• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.147-179
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• 2002

The important role of observational method in geotechnical engineering are emphasized together with the direction of future development, concerning successful application of the technique on the site investigation, design and feed back at various construction stages. Case histories on the application of feed back are introduced in order to achieve the most economical and reliable construction for tunnel, rock slope and deep excavations through feed back system at design and construction stages. Also the limitations and advantages of the observational method and the role of feed back system are discussed for construction of tunnel, rock slope and deep excavation in hard ground such as layered ground conditions including weathered, soft and hard rocks.

• Journal of the Korean Institute of Telematics and Electronics
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• v.15 no.3
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• pp.7-10
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• 1978

A method of full wave rectification is proposed which is accomplished by an inverter circuit including R-feed back. Both halves of the input cycle can be presented in the out put by composing a conductive half cycle and an inactive half cycle substituted by feed back in the cut off state.

• Journal of the Korea Institute of Military Science and Technology
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• v.9 no.2 s.25
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• pp.77-86
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• 2006

Usually, a tracking-gate of the tracker is used to track the target radar signal in the active ECM system. In this paper, we propose the feed-back tracking-gate filtering method. The designed method applies a tracking-gate of the tacker to the ECM system's receiver as a rejection or pass filter selected by the receiver's purpose, and the specific target signals can be passed or rejected though this tracking-gate filter. Thus, the number of input signals within the receiver's search band is minimized owing to this filter except the target signals. In conclusion, the EW equipment's reaction time can be reduced and the error value about the target signals can be lower than the previous methods'.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.258-261
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• 2000

A non-contact battery charger which transfers energy using magnetic field has a difficulty with a feed-back control due to the interaction between the power and signal processing This paper proposes an effective method which uses auxiliary windings of transformer as signal path and copes with cross-talk using the MOSFET ringing phenomenon and ceramic filter. The power stage is half-bridge series resonant converter. Design procedure and experimental verification are presented.

• Journal of the Korean Institute of Telematics and Electronics
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• v.24 no.5
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• pp.823-832
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• 1987

This pper presents a method for constructing multiple-valued logic sequential machines based on Galois field. First, we assign all elements in GF(2**m) to bit codes using mathematical properties of GF(2**m). Then, we realized the sequencial machine circuits with and withoutm feed-back. 1) Sequential machines with feed-back are constructed by using only MUX from state-transition diagram expressing the information of sequential machines. 2) Sequential machines without feed-back are constructed by following steps. First, we assigned states in state-transition disgram to state bit codes, then obtained state function and predecessor table explaining the relationship between present states and previous states. Next, we obtained next-state function from state function and predecessor table. Finally we realized the circuit using MUX and decoder.

• The Journal of Information Technology
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• v.8 no.1
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• pp.51-56
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• 2005

The Back propagation algorithm is a very effective supervised training method for multi-layer feed forward neural networks. This paper studies the decision boundary formation based on the Back propagation algorithm. The discriminating powers of several neural network topology are also investigated against five manually created data sets. It is found that neural networks with multiple hidden layer perform better than single hidden layer.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.2
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• pp.228-236
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• 2004

In this paper. we present a neuro-fuzzy controller which unifies both fuzzy logic and multi-layered feed forward neural networks. Fuzzy logic provides a means for converting linguistic control knowledge into control actions. On the other hand. feed forward neural networks provide salient features. such as learning and parallelism. In the proposed neuro-fuzzy controller. the parameters of membership functions in the antecedent part of fuzzy inference rules are identified by using the error back propagation algorithm as a learning rule. while the coefficients of the linear combination of input variables in the consequent part are determined by using the least square estimation method. Finally. the effectiveness of the proposed controller is verified through computer simulation for an inverted pole system.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.5
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• pp.729-737
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• 2009

This paper introduces the machine tools feed system, which can be optimized the control's performance through simulation and the adjustment of the mechanical components. One method simulates the frequency response of the speed-loop with the design value using the MATLAB application, so that all of the interpolation axis can be equal to the response bandwidth, resulting in a high accuracy rate. The other method sees the mechanical component being adjusted by analyzing the results of various experiments. Lastly, this client's program is able to change the parameters that are related to the FFD, as well as the parameters in the friction compensation of the OPEN-CNC.

• Journal of the Korean Geotechnical Society
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• v.21 no.3
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• pp.109-118
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• 2005

It is a very difficult task to estimate engineering properties of the ground when designing underground structures, especially in tunnelling. Therefore, a feed-back system to combine the data measured in construction field with priorly estimated information at the design stage is necessary. In this paper, 3-dimensional back-analysis in tunnelling, to which only relative convergence is applied as input values, is carried out to estimate the optimum geotechnical parameters. For this purpose, the Extended Bayesian Method (EBM), which appropriately combines the objective information with the subjective one, is applied to optimize engineering parameters and 3-dimensional numerical analysis is carried out to predict a trend of relative convergence occurrence. The data measured from two tunnelling sites are used to verify the applicability of the proposed back-analysis technique. from the results of analysis, the proposed back-analysis technique is verified.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.671-674
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• 2004

We propose accurate classification method of EEG signals during mental tasks. In the experimental task, the tasks of subjects show 3 major measurements; there are mathematical tasks, color decision tasks, and Chinese phrase tasks. The classifier implemented for this work is a feed-forward neural network that trained with the error back-propagation algorithm. The new BCI system is proposed by using neural network. In this system, tr e architecture of the neural network is composed of three layers with a feed-forward network, which implements the error back propagation-learning algorithm. By applying this algorithm to 4 subjects, we achieved $95{\%}$ classification rates. The results for BCI mathematical task experiments show performance better than those of the Chinese phrase tasks. The selection time of each task depends on the mental task of subjects. We expect that the proposed detection method can be a basic technology for brain-computer interface by combining with left/right hand movement or yes/no discrimination methods.