• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1017-1022
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• 2020

LTE-R(Long Term Evolution-Railway) for high speed railway system operation as an essential technology is based on LTE. Recently, moving speed of high speed train is on going to 600[km/h] level over commercial speed 400[㎞/h]. LTE-R as communication technology for a high speed railway system can be able to provide seamless communication to support moving speed for high speed railway system. In this study, a handover method based on prediction is suggested and performance of the suggested method is evaluated. Computer simulation based on NS(Network Simulator)-3 is used for this study.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.171-182
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• 2015

HEVC can increase the coding efficiency significantly compared with H.264/AVC however it requires much larger computational complexities in both encoder and decoder. In this paper, the decision process of inter-prediction modes in the HEVC reference software has been studied and a fast algorithm to reduce the computational complexity of encoder and decoder is introduced. The proposed scheme introduces a early decision criteria using the outputs of uni-directional predictions to skip the bi-directional prediction estimation. From the experimental results, it was proven that the proposed method can reduce the encoding complexity by 12.0%, 14.6% and 17.2% with 0.6%, 1.0% and 1.5% of coding efficiency penalty, respectively. In addition, the ratio of bi-directional prediction mode was reduced by 6.3%, 11.8% and 16.6% at the same level of coding efficiency penalty, respectively, which should lead to the decoder complexity reduction. Finally, the effects of the proposed scheme are maintained regardless of the use of the early skip decision algorithm which is implemented in the HEVC reference software.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.447-454
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• 2010

This paper presents multiple fuzzy prediction systems based on an Interval type-2 TSK fuzzy Logic System so that the uncertainty and the hidden characteristics of nonlinear data can be reflected more effectively to improve prediction quality. In proposed method, multiple fuzzy systems are adopted to handle the nonlinear characteristics of data, and each of multiple system is constructed by using interval type-2 TSK fuzzy logic because it can deal with the uncertainty and the characteristics of data better than type-1 TSK fuzzy logic and other methods. For input of each system, the first-order difference transformation method are used because the difference data generated from it can provide more stable statistical information to each system than the original data. Finally, computer simulations are performed to show the effectiveness of the proposed method for two typical time series examples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.629-637
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• 2013

Chaos communication systems have the characteristics such as non-periodic, wide-band, non-predictability of signals and easy implementation. There have been many studies about chaos communication systems because of these advantages. But, chaos communication systems have low BER(Bit Error Rate) compare to general digital communication system. Existing researches on chaos communication systems only analyze BER performance according to various chaos maps. There are no studies on analysis of BER performance according to PDF(Probability Density Function) of chaos maps. In this paper, we analyze the BER performance according to changing parameter, equation, and initial values of chaos map's PDF. In addition, we propose new chaos map to improve BER performance. Simulation results show that BER performance of CDSK(Correlation Delay Shift Keying) is changed when PDF of chaos map changed. And the proposed chaos map has a better BER performance compare to previous chaos maps such as Tent map, Logistic map, and Henon map.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.10-17
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• 2009

Wyner-Ziv video coding is a new video compression paradigm based on distributed source coding theory of Slepian-Wolf and Wyner-Ziv. Wyner-Ziv coding enables light-encoder/heavy-decoder structure by shifting complex modules including motion estimation/compensation task to the decoder. Instead of performing the complicated motion estimation process in the encoder, the Wyner-Ziv decoder performs the motion estimation for the generation of side information in order to make the predicted signal of the Wyner-Ziv frame. The efficiency of side information generation deeply affects the overall coding performance, since the bit-rates of the Wyner-Ziv coding is directly dependent on side information. In this paper, an improved side information generation method using field coding is proposed. In the proposed method, top fields are coded with the existing SI generation method and bottom fields are coded with new SI generation method using the information of the top fields. Simulation results show that the proposed method improves the quality of the side information and rate-distortion performance compared to the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.4C
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• pp.312-320
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• 2008

The macroblock-based adaptive interpolation filter method has been considered to be able to achieve high coding efficiency in H.264/AVC. In this method, although the filter selection criterion considered in terms of rate and distortion have showed a good performance, it still leaves room for improvement. To improve high coding efficiency better than conventional method, we propose a new filter selection criterion which considers two bit rates, motion vector and prediction error, and reconstruction error. In addition, the algorithm for reducing the overhead of transmitting the selected filter information is presented. Experimental results show that the proposed method significantly improves the coding efficiency compared to ones using conventional criterion. It leads to about a 5.19% (1 reference frame) and 5.14% (5 reference frames) bit rate savings on average compared to H.264/AVC, respectively.

• The KIPS Transactions:PartB
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• v.16B no.6
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• pp.463-470
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• 2009

In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.

• Annual Conference of KIPS
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• 2018.05a
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• pp.377-380
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• 2018

인간의 추론 능력이란 문제에 주어진 조건을 보고 문제 해결에 필요한 것이 무엇인지를 논리적으로 생각해 보는 것으로 문제 상황 속에서 일정한 규칙이나 성질을 발견하고 이를 수학적인 방법으로 법칙을 찾아내거나 해결하는 능력을 말한다. 이러한 인간인지 능력과 유사한 인공지능 시스템을 개발하는데 있어서 핵심적 도전은 비구조적 데이터(unstructured data)로부터 그 개체들(object)과 그들간의 관계(relation)에 대해 추론하는 능력을 부여하는 것이라고 할 수 있다. 지금까지 딥러닝(deep learning) 방법은 구조화 되지 않은 데이터로부터 문제를 해결하는 엄청난 진보를 가져왔지만, 명시적으로 개체간의 관계를 고려하지 않고 이를 수행해왔다. 최근 발표된 구조화되지 않은 데이터로부터 복잡한 관계 추론을 수행하는 심층신경망(deep neural networks)은 관계추론(relational reasoning)의 시도를 이해하는데 기대할 만한 접근법을 보여주고 있다. 그 첫 번째는 관계추론을 위한 간단한 신경망 모듈(A simple neural network module for relational reasoning) 인 RN(Relation Networks)이고, 두 번째는 시각적 관찰을 기반으로 실제대상의 미래 상태를 예측하는 범용 목적의 VIN(Visual Interaction Networks)이다. 관계 추론을 수행하는 이들 심층신경망(deep neural networks)은 세상을 객체(objects)와 그들의 관계(their relations)라는 체계로 분해하고, 신경망(neural networks)이 피상적으로는 매우 달라 보이지만 근본적으로는 공통관계를 갖는 장면들에 대하여 객체와 관계라는 새로운 결합(combinations)을 일반화할 수 있는 강력한 추론 능력(powerful ability to reason)을 보유할 수 있다는 것을 보여주고 있다. 본 논문에서는 관계 추론을 수행하는 심층신경망(deep neural networks) 중에서 Sort-of-CLEVR 데이터 셋(dataset)을 사용하여 RN(Relation Networks)의 성능을 재현 및 관찰해 보았으며, 더 나아가 파라미터(parameters) 튜닝을 통하여 RN(Relation Networks) 모델의 성능 개선방법을 제시하여 보았다.

• Composites Research
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• v.32 no.1
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• pp.13-20
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• 2019

In this study, in order to improve the quality issue and component characteristics of the battery module, which is one of the major parts of the electric vehicle. The structure is reinforced by using the composite material and the mechanism structure optimization of Hybrid concept which can overcome the disadvantages of single material was performed and the performance was compared. For this purpose, figure out the main design variables of composite materials according to Classical Laminated Plate Theory (CLPT) and the algorithm for predicting composite material properties have been studied. Based on the mechanical properties of the designed composite materials, finite element analysis (FEM) and the performance of the battery module was verified. Consequently, according to the verification result, Hybrid Battery Module reinforced with Selective Composite Patch can reduce the weight by 30% and reduce the product thickness by 32.5% compared with the existing Al battery module and proved the merit of Hybrid structure such as maintaining impact performance.

• Journal of the Korea Concrete Institute
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• v.20 no.6
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• pp.765-772
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• 2008

For RC structures, long-term deformation occurs due to the inherent characteristics, which are creep and shrinkage. In terms of serviceability, it is important to limit deflection caused by the deformation to the allowable deflection. In the recent years, various repair and strengthening methods have been used to improve performance of the existing RC structures. One of the typical methods is FRP externally bonded method (EBR). Fiber reinforced polymer (FRP) has been used worldwide as repair and strengthening materials due to its superior properties. Besides, it has to offer improved strengthening performance not only under instantaneous load but sustained load. Therefore, accurate prediction method of deflection for the RC members externally bonded with FRP under sustained load is required. In this paper, three beams were fabricated. Two beams were externally strengthened with one of CFRP plate and GFRP plate respectively. Total three beams were superimposed under sustained load of 25 kN. During 470 days, deflections at midspan were obtained. Moreover, creep coefficients and shrinkage strains were calculated by using ACI-209 code and CEB-FIP code. In order to predict the deflection of the beams, EMM, AEMM, Branson's method and Mayer's method were used. Through the experiment, it was found that the specimen with CFRP plate has the most flexural capacity and Mayer's method is the most precise method to predict total long-term deflections.