• Proceedings of the KSRS Conference
• /
• 2008.03a
• /
• pp.195-200
• /
• 2008

The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

• Korean Journal of Remote Sensing
• /
• v.25 no.3
• /
• pp.263-270
• /
• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Communications of the Korean Mathematical Society
• /
• v.11 no.4
• /
• pp.1105-1116
• /
• 1996

A partial ordering is developed among weakly positive quadrant dependent (WPQD) bivariate random vectors. This permits us to measure the degree of WPQD-ness and to compare pairs of WPQD random vectors. Some properties and closures under certain statistical operations are derived. An application is made to measures of dependence such as Kendall's $\tau$ and Spearman's $\rho$.

• Communications for Statistical Applications and Methods
• /
• v.13 no.3
• /
• pp.657-667
• /
• 2006

The concept of entropy, introduced in communication theory by Shannon (1948) as a measure of uncertainty, is of prime interest in information-theoretic statistics. This paper considers the minimum variance unbiased estimation for the maximum entropy of the transformed inverse Gaussian random variable by $Y=X^{-1/2}$. The properties of the derived UMVU estimator is investigated.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2005.05a
• /
• pp.144-148
• /
• 2005

The sensor network consists of sensor nodes which communicate wirelessly. It requires energy-efficient routing protocols. We measure requirements in routing protocols by using simulation techniques. In this paper, we propose a random routing algorithm and evaluate it by simulation.

• Communications of the Korean Mathematical Society
• /
• v.16 no.2
• /
• pp.297-308
• /
• 2001

A partial ordering is developed here among conditionally positive quadrant dependent (CPQD) bivariate random vectors. This permits us to measure the degree of CPQD-ness and to compare pairs of CPQD random vectors. Some properties and closure under certain statistical operations are derived.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.11a
• /
• pp.1131-1134
• /
• 2007

본 논문에서는 랜덤대치(random substitution) 기법에 대하여 심도 있는 분석을 실시한다. 랜덤대치 기법의 효율적인 구현을 위하여 데이터 재구축(reconstruction) 과정에서 필요로 하는 역행렬을 구하는 공식을 제시한다. 또한, 랜덤대치에 사용되는 다양한 파라미터들의 의미를 실험적으로 밝혀내며, 정확도와 프라이버시를 합리적으로 측정할 수 있는 새로운 측도(measure)들을 제안한다.

• The KIPS Transactions:PartD
• /
• v.15D no.4
• /
• pp.531-540
• /
• 2008

An Adaptive Random Testing(ART) is one of test case generation algorithms, which was designed to get better performance in terms of fault-detection capability than that of Random Testing(RT) algorithm by locating test cases in evenly spreaded area. Two ART algorithms, such as Distance-based ART(D-ART) and Restricted Random Testing(RRT), had been indicated that they have significant drawbacks in computations, i.e., consuming quadratic order of runtime. To reduce the amount of computations of D-ART and RRT, iterative partitioning of input domain strategy was proposed. They achieved, to some extent, the moderate computation cost with relatively high performance of fault detection. Those algorithms, however, have yet the patterns of non-uniform distribution in test cases, which obstructs the scalability. In this paper we analyze the distribution of test cases in an iterative partitioning strategy, and propose a new method of input domain enlargement which makes the test cases get much evenly distributed. The simulation results show that the proposed one has about 3 percent of improvement in terms of mean relative F-measure for 2-dimension input domain, and shows 10 percent improvement for 3-dimension space.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.12
• /
• pp.2240-2250
• /
• 2016

MIFARE Classic is the most popular contactless smart card, which is primarily used in the management of access control and public transport payment systems. It has several security features such as the proprietary stream cipher Crypto 1, a challenge-response mutual authentication protocol, and a random number generator. Unfortunately, multiple studies have reported structural flaws in its security features. Furthermore, various attack methods that target genuine MIFARE Classic cards or readers have been proposed to crack the card. From a practical perspective, these attacks can be partitioned according to the attacker's ability. However, this measure is insufficient to determine the optimal attack flow due to the refined random number generator. Most card-only attack methods assume a predicted or fixed random number, whereas several commercial cards use unpredictable and unfixable random numbers. In this paper, we propose optimal MIFARE Classic attack procedures with regards to the type of random number generator, as well as an adversary's ability. In addition, we show actual attack results from our portable experimental setup, which is comprised of a commercially developed attack device, a smartphone, and our own application retrieving secret data and sector key.

• Journal of the Korean Statistical Society
• /
• v.34 no.3
• /
• pp.185-195
• /
• 2005

This article is concerned with the intraclass correlation in survey sampling. From a design-based viewpoint the intraclass correlation is generalized to a finite population with unequal sized clusters. Under simple random cluster sampling the intraclass correlation is given in an explicit form, which is a generalization of the usual one. The range of it is found and the design effect is expressed by means of it. An example is given to compare the intraclass correlation with the homogeneity measure numerically, which shows that two measures are not the same except some limited cases.