• Journal of Korean Society on Water Environment
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• v.26 no.2
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• pp.297-302
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• 2010

It is very important to know mean and confidence interval of water-quality constituents such as BOD for water-quality control and management of rivers and reservoirs effectively. The mean and confidence interval of BOD at Anseong2 and Hwangguji3 sampling stations which are located at the border of local governments in Anseong Stream were estimated and analyzed in this paper using Bootstrap technique which is one of non-parametric statistics. The results of Bootstrap were compared with arithmetic mean, geometric mean, Biweight method mean as a point estimator and distribution mean came from the appropriate probability distribution of Log-normal. In Bootstrap technique 12 data set was randomly selected in each year and 1000 samples was produced to get parameter of population. Visual Basic for Applications (VBA) of Microsoft Excel was utilized in Bootstrap. It was revealed that the Bootstrap technique can be used to explain more rigorously and robustly the achievement or violation of BOD target concentration in Total Maximum Daily Load (TMDL).

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.875-882
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• 2014

In this paper, we propose a new parameter estimation method that can deal with the data of multiple time intervals simultaneously. If there are common modes in the multiple time intervals, it is possible to create a new polynomial by summing the coefficients of the prediction error polynomials of each time interval. By calculating the roots of the new polynomial, it is possible to estimate the common modes that exist in each time interval. The accuracy of the proposed parameter estimation method has been proven by using appropriate test signals.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.63-70
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• 2018

In this work, we analyze the relationship between the accumulated mileage of hybrid electric vehicle(HEV) and the data provided from vehicle parts. Data were collected while traveling over 70,000 Km in various paths. The data collected in seconds are aggregated for 10 minutes and characterized in terms of centrality, variability, normality, and so on. We examined whether the statistical properties of vehicle parts are different for each cumulative mileage interval of a hybrid car. When the cumulative mileage interval is categorized into =< 30,000, <= 50,000, and >50,000, the statistical properties are classified by the mileage interval as 82.3% accuracy. This indicates that if the data of the vehicle parts is collected by operating the hybrid vehicle for 10 minutes, the cumulative mileage interval of the vehicle can be estimated. This makes it possible to detect the abnormality of the vehicle part relative to the accumulated mileage. It can be used to detect abnormal aging of vehicle parts and to inform maintenance necessity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.779-782
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• 2008

It is important to detect speech active interval from Noisy Speech in speech communication and speech recognition. In this research, we propose characteristic parameter with combining spectral Entropy for detect speech active interval in Noisy Speech, and compare performance of speech active interval based on energy. The results shows that analysis using proposed characteristic parameter is higher performance the others in noisy environment.

• Proceedings of the KOSOMBE Conference
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• v.1989 no.05
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• pp.13-14
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• 1989

Prolongation in QT corrected interval (QTc), measured in surface ECG, has been shown in the majority af patients to be marker of bad prognosis in postmyocardial infarction patients (PMIP). Hence it would seem logical that dynamic QTc interval measurement can be a very usefull indicator to stratify prognosis in PMIP. We present a new algorithm for QT as well as for QTP (distance value from Q wave onset to T wave peak) intervals measurement in 24 hour ECG Holter tapes. Validation of the algorithm by hand measurement has been done on first beats of 18 Holter tapes, resulting in a magnitude of deviations between 10 and 15 ms. Application on 24 hour Holter ECG signal has also been done.

• International Journal of Reliability and Applications
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• v.15 no.1
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• pp.51-64
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• 2014

This paper develops a warranty cost model for complex systems with imperfect repair within a warranty period by addressing a practical case that the first inter-failure interval is longer than any other inter-failure intervals. The product is in its best condition before the first failure if repair is imperfect. After the imperfect repair, other inter-failure intervals which are explained by renewal processes, are stochastically smaller than the first inter-failure interval. Based on this idea, we suggest the failure-interval-failure-criterion model. In this model, we consider two random variables, X and Y where X represents failure intervals and Y represents failure criterion. We also obtain the distribution of the number of failures and conduct the warranty cost analysis. We investigate different types of warranty cost models, reliabilities and other measures for various systems including series-parallel configurations. Several numerical examples are discussed to demonstrate the applicability of the methodologies derived in the paper.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.947-955
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• 2017

A competing risk analysis has been applied when subjects experience more than one type of end points. Geskus (2011) showed three types of estimators of CIF are equivalent under left truncated and right censored data. We extend his approach to an interval censored competing risk data by using a modified risk set and evaluate their performance under several sample sizes. These estimators show very similar results. We also suggest a test statistic combining Sun's test for interval censored data and Gray's test for right censored data. The test sizes and powers are compared under several cases. As a real data application, the suggested method is applied a data where the feasibility of the vaccine to HIV was assessed in the injecting drug uses.

• Structural Engineering and Mechanics
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• v.70 no.1
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• pp.81-96
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• 2019

In this paper, a hybrid uncertain model is applied to system reliability based design optimization (RBDO) of trusses. All random variables are described by random distributions but some key distribution parameters of them which lack information are defined by variation intervals. For system RBDO of trusses, the first order reliability method, as well as monotonicity analysis and the branch and bound method, are utilized to determine the system failure probability; and Improved (${\mu}+{\lambda}$) constrained differential evolution (ICDE) is employed for the optimization process. System reliability assessment of several numerical examples and system RBDO of different truss structures are proposed to verify our results. Moreover, the effect of different classes of interval distribution parameters on the optimum weight of the structure and the reliability index are also investigated. The results indicate that the weight of the structure is increased by increasing the uncertainty level. Moreover, it is shown that for a certain random variable, the optimum weight is more increased by the translation interval parameters than the rotation ones.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.208-217
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• 2021

3D-CNN is one of the deep learning techniques for learning time series data. However, these three-dimensional learning can generate many parameters, requiring high performance or having a significant impact on learning speed. We will use these 3D-CNNs to learn hand gesture and find the parameters that showed the highest accuracy, and then analyze how the accuracy of 3D-CNN varies through input data changes without any structural changes in 3D-CNN. First, choose the interval of the input data. This adjusts the ratio of the stop interval to the gesture interval. Secondly, the corresponding interframe mean value is obtained by measuring and normalizing the similarity of images through interclass 2D cross correlation analysis. This experiment demonstrates that changes in input data affect learning accuracy without structural changes in 3D-CNN. In this paper, we proposed two methods for changing input data. Experimental results show that input data can affect the accuracy of the model.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.59-65
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• 1995

The cam is used to a main component in a variety of automatic machines and instruments. To meet the demand of a complicated operation and of reducing weight for automatic machine, Curve Blending Technology, in which each of the basic curves suitable for individual interval is connected, is used for the cam design. In the curve blending, it is necessary to select appropriate elementary curve for each interval and to confirm the dynamic continuity at connecting points between adjoining elementary curves. This paper represented the elementary curve selection method to select an appropriate curve for each interval, and executed computation for the follower displacement and angular displacement of each interval. The paper made an analysis and examine closely for elementary curves to synthesizing curve blending, and it performed dynamic conditions clearly at every points on the cam motions. Therefore the curve blending technology presented by the paper turned into easier work.