• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.154-163
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• 2014

In this paper, there is suggested a fast intra prediction mode decision method in HEVC. To reduce the number of candidates in rough mode decision (RMD) process and rate-distortion optimization (RDO) process, the edge information and relative RMD cost are utilized. The experiment results show that the proposed method reduces encoding run-time by 26.81% with a negligible coding loss of 0.79% BD-rate on average.

• Journal of Korea Multimedia Society
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• v.21 no.7
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• pp.779-786
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• 2018

In this paper, we are applied a nerve network to allow for the reflection of data learning methods in their overall forms by using cluster data rather than data learning by the stages and then selected a nerve network model and analyzed its variables through learning by the cluster. The CkLR algorithm was proposed to analyze the reaction variables of clustering outcomes through an approach to the initialization of K-means clustering and build a model to assess the prediction rate of clustering and the accuracy rate of prediction in case of new data inputs. The performance evaluation results show that the accuracy rate of test data by the class was over 92%, which was the mean accuracy rate of the entire test data, thus confirming the advantages of a specialized structure found in the proposed learning nerve network by the class.

• 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.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.3
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• pp.396-405
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• 2009

The experimental research was conducted to setup a performance prediction logic for the regenerative cooling system on a small scale liquid rocket engine using kerosene and LOX. Total heat flux of the combustion gas side was determined for the flow rate of the coolant, combustion pressure using the calorimeter thrust chamber. Based on the experimental investigation, a performance prediction scheme for the regenerative cooling system is setup in our own way. A performance prediction logic for the regenerative cooling system has been developed by the correction scheme of the combustion gas side. The key parameters determining the temperature limitation of the coolant are the mass flow rate of the coolant and the length of the combustion chamber and the nozzle. And the parameters to control the limitation of the usable wall temperature are the number of channels and wall thickness.

• Journal of information and communication convergence engineering
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• v.5 no.4
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• pp.339-345
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• 2007

Video transcoding is a technique used to convert a compressed input video stream with an arbitrary format, size, and bitrate into a different attribute video stream different attributes to provide a efficient video streaming service for the customers is dispersed in the heterogeneous networks. Specifically, frames deletion occur in a transcoding scheme that exploits the adjustment of frame rate, and at this time, the loss in temporal relation among frames due to frame deletion is compensated for the prediction of motion estimation by reusing motion vectors in the would-be deleted frames. But the processing time for transcoding don't have an improvement as much as our expectation because transcoding is done only within the transcoder. So in this paper, we propose a new transcoding algorithm based on prediction period to improve transcoding-related processing time. For this, we also modify the existing encoder so as to adjust dynamically frame rate based on the prediction period and deletion period of frames. To check how the proposed algorithm works nicely, we implement a video streaming system with the new transcoder and encoder to which it is applied. The result of the performance test shows that the streaming system with proposed algorithm improve 60% above in processing time and also PSNR have a good performance while the quality of pictures is preserved.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1583-1591
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• 1990

Life prediction and residual life prediction of structures of machines are one of the most strongly world wide needed problems as requirement in the stage of slowly developing economy which comes after rapidly and highly developing stage. For the purpose of statistical life prediction, fatigue test was conducted under the 4 stress levels, and for each stress level, about 20 specimens are used. The statistical properties of crack growth parameter m and C in the fatigue crack growth law of da/dN=C(.DELTA.K)sup m/, and the relationship between m and C, and the statistical distribution pattern of fatigue crack growth rate can be obtained by experimental results.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1239-1248
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• 2021

In this paper, we present FDNN algorithm to perform prediction based on academic understanding. In order to apply prediction based on academic understanding rather than data-dependent prediction to deep learning, we constructed algorithm based on mathematical and hydrology. We construct a model that predicts flow rate of a river as an input of precipitation, and measure the model's performance through K-fold cross validation.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.225-227
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• 2009

International standard specification, H.264/SVC improved from H.264/AVC, is set up so as to promote free use of huge multimedia data in various channel environments.;H.264/AVC is a international standard speicification for video compression, adopted and commercialized as standard for DMB broadcasting by JVT of ISO/IEC MPEG and ITU-T VCEG. SVC standard uses 'intra/inter prediction' in AVC as well as 'inter-layer intra prediction', 'inter-layer motion prediction' and 'inter-layer residual prediction' to improve efficiency of encoding. Among prediction technologies, 'inter-layer intra prediction' is to use co-located block of up sampled sublevels as a prediction signal. At this time, application of interpolation is one of the most important factors to determine encoding efficiency. SVC's currently using poly-phase FIR filter of 4-tap and 2-tap respectively to luma components. This paper is written for the purpose of analyzing encoding performance according to the interpolation. For this purpose, we applied poly-phase FIR filter of '2-tap', '4-tap' and '6-tap' respectively to luma components and then measured bit-rate, PNSR and running time of interpolation filter. We're expecting that the analysis results of this paper will be utilized for effective application of interpolation filter. SVC standard uses 'intra/inter prediction' in AVC as well as 'inter-layer intra prediction', 'inter-layer motion prediction' and 'inter-layer residual prediction' to improve efficiency of encoding.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.359-362
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• 1996

The guidance system which uses the line-of-sight(LOS) rate to guide the missile towards its target has been used to the conventional differential game, such as the pursuer-evader game. Proportional navigation guidance and its derivatives have been shown to be an effective LOS rate guidance system. In this paper, we have used the genetic algorithm to construct the guidance system for the pursuer-evader type differential game. Also we have proposed the prediction model to obtain the informations about the intention of future actions of the pursuer and the evader.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.9-17
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• 2017

The student dropout prediction is an indispensable for many intelligent systems to measure the educational system and success rate of all university. Therefore, in this paper, we propose an intelligent dropout prediction system that minimizes the situation by adopting the proactive process through an effective model that predicts the students who are at risk of dropout. In this paper, the main data sets for students dropout predictions was used as questionnaires and university information. The questionnaire was constructed based on theoretical and empirical grounds about factor affecting student's performance and causes of dropout. University Information included student grade, interviews, attendance in university life. Through these data sets, the proposed dropout prediction model techniques was classified into the risk group and the normal group using statistical methods and Naive Bays algorithm. And the intelligence dropout prediction system was constructed by applying the proposed dropout prediction model. We expect the proposed study would be used effectively to reduce the students dropout in university.