• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.657-663
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• 2005

Under the minimum risk point estimation formulation of Robbins(1959), we consider the sequential point estimation problem for normal population $N({\theta},\;{\theta})$ with unknown parameter ${\theta}$. In the case of completely unknown ${\theta}$, Stein's(1945) two-stage procedure is known to enjoy the consistency property, but it is not even first-order efficient. In the case when ${\theta}>{\theta}_L\;where\;{\theta}_L(>0)$ is known, the revised two-stage procedure is shown to enjoy all the usual second-order properties.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.637-642
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• 2013

In this paper, we consider the maximum entropy test in in nite order autoregressiv models. Its asymptotic distribution is derived under the null hypothesis. A bootstrap version of the test is discussed and its performance is evaluated through Monte Carlo simulations.

• Journal of Information Technology Application
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• v.1
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• pp.173-211
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• 1999

The task of classification permeates all walks of life, from business and economics to science and public policy. In this context, nonlinear techniques from artificial intelligence have often proven to be more effective than the methods of classical statistics. The objective of knowledge discovery and data mining is to support decision making through the effective use of information. The automated approach to knowledge discovery is especially useful when dealing with large data sets or complex relationships. For many applications, automated software may find subtle patterns which escape the notice of manual analysis, or whose complexity exceeds the cognitive capabilities of humans. This paper explores the utility of a collaborative learning approach involving integrated models in the preprocessing and postprocessing stages. For instance, a genetic algorithm effects feature-weight optimization in a preprocessing module. Moreover, an inductive tree, artificial neural network (ANN), and k-nearest neighbor (kNN) techniques serve as postprocessing modules. More specifically, the postprocessors act as second0order classifiers which determine the best first-order classifier on a case-by-case basis. In addition to the second-order models, a voting scheme is investigated as a simple, but efficient, postprocessing model. The first-order models consist of statistical and machine learning models such as logistic regression (logit), multivariate discriminant analysis (MDA), ANN, and kNN. The genetic algorithm, inductive decision tree, and voting scheme act as kernel modules for collaborative learning. These ideas are explored against the background of a practical application relating to financial fraud management which exemplifies a binary classification problem.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.41-45
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• 2019

The 1-serving lunchbox app is designed and developed for enabling consumers to order their lunch box by choosing their own lunch side dishes. In modern society, one-person households are growing in larger areas. It is too burdensome to handle alone because it is cumbersome to cook alone and you should order from two people in a restaurant shop. To resolve such inconveniences, it is an app to choose various detailed menus and order personalized lunches. In the process of selecting a detailed menu, information provided by big data is used. You can use the existing order through the bookmark function, or you can use the recommended lunch menu using big data.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.595-610
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• 2013

Testing of order-restricted alternative hypothesis in $2{\times}k$ contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.

• IE interfaces
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• v.18 no.2
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• pp.205-220
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• 2005

This study presents a web log analysis model for e-CRM, which combines the on-line customer's purchasing pattern data and transaction data between companies in B2B environment of make-to-order company. With this study, the customer evaluation and the customer subdivision are available. We can forecast the estimate demands with periodical products sales records. Also, the purchasing rate per each product, the purchasing intention rate, and the purchasing rate per companies can be used as the basic data for the strategy for receiving the orders in future. These measures are used to evaluate the business strategy, the quality ability on products, the customer's demands, the benefits of customer and the customer's loyalty. And it is used to evaluate the customer's purchasing patterns, the response analysis, the customer's secession rate, the earning rate, and the customer's needs. With this, we can satisfy various customers' demands, therefore, we can multiply the company's benefits. And we presents case of the 'H' company, which has the make-to-order manufacture environment, in order to verify the effect of the proposal system.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.243-250
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• 1999

We consider $Y=X{\lambda}Z,\;{\lambda}>0$, where X and Z are independent random variables, and Y is the length biased distribution or the equilibrium distribution of X. The purpose of this paper is to consider the distribution of X or Y when the distribution of Z is given and the distribution of Z when the distribution of X or Y is given, In particular, we obtain that the necessary and sufficient conditions for X to be $X^{2}({\upsilon})\;is\;Z{\sim}X^{2}(2)\;and\;for\;Z\;to\;be\;X^{2}(1)\;is\;X{\sim}IG({\mu},\;{\mu}^{2}/{\lambda})$, where $IG({\mu},\;{\mu}^{2}/{\lambda})$ is two-parameter inverse Gaussian distribution. Also we show that X is smaller than Y in the reverse Laplace transform ratio order if and only if $X_{e}$ is smaller than $Y_{e}$ in the Laplace transform ratio order. Finally, we can get the results that if X is smaller than Y in the Laplace transform ratio order, then $Y_{L}$ is smaller than $X_{L}$ in the Laplace transform order, and that if X is smaller than Y in the reverse Laplace transform ratio order, then $_{\mu}X_{L}$ is smaller than $_{\nu}Y_{L}$ in the Laplace transform order.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.94-104
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• 2000

The accuracy and reliability of the target tracking is very critical issue in the design of automotive collision warning radar A significant problem in multi-target tracking (MTT) is the target-to-measurement data association If an incorrect measurement is associated with a target, the target could diverge the track and be prematurely terminated or cause other targets to also diverge the track. Most methods for target-to-measurement data association tend to coalesce neighboring targets Therefore, many algorithms have been developed to solve this data association problem. In this paper, a new multi-target data association method based on order statistics is described The new approaches. called the order statistics probabilistic data association (OSPDA) and the order statistics joint probabilistic data association (OSJPDA), are formulated using the association probabilities of the probabilistic data association (PDA) and the joint probabilistic data association (JPDA) filters, respectively Using the decision logic. an optimal or near optimal target-to-measurement data association is made A computer simulation of the proposed method in a heavy cluttered condition is given, including a comparison With the nearest-neighbor CNN). the PDA, and the JPDA filters, Simulation results show that the performances of the OSPDA filter and the OSJPDA filter are superior to those of the PDA filter and the JPDA filter in terms of tracking accuracy about 18% and 19%, respectively In addition, the proposed method is implemented using a developed digital signal processing (DSP) board which can be interfaced with the engine control unit (ECU) of car engine and with the d?xer through the controller area network (CAN)

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.247-257
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• 2007

In this paper, we develop the noninformative priors for the common shape parameter in the gamma distributions. We develop the matching priors and reveal that the second order matching prior does not exist. It turns out that the one-at-a-time reference prior and the two group reference prior satisfy a first order probability matching criterion. Some simulation study is peformed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.993-997
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• 2004

A data error inspection algorithm for wireless digital data communication was developed. Original data converted By wireless digital data error inspection algorithm. Wireless digital data is high possibility to get distortion and lose by noise and barrier on wireless. If the data check damaged and lost at receiver, can't make it clear and can't judge whether this data is right or not. Therefore, by wireless transmission data need the data error inspection algorithm in order to decrease the data distortion and lose and to monitoring the transmission data as real time. This study consists of RF station for wireless transmission, Water Level Meter station for water level measurement and Error inspection algorithm for error check of transmission data. This study is also that investigation and search for error inspection algorithm in order to wireless digital data transmission in condition of the least data's damage and lose. Designed transmitter and receiver with one - chip micro process to protect to swell the volume of circuit. Had designed RF transmitter - receiver station simply by means of ATMEL one - chip micro processing the systems. Used 10mW of the best RF power and 448MHz-449MHz on frequency band which is open to public touse free within the limited power.