• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.442-445
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• 2004

The acoustic target strength (TS) of submarine is associated with its active detection, positioning and classification. That is, the survivability of submarine depends on its target strength. So it should be managed with all possible means. An anechoic coating to existing submarine or changing of curvature can be considered as major measures to reduce the TS of submarine. It is mainly based on the prediction of its TS. Under this circumstances, a study on the more accurate numerical methods becomes big topic for submarine design. In this paper, Kirchhoff approximation method was adopted as a numerical tool for the physical optics region. Secondly, the scaled models of submarine were built and tested in order to verify its performance. Through the comparison, it was found out that the Kirchhoff approximation method could be good design tool for the prediction of TS of submarine.

• Proceedings of the KSRS Conference
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• 2000.04a
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• pp.9-9
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• 2000

For the planning of future land use for economic activities, an essential component is the identification of the vulnerable areas for natural hazard and environmental impacts from the activities. Also, exploration for mineral and energy resources is carried out by a step by step approach. At each step, a selection of the target area for the next exploration strategy is made based on all the data harnessed from the previous steps. The uncertainty of the selected target area containing undiscovered resources is a critical factor for estimating the exploration risk. We have developed not only spatial prediction models based on adapted artificial intelligence techniques to predict target and vulnerable areas but also validation techniques to estimate the uncertainties associated with the predictions. The prediction models will assist the scientists and decision-makers to make two critical decisions: (i) of the selections of the target or vulnerable areas, and (ii) of estimating the risks associated with the selections.

• Journal of Communications and Networks
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• v.15 no.1
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• pp.54-60
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• 2013

In this paper, a novel method called location-based delivery (LBD), which combines the short message service (SMS) and global position system (GPS), is proposed, and further, a realistic system for tracking a target's movement is developed. LBD reduces the number of short message transmissions while maintaining the location tracking accuracy within the acceptable range. The proposed approach, LBD, consists of three primary features: Short message format, location prediction, and dynamic threshold. The defined short message format is proprietary. Location prediction is performed by using the current location, moving speed, and bearing of the target to predict its next location. When the distance between the predicted location and the actual location exceeds a certain threshold, the target transmits a short message to the tracker to update its current location. The threshold is dynamically adjusted to maintain the location tracking accuracy and the number of short messages on the basis of the moving speed of the target. The experimental results show that LBD, indeed, outperforms other methods because it satisfactorily maintains the location tracking accuracy with relatively fewer messages.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.40 no.2
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• pp.118-128
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• 2012

The goal of this paper is to design the target tracking controller for a quadrotor micro UAV using a vision sensor. First of all, the mathematical model of the quadrotor was estimated through the Prediction Error Method(PEM) using experimental input/output flight data, and then the estimated model was validated via the comparison with new experimental flight data. Next, the target tracking controller was designed using LQR(Linear Quadratic Regulator) method based on the estimated model. The relative distance between an object and the quadrotor was obtained by a vision sensor, and the altitude was obtained by a ultra sonic sensor. Finally, the performance of the designed target tracking controller was evaluated through flight tests.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.899-902
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• 2005

Pipeline hazard due to branch instructions is the major factor of the degradation on the performance of microprocessors. Branch target buffer predicts whether a branch will be taken or not and supplies the address of the next instruction on the basis of that prediction. If the branch target buffer predicts correctly, the instruction flow will not be stalled. This leads to the better performance of microprocessor. In this paper, the architecture of a tag memory that branch target buffer and TLB can share is presented. Because the two tag memories used for branch target buffer and TLB each is replaced by single shared tag memory, we can expect the smaller ship size and the faster prediction. This hared tag architecture is more advantageous for the microprocessors that uses more bits of address and exploits much more instruction level parallelism.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.337-342
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• 2016

In this paper, we studied a modified linear prediction method to estimate target signal correctly. Linear prediction method estimate direction-of-arrival to linear combination for any antenna element and other antenna elements. Modified linear prediction used optimal weight and posterior probability method. Through simulation, we are comparative analysis about the performance of proposed, bartlett and MUSIC method. From simulation, Bartlett and MUSIC method was estimation 3 targets signal, and proposed method estimated 4 targets. We showed the superior performance of the proposed algorithm relative to the classical method in order to estimate of target signals.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.1
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• pp.10-17
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• 2013

This thesis proposes an automatic embedded core generator system that supports branch prediction. The proposed system includes a dynamic branch prediction module that enhances execution speed of target applications by inserting history/direction flags into BTAC(Branch Target Address Cache). Entries of BHT(Branch History Table) and BTAC are determined based on branch informations extracted by simulation. To verify the effectiveness of the proposed branch prediction module, ARM9TDMI core including a dynamic branch predictor was described in SMDL and generated. Experimental results show that as the number of entry rises, area increase up to 60% while application execution cycle and BTAC miss rate drop by an average of 1.7% and 9.6%, respectively.

• CELLMED
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• v.3 no.2
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• pp.12.1-12.4
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• 2013

Identification of target protein is an important procedure in the course of drug discovery. Because of complexity, action mechanisms of herbal medicine are rather obscure, unlike small-molecular drugs. Inverse docking simulation is a reverse use of molecular docking involving multiple target searches for known chemical structure. This methodology can be applied in the field of target fishing and toxicity prediction for herbal compounds as well as known drug molecules. The aim of this review is to introduce a series of in silico works for predicting potential drug targets and side-effects based on inverse docking simulations.

• Journal of the Korean Applied Science and Technology
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• v.25 no.4
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• pp.438-445
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• 2008

For recipe prediction of colorant proportion showing nonlinear behavior, we modeled the effects of colorant proportion of basic colors on the target colors and predicted colorant proportion necessary for making target colors. First, colorant proportion of basic colors and color information indicated by the instrument was applied by a linear model and a multi-layer perceptrons model with back-propagation learning method. However, satisfactory results were not obtained because of nonlinear property of colors. Thus, in this study the neuro-fuzzy model with merit of artificial neural networks and fuzzy systems was presented. The proposed model was trained with test data and colorant proportion was predicted. The effectiveness of the proposed model was verified by evaluation of color difference(${\Delta}E$).

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.129-133
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• 2023

Classification or prediction problem is how to solve it using a specific feature to obtain the predicted class. A wheat seeds specifications 4 3 classes of seeds will be used in a prediction process. A multi linear regression will be built, and a prediction error ratio will be calculated. To enhance the prediction ratio an ANN model will be built and trained. The obtained results will be examined to show how to make a prediction tool capable to compute a predicted class number very close to the target class number.