• ETRI Journal
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• v.29 no.5
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• pp.607-613
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• 2007

Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front-end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified-covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in-service SNR estimators in digital communication channels. The simulated performance is also compared to the Cram$\acute{e}$r-Rao bound as derived at the input of the decision circuit.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.191-212
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• 2012

Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked imposes stringent constraints on the "unlearning" capabilities of the estimator used. Therefore, resorting to strong estimators that converge with a probability of 1 is inefficient since they rely on the assumption that the distribution of the user's preferences is stationary. In this vein, we propose to use a family of stochastic-learning based Weak estimators for learning and tracking a user's time varying interests. Experimental results demonstrate that our proposed paradigm outperforms some of the traditional legacy approaches that represent the state-of-the-art technology.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.111-126
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• 2000

Small area estimation is becoming important in survey sampling due to a growing demand for reliable small area statistics. In estimating means, totals, and other parameters for small areas of a finite population, samplie sizes for small areas are typically small because the overall sample size is usually determined to provide specific accuracy at a much higher level of aggregation than that of small area. The usual direct estimators that use the only information which is gotten from the sample in a given small area provide unreliable estimates. However, indirect estimators utilize the information from the areas related with a given small area, that is, borrow strength from other related areas, and so give more accurate estimates than direct estimators. In this paper we investigate small area estimation methods such as synthetic, composite and empirical best linear unbiased prediction estimator, and apply them to real domestic data which is from the Survey of Hotels and Restaurants in In-Chon as of 1996 and then evaluate the performance of these methods by measuring average squared errors. This evaluation shows that indirect estimators, which are small area estimation methods, are more efficient than direct estimator.

• Journal of the Korean Data and Information Science Society
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• v.18 no.4
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• pp.1045-1056
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• 2007

We consider M/M/1 feedback queues with multi-class customers. We assume that different classes of customers have different arrival rates, service rates and feedback probabilities. Using the h-transforms of McDonald(999) we derive an importance sampling estimator for an overflow probability that the total number of customers in the system reaches a high level before emptying.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• International journal of advanced smart convergence
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• v.3 no.2
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• pp.14-17
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• 2014

Precision agriculture relies on information technology, whose precondition is providing real-time and accurate information. It depends on various kinds of advanced sensors, such as environmental temperature and humidity, wind speed, light intensity, and other types of sensors. Currently, it is a hot topic how to collect accurate information, the main raw data for agricultural experts, monitored by these sensors timely. Most existing work in WSNs addresses their fundamental challenges, including power supply, limited memory, processing power and communication bandwidth and focuses entirely on their operating system and networking protocol design and implementation. However, it is not easy to find the self-localization capability of wireless sensor networks. Because of constraints on the cost and size of sensors, energy consumption, implementation environment and the deployment of sensors, most sensors do not know their locations. This paper provides maximum likelihood estimators for sensor location estimation when observations are time-of arrival (TOA) range measurement.

• Journal of Distribution Science
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• v.11 no.4
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• pp.81-88
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• 2013

Purpose - This paper analyzes the influence of the RMB internationalization on the KRW/dollar exchange rate using an autoregressive distributed lag model. Comparing the parameter estimators from the sample period before and after the global financial crisis, we found that the RMB/dollar exchange rate has increasingly become more influential on the KRW/dollar exchange rate. Moreover, for the past several years, the Chinese government has actively utilized the financial service FTA negotiation as a measure for the RMB internationalization. This paper simultaneously considers RMB internationalization and financial service negotiations in the Korean-Chinese FTA. The purpose of this paper is to explicitly suggest a direction for the financial service negotiations in the Korean-Chinese FTA considering the effects of RMB internationalization. Research design, data, and methodology - The research plan of this paper has two parts. First, for an empirical study, this paper uses the daily exchange rate of the U.S. dollar against the currencies of the ASEAN5, Taiwan,and Korea. By using an autoregressive distributed lag model, this paper studies the influence of the change in the RMB/dollar exchange rate on changes in the local currency/dollar exchange rate in seven economies neighboring China. Our sample periods are 06/2005 - 07/2008 and 06/2010 -02/2013. During these periods, China was under the multi-currency basket system. We exempted the period of 08/2008 - 05/2010 from the analysis because there was nearly no RMB/dollar exchange rate fluctuation during those months. Second, after analyzing the recent financial service liberalizations and deregulations in China, we recommend a direction for the financial service negotiations in the Korean-Chinese FTA. In the past several years,the main Chinese financial policy agenda has surrounded the RMB internationalization. Therefore, it is crucial to understand this in the search for strategies for the financial service negotiations in the Korean-Chinese FTA. This paper employs an existing literature survey and examines the FTA protocols in its research methodology. Results and Conclusions - After the global financial crisis, the Chinese government wanted to break away from the dollar influence and pursued independent RMB internationalization in order to continue the growth and stability of its economy. Hence, every neighboring economy of China has been strategically impacted by RMB internationalization. Nevertheless, there is little empirical study on the influence of RMB internationalization on the KRW/dollar exchange rate. This paper is one of the few studies to analyze this problem comprehensively. By using a relatively simple estimation model, we can confirm that the coefficient of the RMB/dollar exchange rate has become more significant, except in the case of Indonesia. Although Korea is not under the multi-currency basket system but under the weakly controlled floating exchange rate system, its coefficient appears as large as that of the ASEAN5. This is the basis of the currency cooperation that has grown from the expansion of trade between the two countries. These empirical results suggest that the Korean government should specifically consider the RMB internationalization in the Korean-Chinese FTA negotiations.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.71-78
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• 2012

This research discusses the application of the control variables to achieve a more precise estimation for the target response in queueing network simulation. The efficiency of control variable method in estimating the response depends upon how we choose a set of control variables strongly correlated with the response and how we construct a function of selected control variables. For a class of queuing network simulations, the random variables that drive the simulation are basically the service-time and routing probability random variables. Most of applications of control variable method focus on utilization of the service time random variables for constructing a controlled estimator. This research attempts to suggest a controlled estimator which uses these two kinds of random variables and explore the efficiency of these estimators in estimating the reponses for computer network system. Simulation experiments on this model show the promising results for application of routing probability control variables. We consider the applications of the routing probability control variables to various simulation models and combined control variables using information of service time and routing probability together in constructing a control variable as future researches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2426-2432
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• 2011

In this study, we evaluated web usability for hospital web sites in Korea and analyzed the evaluation results of web usability. Estimators investigated twelve hospital web sites and answered a questionnaire. They also performed predefined tasks which were frequently used services in hospital web sites. We had an interview with the estimator for finding what happened in process of evaluating usability. The evaluation results showed that university hospital provided comparatively better web usability for users. But ambiguous and complicated user interface caused confusion among users. The simplifications of service processes and interfaces were necessary to improve web usability. Some hospitals did not offer primary web services and their services related to the tasks were not systematic.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.119-126
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• 2005

Load bearing structural members in a wide variety of applications accumulate damage over their service life. From a standpoint of both safety and performance, it is desirable to monitor the occurrence, location, and extent of such damage. Structures require complicated element models with a number of degrees of freedom in structural analysis. During experiment much effort and cost is needed for measuring structural parameters. The sparseness and errors of measured data have to be considered during the parameter estimation Of Structures. In this paper we introduces damage identification algorithm by a system identification(S.I) using static and dynamic response. To study the behaviour of the estimators in noisy environment Using Monte Carlo simulation and a data measured perturbation scheme is adopted to investigate the influence of measurement errors on identification results. The assessment result by static and dynamic response were compared, and the efficiency and applicabilities of the proposed algorithm are demonstrated through simulated static and dynamic responses of a truss bridge. The assessment results by each method were compared and we could observe that the 5.1 method is superior to the other conventional methods.