• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1055-1059
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• 2006

In Wireless Sensor Networks(WSNs), a sensor node broadcasts the acquisited sensing data to neighboring other nodes and it makes serious data duplication problem that increases network traffic loads and data loss. This problem is concerned with the conflict condition for supporting both the reliability of data transfer and avoidance of network congestion. To solve the problem, a reliable congestion control protocol is necessary that considers critical factors affecting on data transfer reliability such as reliable data transmission, wireless loss, and congestion loss for supporting effective congestion control in WSNs. In his paper, we proposes a reliable congestion protocol, called HRCCP, based on hop-hop sequence number, and DSbACK by minimizing useless data transfers as an energy-saved congestion control method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.442-445
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• 2006

In Wireless Sensor Networks(WSNs), a sensor node broadcasts an acquisited data to neighboring other nodes and it makes serious data duplication problem that increases network traffic loads and data loss. This problem is concerned with the conflict condition for supporting both the reliability of data transfer and avoidance of network congestion. To solve the problem, a reliable congestion control protocol is necessary that considers critical factors affecting on data transfer reliability such as reliable data transmission, wireless loss, and congestion loss for supporting effective congestion control in WSNs. In this paper, we proposes a reliable congestion protocol, ratted HRCCP, based on hop-hop sequence number, and DSbACK by minimizing useless data transfers as an energy-saved congestion control method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.34-41
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• 2009

This paper investigates the issue of efficient reading for sensor data of semi-passive sensor tag. The Cold Chain management system requires complete sensor data without data loss and the short processing time of reading sensor tag data. However, reading the sensed data could be interfered by RF environment such as a jamming, obstacle and so on. This study found that it could lead to loss of the sensed data and takes much time to read it when data loss is occurred. To solve this problem, we propose the transaction processing mechanism that guarantees efficient reading of the sensed data. To do this, we present the technique of dynamic packet size and technique of data recovery to execute read transaction. These techniques improve the reliability of reading operation as well as speed up of read process for the large capacity data. This paper contributes to the improvement of efficient reading of sensed data without any loss of data and large time required.

• KSTLE International Journal
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• v.6 no.1
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• pp.21-27
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• 2005

A technique for a wear volume calculation is improved and verified in this research. The wear profile data measured by a surface roughness tester is used. The present technique uses a data flattening, the FFT and the windowing procedure, which is used for a general signal processing. The measured value of an average roughness of an unworn surfnce is used for the baseline of the integration for the volume calculation. The improvements from the previous technique are the procedures of the data flattening and the determination of a baseline. It is found that the flattening procedure efnciently manipulates the raw data when the levels of it are not horizontal, which enables us to calculate the volume reasonably well and readily. By comparing it with the weight loss method by using artificial dents, the present method reveals more volume by aroung 3~10%. It is attributed to the protruded region of the specimen and the inaccuracy and data averaging during the weght loss measurement. From a thorough investigation, it is concluded that the present technique can provide an accurate wear volume.

• Communications for Statistical Applications and Methods
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• v.17 no.1
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• pp.117-126
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• 2010

Clinical researchers often analyze survival data as binary outcomes using the logistic regression method. This paper examines the information loss resulting from analyzing survival time as binary outcomes. We first demonstrate that, under the proportional hazard assumption, this binary discretization does result in a significant information loss. Second, when fitting a logistic model to survival time data, researchers inadvertently use the maximal statistic. We implement a numerical study to examine the properties of the reference distribution for this statistic, finally, we show that the logistic regression method can still be a useful tool for analyzing survival data in particular when the proportional hazard assumption is questionable.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.749-755
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• 2009

Support vector classification (SVC) provides more complete description of the lin-ear and nonlinear relationships between input vectors and classifiers. In this paper. we propose the sparse kernel classifier to solve the optimization problem of classification with a modified hinge loss function and absolute loss function, which provides the efficient computation and the sparsity. We also introduce the generalized cross validation function to select the hyper-parameters which affects the classification performance of the proposed method. Experimental results are then presented which illustrate the performance of the proposed procedure for classification.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.1-6
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• 2005

In this paper we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.291-300
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• 2006

In this research, the performance of widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained empirical Bayes estimator are compared by means of a measurement under balanced loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.219-222
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• 1999

A SBR/Image ray-tracing technique using triangular ray tubes to predict the effects of walls. rooms. floors, and staircase is considered. Suggested technique is very efficient to estimate the path loss in three-dimensional buildings including the staircase. The model to predict the path loss through walls and floors in a multifloored building is presented. Measurements are made for three corridors having the staircase at 850 MHz, Measured data shows a close agreement with a simulated data.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.371-382
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• 2005

The paper compares the performance of some widely used Bayesian estimators such as Bayes estimator, empirical Bayes estimator, constrained Bayes estimator and constrained Bayes estimator by means of a new measurement under squared error loss function for the typical normal-normal situation. The proposed measurement is a weighted sum of the precisions of first and second moments. As a result, one can gets the criterion according to the size of prior variance against the population variance.