• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.4
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• pp.435-441
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• 2012

This paper provides simulation-based results of effect analysis of sample size and sampling periods on accuracy of reliability estimation methods using multiple comparisons with analysis of variance. Sum of squared errors in estimated reliability measures were evaluated through applying seven estimation methods for one-shot systems to simulated quantal-response data. Analysis of variance was implemented to investigate change in these errors according to variations of sample size and sampling periods for each estimation method, and then the effect analysis on accuracy in reliability estimation was performed using multiple comparisons based on sample size and sampling periods. An efficient way to allocate both sample size and sampling periods for reliability estimation tests of one-shot systems is proposed in this paper from the effect analysis results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.938-958
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• 2011

Ubiquitous web services have been expanding in various business areas with the evolution of wireless Internet technologies, accessible and usable with a variety of mobile Internet devices such as smart phones. Ubiquitous mobile-web information services can be evaluated for accessibility and usability with the mobile Internet devices interacting with mobile-web information servers. In human mobile-web activity, a web server could be a unified center for mobile-web interaction services as well as for real-time estimation and analysis of mobile-web interaction sessions. We present a real-time estimation and analysis scheme for time-based accessibility and usability in ubiquitous mobile-web services. With real-time estimation/analysis of sessions in a mobile-web server, we estimated the time-based accessibility and usability for comparison between different web services as well as for applications in mobile cloud computing services. We present empirical results based on the implementation of the real-time estimation/analysis scheme.

• Proceedings of the ESK Conference
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• 1995.10a
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• pp.13-17
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• 1995

A Psychophysical scaling method called magnitude estimation is frequently used to evaluate human sensation to physical stimuli. This paper described the procedure of magnitude estimation data analysis which consists of four modulus; reponse space, CMM(Cross-Modality Matdhing)/merge, standardization, scale building & data analysis method. This procedure is being developed as an expert system in which the four analysis modulus are programmed so that a novice user can perform the analysis.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.275-285
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• 2004

We explore classification analysis using graphical methods such as sliced inverse regression and sliced average variance estimation based on dimension reduction. Some useful information about classification analysis are obtained by sliced inverse regression and sliced average variance estimation through dimension reduction. Two examples are illustrated, and classification rates by sliced inverse regression and sliced average variance estimation are compared with those by discriminant analysis and logistic regression.

• Journal of Korean Academy of Nursing
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• v.41 no.6
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• pp.750-757
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• 2011

Purpose: Cost-benefit analysis is one of the most commonly used economic evaluation methods, which helps to inform the economic value of a program to decision makers. However, the selection of a correct benefit estimation method remains critical for accurate cost-benefit analysis. This paper compared benefit estimations among three different benefit estimation models. Methods: Data from community-based chronic hypertension management programs in a city in South Korea were used. Three different benefit estimation methods were compared. The first was a standard deterministic estimation model; second, a repeated-measures deterministic estimation model; and third, a transitional probability estimation model. Results: The estimated net benefit of the three different methods were $1,273.01, $-3,749.42, and $-5,122.55 respectively. Conclusion: The transitional probability estimation model showed the most correct and realistic benefit estimation, as it traced possible paths of changing status between time points and it accounted for both positive and negative benefits.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.285-294
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• 2012

Using bearing measurement only, target motion state is not directly obtained so that TMA (Target Motion Analysis) is needed for this situation. TMA is a nonlinear estimation technique used in passive SONAR systems. Also it is the one of important techniques for underwater combat management systems. TMA can be divided to two parts: batch estimation and sequential estimation. It is preferable to use sequential estimation for reducing computational load as well as adaptively to target maneuvers, batch estimation is still required to attain target initial state vector for convergence of sequential estimation. Selection of batch time interval which depends on observability is critical in TMA performance. Batch estimation in general utilizes predetermined batch time interval. In this paper, we propose a new method called the BTIS (Batch Time Interval and Initial State Estimation). The proposed BTIS estimates target initial status and determines the batch time interval sequentially by using a bank of GMM-TS (Gaussian Mixture Measurement-Track Splitting) filters. The performance of the proposal method is verified by a Monte Carlo simulation study.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.105-112
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• 2015

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.10
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• pp.788-796
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• 2016

Bearing and frequency measurements of TMA (Target Motion Analysis) in passive line array SONAR have lower bearing rate and frequency doppler, and are not detected or tracked continuously because of various ocean environments. This is a main reason to effect the TMA performance and it takes a long time to get TMA solutions. We propose the bearing and frequency TMA(BFTMA) using accumulative batch estimation to solve the TMA problem of line array passive SONAR. The accumulative batch estimation structure is based on MLE (Maximum Likelihood Estimation) but used accumulative measurements. The accumulative batch estimation is applied for the BFTMA with nonlinear Kalman filter to estimate the target range, speed and course. Simulation and sea data analysis were carried out to verify the performance and applicability of the proposed techniques.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1129-1134
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• 2006

Mass estimation was derived as functions of acceleration magnitude and primary frequency. The conventional method of mass estimation used frequency data directly in the frequency domain. The signals that can be obtained sensor contained noise as well as impact signal. Therefore, how well we can detect the frequency data in noise directly determines the quality of mass estimation. To find exact frequency data, we used time-frequency analysis. The time frequency method are expected to be more useful than the conventional frequency domain analyses for the mass estimation problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the mass estimation in a noisy environment.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.16 no.8 s.113
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• pp.872-878
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• 2006

Mass estimation was derived as functions of acceleration magnitude and primary frequency. The conventional method of mass estimation used frequency data directly in the frequency domain. The signals that can be obtained sensor contained noise as well as impact signal. Therefore, how well we can detect the frequency data in noise directly determines the quality of mass estimation. To find exact frequency data, we used time-frequency analysis. The time-frequency methods are expected to be more useful than the conventional frequency domain analyses for the mass estimation problem on a plate type structure. Also it has been concluded that the smoothed WVD can give more reliable means than the other methodologies for the mass estimation in a noisy environment.