• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.922-925
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• 2008

Many highway projects are under way in Korea. However, owners frequently find that the project cost exceeds the budget and they are unable to identify the underlining reasons. The main purpose of this research is to develop cost models for transportation projects in Korea using the multiple linear regression (MLR). The data consist of 27 completed transportation projects, built from 1991 to 2001, The technique of multiple regression analysis is used to develop the parametric cost estimating model for total budget cost per highway square meter (TBC/$m^2$). Findings of the study indicated that MLR car be applied to highway projects in Korea. There are twf) major contributions of this research. (1) the identification of transportation parameters as a significant cost driver for transportation costs and (2) the successful development of the parametric cost estimating models for transportation projects in Korea.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.877-882
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• 2002

A new estimation model of predicting the sound absorption performance for multiple perforated plate sound absorbing system was developed using transfer matrix method. The proposed method was validated by comparing the calculated absorption coefficients of a single layer perforated plate with the values measured by the two-microphone impedance tube method far various porosity and cavity depth. The developed transfer matrix method was further applied to estimate the multiple layer perforated plates and it is shown that the estimated absorption coefficients generally agree well with the measured values.

• Journal of the Society of Naval Architects of Korea
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• v.50 no.6
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• pp.373-382
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• 2013

The weight of floating offshore plant, such as an FPSO(Floating, Production, Storage, and Off-loading unit) and an offshore wind turbine, is important for estimating the amount of production material and for determining the production method. Furthermore, the weight is a factor which affects in the building cost and production time of the floating offshore plant. Although the importance of the weight has long been recognized, the weight has been roughly estimated by using the existing design and production data, and designer's experience. To solve this problem, a simplified model for the weight estimation of the floating offshore plant using the statistical method was proposed in this study. To do this, various data for estimating the weight of the floating offshore plant were collected through the literature survey, and then the correlation analysis and the multiple regression analysis were performed to generate the simplified model for the weight estimation. Finally, to examine the applicability of the developed model, it was applied to examples of the weight estimation of an FPSO topsides and an offshore wind turbine. As a result, it was shown that the developed model can be applied the weight estimation process of the floating offshore plant at the early design stage.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.1-16
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• 2007

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi-path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment and other multiple decision parameters than the received signal strength.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.394-398
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• 2016

In this paper, a fire detection system based on quantitative risk estimation is presented. Multiple sensors are used to build a comprehensive indicator that represents the risk of fire quantitatively. The proposed fire risk estimation method consists of two stages which determines the occurrence of fire and estimates the toxicity of the surveillance area. In the first stage, fire is reliably detected under diverse fire scenarios. The risk of fire is estimated in the second stage. Applying Purser's Fractional Effective Dose (FED) model which quantitates harmfulness of toxic gases, the risk of the surveillance area and evacuation time are calculated. A fire experiment conducted using four different types of combustion materials for the verification of the system resulted in a maximum error rate of 12.5%. By using FED calculation and risk estimation methods, the proposed system can detect various signs of fire faster than conventional systems.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.445-453
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• 2001

The multiple targets tracking problem has been one of the main issues in the radar applications area in the last decade. Besides the standard Kalman filtering, various methods including the variable dimen-sion filter, input estimation filter, interacting multiple model(IMM) filter, dederated variable dimension filter with input estimation, etc., have proposed to address the tracking and sensor fusion issues. In this pa- per, two existing tracking algorithm, i.e, the IMM filter and the variable dimension filter with input estima-tion(VDIE), are combined for the purpose of improving the tracking performance for maneuvering targets. To evaluate the tracking performance of the proposed algorithm, three typical maneuvering patterns, i.e., waver, pop-up, and high-diver motions, are defined and are applied to the modified IMM filter as well as the standard IMM filter. The smaller RMS tracking errors, in position and velocity, of the modified IMM filter than the standard IMM filter are demonstrated though computer simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.598-601
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• 1995

This paper proposes a federated Kalman filter approach which utilizes information from multiple sensors and variable estimation model. Compared with the decentralized Kalman filter, the algorithm proposed in this paper demonstrates much better tracking performance in both maneuvering and constant velocity movement of the target.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.412-418
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• 2000

The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.193-206
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• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• Asian-Australasian Journal of Animal Sciences
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• v.13 no.5
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• pp.575-579
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• 2000

First lactation records of 683 Murrah buffaloes maintained at NDRI, Karnal which were progeny of 84 sires used for comparing the heritability estimates of age at first calving, first lactation milk yield and first service period under single and multiple trait models using restricted maximum likelihood (REML) method of estimation under an individual animal model. The results indicated that the heritability estimates may vary under single and multiple trait models depending upon the magnitude of genetic and environmental correlation among the traits being considered. Therefore, a single or multiple trait model is recommended for estimation of variance components depending upon the goal of breeding programme. However, there may not be any advantage of considering a trait with zero or near zero heritability and having no or very low genetic correlation with other traits in the model. Lower heritability estimates of part lactation yield (120-day milk yield) implied that there may not be any advantage of considering this trait in place of actual 305-day milk yield, whereas, comparable heritability estimates of predicted 305-day milk yield suggested that it could be used for sire evaluation to reduce the cost of milk recording under field conditions.