• Journal of Wetlands Research
• /
• v.11 no.2
• /
• pp.89-98
• /
• 2009

This study determines the stream mean slope, stream slope and longitudinal stream profile based on the concept of informational entropy. Maximizing the entropy will make the probability distribution of longitudinal stream profile as uniform as possible while satisfying the constraints. Using this relationships the mean stream slope, stream slope and longitudinal stream profile formulas were derived. The parameters of the applied streams were estimated by the least square method using the geomorphological factors of Dalchon stream basin obtained from Chungcheong Buk-Do local stream consolidation scheme drawings. The comparative investigation was performed between the observed and simulated mean stream slope and longitudinal stream profile, and are in good agreement with the measured data. It is noted that this results can be used in the estimation of stream mean slope and longitudinal stream profile.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.855-859
• /
• 2007

It is essential to obtain accurate and highly reliable streamflow data for water resources planning, evaluation and management as well as design of hydraulic structures. A new discharge estimation method, which is named 'non-dimensional velocity distribution and index-velocity method,' was proposed in this research. This method showed very close channel discharges which were calculated with the exiting velocity-area method. When velocity-area method is used to estimate channel discharge, it is required to observe point velocities at every desired point and vertical using a current meter like Price-AA. However 'non-dimensional velocity distribution and index-velocity method' is used, it become optional to observe point velocities at every desired point and vertical. But this method can not be applied for the cases of very complex and strongly asymmetric channel cross-sections because non-dimensional velocity distribution by entropy concept may be quite biased from that of natural rivers.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.1
• /
• pp.25-39
• /
• 2018

NIST(National Institute of Standards and Technology) has recently published SP 800-90B second draft which is the document for evaluating security of entropy source, a key element of a cryptographic random number generator(RNG), and provided a tool implemented on Python code. In SP 800-90B, the security evaluation of the entropy sources is a process of estimating min-entropy by several estimators. The process of estimating min-entropy is divided into IID track and non-IID track. In IID track, the entropy sources are estimated only from MCV estimator. In non-IID Track, the entropy sources are estimated from 10 estimators including MCV estimator. The running time of the NIST's tool in non-IID track is approximately 20 minutes and the memory usage is over 5.5 GB. For evaluation agencies that have to perform repeatedly evaluations on various samples, and developers or researchers who have to perform experiments in various environments, it may be inconvenient to estimate entropy using the tool and depending on the environment, it may be impossible to execute. In this paper, we propose high-speed implementations and an efficient memory usage technique for min-entropy estimation algorithm of SP 800-90B. Our major achievements are the three improved speed and efficient memory usage reduction methods which are the method applying advantages of C++ code for improving speed of MultiMCW estimator, the method effectively reducing the memory and improving speed of MultiMMC by rebuilding the data storage structure, and the method improving the speed of LZ78Y by rebuilding the data structure. The tool applied our proposed methods is 14 times faster and saves 13 times more memory usage than NIST's tool.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.1C
• /
• pp.35-44
• /
• 2004

In this paper, we design an efficient VLSI architecture of entropy coding algorithm in JPEG2000. Entropy coder is a context-based binary arithmetic encoder, and composed of a Context Extractor(CE) and an Arithmetic Coder(AC). We speed-up CE by skipping no-operation bits in coding passes, and AC is to be performed based on MQ coder. Because of using Qe value associated with each allowed context and probability estimation, MQ coder is a multiplication free coder that reduces computation loads and makes simple the structure of arithmetic coder. We have developed and synthesized the VHDL models of CE and AC pairs using Xilinx FPGA technology. The proposed architecture operates up to 30MHz.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.28 no.4
• /
• pp.809-826
• /
• 2018

The entropy evaluation method for noise sources is one of the evaluation methods for the random number generator that is the essential element of modern cryptographic systems and cryptographic modules. The primary entropy evaluation methods outside of the country are more suitable to apply to hardware noise sources than software noise sources, and there is a difficulty in quantitative evaluation of entropy by software noise source. In this paper, we propose an entropy evaluation method that is suitable for software noise sources, considering characteristics of software noise sources. We select time-dependent noise sources that are software noise sources of Windows OS, and the heuristic analysis and experimental analysis are performed considering the characteristics of each time-dependent noise source. Based on these analyses, we propose an entropy harvest method from the noise source and the min-entropy estimation method as the entropy evaluation method for time-dependent noise sources. We also show how to use our entropy evaluation method in the Conditioning Component described in SP 800-90B of NIST(USA).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.12
• /
• pp.1892-1902
• /
• 2016

NIST SP 800-90B is developed to evaluate the security of entropy sources. As SP 800-90B was updated to Second Draft, Estimators with predictors were added at Non-IID track. Though the predictors are known as detecting periodic property of noise sources, periodic properties which are detected by predictor are not clearly known. In this paper, we experiment to find properties of predictors. Once, by experiments we have a result that the min-entropy of Non-IID noise sources is generally determined by tests except for estimators with predictors. And then through presenting various experimental results for clarifying periodic properties detected by predictor, we experimentally analyze on its meaning and role of predictor estimation.

• Proceedings of the KIPE Conference
• /
• 2015.07a
• /
• pp.381-382
• /
• 2015

배터리의 열역학적 인자, 즉, 엔탈피, 엔트로피, 깁스 자유 에너지는 배터리의 상태인 SOH (State Of Health)를 추정하는 데 있어서 매우 밀접한 관련이 있으며, 정밀한 측정을 필요로 한다. 이러한 열역학적 인자 중 엔트로피의 측정이 중요한데 ETM (Electrochemical thermodynamics measurements) 방법이 대표적으로 사용되고 있다. 본 논문에서는 기존 ETM 방법을 설명하고, 이를 보완한 새로운 엔트로피 측정 방법을 제안하며, 실험을 통해 유효성을 입증한다.

• Speech Sciences
• /
• v.14 no.4
• /
• pp.145-156
• /
• 2007

The performance of speaker identification is severely degraded in noisy environments. Recently probability weighting method based on observation membership was proposed for overcoming the noise problem[1]. In the paper[1] the observation confidence was calculated from SNR with sigmoid function. However, estimating SNR needs additive calculation amount and estimated SNR is corrupted in dynamic noisy environments. In this paper we propose estimation methods of the observation confidence based on score-based reliabilities (SBR) of entropy and dispersion measures. Generally SBRs are obtained from speaker models' probabilities. The proposed methods are evaluated with ETRI speaker recognition DB. We compared the performances of the proposed methods with those in [1][8]. The experimental results show that the proposed methods can be successfully applied for the case where SNR is not available.

• Journal of Broadcast Engineering
• /
• v.16 no.1
• /
• pp.133-143
• /
• 2011

In this paper, a complexity-balancing algorithm is proposed for distributed video coding based on entropy coding. In order to reduce complexity of DVC-based decoders, the proposed method employs an entropy coder instead of channel coders and the complexity-balancing method is designed to improve RD performance with minimal computational complexity. The proposed method performs motion estimation in the decoder side and transmits the estimated motion vectors to the encoder. The proposed encoder can perform more accurate refinement using the transmitted motion vectors from the decoder. During the motion refinement, the optimal predicted motion vectors are decided by the received motion vector and the predicted motion vectors and complexity load of block is allocated by adjusting the search range based on the difference between the received motion vector and the predicted motion vectors. The computational complexity of the proposed encoder is decreased 11.9% compared to the H.264/AVC encoder and that of the proposed decoder are reduced 99% compared to the conventional DVC decoder.

• The Journal of Korea Robotics Society
• /
• v.2 no.1
• /
• pp.29-39
• /
• 2007

We present an implementation of particle filter algorithm for global localization and kidnap recovery of mobile robot. Firstly, we propose an algorithm for efficient particle initialization using sonar line features. And then, the average likelihood and entropy of normalized weights are used as a quality measure of pose estimation. Finally, we propose an active kidnap recovery by adding new particle set. New and independent particle set can be initialized by monitoring two quality measures. Added particle set can re-estimate the pose of kidnapped robot. Experimental results demonstrate the capability of our global localization and kidnap recovery algorithm.