• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.56-60
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• 2008

Increasing urban sprawl and climate changes have been causing unexpected high-intensity rainfall events. Thus there are needs to enhance conventional disaster management system for comprehensive actions to secure safety. Therefore long-term and comprehensive flood management plans need to be well established. Recently torrential snowfall are occurring frequently, causing have snow traffic jams on the road. To secure safety and on-time operation of the Bi-modal tram system, well-structured disaster management system capable of analyzing the urban flash flooding and snow pack melt/freezing due to unexpected rainfall event and snowfall are needed. To secure safety of the Bi-modal tram system due to torrential snowfall, the snow melt simulation capability was investigated. The snow accumulation and snow melt were measured to validate the SWMM snow melt component. It showed that there was a good agreement between measured snow melt data and the simulated ones. Therefore, the Bi-modal tram disaster management system will be able to predict snow melt reasonably well to secure safety of the Bi-modal tram system during the winter. The Bi-modal tram disaster management system can be used to identify top priority area for snow removal within the tram route in case of torrential snowfall to secure on-time operation of the tram. Also it can be used for detour route in the tram networks based on the disaster management system predicted data.

• 에너지공학
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• 제5권2호
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• pp.131-137
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• 1996

Typical size distribution of emission particulates is bi-modal in shape with particles in the fine mode (< 2.0 $\mu\textrm{m}$) and the coarse mode. An experimental study of pressure drop across the industrial gas cleaning filters has been conducted using particle mixture of fine alumina and coarse Arizona dusts with a rotating aerosol disperser to generate the bi-modal test aerosol. Pressure drop increased linearly with increasing mass loading. The pressure drop was found to be strongly dependent upon the mass ratio of fine to coarse particles. The smaller the mass ratio of fine to coarse particles and the higher face velocity are, the faster pressure drop rises. The fine particles and the greater inertia of the particle moving fast would cause a denser cake formation on the filter surface, resulting in a greater specific resistance to the gas flow.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2001년도 추계학술대회 논문집
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• pp.62-73
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• 2001

The scope of this study is focused on the survey of new logistics transportation systems in railroad and case studies of new systems such as piggyback system, bi-modal system swapbody, and double stack train(DST). Piggyback system, bi-modal system, swapbody, and double stack train are reviewed in term of technological validity and economic validity in Korea. Piggyback - trailer does pass loaded weight limits but does not pass train limits and can not utilize the existing freight cars. Piggyback - cargo trunk does pass all the criteria and could be developed by a domestic technology. But this study suggests to expand the length of train cars to 18.300mm for accommodation of two cargo trucks. Bi-modal system and swapbody do also pass. Double stack train could only pass the loaded weights and does not meet the train limit and the possibility of using existing freight cars. Domestic technology could not development DST, due to civil engineering construction limits and low standard height of electric line, which could not afford to operate DST.

• 제어로봇시스템학회논문지
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• 제13권8호
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• pp.754-759
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• 2007

In this paper, we proposed the Bi-Modal Sensor Fusion Algorithm which is the emotional recognition method that be able to classify 4 emotions (Happy, Sad, Angry, Surprise) by using facial image and speech signal together. We extract the feature vectors from speech signal using acoustic feature without language feature and classify emotional pattern using Neural-Network. We also make the feature selection of mouth, eyes and eyebrows from facial image. and extracted feature vectors that apply to Principal Component Analysis(PCA) remakes low dimension feature vector. So we proposed method to fused into result value of emotion recognition by using facial image and speech.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.1717-1725
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• 2008

In this paper, the HILS system is proposed for the AWS ECU of the bi-modal tram. Using the HILS of the AWS ECU, the behavior of the vehicle can be predicted and the reliability of the AWS system also can be verified. The hardware part of the HILS system includes the ECUs, hydraulic systems, steering linkages and sensors of the bi-modal tram. The software part of the HILS system contains the virtual vehicle model and sensor emulation. Driver input conditions, such as vehicle velocity and front steering angle, are provided to the ECUs by the software. The driving simulation of the bi-modal tram is carried out by the HILS. Also, the reliability of the AWS system, including the ECUs and hydraulic systems, is verified.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2008년도 추계학술대회 논문집
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• pp.584-589
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• 2008

A bi-modal tram has been developing to consist of articulated-two cars propelled by CNG hybrid (series type) in Korea since 2003. All wheels are driven by electrical motors independently, which can eliminate differential gears to reduce turning radius and make low floor to provide the old and the handicapped with easy access. In the bi-modal tram, therefore, reduction gear unit is key technology to make low floor and drive wheels independently. This study was aimed at performance evaluations of the reduction gear unit for the bi-modal tram. Oil leakage, oil temperature, vibration, acoustic noise in idle operations were measured for the reduction gear unit of the bimodal tram.

• 한국자동차공학회논문집
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• 제17권5호
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• pp.84-90
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• 2009

The bi-modal tram is under development as a new public transportation. The features of the tram are an extended wheel base and its length. This features result in difficulties for drivers on maneuvering the tram. Therefore, the all wheel steering system is applied to the articulated vehicle. The AWS system enables the vehicle to steer all the rear wheels independently and improves its driving characteristics. However, the bi-modal tram has a problem to move backward in the limited place because of its geometric feature and the AWS system. Hence, the reverse parking assistant algorithm for articulated vehicle is developed to solve the problems of the reverse parking. Using the vehicle model which includes the reverse parking assistant algorithm, the dynamic analysis is performed for several parking cases. By the result of the analysis, the stability and validity of the reverse parking assistant algorithm is verified.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.319-324
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• 2012

This paper presents the study of 3-Phase bi-directional DC to AC inverter with unity power factor. 3-Phase bi-directional DC to AC inverter is important for the bi-modal PV PCS with an energy storage system. Both Inverting and converting are needed to connect between the grid side and boost converting side to charge and discharge the energy storage system. The paper proposes the appropriate circuit topology and proper control system for the bi-directional inverter. It also proposes the method of selecting the optimum control method considering system stability. PSIM simulation is used to validate the proposed algorithm.

• 대한교통학회지
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• 제23권7호
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• pp.111-123
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• 2005

본 논문에서는 교통시설투자 의사결정을 위한 네트워크 설계 모형이 제시되었다. 모형은 사용자 평형의 통행패턴을 예측할 수 있으면서, 링크의 설치 여부를 정하는 이산형 의사결정변수를 갖는 Bi-Level Programming 형태로 구축되었다. 제시된 모형의 장점으로는 사회적 비용을 감안한 투자 결정을 묘사했다는 점과 도로와 철도로 이루어진 네트워크에서의 평형 통행패턴을 예측할 수 있다는 점이다. 정수형 변수의 Bit 구조를 이용한 효율적인 해법 알고리즘이 개발되었다. 예제를 통하여 모형과 알고리즘의 유효성을 검증하였는데, 예제 결과에서 투자의 한계효과 감소현상을 발견하였다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 학술발표대회 논문집 제17권 1호
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• pp.111-114
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• 1998

기존의 음성인식시스템의 잡음환경에서 인식률의 한계를 극복하기 위해 음성신호뿐만이 아니라 입술정보를 결합하여 음성인식에 이용하여 바이모달(Bi-modal) 음성인식이 근래에 제안되어지고 있다. 그래서 바이모달 음성인식 시스템을 실제로 구현해보고 인식 실험을 수행해 보았다. 입술영상은 이미지에 근거한 입술모양을 파라메터화하여 인식실험에 사용하였으며 음성과 입술영상을 각각 인식한 후 인식스코어(Score)에 가중치를 적용하여 통합하는 방법을 사용하였다. 마지막으로 바이모달 음성인식의 잡음환경에서의 성능을 알아보기 위해 음성신호에 여러 레벨의 잡음을 섞어서 실험을 하고 잡음환경에서 인식률의 한계를 입술정보를 이용하여 극복할 수 있다는 것을 보이고자 한다.