• Communications for Statistical Applications and Methods
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• v.20 no.1
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• pp.29-39
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• 2013

This paper derives maximum likelihood estimators (MLEs) and some approximate MLEs (AMLEs) of unknown parameters of the generalized exponential distribution when data are lower record values. We derive approximate Bayes estimators through importance sampling and obtain corresponding Bayes predictive intervals for unknown parameters for lower record values from the generalized exponential distribution. For illustrative purposes, we examine the validity of the proposed estimation method by using real and simulated data.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.675-678
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• 2004

The importance of predicting concrete compressive strength of in concrete structures is gradually increasing in construction industry. The estimation of concrete compressive strength of is a critical factor of the construction schedule and quality control. This study was performed to examine the relationship between concrete compressive strength and stress wave velocity which was determined by the impact echo method and SASW method.

• IE interfaces
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• v.11 no.2
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• pp.191-197
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• 1998

Having a reliable standard time data is very important for productivity improvement of any manufacturing company. In this study we present an estimation procedure of standard time data for companies having multi-item extremely small quantity production type and discuss a case study. Included in the discussion are the importance of setup time reduction and the roles of management supervisors, and labor.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.47.1-47
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• 2001

The drilling process has a great importance for the production technology due to its widerspread use in the manufacturing industry. In order to enhance a maximum production rate and prevent the drill from the damage, it is important to monitor and control the drilling system. Thrust force and cutting torque are the main output variables in the design of drilling control systems. In this paper, an alternative estimation method of thrust force by using flexible neural networks is proposed. Flexible neural network uses the sigmoid activation function with adjustable parameter in order to enhance the approximation accuracy ...

• Structural Engineering and Mechanics
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• v.68 no.4
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• pp.399-408
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• 2018

Cable supported structures have been widely used in civil engineering. Cable tension estimation has great importance in cable supported structures' analysis, ranging from design to construction and from inspection to maintenance. Even though the Bernoulli-Euler beam element is commonly used in the traditional finite element method for calculation of frequency and cable tension estimation, many elements must be meshed to achieve accurate results, leading to expensive computation. To improve the accuracy and efficiency, a dynamic finite element method for estimation of cable tension is proposed. In this method, following the dynamic stiffness matrix method, frequency-dependent shape functions are adopted to derive the stiffness and mass matrices of an exact beam element that can be used for natural frequency calculation and cable tension estimation. An iterative algorithm is used for the exact beam element to determine both the exact natural frequencies and the cable tension. Illustrative examples show that, compared with the cable tension estimation method using the conventional beam element, the proposed method has a distinct advantage regarding the accuracy and the computational time.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.531-534
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• 2001

At the beginning of construction, the estimation for the construction duration is very important to effectively control and use labors, builder's equipment, permanent and temporary materials, supplies and utilities, and money. In spite of the importance of the estimation for the construction duration, there is no estimation standard of optimal construction duration in korea. The purpose of this study is to suggest the estimation standard of optimal construction duration that is reasonable and systematical through developing the method for estimating, the construction duration. it is expected to be helpful for estimating, planning and scheduling. The analysis is executed the existing estimation standards and consulting the results of the interviews with the on-site engineers and the concrete compressive stress tests.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.3
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• pp.517-523
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• 2011

The estimation filter in radar systems must track targets' position within low tracking error. In the Multi-Function Radar(MFR), ${\alpha}-{\beta}$ filter and Kalman filter are widely used to track single or multiple targets. However, due to target maneuvering, these filters may not reduce tracking error, therefore, may lost target tracks. In this paper, a target tracking filter based on particle filtering algorithm is proposed for the MFR. The advantage of this method is that it can track targets within low tracking error while targets maneuver and reduce impoverishment of particles by the proposed resampling method. From the simulation results, the improved tracking performance is obtained by the proposed filtering algorithm.

• Journal of Internet Computing and Services
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• v.6 no.3
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• pp.159-170
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• 2005

OC-SVM(One Class Support Vector Machine) avoids solving a full density estimation problem, and instead focuses on a simpler task, estimating quantiles of a data distribution, i.e. its support. OC-SVM seeks to estimate regions where most of data resides and represents the regions as a function of the support vectors, Although OC-SVM is powerful method for data description, it is difficult to incorporate human subjective importance into its estimation process, In order to integrate the importance of each point into the OC-SVM process, we propose a fuzzy version of OC-SVM. In FOC-SVM (Fuzzy One-Class Support Vector Machine), we do not equally treat data points and instead weight data points according to the importance measure of the corresponding objects. That is, we scale the kernel feature vector according to the importance measure of the object so that a kernel feature vector of a less important object should contribute less to the detection process of OC-SVM. We demonstrate the performance of our algorithm on several synthesized data sets, Experimental results showed the promising results.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.2092-2093
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• 2008

Since Jan. 2004, the Ministry of Construction and Transportation has partly introduced estimation system of historical cost data in order to reflect result cost of construction market to cost estimation for public construction. And KEPCO started estimation system of historical cost data in the electrical construction works. Electrical construction cost index a matter of great importance. This paper was conducted to examine estimation methods of the items of the price index estimation system of historical cost data and suggest reasonable applications.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.59-60
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• 2016

Flooded lead acid batteries are still very popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation is of great importance for a flooded lead acid battery to ensure its safe working and to prevent it from over-charging or over-discharging. Different types of Kalman Filters are widely used for SOC estimation of batteries. The values of process and measurement noise covariance of a filter are usually calculated by trial and error method and taken as constant throughout the estimation process. While in practical cases, these values can vary as well depending upon the dynamics of the system. Therefore an Adaptive Unscented Kalman Filter (AUKF) is introduced in which the values of the process and measurement noise covariance are updated in each iteration based on the residual system error. A comparison of traditional and Adaptive Unscented Kalman Filter is presented in the paper. The results show that SOC estimation error by the proposed method is further reduced by 3 % as compared to traditional Unscented Kalman Filter.