• Journal of Environmental Science International
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• v.23 no.3
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• pp.387-397
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• 2014

This study is carried out to propose an empirical equation which can promptly predict the aircraft noise level at a specific point (a receptor) near Jeju international airport by using the information of the flight path data. For this purpose, Analyses of multiple linear regression with the slant distances (SD) calculated from the gate analyses of the flight path data, aircraft noise certification levels with unit of EPNL(effective perceived noise level) and noise levels measured at receptors are performed by SPSS package. From these regression analyses for approach and departure of aircraft, we can propose empirical equations which is statistically significant. The noise levels predicted by these empirical equations are highly correlated the measured data.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.6
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• pp.613-623
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• 2017

A semi-empirical model to predict ship resistance in level ice based on Lindqvist's model is presented. This model assumes that contact between the ship and the ice is a case of symmetrical collision, and two contact cases are considered. Submersion force is calculated via Lindqvist's formula, and the crushing and breaking forces are determined by a concept of energy consideration during ship and ice impact. The effect of the contact coefficient is analyzed in the ice resistance prediction. To validate this model, the predicted results are compared with model test data of USCGC Healy and icebreaker Araon, and full-scale data of the icebreaker KV Svalbard. A relatively good agreement is achieved. As a result, the presented model is recommended for preliminary total resistance prediction in advance of the evaluation of the icebreaking performance of vessels.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.41-48
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• 1997

We construct the empirical Bayes(EB) confidence intervals that attain a specified level of EB coverage for the unknown scale parameter in the Weibull distribution with the known shape parameter under the type II censored data. Our general approach is to use an EB bootstrap samples introduced by Larid and Louis(1987). Also, we compare the coverage probability and the expected interval length for these bootstrap intervals with those of the naive intervals through Monte Carlo simulation.

• International Journal of Quality Innovation
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• v.6 no.3
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• pp.1-18
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• 2005

This paper presents the empirical research results conducted in a Swedish care organization for elderly and handicapped. The objective of the research was to empirically assess the implementation and practices of a quality system (ISO 9000) from an organizational change and development perspective. The empirical data were collected through multiple methods; interviews were carried out with key-persons and leadership in the organisation and surveys were conducted to all employees. Interactive methods have been applied to various groups in the organisations e.g., directors, supervisors, and the leadership of the quality project and the local politicians. The empirical findings indicate, among others, that the implementation processes were received and perceived differently in the different parts of the care organisation due to different leadership strategies and employee involvement policies. Other critical factors such as acceptance, resistance, motivation, commitment, the role of leadership, learning possibility, etc. have also been investigated, analysed and discussed. Finally some recommendations on how to approach organisational change as well as strategies for implementing a quality system in the care sector are presented.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.238-241
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• 2009

In order to design a good quantizer for the underlying distribution using a training sequence (TS), the traditional approach is seeking for the empirical minimum based on the empirical risk minimization principle. As the size of TS increases, we may obtain a good quantizer for the true distribution. However, if we have a relatively small TS, searching the empirical minimum for the TS causes the overfitting problem, which even worsens the performance of the trained codebook. In this paper, the performance of codebooks trained by small TSs is studied, and it is shown that a piecewise uniform codebook can be better than an empirically minimized codebook is.

• Membrane and Water Treatment
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• v.2 no.4
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• pp.225-237
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• 2011

In this study, response of reversibility of membrane flux during chemically enhanced backwash (CEB) to changes in filtration time, filtration flux and coagulant concentration dosing during ultrafiltration (UF) process was investigated using a regression model. The model was developed via empirical modelling approach using response surface methodology. In developing the model, statistically designed UF experiments were conducted and the results compared with the model output. The results showed that the performance of CEB, evaluated in terms of the reversibility of the membrane flux, depends strongly on the changes in coagulant concentration dosage and the filtration flux. Also the response of the reversibility of membrane flux during CEB is independent of the filtration time. The variance ratio, VR << $F_{value}$ and $R^2$ = 0.98 obtained from the cross-validation experiments indicate perfect agreement of the model output with experimental results and also testify to the validity and suitability of the model to predict reversibility of the membrane flux during CEB in UF operation.

• The Journal of Information Systems
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• v.30 no.4
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• pp.71-94
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• 2021

Purpose The purpose of this study is to verify impacts of factors, representing Push-Pull-Mooring(PPM) on switch intention to OTT(Over-The-Top) service in demand for content and to find relationship between factors through empirical analysis. Design/methodology/approach This study designed a research model by deriving factors affecting the intention to switch on OTT service based on the Push-Pull-Mooring framework and researches on OTT service. To test the hypothesis, a total of 357 responses were collected from individuals with experience in using OTT service and analyzed using SPSS26 and SmartPLS3.0. Findings According to the empirical analysis result, this study confirmed that the push, pull, and mooring factors proposed in this study had a significant effect on switching intention on OTT service. In addition, this study confirmed that both low switching cost and need for variety had a significant effect except for hypothesis H8.

• The Journal of Information Systems
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• v.16 no.1
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• pp.111-133
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• 2007

The purpose of this study is to present a new function point estimation approach for the Object-Oriented information systems. In order to fulfill this purpose, we first review the literature on Function Point Analysis of IFPUG, Unified Modeling Language, and Unified Process. Then, we derive a method and rules for estimating Function Points based on Use Cases and Class Diagrams. To analyze the appropriateness of the proposed approach, we conduct the empirical testing. 143 use cases are collected from production, marketing, distribution, sales, and other areas from the Object-Oriented systems development projects. We compare our new approach with the existing methods that are usually used for traditional systems development projects. The results show that our proposed approach is more appropriate for the Object-Oriented environment.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 1998.11a
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• pp.27-31
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• 1998

Most models for the simulation of multi-phase flow and multi-species transport employ the capillary approach which uses the Darcy's law for the representation of mass flux of each phase. The capillary approach based on the Darcy's law require many empirical coefficients with complex functional dependencies rather than rigrous mathematical and physical formulation. The shortcoming of the capillary approach cause the numerical errors in the simulations by the multi-phase flow and transport models. This study discuss some of the problems related with the use of models.