• Journal of electromagnetic engineering and science
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• v.11 no.2
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• pp.133-142
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• 2011

Coded cooperation that integrates channel coding in cooperative transmission has gained a great deal of interest in wireless relay networks. The performance analysis of coded cooperation protocol with multiple relays is investigated in this paper. We show that the diversity order achieved by the coded cooperation in a multi-relay wireless network is not only dependent on the number of cooperating relays but is also dependent on the code-rate of the system. We derive the code-rate bound, which is required to achieve the full diversity gain of the order of cooperating nodes. The code-rate required to achieve full diversity is a linearly decreasing function of the number of available relays in the network. We show that the instantaneous channel state information (CSI)-based relay selection can effectively alleviate this code-rate bound. Analysis shows that the coded cooperation with instantaneous CSI-based relay selection can achieve the full diversity, for an arbitrary number of relays, with a fixed code-rate. Finally, we develop tight upper bounds for the bit error rate (BER) and frame error rate (FER) of the relay selection based on coded cooperation under a Rayleigh fading environment. The analytical upper bounds are verified with simulation results.

• Management & Information Systems Review
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• v.3
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• pp.15-45
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• 1999

Processing techniques of remote sensed image data using computer have been recognized very necessary techniques to all social fields, such as, environmental observation, land cultivation, resource investigation, military trend grasp and agricultural product estimation, etc. Especially, accurate classification and analysis to remote sensed image da are important elements that can determine reliability of remote sensed image data processing systems, and many researches have been processed to improve these accuracy of classification and analysis. Traditionally, remote sensed image data processing systems have been processed 2 or 3 selected bands in multiple bands, in this time, their selection criterions are statistical separability or wavelength properties. But, it have be bring up the necessity of bands selection method by data distribution characteristics than traditional bands selection by wavelength properties or statistical separability. Because data sensing environments change from multispectral environments to hyperspectral environments. In this paper for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theory is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band using indiscernibility relation of Rough set theory from analysis results. Proposed method is applied to LANDSAT TM data on 2 June 1992. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.5
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• pp.1079-1086
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• 1990

Recently, demand for the experimental analysis of crack, such as arbitrary or distributed ones which has been considered quite difficult to investigate by the theoretical and numerical method, is increasing. Among existent experimental methods applied to the analysis of stress intensity factors, the slab analogy method have the following merits; cracks can be replaced by similarity-shaped rigid body, and the distribution of stress is represented by slab curvature of duly bent specimen. For the accuracy improvement of this method, multi-point selection method was introduced and its accuracy proved by applying this method to the analysis of centrally linear and inclined cracks in a finite plate which are theoretically known. In this paper, moreover, the stress intensity factors of eccentric and skew-symmetric bent cracks were determined by multi-point selection method and newly developed moire tilted master grating method. The results obtained by this method showed good agreement with the reliably theoretical solutions.

• KIEAE Journal
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• v.7 no.6
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• pp.91-97
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• 2007

This research examines the characteristics of the "rammed earth form" based on the criteria for the selection of forms. For this purpose, the paper first reviews the characteristics and orientation of the earth-construction and looks into the outline, the prerequisite, the current status and the tendency of the rammed earth form system through previous studies. Consequently, we aims to contribute to the criteria for the selection of rammed earth forms in the future through a comparative analysis of the construction cost, quality, safety and easiness of works between the veneer board form and the euroform, which are most widely used at earth housing project in the domestic country. The results reveals that the euroform is better than the veneer board with 21% of total cost in the cost analysis. But this better than that in the side of easiness of construction. In both cases, the buckling of wall panel form and the labor-oriented characteristics of the methods are the future research issues in the rammed earth form system.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.1-7
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• 2023

In this paper, we propose a base address candidate selection method using the $gp register and page granularity as a way to build a static analysis environment for firmware based on MIPS architecture. As a way to shorten the base address search time, which is a disadvantage of the base address candidate selection method through inductive reasoning in existing studies, this study proposes a method to perform page-level search based on the $gp register in the existing base address candidate selection method as a reference point for search. Then, based on the proposed method, a base address search tool is implemented and a static analysis environment is constructed to prove the validity of the target tool. The results show that the proposed method is faster than the existing candidate selection method through inductive reasoning.

• Journal of the Korean Data and Information Science Society
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• v.24 no.5
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• pp.1077-1088
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• 2013

High-dimensional data analysis arises from almost all scientific areas, evolving with development of computing skills, and has encouraged penalized estimations that play important roles in statistical learning. For the past years, various penalized estimations have been developed, and the least absolute shrinkage and selection operator (LASSO) proposed by Tibshirani (1996) has shown outstanding ability, earning the first place on the development of penalized estimation. In this paper, we first introduce a number of recent advances in high-dimensional data analysis using the LASSO. The topics include various statistical problems such as variable selection and grouped or structured variable selection under sparse high-dimensional linear regression models. Several unsupervised learning methods including inverse covariance matrix estimation are presented. In addition, we address further studies on new applications which may establish a guideline on how to use the LASSO for statistical challenges of high-dimensional data analysis.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.5-12
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• 2000

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. We consider hierarchical models including selection models under a skewed heavy tailed error distribution and it is shown to be useful in such Bayesian meta-analysis. A general class of skewed elliptical distribution is reviewed and developed. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierarchical selection model and use Markov chain Monte Carlo methods to develop inference for the parameters of interest.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.05a
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• pp.54-55
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• 2017

Recently, plastic panels have replaced plywood panels in formwork. Since, plastic panels have excellent workability, can be re-used for over 50 times, and are lighter than Plywood. This paper aims to perform an economic analysis of plastic panels by considering unit cost, cost of form oil and the number of use. The results showed that plastic panels are more economical than plywood according to an increase in area of construction site. This result of the study can be used as a basic data for the selection of plastic formwork panels.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.563-564
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• 2006

In silicon wafer manufacturing process, the grinding process has been adopted to improve the flatness of water. The grinding of wafer is usually used by the infeed grinding machine. Grinding conditions are spindle speed, feed speed, rotation speed, grinding stone etc. But grinding condition selection and analysis is so difficult in grinding machine. In the intelligent grinding system based on knowledge many researchers have studied expert system, neural network, fuzzy etc. In this paper we deal grinding condition selection method, Taguchi method and Genetic Analysis.

• Phonetics and Speech Sciences
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• v.3 no.3
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• pp.99-108
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• 2011

The perturbation parameters like jitter, shimmer, and signal-to-noise ratio (SNR) are largely estimated in the particular segment from the subjective or whole portion of the given pathological voice signal although there are many possible regions to be able to analyze the voice signals. In this paper, the pathological voice signals were classified as type 1, 2, 3, or 4 according to narrow band spectrogram and the value differences of the perturbation parameters extracted in the subjective and entire portion tended to be getting bigger as from type 1 to type 4 signals. Therefore, sample selection method based on moving window to analyze type 2 and 3 signals as well as type 1 signals is proposed. Although type 3 signals cannot be analyzed using the perturbation analysis, the type 3 signals by selecting out the samples in which error count is less than 10 through moving window were analyzed. At present, there is no method to be able to analyze the type 4 signals. Future research will endeavor to determine the best way to evaluate such voices.