결정성을 분석하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.202-208
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• 2015

A wireless ship area network is required to configure and control various sensors and electrical instruments embedded or boarded in a ship. In such environment, wireless communication protocol adopting relaying function is needed because direct link or communication between two nodes is hardly guaranteed due to spatial constraints in a ship. In this study, we introduce and analyze a WiMedia Distributed MAC (D-MAC) based approach considering throughput and energy constraint of wireless communication module. Performance evaluation results demonstrate that the relay-based wireless communication protocol improves reliability of wireless communication network in a ship.

• Smart Media Journal
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• v.5 no.3
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• pp.35-41
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• 2016

In this paper, we propose hand-gesture signal recognition based on EPS(Electronic Potential Sensor) using Deep learning model. Extracted signals which from Electronic field based sensor, EPS have much of the noise, so it must remove in pre-processing. After the noise are removed with filter using frequency feature, the signals are reconstructed with dimensional transformation to overcome limit which have just one-dimension feature with voltage value for using convolution operation. Then, the reconstructed signal data is finally classified and recognized using multiple learning layers model based on deep learning. Since the statistical model based on probability is sensitive to initial parameters, the result can change after training in modeling phase. Deep learning model can overcome this problem because of several layers in training phase. In experiment, we used two different deep learning structures, Convolutional neural networks and Recurrent Neural Network and compared with statistical model algorithm with four kinds of gestures. The recognition result of method using convolutional neural network is better than other algorithms in EPS gesture signal recognition.