• The KIPS Transactions:PartC
• /
• v.17C no.2
• /
• pp.165-172
• /
• 2010

Sensor network can be applied in many areas in our life, and security is very important in applying sensor network. For secure sensor communication, pairwise key establishment between sensor nodes is essential. In this paper, we cluster the network field in hexagonal shapes and preassign three different kinds of key information for each sensor according to its expected location. We adopt overlapped key string pool concept for our clustered network architecture and every node uses the part of sub-strings for setting up pairwise keys with all neighboring nodes in its own cluster and from different clusters according to respective position with small amount of information. Our proposal decreases the memory requirement and increases security level efficiently.

• ETRI Journal
• /
• v.43 no.3
• /
• pp.524-537
• /
• 2021

High-performance Linpack (HPL) is among the most popular benchmarks for evaluating the capabilities of computing systems and has been used as a standard to compare the performance of computing systems since the early 1980s. In the initial system-design stage, it is critical to estimate the capabilities of a system quickly and accurately. However, the original HPL mathematical model based on a single core and single communication layer yields varying accuracy for modern processors and accelerators comprising large numbers of cores. To reduce the performance-estimation gap between the HPL model and an actual system, we propose a mathematical model for multi-communication layered HPL. The effectiveness of the proposed model is evaluated by applying it to a GPU cluster and well-known systems. The results reveal performance differences of 1.1% on a single GPU. The GPU cluster and well-known large system show 5.5% and 4.1% differences on average, respectively. Compared to the original HPL model, the proposed multi-communication layered HPL model provides performance estimates within a few seconds and a smaller error range from the processor/accelerator level to the large system level.

• The Korean Journal of Applied Statistics
• /
• v.22 no.2
• /
• pp.355-364
• /
• 2009

A simple method is proposed for constructing nonparametric confidence intervals for the difference or ratio of two median failure times. The method applies when clustered survival data with censoring is randomized either (I) under cluster randomization or (II) subunit randomization. This method is simple to calculate and is based on non-parametric density estimation. The proposed method is illustrated with the otology study data and HL-A antigen study data. Moreover, the simulation results are reported for practical sample sizes.

• Communications for Statistical Applications and Methods
• /
• v.22 no.3
• /
• pp.265-276
• /
• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Journal of the Korean Society for Precision Engineering
• /
• v.29 no.5
• /
• pp.494-499
• /
• 2012

Reliable results can't be derived without the notion of measurement uncertainty. The reason is that the measured value includes a lot of uncertain factors. Finding the factor that affect the measurement of parameter is important for estimation of measurement uncertainty. In this paper, the evaluation of uncertainty analysis about positioning accuracy measurements of high precision feed mechanism is presented to evaluate the important factors of uncertainty.

• International journal of advanced smart convergence
• /
• v.7 no.2
• /
• pp.33-37
• /
• 2018

In this study, we propose an iterative clustering algorithm that automatically clusters a set of voice signal data without a label into an optimal number of clusters and generates hmm model for each cluster. In the clustering process, the likelihood calculations of the clusters are performed using iterative hmm learning and testing while varying the number of clusters for given data, and the maximum likelihood estimation method is used to determine the optimal number of clusters. We tested the effectiveness of this clustering algorithm on a small-vocabulary digit clustering task by mapping the unsupervised decoded output of the optimal cluster to the ground-truth transcription, we found out that they were highly correlated.

• Journal of the Korean Society for Precision Engineering
• /
• v.28 no.4
• /
• pp.404-409
• /
• 2011

Report on the notion of uncertainty is important. The reason is that the measured value includes a lot of uncertain factors. Reliable results can't be derived without the notion of uncertainty. The mathematical model to evaluate uncertainty considering the quality of vibration is important to evaluate uncertainty, and it must contain the every quantity which contributes significantly to uncertainty in the measured results. In this paper, the evaluation of uncertainty analysis about rotor vibration measurements of machine tools is presented to evaluate the most important factors of uncertainty.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.10C
• /
• pp.976-982
• /
• 2005

In this paper, a channel-adaptive beamforming method is proposed for OFDMA (Orthogonal Frequency Division Multilexing Access) systems with smart antenna, in which the size of a cluster is determined adaptively depending on the frequency selectivity of the channel. The proposed method consists of 4 steps: initial channel estimation, refinement of channel estimates, region-splitting, and computation of weight vector for each region. In the proposed method, the size of a cluster for resource unit is determined adaptively according to a region-splitting criterion. It is shown by simulation that the proposed method shows good performances in both frequency-flat and frequency-selective channels.

• Journal of Korean Society of Forest Science
• /
• v.96 no.2
• /
• pp.125-130
• /
• 2007

The principal morphological characters used for identification of hydrangea cultivars are often dependent on agroclimatic conditions. Furthermore, information on the selection or the genetic background of the hydrangea breeding is so rare that a molecular marker system for cultivar identification is needed. Amplified fragment length polymorphism (AFLP) markers were employed for fingerprinting Hydrangea macrophylla cultivars and candidate cultivars of H. macrophylla selected in Korea. One AFLP primer combination was sufficient to distinguish 17 H. macrophylla cultivars and 4 candidate cultivars. The profile of 19 loci that can minimize the error of amplification peak detection was constructed. AFLP markers were efficient for identification, estimation of genetic distances between cultivars, and cultivar discrimination. Based on the observed AFLP markers, genetic relationship was reconstructed by the UPGMA method. Seventeen H. macrophylla cultivars and H. macrophylla for. normalis formed a major cluster, and candidate cultivars selected in Korea formed another cluster.

• Journal of the Ergonomics Society of Korea
• /
• v.29 no.2
• /
• pp.217-224
• /
• 2010

Research has been conducted to examine the effects of mechanical and sound characteristics of fabrics on affective quality. The present study developed the Affective Quality Evaluation and Estimation System for Textiles (AQEEST) with distinguished features that can be effectively used in the affective research of fabric frictional sound. The AQEEST consists of three subsystems (affective quality evaluation, affective quality estimation, and audible distance estimation subsystems) and each subsystem consists of three to four modules (e.g., evaluation condition setup, evaluation experimentation, and textile database management modules) depending on its functional requirements. The affective quality evaluation subsystem was designed to help administer an experiment in a systematic manner and present acoustic and visual stimuli simultaneously in various gait conditions (walking, jogging, and running) to mimic a more realistic situation of textile frictional sound production. Next, the affective quality estimation subsystem was designed to estimate the sound characteristics, affective qualities, overall psychological satisfaction, and reference cluster of a textile using its mechanical and/or sound characteristic information. Lastly, the audible distance estimation subsystem was designed to estimate the just noticeable sound pressure levels and audible distances of a textile for various gait conditions using its mechanical characteristic information. The AQEEST can be upgraded by accommodating more affective quality study results for various textiles.