• The Korean Journal of Applied Statistics
• /
• v.29 no.3
• /
• pp.513-523
• /
• 2016

Fitting a mixture of multivariate skew normal distribution (MSNMix) with multiple skewness parameter vectors via EM algorithm often requires a highly expensive computational cost to calculate the moments and probabilities of multivariate truncated normal distribution in E-step. Subsequently, it is common to fit an asymmetric data set with MSNMix with a simple skewness parameter vector since it allows us to compute them in E-step in an univariate manner that guarantees a cheap computational cost. However, the adaptation of a simple skewness parameter is unrealistic in many situations. This paper proposes an approximate estimation for the MSNMix with multiple skewness parameter vectors that also allows us to treat them in an univariate manner. We additionally provide some experiments to show its effectiveness.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.8
• /
• pp.35-44
• /
• 2014

This paper proposes a 3D pointing interface that is designed for the efficient application of a hand mouse. The proposed method uses depth images to secure high-quality results even in response to changes in lighting and environmental conditions and uses the normal vector of the palm of the hand to perform 3D pointing. First, the hand region is detected and tracked using the existing conventional method; based on the information thus obtained, the region of the palm is predicted and the region of interest is obtained. Once the region of interest has been identified, this region is approximated by the plane equation and the normal vector is extracted. Next, to ensure stable control, interpolation is performed using the extracted normal vector and the intersection point is detected. For stability and efficiency, the dynamic weight using the sigmoid function is applied to the above detected intersection point, and finally, this is converted into the 2D coordinate system. This paper explains the methods of detecting the region of interest and the direction vector and proposes a method of interpolating and applying the dynamic weight in order to stabilize control. Lastly, qualitative and quantitative analyses are performed on the proposed 3D pointing method to verify its ability to deliver stable control.

• BMB Reports
• /
• v.38 no.2
• /
• pp.191-197
• /
• 2005

Although the human genome has been nearly completely sequenced, the functions and the roles of the vast majority of the genes, and the influences of single nucleotide polymorphisms (SNPs) in these genes are not entirely known. A modified mutation detection method was developed for large-scale cloning of the possible SNPs between tumor and normal cells for facilitating the identification of genetic factors that associated with cancer formation and progression. The method involves hybridization of restriction enzyme-cut chromosomal DNA, cleavage and modification of the sites of differences by enzymes, and differential cloning of sequence variations with a designed vector. Experimental validations of the presence and location of sequence variations in the isolated clones by PCR and DNA sequencing support the capability of this method in identifying sequence differences between tumor cells and normal cells.

• Communications for Statistical Applications and Methods
• /
• v.24 no.6
• /
• pp.641-649
• /
• 2017

Multivariate confidence regions were defined using a chi-square distribution function under a normal assumption and were represented with ellipse and ellipsoid types of bivariate and trivariate normal distribution functions. In this work, an alternative confidence region using the multivariate quantile vectors is proposed to define the normal distribution as well as any other distributions. These lower and upper bounds could be obtained using quantile vectors, and then the appropriate region between two bounds is referred to as the quantile confidence region. It notes that the upper and lower bounds of the bivariate and trivariate quantile confidence regions are represented as a curve and surface shapes, respectively. The quantile confidence region is obtained for various types of distribution functions that are both symmetric and asymmetric distribution functions. Then, its coverage rate is also calculated and compared. Therefore, we conclude that the quantile confidence region will be useful for the analysis of multivariate data, since it is found to have better coverage rates, even for asymmetric distributions.

• Communications for Statistical Applications and Methods
• /
• v.28 no.6
• /
• pp.673-679
• /
• 2021

The moment calculation in a truncated multivariate normal distribution is a long-standing problem in statistical computation. Recently, Kan and Robotti (2017) developed an algorithm able to calculate all orders of moment under different types of truncation. This result was implemented in an R package MomTrunc by Galarza et al. (2021); however, it is difficult to use the package in practical statistical problems because the computational burden increases exponentially as the order of the moment or the dimension of the random vector increases. Meanwhile, Lee (2021) presented an efficient numerical method in both accuracy and computational burden using Gauss-Hermit quadrature. This article introduces trunmnt implementation of Lee's work as an R package. The Package is believed to be useful for moment calculations in most practical statistical problems.

• Journal of Power Electronics
• /
• v.18 no.3
• /
• pp.714-722
• /
• 2018

This paper presents a wide-range speed control scheme of brushless DC (BLDC) motors based on a hall sensor with separated low- and normal-speed controllers. However, the use of the hall sensor signal is insufficient to detect motor speed in the low-speed region because of low sensor resolution and time delay. In the proposed method, a micro-stepping current control method according to the torque angle variation is presented. In this mode, the motor current frequency and rotating angle are determined by the reference speed without the actual speed fed by the hall sensor. The detected torque angle is used to adjust the current value in a limited band to control the current value in accordance with the load. The torque angle is detected exactly at the changing point of the hall sensor signal. The rotor can follow the rotating flux with the variable torque angle. In a normal speed range, the conventional vector control scheme is used to control the motor current with a PI speed controller using the hall sensor. The torque characteristics are analyzed on the basis of the back EMF and current shape. To adopt the vector control scheme, the continuous rotor position is estimated by the measured speed and hall sensor position. At the mode changing point between low and normal speed range, the proper initial current command and reference rotor position are calculated. The calculated current command can reduce the torque ripple during transient mode. The proposed method is simple but effective in extending the speed control range of a conventional BLDC motor with hall sensor without the need for a high-resolution encoder. The effectiveness of the proposed method is verified by various experiments on a practical BLDC motor.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.14 no.1
• /
• pp.35-45
• /
• 2004

In explosively increasing internet environments, information security is one of the most important consideration. Nowadays, various security solutions are used as such problems countermeasure; IDS, Firewall and VPN. However, basically internet has much vulnerability of protocol itself. Specially, it is possible to establish a covert channel using TCP/IP header fields such as identification, sequence number, acknowledge number, timestamp and so on. In this Paper, we focus cm the covert channels using identification field of IP header and the sequence number field of TCP header. To detect such covert channels, we used Support Vector Machine which has excellent performance in pattern classification problems. Our experiments showed that proposed method could discern the abnormal cases(including covert channels) from normal TCP/IP traffic using Support Vector Machine.

• Journal of Information Processing Systems
• /
• v.16 no.6
• /
• pp.1359-1371
• /
• 2020

In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.14 no.2
• /
• pp.23-33
• /
• 2004

Because of a rapid growth of internet environment, it is also fast increasing to exchange message using e-mail. But, despite the convenience of e-mail, it is rising a currently bi9 issue to waste their time and cost due to the spam mail in an individual or enterprise. Many kinds of solutions have been studied to solve harmful effects of spam mail. Such typical methods are as follows; pattern matching using the keyword with representative method and method using the probability like Naive Bayesian. In this paper, we propose a classification method of spam mails from normal mails using Support Vector Machine, which has excellent performance in pattern classification problems, to compensate for the problems of existing research. Especially, the proposed method practices efficiently a teaming procedure with a word dictionary including a generated index by the n-Gram. In the conclusion, we verified the proposed method through the accuracy comparison of spm mail separation between an existing research and proposed scheme.

• Proceedings of the KIEE Conference
• /
• 2000.11a
• /
• pp.39-42
• /
• 2000

In stressed power system, due to the presence of increased nonlinearity and the existence of nonlinear modal interactions, there exist some limitations to the use of conventional linear system theory to identify the optimum sites for controller. This paper proposes an approach to identify the optimum sites for controller using the method of normal forms. In this paper nonlinear participation factor and coupling factor are proposed as a measures of identification of optimum sites for controller and a selection procedure is also proposed. The proposed procedure is applied to the 10-generator New England System and the KEPCO System in the year of 2010 to illustrate its capabilities.