• 전력전자학회:학술대회논문집
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• 전력전자학회 2009년도 정기총회 및 추계학술대회 논문집
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• pp.105-110
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• 2009

The On Line Electric Vehicles(OLEV) that can pick up inductive power from underground coils on driving with high efficiency have been developed this year, and is now proposed in this paper. The IPS(Inductive Power Supply) system consists of power supply inverters, power supply rails, pick up modules, and a regulator. There are 3 generations of IPS have been developed so far, and the $4^{th}$ generation IPS is being developed. The $1^{st}$ generation has been demonstrated this Feb. 27, which is equipped with mechanically auto tracking pick-up module with 1cm air gap, and showed 80% power efficiency. The $2^{nd}$ generation IPS applied to an 120kW (average)/240kW(peak) motor powered electric bus has 17cm air gap with 72% power efficiency. For the $2^{nd}$ generation IPS, the Power supply inverter has 440V, 3phase input and 200A @ 20kHz output. The test power supply rail of 240m long is segmented by 60m each, where newly developed core structure and power cable are constructed under the road covered with asphalt of 5cm thickness. The pick-up modules which consist of core, winding wire, and rectifiers are fixed to the bottom of the bus which can carry more than 40 passengers and can pick up max. 60kW. To remove parasitic component and to transfer maximum power between them resonant circuit topology is applied to the primary and secondary sides. The EMF level is below 62.5mG at 1.75m from the center of the road to meet the regulation. Several effective ways of reducing EMF levels have been developed. In addition, effective ways to solve problems related high frequency power cables buried in ground and it's proof from soil have been studied also. This development shows that the IPS system is capable of supplying enough power to the pick-up of OLEV and can reduce battery size, weight and cost, which means the IPS with OLEV is one of the best candidate for EV.

• 전기학회논문지
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• 제67권1호
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

• 재활치료과학
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• 제8권1호
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• pp.41-50
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• 2019

목적: 본 연구의 목적은 건강한 성인을 대상으로 양측상지기능 훈련을 통해서 활성화 되는 대뇌 연결성에서 상상 훈련과 신체적 수행 간에 차이가 있는지를 알아보고자 한다. 연구방법: 연구 대상자는 건강한 성인 1명으로 상상훈련과 신체적 수행 시 EEG 측정이 이루어졌다. 양측상지기능 훈련은 대칭 과제와 비대칭 과제로 구성되었다. 대칭 과제는 양손으로 박스를 잡고 동시에 위의 선반으로 올렸다가 다시 내려놓는 과제이고, 비대칭 과제는 한 손으로 병을 잡고 다른 한 손으로 뚜껑을 여는 과제였다. EEG 전극은 Fp1, Fp2, F3, F4, T3, T4, P3 및 P4에 부착되었다. 데이터 분석은 EEG 전극 쌍 간의 상관 분석을 위해 Cross-Line Mapping을 사용하였다. 결론: 본 연구 결과 대칭 및 비대칭의 양측 상지 과제에서 대뇌 연결성 패턴은 운동과 감각 영역에서 유사한 패턴을 가지는 것으로 나타났다. 또한 본 연구를 통해 양측상지기능 훈련 시 상상훈련보다 신체적 수행에서 대뇌 연결성이 더 높은 상호상관을 갖는다는 것을 확인하였다.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2011년도 제36회 춘계학술대회논문집
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• pp.1-2
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• 2011

Hybrid rockets have lately attracted attention as a strong candidate of small, low cost, safe and reliable launch vehicles. A significant topic is that the first commercially sponsored space ship, SpaceShipOne vehicle chose a hybrid rocket. The main factors for the choice were safety of operation, system cost, quick turnaround, and thrust termination. In Japan, five universities including Hokkaido University and three private companies organized "Hybrid Rocket Research Group" from 1998 to 2002. Their main purpose was to downsize the cost and scale of rocket experiments. In 2002, UNISEC (University Space Engineering Consortium) and HASTIC (Hokkaido Aerospace Science and Technology Incubation Center) took over the educational and R&D rocket activities respectively and the research group dissolved. In 2008, JAXA/ISAS and eleven universities formed "Hybrid Rocket Research Working Group" as a subcommittee of the Steering Committee for Space Engineering in ISAS. Their goal is to demonstrate technical feasibility of lowcost and high frequency launches of nano/micro satellites into sun-synchronous orbits. Hybrid rockets use a combination of solid and liquid propellants. Usually the fuel is in a solid phase. A serious problem of hybrid rockets is the low regression rate of the solid fuel. In single port hybrids the low regression rate below 1 mm/s causes large L/D exceeding a hundred and small fuel loading ratio falling below 0.3. Multi-port hybrids are a typical solution to solve this problem. However, this solution is not the mainstream in Japan. Another approach is to use high regression rate fuels. For example, a fuel regression rate of 4 mm/s decreases L/D to around 10 and increases the loading ratio to around 0.75. Liquefying fuels such as paraffins are strong candidates for high regression fuels and subject of active research in Japan too. Nakagawa et al. in Tokai University employed EVA (Ethylene Vinyl Acetate) to modify viscosity of paraffin based fuels and investigated the effect of viscosity on regression rates. Wada et al. in Akita University employed LTP (Low melting ThermoPlastic) as another candidate of liquefying fuels and demonstrated high regression rates comparable to paraffin fuels. Hori et al. in JAXA/ISAS employed glycidylazide-poly(ethylene glycol) (GAP-PEG) copolymers as high regression rate fuels and modified the combustion characteristics by changing the PEG mixing ratio. Regression rate improvement by changing internal ballistics is another stream of research. The author proposed a new fuel configuration named "CAMUI" in 1998. CAMUI comes from an abbreviation of "cascaded multistage impinging-jet" meaning the distinctive flow field. A CAMUI type fuel grain consists of several cylindrical fuel blocks with two ports in axial direction. The port alignment shifts 90 degrees with each other to make jets out of ports impinge on the upstream end face of the downstream fuel block, resulting in intense heat transfer to the fuel. Yuasa et al. in Tokyo Metropolitan University employed swirling injection method and improved regression rates more than three times higher. However, regression rate distribution along the axis is not uniform due to the decay of the swirl strength. Aso et al. in Kyushu University employed multi-swirl injection to solve this problem. Combinations of swirling injection and paraffin based fuel have been tried and some results show very high regression rates exceeding ten times of conventional one. High fuel regression rates by new fuel, new internal ballistics, or combination of them require faster fuel-oxidizer mixing to maintain combustion efficiency. Nakagawa et al. succeeded to improve combustion efficiency of a paraffin-based fuel from 77% to 96% by a baffle plate. Another effective approach some researchers are trying is to use an aft-chamber to increase residence time. Better understanding of the new flow fields is necessary to reveal basic mechanisms of regression enhancement. Yuasa et al. visualized the combustion field in a swirling injection type motor. Nakagawa et al. observed boundary layer combustion of wax-based fuels. To understand detailed flow structures in swirling flow type hybrids, Sawada et al. (Tohoku Univ.), Teramoto et al. (Univ. of Tokyo), Shimada et al. (ISAS), and Tsuboi et al. (Kyushu Inst. Tech.) are trying to simulate the flow field numerically. Main challenges are turbulent reaction, stiffness due to low Mach number flow, fuel regression model, and other non-steady phenomena. Oshima et al. in Hokkaido University simulated CAMUI type flow fields and discussed correspondence relation between regression distribution of a burning surface and the vortex structure over the surface.