• Environmental Engineering Research
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• v.17 no.3
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• pp.167-174
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• 2012

In situ particle size spectra are obtained from two sequent cruises in order to evaluate the physical consequences of suspended particulate matters caused by episodic storm runoff from the Santa Ana River watershed, an urbanized coastal watershed. Suspended particles from various sources including surface runoff, near-bed resuspension, and phytoplankton are identified in empirical orthogonal function (EOF) analysis and an entropy-based parameterization (Shannon entropy). The first EOF mode is associated with high turbidity and fine particles as indicated by the elevated beam attenuation near the Santa Ana River and Newport Bay outlets, and the second EOF mode explains the suspended sediment dispersal and particle coarsening at the near-surface plume. Chlorophyll particles are also distinguished by negative magnitudes of the first EOF mode, which is supported by the relationship between fluorescence and beam attenuation. The integrated observation between the first EOF mode and the Shannon entropy index accentuates the characteristics of two different structures and/or sources of sediment particles; the near-surface plumes are originated from runoff water outflow, while the near-bottom particles are resuspended due to increased wave heights or mobilizing bottom turbidity currents. In a coastal pollution context, these methods may offer useful means of characterizing particle-associated pollutants for purposes of source tracking and environmental interpretation.

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

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.17-24
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• 2011

In this paper, we propose an Entropy-based Routing Protocol using Mobility (ERPM) for supporting ubiquitous convergence services efficiently in mobile ad-hoc wireless networks. The main features that the ERPM introduces to obtain the goals can be summarized as follows. First, ERPM can construct stable routing routes based on the entropy concepts using mobility of nodes. Second, ERPM can quantitatively evaluate the stability of route by entropy concepts using mobility of nodes. Third, ERPM can select the most stable route in the view points of mobility of routes between a source node and a destination node, where multiple paths are available. The performance evaluation of the proposed ERPM performed via simulation using OPNET and analysis shows that the ERPM can support the construction of stable routing routes and increase the transmission ratio of data efficiently.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.984-986
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• 1989

101 coding scheme, one of sliding block coding techniques, provides practically attractive features in some compression applications for image sources such as facsimile. This paper presents a new simple model of 101 coder. The results show that the entropy of the output of the 101 coder can be reduced close to the rate distortion bound of a binary first-order markov source.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.89-103
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• 2018

A genius "Prince of Mathematician" Gaussian and "Father of Communication" Shannon comes up with the creative idea of motivation to meet each other? The answer is a coin leaf. Gaussian found some creative ideas in the matter of obtaining a sum of 1 to 100. This is the same as the probability distribution curve when a coin leaf is thrown. Shannon extended the Gaussian probability distribution to define the entropy, taking the source symbol and the reciprocal logarithm to obtain the weighted average. These where the genius Gaussian and Shannon meet in the same coin leaf. This paper focuses on this point, and easily proves Gaussian distribution and Shannon entropy. As an application example, we have obtained the capacity and transition probability of Jeongju seminal vesicle, and the Shannon channel capacity is 1 when the equivalent transition probability is 1/2.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.606-609
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• 2008

Deconvolution is one of the most used techniques for processing seismic reflection data. It is applied to improve temporal resolution by wavelet shaping and removal of short period reverberations. Several deconvolution algorithms such as predicted, spike, minimum entropy deconvolution and so on has been proposed to obtain such above purposes. Among of them, $\iota_1$ norm proposed by Taylor et al., (1979) and used to compared to minimum entropy deconvolution by Sacchi et al., (1994) has given some advantages on time computing and high efficiency. Theoritically, the deconvolution can be considered as inversion technique to invert the single seismic trace to the reflectivity, but it has not been successfully adopted due to noisy signals of the real data set and unknown source wavelet. After stacking, the seismic traces are moved to zero offset, thus each seismic traces now can be a single trace that is created by convolving the seismic source wavelet and reflectivity. In this paper, the fundamental of $\iota_1$ norm deconvolution method will be introduced. The method will be tested by synthetic data and applied to improve the stacked section of gas hydrate.

• ETRI Journal
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• v.45 no.2
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• pp.346-357
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• 2023

Hardware security primitives, also known as physical unclonable functions (PUFs), perform innovative roles to extract the randomness unique to specific hardware. This paper proposes a novel hardware security primitive using a commercial off-the-shelf flash memory chip that is an intrinsic part of most commercial Internet of Things (IoT) devices. First, we define a hardware security source model to describe a hardware-based fixed random bit generator for use in security applications, such as cryptographic key generation. Then, we propose a hardware security primitive with flash memory by exploiting the variability of tunneling electrons in the floating gate. In accordance with the requirements for robustness against the environment, timing variations, and random errors, we developed an adaptive extraction algorithm for the flash PUF. Experimental results show that the proposed flash PUF successfully generates a fixed random response, where the uniqueness is 49.1%, steadiness is 3.8%, uniformity is 50.2%, and min-entropy per bit is 0.87. Thus, our approach can be applied to security applications with reliability and satisfy high-entropy requirements, such as cryptographic key generation for IoT devices.

• Journal of ILASS-Korea
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• v.1 no.1
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• pp.44-54
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• 1996

A theoretical and experimental study was carried out on the prediction of drop size distribution of the pressure swirl atomizer. Drop size distribution was obtained by using maximum entropy formal ism. Several constraints in the form of the definition of mean diameter were used in this formulation in order to avoid the difficulties of the estimating source terms. In this study $D_{10}$ was only introduced into the formulation as a constraint. A drop size obtained by using linear Kelvin-Helmholtz instability theory was considered as an unknown characteristic length scale. As a result, the calculated drop size was agreed well with measured mean diameter, particularly with $D_{32}$. The predicted drop size distribution was agreed welt with experimental data measured wi th Malvern 2600.

• Journal of ILASS-Korea
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• v.3 no.2
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• pp.1-13
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• 1998

A theoretical and experimental study was carried out to predict the drop size distribution of the pressure swirl atomizer. Various analytical methods using the Kelvin-Helmholtz instability theory were tried to examine the wave growth on cylindrical liquid sheets. Cylinderical liquid sheets were extended to the case with the conical sheets. Perturbations due to tangential motion as well as longitudinal one were taken into account. And it was assumed that the breakup occurs when amplitude ratio exceeds exp(12), drop sizes were predicted only by theoretical approach. Drop size distribution was obtained by using maximum entropy formalism. Seven constraints in the form of the definition of mean diameter were used in this formulation in order to avoid the difficulties of estimating source terms. In this study $D_{10}$ only was introduced into the formulation as a constraint. The predicted drop size and drop size distribution agreed well with the measured data.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.77-86
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• 2024

Using random numbers to represent uncertainty and unpredictability is essential in many industries. This is crucial in disciplines like computer science, cryptography, and statistics where the use of randomness helps to guarantee the security and dependability of systems and procedures. In computer science, random number generation is used to generate passwords, keys, and other security tokens as well as to add randomness to algorithms and simulations. According to recent research, the hardware random number generators used in billions of Internet of Things devices do not produce enough entropy. This article describes how raw data gathered by IoT system sensors can be used to generate random numbers for cryptography systems and also examines the results of these random numbers. The results obtained have been validated by successfully passing the FIPS 140-1 and NIST 800-22 test suites.