• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.482-482
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• 2000

The essential requirements of neural network for human skill transfer are fast convergence, high storage capacity, and strong noise immunity. Bidirectional associative memory(BAM) suffering from low storage capacity and abundance of spurious memories is rarely used for skill transfer application though it has fast and wide association characteristics for visual data. This paper suggests generalization of classical BAM structure and new learning algorithm which uses supervised learning to guarantee perfect recall starting with correlation matrix. The generalization is validated to accelerate convergence speed, to increase storage capacity, to lessen spurious memories, to enhance noise immunity, and to enable multiple association using simulation work.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.561-566
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• 2003

This paper proposes a new algorithm that generates smooth and realistic transition views from one viewpoint to another view point on the panorama based navigation system. The proposed algorithm is composed with two steps. One is prewarping that aligns the viewing direction in two panorama image, the other is bidirectional disparity morphing (BDM) that generates the intermediate scene from the aligned panorama images. For the prewarping, first of all, we compute the phase correlation between two images in order to get the information such as the displacement, rotation, and scale. Then we align the original images using these information. As soon as finishing the prewarping, we compute the block based disparity vectors (DVs) and smooth them using the two occluding patterns. As we apply these DVs to the BDM, we can get the elaborate intermediate scenes. We make an experiment on the proposed algorithm with real panoramic images and we can get the satisfactory results.

• Journal of Power Electronics
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• v.9 no.5
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• pp.726-735
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• 2009

This paper presents a Bidirectional High-Frequency Link (BHFL) inverter that utilizes the Deadbeat controller. The main features of this topology are the reduced size of the inverter and fewer power switches. On the secondary side of the transformer, the active rectifier employs only two power switches, thus reducing switching losses. Using this configuration, the inverter is capable of carrying a bidirectional power flow. The inverter is controlled by a Deadbeat controller, which consists of the inner current loop, outer voltage loop and a feedforward controller. Additional disturbance decoupling networks are employed to improve the system's robustness towards load variations. A 1-kVA prototype inverter has been constructed and the Deadbeat control algorithm is experimentally verified. The experimental results show that the inverter has high efficiency (91%) with low steady state output voltage total harmonics distortion (1.5%).

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.5
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• pp.428-435
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• 2005

In this paper a power controller is proposed to accurately control the commanded power for charge and discharge operation of a bidirectional DC-DC converter so that durability is improved in hybrid systems such as fuel cell vehicles. Also, a control algorithm for charge and discharge operation is proposed to improve fuel utilization and keep battery SOC constant so that energy is effectively utilized.

• IE interfaces
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• v.10 no.3
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• pp.179-187
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• 1997

The efficiency of material flow systems in terms of optimal network flow and minimum cost flow has always been an important design and operational goal in material handling and distribution system. In this research, an attempt was made to develop a new algorithm and the model to solve a stochastic material flow network with bidirectional and uncertain flows. A stochastic material flow network with bidirectional flows can be considered from a finite set with unknown demand probabilities of each node. This problem can be formulated as a special case of a two-stage linear programming problem which can be converted into an equivalent linear program. To find the optimal solution of proposed stochastic material flow network, some terminologies and algorithms together with theories are developed based on the partitioning and subgradient techniques. A computer program applying the proposed method was developed and was applied to various problems.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.596-597
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• 2012

본 논문은 EVs/PHEVs에 사용되는 Bidirectional-LDC 일체형 OBC의 회로구조 및 동작특성 분석결과를 보고한다. 설계된 OBC는 한 개의 트랜스포머와 히트싱크를 LDC 회로와 공유하며, OBC의 출력 측 브릿지 방식의 정류회로는 LDC 동작 시 양방향 운용이 가능하다. 논문에서는 배터리 충전 조건에 따른 적합한 동작모드 제어 알고리즘을 분석하고 검증을 위한 프로토타입의 시험결과를 보고한다.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.905-914
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• 2016

This paper proposes a new phase current reconstruction technique for interleaved three-phase bidirectional dc-dc converters using a single current sensor. In the proposed current reconstruction algorithm, a single current sensor is employed at the dc-link, and the dc-link current information is sampled at either the peak or valley point of the pulse-width modulation (PWM) carriers regularly. From the obtained current information, all phase currents are reconstructed in a single PWM cycle. After that, the digital current controller is applied to achieve current balancing in each phase. Compare to the previous multiple current sensor method, the proposed strategy reduces the number of the current sensors in the interleaved three-phase bidirectional converter as well as reducing potential current sensing error caused by non-ideal characteristics of the multiple current sensors. The effectiveness of the proposed method is verified from the experiments based on a 3kW three-phase bidirectional converter prototype for the automotive battery charging application.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.441-447
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• 2000

Automatic word spacing is needed to solve the automatic indexing problem of the non-spaced documents and the space-insertion problem of the character recognition system at the end of a line. We propose a word spacing algorithm that automatically finds out word spacing positions. It is based on the recognition of Eojeol components by using the sentence partition and bidirectional longest-match algorithm. The sentence partition utilizes an extraction of Eojeol-block where the Eojeol boundary is relatively clear, and a Korean morphological analyzer is applied bidirectionally to the recognition of Eojeol components. We tested the algorithm on two sentence groups of about 4,500 Eojeols. The space-level recall ratio was 97.3% and the Eojeol-level recall ratio was 93.2%.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1630-1643
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• 2023

The correct situation awareness (SA) of operators is important for managing nuclear power plants (NPPs), particularly in accident-related situations. Among the three levels of SA suggested by Ensley, Level 3 SA (i.e., projection of the future status of the situation) is challenging because of the complexity of NPPs as well as the uncertainty of accidents. Hence, several prediction methods using artificial intelligence techniques have been proposed to assist operators in accident prediction. However, these methods only predict short-term plant status (e.g., the status after a few minutes) and do not provide information regarding the uncertainty associated with the prediction. This paper proposes an algorithm that can predict the multivariate and long-term behavior of plant parameters for 2 h with 120 steps and provide the uncertainty of the prediction. The algorithm applies bidirectional long short-term memory and an attention mechanism, which enable the algorithm to predict the precise long-term trends of the parameters with high prediction accuracy. A conditional variational autoencoder was used to provide uncertainty information about the network prediction. The algorithm was trained, optimized, and validated using a compact nuclear simulator for a Westinghouse 900 MWe NPP.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.681-684
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• 2008

We proposed a method to improve moving object detection capability of Gaussian Mixture Model by suggesting shape adaptive bidirectional block matching algorithm. This method achieves more accurate detection and tracking performance at various motion types such as slow, fast, and bimodal motions than that of Gaussian Mixture Model. Experimental results showed that the proposed method outperformed the conventional methods.