• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.9
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• pp.514-518
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• 2014

The shingled magnetic recording method has interference between adjacent tracks. Furthermore, when read-head reads the data along the track, the head can be skewed by some physical effects. In this paper, in order to solve this problem, we propose a two-dimensional equalizer that uses two heads. If the head is skewed, it is possible to complement the performance by positioning the two heads at the center of the current track.

• 유체기계공업학회:학술대회논문집
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• 2001.11a
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• pp.23-29
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• 2001

Three-dimensional flow through a tubular centrifugal fan with airfoil type blades are analyzed using CFX-TASCflow. Standard k - $\epsilon$ model and k - $\omega$ model are used as turbulence closures. The numerical schemes for convetion terms, i.e., Upwind Differencing Scheme(UDS), Mass Weighted Skewed Upstream Differencing Scheme(MWS), Linear Profile Skewed Upstream Differencing Scheme(LPS), and Modified Linear Profile Skewed Upstream Differencing Scheme(MLPS) are also tested. And, the performance of these schemes coupled with two turbulence models are evaluated. Computational static pressure distributions are compared with experimental data obtained in this work.

• 한국데이터정보과학회:학술대회논문집
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• 2006.11a
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• pp.37-42
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• 2006

We shall consider an inference of the reliability P(Y

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.69-85
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• 2006

Broadcast has been often used to disseminate the frequently requested data efficiently to a large volume of mobile clients over a single or multiple channels. Conventional concurrency control protocols for mobile transactions are not suitable for the wireless broadcast environments due to the limited bandwidth of the up-link communication channel. In wireless broadcast environments, the server often broadcast different data items with different frequency to incorporate the data access patterns of mobile transactions. The previously proposed concurrency control protocols for mobile transactions in wireless broadcast environments are focused on the mobile transactions with uniform data access patterns. However, these protocols perform poorly when the data access pattern of update mobile transaction are not uniform but skewed. The update mobile transactions with skewed data access patterns will be frequently aborted and restarted due 4o the update conflict of the same data items with a high access frequency. In this paper, we propose an energy-efficient concurrence control protocol for mobile transactions with skewed data access as well as uniform data access patterns. Our protocol use a random back-off technique to avoid the frequent abort and restart of update mobile transactions. We present in-depth experimental analysis of our method by comparing it with existing concurrency control protocols. Our performance analysis show that it significantly decrease the average response time, the amount of upstream and downstream bandwidth usage over existing protocols.

• The KIPS Transactions:PartD
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• v.12D no.2 s.98
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• pp.179-188
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• 2005

Much research for spatial join has been extensively studied over the last decade. In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. In this case, many algorithms has presented and showed excellent performance over most spatial data. However, if data sets of input table for the spatial join ale skewed, the join performance is dramatically degraded. Also, little research on solving the problem in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join (SHSJ) algorithm that combines properties of the existing spatial hash join (SHJ) algorithm based on spatial partition for input data set's distribution and SSSJ algorithm. Finally, in order to show SHSJ the outperform in uniform/skew cases, we experiment SHSJ using the Tiger/line data sets and compare it with the SHJ algorithm.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.536-546
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• 2005

In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. Over the last decade, several spatial Join algorithms for the input tables with index have been extensively studied. Those algorithms show excellent performance over most spatial data, while little research on solving the performance degradation in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join(SHSJ) algorithm that can refine the problem of skewed data in the conventional spatial hash Join(SHJ) algorithm. The basic idea is similar to the conventional SHJ algorithm, but the differences are that bucket capacities are not limited while allocating data into buckets and SSSJ algorithm is applied to bucket join operations. Finally, as a result of experiment using Tiger/line data set, the performance of the spatial hash strip join operation was improved over existing SHJ algorithm and SSSJ algorithm.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Communications for Statistical Applications and Methods
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• v.24 no.2
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• pp.129-142
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• 2017

In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.227-244
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• 2023

In this paper, a depth-based nonparametric test for a multivariate two-sample scale problem is proposed. The proposed test statistic is based on the depth-induced ranks and is thus distribution-free. In this article, the depth values of data points of one sample are calculated with respect to the other sample or distribution and vice versa. A comprehensive simulation study is used to examine the performance of the proposed test for symmetric as well as skewed distributions. Comparison of the proposed test with the existing depth-based nonparametric tests is accomplished through empirical powers over different depth functions. The simulation study admits that the proposed test outperforms existing nonparametric depth-based tests for symmetric and skewed distributions. Finally, an actual life data set is used to demonstrate the applicability of the proposed test.

• Journal of KIISE:Databases
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• v.35 no.6
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• pp.518-532
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• 2008

Broadcast scheme has been widely researched for efficient data delivery in the mobile environment because the downlink capacity of a mobile client is much greater than the uplink capacity, and the power of a mobile client is limited. In the proposed scheme, the index lets the client know when data items would be broadcasted and enables the client to minimize the tuning time and power consumption. Single channel index schemes are fit to flat broadcast that performs well when all the broadcasted data items are accessed with the same probability whereas the multi-disk broadcast scheme is proper when the data access distribution is skewed. The existing index schemes, however, cannot work on the Multi-disk broadcast scheme because they cannot point the replicating data items in a broadcast cycle. This paper proposes a Multi-disk Exponential Index (MDEI) which is a single channel index scheme fit to Multi-disk broadcast scheme. Because MDEI scheme organizes a separate index for each disk, it functions with multi-disk broadcast, resulting in a greater reduction of average access latency than that of other flat-broadcast index schemes when the data access distribution is skewed. The performance evaluation showed that MDEI has a good performance when data access distribution is skewed. MDEI has short average access latency and not much average tuning time when the data access distribution is skewed.